🔖 chore(release): v1.133.3 [skip ci]

### [Version 1.133.3](https://github.com/lobehub/lobe-chat/compare/v1.133.2...v1.133.3) <sup>Released on **2025-10-01**</sup> #### ♻ Code Refactoring - **misc**: Refactor a `ssrf-safe-fetch` module. #### 🐛 Bug Fixes - **misc**: Fix frontend random API key config not work. <br/> <details> <summary><kbd>Improvements and Fixes</kbd></summary> #### Code refactoring * **misc**: Refactor a `ssrf-safe-fetch` module, closes [#9474](https://github.com/lobehub/lobe-chat/issues/9474) ([92da716](https://github.com/lobehub/lobe-chat/commit/92da716)) #### What's fixed * **misc**: Fix frontend random API key config not work, closes [#9477](https://github.com/lobehub/lobe-chat/issues/9477) [#9255](https://github.com/lobehub/lobe-chat/issues/9255) ([a194d48](https://github.com/lobehub/lobe-chat/commit/a194d48)) </details> <div align="right"> [![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top) </div>
♻️ refactor: refactor a ssrf-safe-fetch module (#9474 )
2026-06-15 20:16:02 +00:00 · 2025-10-01 19:40:38 +00:00 · 2025-10-02 03:31:20 +08:00 · 2025-10-01 14:54:05 +08:00 · 2025-10-01 14:53:58 +08:00 · 2025-10-01 05:46:24 +08:00
266 changed files with 15008 additions and 1421 deletions
@@ -1,176 +0,0 @@
---
-description:
-globs: src/services/**/*,src/database/**/*,src/server/**/*
-alwaysApply: false
---
-
-# LobeChat 后端技术架构指南
-
-本指南旨在阐述 LobeChat 项目的后端分层架构，重点介绍各核心目录的职责以及它们之间的协作方式。
-
-## 目录结构映射
-
-```
-src/
-├── server/
-│   ├── routers/          # tRPC API 路由定义
-│   └── services/         # 业务逻辑服务层
-│       └── */impls/      # 平台特定实现
-├── database/
-│   ├── models/           # 数据模型 (单表 CRUD)
-│   ├── repositories/     # 仓库层 (复杂查询/聚合)
-│   └── schemas/          # Drizzle ORM 表定义
-└── services/             # 客户端服务 (调用 tRPC 或直接访问 Model)
-```
-
-## 核心架构分层
-
-LobeChat 的后端设计注重模块化、可测试性和灵活性，以适应不同的运行环境（如浏览器端 PGLite、服务端远程 PostgreSQL 以及 Electron 桌面应用）。
-
-其主要分层如下：
-
-1.  客户端服务层 (`src/services`):
-    - 位于 src/services/。
-    - 这是客户端业务逻辑的核心层，负责封装各种业务操作和数据处理逻辑。
-    - 环境适配: 根据不同的运行环境，服务层会选择合适的数据访问方式：
-      - 本地数据库模式: 直接调用 `Model` 层进行数据操作，适用于浏览器 PGLite 和本地 Electron 应用。
-      - 远程数据库模式: 通过 `tRPC` 客户端调用服务端 API，适用于需要云同步的场景。
-    - 类型转换: 对于简单的数据类型转换，直接在此层进行类型断言，如 `this.pluginModel.query() as Promise<LobeTool[]>`
-    - 每个服务模块通常包含 `client.ts`（本地模式）、`server.ts`（远程模式）和 `type.ts`（接口定义）文件，在实现时应该确保本地模式和远程模式业务逻辑实现一致，只是数据库不同。
-
-2.  API 接口层 (`TRPC`):
-    - 位于 src/server/routers/
-    - 使用 `tRPC` 构建类型安全的 API。Router 根据运行时环境（如 Edge Functions, Node.js Lambda）进行组织。
-    - 负责接收客户端请求，并将其路由到相应的 `Service` 层进行处理。
-    - 新建 lambda 端点时可以参考 src/server/routers/lambda/\_template.ts
-
-3.  仓库层 (`Repositories`):
-    - 位于 src/database/repositories/。
-    - 主要处理复杂的跨表查询和数据聚合逻辑，特别是当需要从多个 `Model` 获取数据并进行组合时。
-    - 与 `Model` 层不同，`Repository` 层专注于复杂的业务查询场景，而不涉及简单的领域模型转换。
-    - 当业务逻辑涉及多表关联、复杂的数据统计或需要事务处理时，会使用 `Repository` 层。
-    - 如果数据操作简单（仅涉及单个 `Model`），则通常直接在 `src/services` 层调用 `Model` 并进行简单的类型断言。
-
-4.  模型层 (`Models`):
-    - 位于 src/database/models/ (例如 src/database/models/plugin.ts 和 src/database/models/document.ts)。
-    - 提供对数据库中各个表（由 src/database/schemas/ 中的 Drizzle ORM schema 定义）的基本 CRUD (创建、读取、更新、删除) 操作和简单的查询能力。
-    - `Model` 类专注于单个数据表的直接操作，不涉及复杂的领域模型转换，这些转换通常在上层的 `src/services` 中通过类型断言完成。
-    - model（例如 Topic） 层接口经常需要从对应的 schema 层导入 NewTopic 和 TopicItem
-    - 创建新的 model 时可以参考 src/database/models/\_template.ts
-
-5.  数据库 (`Database`):
-    - 客户端模式 (浏览器/PWA): 使用 PGLite (基于 WASM 的 PostgreSQL)，数据存储在用户浏览器本地。
-    - 服务端模式 (云部署): 使用远程 PostgreSQL 数据库。
-    - Electron 桌面应用:
-      - Electron 客户端会启动一个本地 Node.js 服务。
-      - 本地服务通过 `tRPC` 与 Electron 的渲染进程通信。
-      - 数据库选择依赖于是否开启云同步功能：
-        - 云同步开启: 连接到远程 PostgreSQL 数据库。
-        - 云同步关闭: 使用 PGLite (通过 Node.js 的 WASM 实现) 在本地存储数据。
-
-## 数据流向说明
-
-### 浏览器/PWA 模式
-
-```
-UI (React) → Zustand action -> Client Service → Model Layer → PGLite (本地数据库)
-```
-
-### 服务端模式
-
-```
-UI (React) → Zustand action → Client Service -> TRPC Client → TRPC Routers  → Repositories/Models → Remote PostgreSQL
-```
-
-### Electron 桌面应用模式
-
-```
-UI (Electron Renderer) → Zustand action → Client Service -> TRPC Client → 本地 Node.js 服务 → TRPC Routers → Repositories/Models → PGLite/Remote PostgreSQL (取决于云同步设置)
-```
-
-## 服务层 (Server Services)
-
- 位于 src/server/services/。
- 核心职责是封装独立的、可复用的业务逻辑单元。这些服务应易于测试。
- 平台差异抽象: 一个关键特性是通过其内部的 `impls` 子目录（例如 src/server/services/file/impls 包含 s3.ts 和 local.ts）来抹平不同运行环境带来的差异（例如云端使用 S3 存储，桌面版使用本地文件系统）。这使得上层（如 `tRPC` routers）无需关心底层具体实现。
- 目标是使 `tRPC` router 层的逻辑尽可能纯粹，专注于请求处理和业务流程编排。
- 服务可能会调用 `Repository` 层或直接调用 `Model` 层进行数据持久化和检索，也可能调用其他服务。
-
-## 最佳实践 (Best Practices)
-
-### 数据库操作封装原则
-
-**连续的数据库操作应该封装到 Model 层**
-
-当业务逻辑涉及多个相关的数据库操作时，建议将这些操作封装到 Model 层中，而不是在上层（Service 或 Router 层）中进行多次数据库调用。
-
-**优势：**
-
- **代码复用**: Client DB 环境的 service 实现和 Server DB 的 lambda 层实现可以复用相同的 Model 方法
- **事务一致性**: 相关的数据库操作可以在同一个方法中管理，便于维护数据一致性
- **性能优化**: 减少数据库连接次数，提高查询效率
- **职责清晰**: Model 层专注数据访问，上层专注业务协调
-
-**示例：**
-
-```typescript
-// ✅ 推荐：在 Model 层封装连续的数据库操作
-class GenerationBatchModel {
-  async delete(id: string): Promise<{ deletedBatch: BatchItem; thumbnailUrls: string[] }> {
-    // 1. 查询相关数据
-    const batchWithGenerations = await this.db.query.generationBatches.findFirst({...});
-
-    // 2. 收集需要处理的数据
-    const thumbnailUrls = [...];
-
-    // 3. 执行删除操作
-    const [deletedBatch] = await this.db.delete(generationBatches)...;
-
-    return { deletedBatch, thumbnailUrls };
-  }
-}
-
-// ✅ 上层使用简洁
-const { thumbnailUrls } = await model.delete(id);
-await fileService.deleteFiles(thumbnailUrls);
-```
-
-### 文件操作与数据库操作的执行顺序
-
-**删除操作原则：数据库删除在前，文件删除在后**
-
-当业务逻辑同时涉及数据库记录和文件系统操作时，应该遵循"数据库优先"的原则。
-
-**原因：**
-
- **用户体验优先**: 如果先删除文件再删除数据库记录，可能出现文件已删除但数据库记录仍存在的情况，用户访问时会遇到文件不存在的错误
- **影响程度较小**: 如果先删除数据库记录再删除文件，即使文件删除失败，用户也看不到这个记录，只是造成一些存储空间浪费，对用户体验影响更小
- **数据一致性**: 数据库记录是业务逻辑的核心，应该优先保证其一致性
-
-**示例：**
-
-```typescript
-// ✅ 推荐：先删除数据库记录，再删除文件
-async deleteGeneration(id: string) {
-  // 1. 先删除数据库记录
-  const deletedGeneration = await generationModel.delete(id);
-
-  // 2. 再删除相关文件
-  if (deletedGeneration.asset?.thumbnailUrl) {
-    await fileService.deleteFile(deletedGeneration.asset.thumbnailUrl);
-  }
-}
-
-// ❌ 不推荐：先删除文件
-async deleteGeneration(id: string) {
-  const generation = await generationModel.findById(id);
-
-  // 如果这里删除成功，但后面数据库删除失败，用户会遇到访问错误
-  await fileService.deleteFile(generation.asset.thumbnailUrl);
-  await generationModel.delete(id); // 可能失败
-}
-```
-
-**创建操作原则：数据库创建在前，文件操作在后**
-
-创建操作同样应该优先处理数据库记录，确保数据的一致性和完整性。
@@ -1,58 +0,0 @@
---
-description: How to code review
-globs:
-alwaysApply: false
---
-
-# Role Description
-
- You are a senior full-stack engineer skilled in performance optimization, security, and design systems.
- You excel at reviewing code and providing constructive feedback.
- Your task is to review submitted Git diffs **in Chinese** and return a structured review report.
- Review style: concise, direct, focused on what matters most, with actionable suggestions.
-
-## Before the Review
-
-Gather the modified code and context. Please strictly follow the process below:
-
-1. Use `read_file` to read [package.json](mdc:package.json)
-2. Use terminal to run command `git diff HEAD | cat` to obtain the diff and list the changed files. If you recieived empty result, run the same command once more.
-3. Use `read_file` to open each changed file.
-4. Use `read_file` to read [rules-attach.mdc](mdc:.cursor/rules/rules-attach.mdc). Even if you think it's unnecessary, you must read it.
-5. combine changed files, step3 and `agent_requestable_workspace_rules`, list the rules which need to read
-6. Use `read_file` to read the rules list in step 5
-
-## Review
-
-### Code Style
-
-read [typescript.mdc](mdc:.cursor/rules/typescript.mdc) for the consolidated project code style and optimization rules.
-
-### Code Optimization
-
-The optimization checklist has been consolidated into [typescript.mdc](mdc:.cursor/rules/typescript.mdc): loops, debouncing/throttling, design system components, theming tokens, concurrency with `Promise.*`, minimal DB column selection, and package reuse.
-
-### Obvious Bugs
-
- Do not silently swallow errors in `catch` blocks; at minimum, log them.
- Revert temporary code used only for testing (e.g., debug logs, temporary configs).
- Remove empty handlers (e.g., an empty `onClick`).
- Confirm the UI degrades gracefully for unauthenticated users.
- Don't leave any debug logs in the code (except when using the `debug` module properly).
-  - When using the `debug` module, avoid `import { log } from 'debug'` as it logs directly to console. Use proper debug namespaces instead.
- Check logs for sensitive information like api key, etc
-
-## After the Review: output
-
-1. Summary
-   - Start with a brief explanation of what the change set does.
-   - Summarize the changes for each modified file (or logical group).
-2. Comments Issues
-   - List the most critical issues first.
-   - Use an ordered list, which will be convenient for me to reference later.
-   - For each issue:
-     - Mark severity tag (`❌ Must fix`, `⚠️ Should fix`, `💅 Nitpick`)
-     - Provode file path to the relevant file.
-     - Provide recommended fix
-   - End with a **git commit** command, instruct the author to run it.
-     - We use gitmoji to label commit messages, format: [emoji] <type>(<scope>): <subject>
@@ -1,32 +0,0 @@
---
-description:
-globs:
-alwaysApply: true
---
-
-# Guide to Optimize Output(Response) Rendering
-
-## File Path and Code Symbol Rendering
-
- When rendering file paths, use backtick wrapping instead of markdown links so they can be parsed as clickable links in Cursor IDE.
-  - Good: `src/components/Button.tsx`
-  - Bad: [src/components/Button.tsx](src/components/Button.tsx)
-
- Don't use line and column number in file path, this will make file path not clickable in Cursor IDE.
-  - Good: `src/components/Button.tsx` `10:20` (add a space between the file path and the line and column number)
-  - Bad: `src/components/Button.tsx:10:20`
-
- When rendering functions, variables, or other code symbols, use backtick wrapping so they can be parsed as navigable links in Cursor IDE
-  - Good: The `useState` hook in `MyComponent`
-  - Bad: The useState hook in MyComponent
-
-## Markdown Render
-
- don't use br tag to wrap in table cell
-
-## Terminal Command Output
-
- If terminal commands don't produce output, it's likely due to paging issues. Try piping the command to `cat` to ensure full output is displayed.
-  - Good: `git show commit_hash -- file.txt | cat`
-  - Good: `git log --oneline | cat`
-  - Reason: Some git commands use pagers by default, which may prevent output from being captured properly
@@ -1,8 +0,0 @@
---
-description: 
-globs: src/database/models/**/*
-alwaysApply: false
---
-1. first read [lobe-chat-backend-architecture.mdc](mdc:.cursor/rules/lobe-chat-backend-architecture.mdc)
-2. refer to the [_template.ts](mdc:src/database/models/_template.ts) to create new model
-3. if an operation involves multiple models or complex queries, consider defining it in the `repositories` layer under `src/database/repositories/`
@@ -4,41 +4,35 @@ alwaysApply: true

 ## Project Description

-You are developing an open-source, modern-design AI chat framework: lobe chat.
+You are developing an open-source, modern-design AI chat framework: lobehub(previous lobe-chat).

-Emoji logo: 🤯
+support platforms:
+
+- web desktop/mobile
+- desktop(electron)
+- mobile app(react native). coming soon
+
+logo emoji: 🤯

 ## Project Technologies Stack

 read [package.json](mdc:package.json) to know all npm packages you can use.

-The project uses the following technologies:
-
- pnpm as package manager
- Next.js 15 for frontend and backend, using app router instead of pages router
- react 19, using hooks, functional components, react server components
- TypeScript programming language
- antd, `@lobehub/ui` for component framework
+- Next.js 15
+- react 19
+- TypeScript
+- `@lobehub/ui`, antd for component framework
 - antd-style for css-in-js framework
- react-layout-kit for flex layout
- react-i18next for i18n
 - lucide-react, `@ant-design/icons` for icons
- `@lobehub/icons` for AI provider/model logo icon
- `@formkit/auto-animate` for react list animation
- zustand for global state management
- nuqs for type-safe search params state manager
- SWR for react data fetch
+- react-layout-kit for flex layout component
+- react-i18next for i18n
+- zustand for state management
+- nuqs for search params management
+- SWR for data fetch
 - aHooks for react hooks library
- dayjs for date and time library
+- dayjs for time library
 - lodash-es for utility library
- fast-deep-equal for deep comparison of JavaScript objects
- zod for data validation
 - TRPC for type safe backend
 - PGLite for client DB and PostgreSQL for backend DB
 - Drizzle ORM
- Vitest for testing, testing-library for react component test
- Prettier for code formatting
- ESLint for code linting
- Cursor AI for code editing and AI coding assistance
-
-Note: All tools and libraries used are the latest versions. The application only needs to be compatible with the latest browsers;
+- Vitest for testing
@@ -5,235 +5,116 @@ alwaysApply: false

 # LobeChat Project Structure

-## Directory Structure
+note: some not very important files are not shown for simplicity.

-note: some files are not shown for simplicity.
+## Complete Project Structure
+
+this project use common monorepo structure. The workspace packages name use `@lobechat/` namespace.

 ```plaintext
 lobe-chat/
-├── apps/                           # Applications directory
-│   └── desktop/                    # Electron desktop application
-│       ├── src/                    # Desktop app source code
-│       └── resources/              # Desktop app resources
-├── docs/                           # Project documentation
-│   ├── development/                # Development docs
-│   ├── self-hosting/               # Self-hosting docs
-│   └── usage/                      # Usage guides
-├── locales/                        # Internationalization files (multiple locales)
-│   ├── en-US/                      # English (example)
-│   └── zh-CN/                      # Simplified Chinese (example)
-├── packages/                       # Monorepo packages directory
-│   ├── const/                      # Constants definition package
-│   ├── database/                   # Database related package
-│   ├── electron-client-ipc/        # Electron renderer ↔ main IPC client
-│   ├── electron-server-ipc/        # Electron main process IPC server
-│   ├── model-bank/                 # Built-in model presets/catalog exports
-│   ├── model-runtime/              # AI model runtime package
-│   ├── types/                      # TypeScript type definitions
-│   ├── utils/                      # Utility functions package
-│   ├── file-loaders/               # File processing packages
-│   ├── prompts/                    # AI prompt management
-│   └── web-crawler/                # Web crawling functionality
-├── public/                         # Static assets
-│   ├── icons/                      # Application icons
-│   ├── images/                     # Image resources
-│   └── screenshots/                # Application screenshots
-├── scripts/                        # Build and tool scripts
-├── src/                            # Main application source code (see below)
-├── .cursor/                        # Cursor AI configuration
-├── docker-compose/                 # Docker configuration
-├── package.json                    # Project dependencies
-├── pnpm-workspace.yaml            # pnpm monorepo configuration
-├── next.config.ts                  # Next.js configuration
-├── drizzle.config.ts              # Drizzle ORM configuration
-└── tsconfig.json                   # TypeScript configuration
-```
-
-## Core Source Directory (`src/`)
-
-```plaintext
-src/
-├── app/                            # Next.js App Router routes
-│   ├── (backend)/                  # Backend API routes
-│   │   ├── api/                    # REST API endpoints
-│   │   │   ├── auth/               # Authentication endpoints
-│   │   │   └── webhooks/           # Webhook handlers for various auth providers
-│   │   ├── middleware/             # Request middleware
-│   │   ├── oidc/                   # OpenID Connect endpoints
-│   │   ├── trpc/                   # tRPC API routes
-│   │   │   ├── async/              # Async tRPC endpoints
-│   │   │   ├── desktop/            # Desktop runtime endpoints
-│   │   │   ├── edge/               # Edge runtime endpoints
-│   │   │   ├── lambda/             # Lambda runtime endpoints
-│   │   │   └── tools/              # Tools-specific endpoints
-│   │   └── webapi/                 # Web API endpoints
-│   │       ├── chat/               # Chat-related APIs for various providers
-│   │       ├── models/             # Model management APIs
-│   │       ├── plugin/             # Plugin system APIs
-│   │       ├── stt/                # Speech-to-text APIs
-│   │       ├── text-to-image/      # Image generation APIs
-│   │       └── tts/                # Text-to-speech APIs
-│   ├── [variants]/                 # Page route variants
-│   │   ├── (main)/                 # Main application routes
-│   │   │   ├── chat/               # Chat interface and workspace
-│   │   │   ├── discover/           # Discover page (assistants, models, providers)
-│   │   │   ├── files/              # File management interface
-│   │   │   ├── image/              # Image generation interface
-│   │   │   ├── profile/            # User profile and stats
-│   │   │   ├── repos/              # Knowledge base repositories
-│   │   │   └── settings/           # Application settings
-│   │   └── @modal/                 # Modal routes
-│   └── manifest.ts                 # PWA configuration
-├── components/                     # Global shared components
-│   ├── Analytics/                  # Analytics tracking components
-│   ├── Error/                      # Error handling components
-│   └── Loading/                    # Loading state components
-├── config/                         # Application configuration
-│   ├── featureFlags/               # Feature flags & experiments
-│   └── modelProviders/             # Model provider configurations
-├── features/                       # Feature components (UI Layer)
-│   ├── AgentSetting/               # Agent configuration and management
-│   ├── ChatInput/                  # Chat input with file upload and tools
-│   ├── Conversation/               # Message display and interaction
-│   ├── FileManager/                # File upload and knowledge base
-│   └── PluginStore/                # Plugin marketplace and management
-├── hooks/                          # Custom React hooks
-├── layout/                         # Global layout components
-│   ├── AuthProvider/               # Authentication provider
-│   └── GlobalProvider/             # Global state provider
-├── libs/                           # External library integrations
-│   ├── analytics/                  # Analytics services integration
-│   ├── next-auth/                  # NextAuth.js configuration
-│   └── oidc-provider/              # OIDC provider implementation
-├── locales/                        # Internationalization resources
-│   └── default/                    # Default language definitions
-├── migrations/                     # Client-side data migrations
-├── server/                         # Server-side code
-│   ├── modules/                    # Server modules
-│   ├── routers/                    # tRPC routers
-│   └── services/                   # Server services
-├── services/                       # Service layer (per-domain, client/server split)
-│   ├── user/                       # User services
-│   │   ├── client.ts               # Client DB (PGLite) implementation
-│   │   └── server.ts               # Server DB implementation (via tRPC)
-│   ├── aiModel/                    # AI model services
-│   ├── session/                    # Session services
-│   └── message/                    # Message services
-├── store/                          # Zustand state management
-│   ├── agent/                      # Agent state
-│   ├── chat/                       # Chat state
-│   └── user/                       # User state
-├── styles/                         # Global styles
-├── tools/                          # Built-in tool system
-│   ├── artifacts/                  # Code artifacts and preview
-│   └── web-browsing/               # Web search and browsing
-├── types/                          # TypeScript type definitions
-└── utils/                          # Utility functions
-    ├── client/                     # Client-side utilities
-    └── server/                     # Server-side utilities
-```
-
-## Key Monorepo Packages
-
-```plaintext
-packages/
-├── const/                          # Global constants and configurations
-├── database/                       # Database schemas and models
-│   ├── src/models/                 # Data models (CRUD operations)
-│   ├── src/schemas/                # Drizzle database schemas
-│   ├── src/repositories/           # Complex query layer
-│   └── migrations/                 # Database migration files
-├── model-runtime/                  # AI model runtime
-│   └── src/
-│       ├── openai/                 # OpenAI provider integration
-│       ├── anthropic/              # Anthropic provider integration
-│       ├── google/                 # Google AI provider integration
-│       ├── ollama/                 # Ollama local model integration
-│       ├── types/                  # Runtime type definitions
-│       └── utils/                  # Runtime utilities
-├── types/                          # Shared TypeScript type definitions
-│   └── src/
-│       ├── agent/                  # Agent-related types
-│       ├── message/                # Message and chat types
-│       ├── user/                   # User and session types
-│       └── tool/                   # Tool and plugin types
-├── utils/                          # Shared utility functions
-│   └── src/
-│       ├── client/                 # Client-side utilities
-│       ├── server/                 # Server-side utilities
-│       ├── fetch/                  # HTTP request utilities
-│       └── tokenizer/              # Token counting utilities
-├── file-loaders/                   # File loaders (PDF, DOCX, etc.)
-├── prompts/                        # AI prompt management
-└── web-crawler/                    # Web crawling functionality
+├── apps/
+│   └── desktop/
+├── docs/
+├── locales/
+│   ├── en-US/
+│   └── zh-CN/
+├── packages/
+│   ├── const/
+│   ├── context-engine/
+│   ├── database/
+│   │   ├── src/
+│   │   │   ├── models/
+│   │   │   ├── schemas/
+│   │   │   └── repositories/
+│   ├── model-bank/
+│   ├── model-runtime/
+│   │   └── src/
+│   │       ├── openai/
+│   │       └── anthropic/
+│   ├── types/
+│   │   └── src/
+│   │       ├── message/
+│   │       └── user/
+│   └── utils/
+├── public/
+├── scripts/
+├── src/
+│   ├── app/
+│   │   ├── (backend)/
+│   │   │   ├── api/
+│   │   │   │   ├── auth/
+│   │   │   │   └── webhooks/
+│   │   │   ├── middleware/
+│   │   │   ├── oidc/
+│   │   │   ├── trpc/
+│   │   │   └── webapi/
+│   │   │       ├── chat/
+│   │   │       └── tts/
+│   │   ├── [variants]/
+│   │   │   ├── (main)/
+│   │   │   │   ├── chat/
+│   │   │   │   └── settings/
+│   │   │   └── @modal/
+│   │   └── manifest.ts
+│   ├── components/
+│   ├── config/
+│   ├── features/
+│   │   └── ChatInput/
+│   ├── hooks/
+│   ├── layout/
+│   │   ├── AuthProvider/
+│   │   └── GlobalProvider/
+│   ├── libs/
+│   │   └── oidc-provider/
+│   ├── locales/
+│   │   └── default/
+│   ├── server/
+│   │   ├── modules/
+│   │   ├── routers/
+│   │   │   ├── async/
+│   │   │   ├── desktop/
+│   │   │   ├── edge/
+│   │   │   └── lambda/
+│   │   └── services/
+│   ├── services/
+│   │   ├── user/
+│   │   │   ├── client.ts
+│   │   │   └── server.ts
+│   │   └── message/
+│   ├── store/
+│   │   ├── agent/
+│   │   ├── chat/
+│   │   └── user/
+│   ├── styles/
+│   └── utils/
+└── package.json
 ```

 ## Architecture Map

- Presentation: `src/features`, `src/components`, `src/layout` — UI composition, global providers
- State: `src/store` — Zustand slices, selectors, middleware
- Client Services: `src/services/<domain>/{client|server}.ts` — client: PGLite; server: tRPC bridge
- API Routers: `src/app/(backend)/webapi` (REST), `src/app/(backend)/trpc/{edge|lambda|async|desktop|tools}`; Lambda router triggers Async router for long-running tasks (e.g., image)
- Server Services: `src/server/services` (business logic), `src/server/modules` (infra adapters)
- Data Access: `packages/database/src/{schemas,models,repositories}` — Schema (Drizzle), Model (CRUD), Repository (complex queries)
- Integrations: `src/libs` — analytics, auth, trpc, logging, runtime helpers
+- UI Components: `src/components`, `src/features`
+- Global providers: `src/layout`
+- Zustand stores: `src/store`
+- Client Services: `src/services/`
+  - clientDB: `src/services/<domain>/client.ts`
+  - serverDB: `src/services/<domain>/server.ts`
+- API Routers:
+  - `src/app/(backend)/webapi` (REST)
+  - `src/server/routers/{edge|lambda|async|desktop|tools}` (tRPC)
+- Server:
+  - Services(can access serverDB): `src/server/services`
+  - Modules(can't access db): `src/server/modules` (Server only Third-party Service Module)
+- Database:
+  - Schema (Drizzle): `packages/database/src/schemas`
+  - Model (CRUD): `packages/database/src/models`
+  - Repository (bff-queries): `packages/database/src/repositories`
+- Third-party Integrations: `src/libs` — analytics, oidc etc.

 ## Data Flow Architecture

-### Unified Flow Pattern
-
-```
-UI Layer → State Management → Client Service → [Environment Branch] → Database
-   ↓              ↓               ↓                    ↓                ↓
- React         Zustand     Environment         Local/Remote        PGLite/
-Components      Store      Adaptation            Routing          PostgreSQL
-```
-
-### Environment-Specific Routing
-
-| Mode            | UI       | Service Route          | Database            |
-| --------------- | -------- | ---------------------- | ------------------- |
-| **Browser/PWA** | React    | Direct Model Access    | PGLite (Local)      |
-| **Server**      | React    | tRPC → Server Services | PostgreSQL (Remote) |
-| **Desktop**     | Electron | tRPC → Local Node.js   | PGLite/PostgreSQL\* |
-
-_\*Depends on cloud sync configuration_
-
-### Key Characteristics
-
- **Type Safety**: End-to-end type safety via tRPC and Drizzle ORM
- **Local/Remote Dual Mode**: PGLite enables user data ownership and local control
-
-## Quick Map
-
- App Routes: `src/app` — UI routes (App Router) and backend routes under `(backend)`
- Web API: `src/app/(backend)/webapi` — REST-like endpoints
- tRPC Routers: `src/server/routers` — typed RPC endpoints by runtime
- Client Services: `src/services` — environment-adaptive client-side business logic
- Server Services: `src/server/services` — platform-agnostic business logic
- Database: `packages/database` — schemas/models/repositories/migrations
- State: `src/store` — Zustand stores and slices
- Integrations: `src/libs` — analytics/auth/trpc/logging/runtime helpers
- Tools: `src/tools` — built-in tool system
-
-## Common Tasks
-
- Add Web API route: `src/app/(backend)/webapi/<module>/route.ts`
- Add tRPC endpoint: `src/server/routers/{edge|lambda|desktop}/...`
- Add client/server service: `src/services/<domain>/{client|server}.ts` (client: PGLite; server: tRPC)
- Add server service: `src/server/services/<domain>`
- Add a new model/provider: `src/config/modelProviders/<provider>.ts` + `packages/model-bank/src/aiModels/<provider>.ts` + `packages/model-runtime/src/<provider>/index.ts`
- Add DB schema/model/repository: `packages/database/src/{schemas|models|repositories}`
- Add Zustand slice: `src/store/<domain>/slices`
-
-## Env Modes
-
- `NEXT_PUBLIC_CLIENT_DB`: selects client DB mode (e.g., `pglite`) vs server-backed
- `NEXT_PUBLIC_IS_DESKTOP_APP`: enables desktop-specific routes and behavior
- `NEXT_PUBLIC_SERVICE_MODE`: controls service routing preference (client/server)
-
-## Boundaries
-
- Keep client logic in `src/services`; server-only logic stays in `src/server/services`
- Don’t mix Web API (`webapi/`) with tRPC (`src/server/routers/`)
- Place business UI under `src/features`, global reusable UI under `src/components`
+- **Browser/PWA**: React UI → Client Service → Direct Model Access → PGLite (Web WASM)
+- **Server**: React UI → Client Service → tRPC Lambda → Server Services → PostgreSQL (Remote)
+- **Desktop**:
+  - Cloud sync disabled: Electron UI → Client Service → tRPC Lambda → Local Server Services → PGLite (Node WASM)
+  - Cloud sync enabled: Electron UI → Client Service → tRPC Lambda → Cloud Server Services → PostgreSQL (Remote)
@@ -4,20 +4,12 @@ globs:
 alwaysApply: true
 ---

-# 📋 Available Rules Index
+# Available project rules index

-The following rules are available via `read_file` from the `.cursor/rules/` directory:
-
-## General
-
- `project-introduce.mdc` – Project description and tech stack
- `cursor-rules.mdc` – Cursor rules authoring and optimization guide
- `code-review.mdc` – How to code review
+All following rules are saved under `.cursor/rules/` directory:

 ## Backend

- `backend-architecture.mdc` – Backend layer architecture and design guidelines
- `define-database-model.mdc` – Database model definition guidelines
 - `drizzle-schema-style-guide.mdc` – Style guide for defining Drizzle ORM schemas

 ## Frontend
@@ -42,7 +34,6 @@ The following rules are available via `read_file` from the `.cursor/rules/` dire

 ## Debugging

- `debug.mdc` – General debugging guide
 - `debug-usage.mdc` – Using the debug package and namespace conventions

 ## Testing
@@ -1,31 +0,0 @@
---
-description:
-globs:
-alwaysApply: true
---
-
-## System Role
-
-You are an expert in full-stack Web development, proficient in JavaScript, TypeScript, CSS, React, Node.js, Next.js, Postgresql, Redis, S3, all kinds of network protocols.
-
-You are an LLM expert, you are familiar with all kinds of LLM models, ai agents, ai workflow, prompt engineering and context engineering.
-
-You are an expert in Ai art. In Ai image generation, you are proficient in Stable Diffusion and ComfyUI's architectural principles, workflows, model structures, parameter configurations, training methods, and inference optimization.
-
-You are an expert in UI/UX design, proficient in web interaction patterns, responsive design, accessibility, and user behavior optimization. You excel at improving user retention and paid conversion rates through various interaction details.
-
-## Problem Solving
-
- When modifying existing code, clearly describe the differences and reasons for the changes
- Provide alternative solutions that may be better overall or superior in specific aspects
- Provide optimization suggestions for deprecated API usage
- Cite sources whenever possible at the end, not inline
- When you provide multiple solutions, provide the recommended solution first, and note it as `Recommended`
- Express uncertainty when there might not be a correct answer, instead of take action by guessing and assuming
-
-## Code Implementation
-
- Focus on maintainable over being performant
- Be sure to reference file path
- If doc links or required files are missing, ask for them before proceeding with the task rather than making assumptions
- If you're unable to get valid result when using tools, please clearly state in the output
@@ -10,61 +10,11 @@ alwaysApply: false

 - avoid explicit type annotations when TypeScript can infer types.
 - avoid implicitly `any` variables; explicitly type when necessary (e.g., `let a: number` instead of `let a`).
- use the most accurate type possible (e.g., prefer `Record<PropertyKey, unknown>` over `object`).
+- use the most accurate type possible (e.g., prefer `Record<PropertyKey, unknown>` over `object` and `any`).
 - prefer `interface` over `type` for object shapes (e.g., React component props). Keep `type` for unions, intersections, and utility types.
 - prefer `as const satisfies XyzInterface` over plain `as const` when suitable.
- prefer `@ts-expect-error` over `@ts-ignore`
- prefer `Record<string, any>` over `any`
-
- **Avoid unnecessary null checks**: Before adding `xxx !== null`, `?.`, `??`, or `!.`, read the type definition to confirm the necessary. **Example:**
-
-  ```typescript
-  // ❌ Wrong: budget.spend and budget.maxBudget is number, not number | null
-  if (budget.spend !== null && budget.maxBudget !== null && budget.spend >= budget.maxBudget) {
-    // ...
-  }
-
-  // ✅ Right
-  if (budget.spend >= budget.maxBudget) {
-    // ...
-  }
-  ```
-
- **Avoid redundant runtime checks**: Don't add runtime validation for conditions already guaranteed by types or previous checks. Trust the type system and calling contract. **Example:**
-
-  ```typescript
-  // ❌ Wrong: Adding impossible-to-fail checks
-  const due = await db.query.budgets.findMany({
-    where: and(isNotNull(budgets.budgetDuration)), // Already filtered non-null
-  });
-  const result = due.map(b => {
-    const nextReset = computeNextResetAt(b.budgetResetAt!, b.budgetDuration!);
-    if (!nextReset) { // This check is impossible to fail
-      throw new Error(`Unexpected null nextResetAt`);
-    }
-    return nextReset;
-  });
-
-  // ✅ Right: Trust the contract
-  const due = await db.query.budgets.findMany({
-    where: and(isNotNull(budgets.budgetDuration)),
-  });
-  const result = due.map(b => computeNextResetAt(b.budgetResetAt!, b.budgetDuration!));
-  ```
-
- **Avoid meaningless null/undefined parameters**: Don't accept null/undefined for parameters that have no business meaning when null. Design strict function contracts. **Example:**
-
-  ```typescript
-  // ❌ Wrong: Function accepts meaningless null input
-  function computeNextResetAt(currentResetAt: Date, durationStr: string | null): Date | null {
-    if (!durationStr) return null; // Why accept null if it just returns null?
-  }
-
-  // ✅ Right: Strict contract, clear responsibility
-  function computeNextResetAt(currentResetAt: Date, durationStr: string): Date {
-    // Function has single clear purpose, caller ensures valid input
-  }
-  ```
+- prefer `@ts-expect-error` over `@ts-ignore` over `as any`
+- Avoid meaningless null/undefined parameters; design strict function contracts.

 ## Imports and Modules

@@ -1,87 +0,0 @@
-name: '🐛 反馈缺陷'
-description: '反馈一个问题缺陷'
-labels: ['unconfirm']
-type: Bug
-body:
-  - type: markdown
-    attributes:
-      value: |
-        在创建新的 Issue 之前，请先[搜索已有问题](https://github.com/lobehub/lobe-chat/issues)，如果发现已有类似的问题，请给它 **👍 点赞**，这样可以帮助我们更快地解决问题。  
-        如果你在使用过程中遇到问题，可以尝试以下方式获取帮助：  
-        - 在 [GitHub Discussions](https://github.com/lobehub/lobe-chat/discussions) 的版块发起讨论。  
-        - 在 [LobeChat 社区](https://discord.gg/AYFPHvv2jT) 提问，与其他用户交流。 
-  - type: dropdown
-    attributes:
-      label: '📦 部署环境'
-      multiple: true
-      options:
-        - 'Official Preview'
-        - 'Official Cloud'
-        - 'Vercel'
-        - 'Zeabur'
-        - 'Sealos'
-        - 'Netlify'
-        - 'Docker'
-        - 'Other'
-    validations:
-      required: true
-  - type: dropdown
-    attributes:
-      label: '📦 部署模式'
-      multiple: true
-      options:
-        - '客户端模式(lobe-chat 镜像)'
-        - '客户端 Pglite 模式(lobe-chat-pglite 镜像)'
-        - '服务端模式(lobe-chat-database 镜像)'
-    validations:
-      required: true
-  - type: input
-    attributes:
-      label: '📌 软件版本'
-    validations:
-      required: true
-
-  - type: dropdown
-    attributes:
-      label: '💻 系统环境'
-      multiple: true
-      options:
-        - 'Windows'
-        - 'macOS'
-        - 'Ubuntu'
-        - 'Other Linux'
-        - 'iOS'
-        - 'Android'
-        - 'Other'
-    validations:
-      required: true
-  - type: dropdown
-    attributes:
-      label: '🌐 浏览器'
-      multiple: true
-      options:
-        - 'Chrome'
-        - 'Edge'
-        - 'Safari'
-        - 'Firefox'
-        - 'Other'
-    validations:
-      required: true
-  - type: textarea
-    attributes:
-      label: '🐛 问题描述'
-      description: 请提供一个清晰且简洁的问题描述，若上述选项为`Other`，也请详细说明。
-    validations:
-      required: true
-  - type: textarea
-    attributes:
-      label: '📷 复现步骤'
-      description: 请提供一个清晰且简洁的描述，说明如何复现问题。
-  - type: textarea
-    attributes:
-      label: '🚦 期望结果'
-      description: 请提供一个清晰且简洁的描述，说明您期望发生什么。
-  - type: textarea
-    attributes:
-      label: '📝 补充信息'
-      description: 如果您的问题需要进一步说明，或者您遇到的问题无法在一个简单的示例中复现，请在这里添加更多信息。
@@ -1,21 +0,0 @@
-name: '🌠 功能需求'
-description: '提出需求或建议'
-title: '[Request] '
-type: Feature
-body:
-  - type: textarea
-    attributes:
-      label: '🥰 需求描述'
-      description: 请添加一个清晰且简洁的问题描述，阐述您希望通过这个功能需求解决的问题。
-    validations:
-      required: true
-  - type: textarea
-    attributes:
-      label: '🧐 解决方案'
-      description: 请清晰且简洁地描述您想要的解决方案。
-    validations:
-      required: true
-  - type: textarea
-    attributes:
-      label: '📝 补充信息'
-      description: 在这里添加关于问题的任何其他背景信息。
@@ -1,7 +1,7 @@
 contact_links:
-  - name: Ask a question for self-hosting | 咨询自部署问题
+  - name: Ask a question for self-hosting
    url: https://github.com/lobehub/lobe-chat/discussions/new?category=self-hosting-%E7%A7%81%E6%9C%89%E5%8C%96%E9%83%A8%E7%BD%B2
-    about: Please post questions, and ideas in discussions. | 请在讨论区发布问题和想法。
-  - name: Questions and ideas | 其他问题和想法
+    about: Please post questions, and ideas in discussions.
+  - name: Questions and ideas
    url: https://github.com/lobehub/lobe-chat/discussions/new/choose
-    about: Please post questions, and ideas in discussions. | 请在讨论区发布问题和想法。
+    about: Please post questions, and ideas in discussions.
@@ -1,4 +1,4 @@
-#### 💻 变更类型 | Change Type
+#### 💻 Change Type

 <!-- For change type, change [ ] to [x]. -->

@@ -12,10 +12,10 @@
 - [ ] 📝 docs
 - [ ] 🔨 chore

-#### 🔀 变更说明 | Description of Change
+#### 🔀 Description of Change

 <!-- Thank you for your Pull Request. Please provide a description above. -->

-#### 📝 补充信息 | Additional Information
+#### 📝 Additional Information

 <!-- Add any other context about the Pull Request here. -->
@@ -0,0 +1,78 @@
+// @ts-check
+/**
+ * Lock closed issues after 7 days of inactivity
+ * @param {object} github - GitHub API client
+ * @param {object} context - GitHub Actions context
+ */
+module.exports = async ({ github, context }) => {
+  const sevenDaysAgo = new Date();
+  sevenDaysAgo.setDate(sevenDaysAgo.getDate() - 7);
+
+  const lockComment = `This issue has been automatically locked since it was closed and has not had any activity for 7 days. If you're experiencing a similar issue, please file a new issue and reference this one if it's relevant.`;
+
+  let page = 1;
+  let hasMore = true;
+  let totalLocked = 0;
+
+  while (hasMore) {
+    // Get closed issues (pagination)
+    const { data: issues } = await github.rest.issues.listForRepo({
+      owner: context.repo.owner,
+      repo: context.repo.repo,
+      state: 'closed',
+      sort: 'updated',
+      direction: 'asc',
+      per_page: 100,
+      page: page,
+    });
+
+    if (issues.length === 0) {
+      hasMore = false;
+      break;
+    }
+
+    for (const issue of issues) {
+      // Skip if already locked
+      if (issue.locked) continue;
+
+      // Skip pull requests
+      if (issue.pull_request) continue;
+
+      // Check if updated more than 7 days ago
+      const updatedAt = new Date(issue.updated_at);
+      if (updatedAt > sevenDaysAgo) {
+        // Since issues are sorted by updated_at ascending,
+        // once we hit a recent issue, all remaining will be recent too
+        hasMore = false;
+        break;
+      }
+
+      try {
+        // Add comment before locking
+        await github.rest.issues.createComment({
+          owner: context.repo.owner,
+          repo: context.repo.repo,
+          issue_number: issue.number,
+          body: lockComment,
+        });
+
+        // Lock the issue
+        await github.rest.issues.lock({
+          owner: context.repo.owner,
+          repo: context.repo.repo,
+          issue_number: issue.number,
+          lock_reason: 'resolved',
+        });
+
+        totalLocked++;
+        console.log(`Locked issue #${issue.number}: ${issue.title}`);
+      } catch (error) {
+        console.error(`Failed to lock issue #${issue.number}: ${error.message}`);
+      }
+    }
+
+    page++;
+  }
+
+  console.log(`Total issues locked: ${totalLocked}`);
+};
@@ -0,0 +1,109 @@
+name: Claude Translator
+concurrency:
+  group: translator-${{ github.event.comment.id || github.event.issue.number || github.event.review.id }}
+  cancel-in-progress: false
+
+on:
+  issues:
+    types: [opened]
+  issue_comment:
+    types: [created, edited]
+  pull_request_review:
+    types: [submitted, edited]
+  pull_request_review_comment:
+    types: [created, edited]
+
+jobs:
+  translate:
+    if: |
+      (github.event_name == 'issues') ||
+      (github.event_name == 'issue_comment' && github.event.sender.type != 'Bot') ||
+      (github.event_name == 'pull_request_review' && github.event.sender.type != 'Bot') ||
+      (github.event_name == 'pull_request_review_comment' && github.event.sender.type != 'Bot')
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      # update issues/comments
+      issues: write
+      pull-requests: write
+      id-token: write
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
+
+      - name: Run Claude for translation
+        uses: anthropics/claude-code-action@main
+        id: claude
+        with:
+          # Warning: Permissions should have been controlled by workflow permission.
+          # Now `contents: read` is safe for files, but we could make a fine-grained token to control it.
+          # See: https://github.com/anthropics/claude-code-action/blob/main/docs/security.md
+          github_token: ${{ secrets.GH_TOKEN }}
+          allowed_non_write_users: "*"
+          claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
+          claude_args: "--allowed-tools Bash(gh issue:*),Bash(gh api:repos/*/issues:*),Bash(gh api:repos/*/pulls/*/reviews/*),Bash(gh api:repos/*/pulls/comments/*)"
+          prompt: |
+            You are a multilingual translation assistant. You need to respond to the following four types of GitHub Webhook events:
+
+            - issues
+            - issue_comment
+            - pull_request_review
+            - pull_request_review_comment
+
+            Please complete the following tasks:
+
+            1. Retrieve complete information for the current event.
+
+               - If the current event is 'issues', get the issue information.
+               - If the current event is 'issue_comment', get the comment information.
+               - If the current event is 'pull_request_review', get the review information.
+               - If the current event is 'pull_request_review_comment', get the comment information.
+
+            2. Intelligently detect content.
+
+                - If the retrieved information is already translated content following the format requirements, check if the translation matches the original content. If not, retranslate to match and follow the format requirements.
+                - If the retrieved information is untranslated content, check its language. If not in English, translate to English.
+                - If the retrieved information is partially translated to English, translate it completely to English.
+                - If the retrieved information contains references to already translated content, clean the referenced content to contain only English. Referenced content should not include "This xxx was translated by Claude" and "Original Content" etc.
+                - If the retrieved information contains other types of references (i.e., references to non-Claude translated content), keep them as-is without translation.
+                - If the retrieved information is email reply content, place email content references at the end during translation. Include only the reply content itself in both original and translated content, without email content references.
+                - If the retrieved information doesn't need any processing, skip the task.
+
+            3. Format requirements:
+
+               - Title: English translation (if non-English)
+               - Content format:
+                 > [!NOTE]
+                 > This issue/comment/review was translated by Claude.
+
+                 [Translated content]
+
+                 ---
+                 <details>
+                 <summary>Original Content</summary>
+                 [Original content]
+                 </details>
+
+            4. Update using gh tool:
+
+               - Choose the correct command based on the Event type in environment information:
+                 - If Event is 'issues': gh issue edit [ISSUE_NUMBER] --title "[English title]" --body "[Translated content + Original content]"
+                 - If Event is 'issue_comment': gh api -X PATCH /repos/${{ github.repository }}/issues/comments/${{ github.event.comment.id }} -f body="[Translated content + Original content]"
+                 - If Event is 'pull_request_review': gh api -X PUT /repos/${{ github.repository }}/pulls/${{ github.event.pull_request.number }}/reviews/${{ github.event.review.id }} -f body="[Translated content]"
+                 - If Event is 'pull_request_review_comment': gh api -X PATCH /repos/${{ github.repository }}/pulls/comments/${{ github.event.comment.id }} -f body="[Translated content + Original content]"
+
+            <environment_context>
+            - Event: ${{ github.event_name }}
+            - Issue Number: ${{ github.event.issue.number }}
+            - Repository: ${{ github.repository }}
+            - (Review) Comment ID: ${{ github.event.comment.id || 'N/A' }}
+            - Pull Request Number: ${{ github.event.pull_request.number || 'N/A' }}
+            - Review ID: ${{ github.event.review.id || 'N/A' }}
+            </environment_context>
+
+
+            Use the following command to get complete information:
+            gh issue view ${{ github.event.issue.number }} --json title,body,comments
@@ -1,14 +0,0 @@
-name: Issue Translate
-on:
-  issue_comment:
-    types: [created]
-  issues:
-    types: [opened]
-
-jobs:
-  build:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: usthe/issues-translate-action@v2.7
-        with:
-          BOT_GITHUB_TOKEN: ${{ secrets.GH_TOKEN }}
@@ -0,0 +1,26 @@
+name: "Lock Stale Issues"
+
+on:
+  schedule:
+    - cron: "0 1 * * *"
+  workflow_dispatch:
+
+permissions:
+  issues: write
+
+concurrency:
+  group: lock-threads
+
+jobs:
+  lock-closed-issues:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Lock closed issues after 7 days of inactivity
+        uses: actions/github-script@v7
+        with:
+          script: |
+            const lockScript = require('./.github/scripts/lock-closed-issues.js');
+            await lockScript({ github, context });
@@ -18,6 +18,7 @@ jobs:
          - web-crawler
          - electron-server-ipc
          - utils
+          - python-interpreter
          - context-engine
          - agent-runtime

@@ -11,6 +11,7 @@
    { "rule": "prettier/prettier", "severity": "off" },
    { "rule": "react/jsx-sort-props", "severity": "off" },
    { "rule": "sort-keys-fix/sort-keys-fix", "severity": "off" },
+    { "rule": "simple-import-sort/exports", "severity": "off" },
    { "rule": "typescript-sort-keys/interface", "severity": "off" }
  ],
  "eslint.validate": [
@@ -81,7 +82,7 @@

    "**/src/config/modelProviders/*.ts": "${filename} • provider",
    "**/packages/model-bank/src/aiModels/*.ts": "${filename} • model",
-    "**/packages/model-runtime/src/*/index.ts": "${dirname} • runtime",
+    "**/packages/model-runtime/src/providers/*/index.ts": "${dirname} • runtime",

    "**/src/server/services/*/index.ts": "${dirname} • server/service",
    "**/src/server/routers/lambda/*.ts": "${filename} • lambda",
@@ -44,21 +44,7 @@ The project follows a well-organized monorepo structure:

 #### TypeScript

- Follow strict TypeScript practices for type safety and code quality
- Use proper type annotations
 - Prefer interfaces over types for object shapes
- Use generics for reusable components
-
-#### React Components
-
- Use functional components with hooks
-
-#### Database Schema
-
- Follow Drizzle ORM naming conventions
- Use plural snake_case for table names
- Implement proper foreign key relationships
- Follow the schema style guide

 ### Testing Strategy

@@ -67,64 +53,57 @@ The project follows a well-organized monorepo structure:
 **Commands**:

 - Web: `bunx vitest run --silent='passed-only' '[file-path-pattern]'`
- Packages: `cd packages/[package-name] && bunx vitest run --silent='passed-only' '[file-path-pattern]'`
+- Packages: `cd packages/[package-name] && bunx vitest run --silent='passed-only' '[file-path-pattern]'` (each subpackage contains its own vitest.config.mts)

 **Important Notes**:

 - Wrap file paths in single quotes to avoid shell expansion
- Never run `bun run test` - this runs all tests and takes ~10 minutes
- If a test fails twice, stop and ask for help
- Always add tests for new code
+- Never run `bun run test` - this runs all tests and takes \~10 minutes

 ### Type Checking

 - Use `bun run type-check` to check for type errors
- Ensure all TypeScript errors are resolved before committing

-### Internationalization
+### i18n

- Add new keys to `src/locales/default/namespace.ts`
- Translate at least `zh-CN` files for development preview
- Use hierarchical nested objects, not flat keys
- Don't run `pnpm i18n` manually (handled by CI)
+- **Keys**: Add to `src/locales/default/namespace.ts`
+- **Dev**: Translate `locales/zh-CN/namespace.json` locale file only for preview
+- DON'T run `pnpm i18n`, let CI auto handle it

-## Available Development Rules
+## Project Rules Index

-The project provides comprehensive rules in `.cursor/rules/` directory:
+All following rules are saved under `.cursor/rules/` directory:

-### Core Development
+### Backend

- `backend-architecture.mdc` - Three-layer architecture and data flow
- `react-component.mdc` - Component patterns and UI library usage
- `drizzle-schema-style-guide.mdc` - Database schema conventions
- `define-database-model.mdc` - Model templates and CRUD patterns
- `i18n.mdc` - Internationalization workflow
+- `drizzle-schema-style-guide.mdc` – Style guide for defining Drizzle ORM schemas

-### State Management & UI
+### Frontend

- `zustand-slice-organization.mdc` - Store organization patterns
- `zustand-action-patterns.mdc` - Action implementation patterns
- `packages/react-layout-kit.mdc` - Flex layout component usage
+- `react-component.mdc` – React component style guide and conventions
+- `i18n.mdc` – Internationalization guide using react-i18next
+- `typescript.mdc` – TypeScript code style guide
+- `packages/react-layout-kit.mdc` – Usage guide for react-layout-kit

-### Testing & Quality
+### State Management

- `testing-guide/testing-guide.mdc` - Comprehensive testing strategy
- `code-review.mdc` - Code review process and standards
+- `zustand-action-patterns.mdc` – Recommended patterns for organizing Zustand actions
+- `zustand-slice-organization.mdc` – Best practices for structuring Zustand slices

 ### Desktop (Electron)

- `desktop-feature-implementation.mdc` - Main/renderer process patterns
- `desktop-local-tools-implement.mdc` - Tool integration workflow
- `desktop-menu-configuration.mdc` - Menu system configuration
- `desktop-window-management.mdc` - Window management patterns
- `desktop-controller-tests.mdc` - Controller testing guide
+- `desktop-feature-implementation.mdc` – Implementing new Electron desktop features
+- `desktop-controller-tests.mdc` – Desktop controller unit testing guide
+- `desktop-local-tools-implement.mdc` – Workflow to add new desktop local tools
+- `desktop-menu-configuration.mdc` – Desktop menu configuration guide
+- `desktop-window-management.mdc` – Desktop window management guide

-## Best Practices
+### Debugging

- **Conservative for existing code, modern approaches for new features**
- **Code Language**: Use Chinese for files with existing Chinese comments, American English for new files
- Always add tests for new functionality
- Follow the established patterns in the codebase
- Use proper error handling and logging
- Implement proper accessibility features
- Consider internationalization from the start
+- `debug-usage.mdc` – Using the debug package and namespace conventions
+
+### Testing
+
+- `testing-guide/testing-guide.mdc` – Comprehensive testing guide for Vitest
+- `testing-guide/electron-ipc-test.mdc` – Electron IPC interface testing strategy
+- `testing-guide/db-model-test.mdc` – Database Model testing guide
@@ -2,6 +2,215 @@

 # Changelog

+### [Version 1.133.3](https://github.com/lobehub/lobe-chat/compare/v1.133.2...v1.133.3)
+
+<sup>Released on **2025-10-01**</sup>
+
+#### ♻ Code Refactoring
+
+- **misc**: Refactor a `ssrf-safe-fetch` module.
+
+#### 🐛 Bug Fixes
+
+- **misc**: Fix frontend random API key config not work.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Code refactoring
+
+- **misc**: Refactor a `ssrf-safe-fetch` module, closes [#9474](https://github.com/lobehub/lobe-chat/issues/9474) ([92da716](https://github.com/lobehub/lobe-chat/commit/92da716))
+
+#### What's fixed
+
+- **misc**: Fix frontend random API key config not work, closes [#9477](https://github.com/lobehub/lobe-chat/issues/9477) [#9255](https://github.com/lobehub/lobe-chat/issues/9255) ([a194d48](https://github.com/lobehub/lobe-chat/commit/a194d48))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.133.2](https://github.com/lobehub/lobe-chat/compare/v1.133.1...v1.133.2)
+
+<sup>Released on **2025-09-30**</sup>
+
+#### 💄 Styles
+
+- **misc**: Add minimap to chat list for quick navigation.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Styles
+
+- **misc**: Add minimap to chat list for quick navigation, closes [#9470](https://github.com/lobehub/lobe-chat/issues/9470) ([8db47eb](https://github.com/lobehub/lobe-chat/commit/8db47eb))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.133.1](https://github.com/lobehub/lobe-chat/compare/v1.133.0...v1.133.1)
+
+<sup>Released on **2025-09-30**</sup>
+
+#### 💄 Styles
+
+- **misc**: Update i18n.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Styles
+
+- **misc**: Update i18n, closes [#9480](https://github.com/lobehub/lobe-chat/issues/9480) ([dfeb42c](https://github.com/lobehub/lobe-chat/commit/dfeb42c))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+## [Version 1.133.0](https://github.com/lobehub/lobe-chat/compare/v1.132.19...v1.133.0)
+
+<sup>Released on **2025-09-29**</sup>
+
+#### ✨ Features
+
+- **misc**: Add builtin Python plugin, add Claude Sonnet 4.5 model to AI chat models.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's improved
+
+- **misc**: Add builtin Python plugin, closes [#8873](https://github.com/lobehub/lobe-chat/issues/8873) ([fa6ef94](https://github.com/lobehub/lobe-chat/commit/fa6ef94))
+- **misc**: Add Claude Sonnet 4.5 model to AI chat models, closes [#9476](https://github.com/lobehub/lobe-chat/issues/9476) ([a30a65c](https://github.com/lobehub/lobe-chat/commit/a30a65c))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.132.19](https://github.com/lobehub/lobe-chat/compare/v1.132.18...v1.132.19)
+
+<sup>Released on **2025-09-29**</sup>
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.132.18](https://github.com/lobehub/lobe-chat/compare/v1.132.17...v1.132.18)
+
+<sup>Released on **2025-09-28**</sup>
+
+#### 🐛 Bug Fixes
+
+- **misc**: Refactor tools-engine and fix search token count.
+
+#### 💄 Styles
+
+- **misc**: Update i18n.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **misc**: Refactor tools-engine and fix search token count, closes [#9448](https://github.com/lobehub/lobe-chat/issues/9448) ([e82d4b7](https://github.com/lobehub/lobe-chat/commit/e82d4b7))
+
+#### Styles
+
+- **misc**: Update i18n, closes [#9449](https://github.com/lobehub/lobe-chat/issues/9449) ([b04a5d7](https://github.com/lobehub/lobe-chat/commit/b04a5d7))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.132.17](https://github.com/lobehub/lobe-chat/compare/v1.132.16...v1.132.17)
+
+<sup>Released on **2025-09-27**</sup>
+
+#### 🐛 Bug Fixes
+
+- **misc**: Fix input empty group name.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **misc**: Fix input empty group name, closes [#9441](https://github.com/lobehub/lobe-chat/issues/9441) ([f653ce1](https://github.com/lobehub/lobe-chat/commit/f653ce1))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.132.16](https://github.com/lobehub/lobe-chat/compare/v1.132.15...v1.132.16)
+
+<sup>Released on **2025-09-26**</sup>
+
+#### 🐛 Bug Fixes
+
+- **misc**: Resolve qwen-image-edit imageUrls conversion issue.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **misc**: Resolve qwen-image-edit imageUrls conversion issue, closes [#9414](https://github.com/lobehub/lobe-chat/issues/9414) ([ec5af1b](https://github.com/lobehub/lobe-chat/commit/ec5af1b))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
 ### [Version 1.132.15](https://github.com/lobehub/lobe-chat/compare/v1.132.14...v1.132.15)

 <sup>Released on **2025-09-25**</sup>
@@ -72,29 +72,4 @@ Some useful rules of this project. Read them when needed.

 ### 📋 Complete Rule Files

-**Core Development**
-
- `backend-architecture.mdc` - Three-layer architecture, data flow
- `react-component.mdc` - antd-style, Lobe UI usage
- `drizzle-schema-style-guide.mdc` - Schema naming, patterns
- `define-database-model.mdc` - Model templates, CRUD patterns
- `i18n.mdc` - Internationalization workflow
-
-**State & UI**
-
- `zustand-slice-organization.mdc` - Store organization
- `zustand-action-patterns.mdc` - Action patterns
- `packages/react-layout-kit.mdc` - flex layout components usage
-
-**Testing & Quality**
-
- `testing-guide/testing-guide.mdc` - Test strategy, mock patterns
- `code-review.mdc` - Review process and standards
-
-**Desktop (Electron)**
-
- `desktop-feature-implementation.mdc` - Main/renderer process patterns
- `desktop-local-tools-implement.mdc` - Tool integration workflow
- `desktop-menu-configuration.mdc` - App menu, context menu, tray menu
- `desktop-window-management.mdc` - Window creation, state management, multi-window
- `desktop-controller-tests.mdc` - Controller unit testing guide
+Some useful project rules are listed in @.cursor/rules/rules-index.mdc
@@ -382,14 +382,14 @@ In addition, these plugins are not limited to news aggregation, but can also ext

 <!-- PLUGIN LIST -->

-| Recent Submits                                                                                                                            | Description                                                                                                                |
-| ----------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------- |
-| [Web](https://lobechat.com/discover/plugin/web)<br/><sup>By **Proghit** on **2025-01-24**</sup>                                           | Smart web search that reads and analyzes pages to deliver comprehensive answers from Google results.<br/>`web` `search`    |
-| [Bing_websearch](https://lobechat.com/discover/plugin/Bingsearch-identifier)<br/><sup>By **FineHow** on **2024-12-22**</sup>              | Search for information from the internet base BingApi<br/>`bingsearch`                                                     |
-| [Google CSE](https://lobechat.com/discover/plugin/google-cse)<br/><sup>By **vsnthdev** on **2024-12-02**</sup>                            | Searches Google through their official CSE API.<br/>`web` `search`                                                         |
-| [Tongyi wanxiang Image Generator](https://lobechat.com/discover/plugin/alps-tongyi-image)<br/><sup>By **YoungTx** on **2024-08-09**</sup> | This plugin uses Alibaba's Tongyi Wanxiang model to generate images based on text prompts.<br/>`image` `tongyi` `wanxiang` |
+| Recent Submits                                                                                                               | Description                                                                                                             |
+| ---------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------- |
+| [PortfolioMeta](https://lobechat.com/discover/plugin/StockData)<br/><sup>By **portfoliometa** on **2025-09-27**</sup>        | Analyze stocks and get comprehensive real-time investment data and analytics.<br/>`stock`                               |
+| [Web](https://lobechat.com/discover/plugin/web)<br/><sup>By **Proghit** on **2025-01-24**</sup>                              | Smart web search that reads and analyzes pages to deliver comprehensive answers from Google results.<br/>`web` `search` |
+| [Bing_websearch](https://lobechat.com/discover/plugin/Bingsearch-identifier)<br/><sup>By **FineHow** on **2024-12-22**</sup> | Search for information from the internet base BingApi<br/>`bingsearch`                                                  |
+| [Google CSE](https://lobechat.com/discover/plugin/google-cse)<br/><sup>By **vsnthdev** on **2024-12-02**</sup>               | Searches Google through their official CSE API.<br/>`web` `search`                                                      |

-> 📊 Total plugins: [<kbd>**41**</kbd>](https://lobechat.com/discover/plugins)
+> 📊 Total plugins: [<kbd>**42**</kbd>](https://lobechat.com/discover/plugins)

 <!-- PLUGIN LIST -->

@@ -375,14 +375,14 @@ LobeChat 的插件生态系统是其核心功能的重要扩展，它极大地

 <!-- PLUGIN LIST -->

-| 最近新增                                                                                                                     | 描述                                                                               |
-| ---------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------- |
-| [网页](https://lobechat.com/discover/plugin/web)<br/><sup>By **Proghit** on **2025-01-24**</sup>                             | 智能网页搜索，读取和分析页面，以提供来自 Google 结果的全面答案。<br/>`网页` `搜索` |
-| [必应网页搜索](https://lobechat.com/discover/plugin/Bingsearch-identifier)<br/><sup>By **FineHow** on **2024-12-22**</sup>   | 通过 BingApi 搜索互联网上的信息<br/>`bingsearch`                                   |
-| [谷歌自定义搜索引擎](https://lobechat.com/discover/plugin/google-cse)<br/><sup>By **vsnthdev** on **2024-12-02**</sup>       | 通过他们的官方自定义搜索引擎 API 搜索谷歌。<br/>`网络` `搜索`                      |
-| [通义万象图像生成器](https://lobechat.com/discover/plugin/alps-tongyi-image)<br/><sup>By **YoungTx** on **2024-08-09**</sup> | 此插件使用阿里巴巴的通义万象模型根据文本提示生成图像。<br/>`图像` `通义` `万象`    |
+| 最近新增                                                                                                                   | 描述                                                                               |
+| -------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------- |
+| [PortfolioMeta](https://lobechat.com/discover/plugin/StockData)<br/><sup>By **portfoliometa** on **2025-09-27**</sup>      | 分析股票并获取全面的实时投资数据和分析。<br/>`股票`                                |
+| [网页](https://lobechat.com/discover/plugin/web)<br/><sup>By **Proghit** on **2025-01-24**</sup>                           | 智能网页搜索，读取和分析页面，以提供来自 Google 结果的全面答案。<br/>`网页` `搜索` |
+| [必应网页搜索](https://lobechat.com/discover/plugin/Bingsearch-identifier)<br/><sup>By **FineHow** on **2024-12-22**</sup> | 通过 BingApi 搜索互联网上的信息<br/>`bingsearch`                                   |
+| [谷歌自定义搜索引擎](https://lobechat.com/discover/plugin/google-cse)<br/><sup>By **vsnthdev** on **2024-12-02**</sup>     | 通过他们的官方自定义搜索引擎 API 搜索谷歌。<br/>`网络` `搜索`                      |

-> 📊 Total plugins: [<kbd>**41**</kbd>](https://lobechat.com/discover/plugins)
+> 📊 Total plugins: [<kbd>**42**</kbd>](https://lobechat.com/discover/plugins)

 <!-- PLUGIN LIST -->

@@ -336,7 +336,6 @@ export default class Browser {
      vibrancy: 'sidebar',
      visualEffectState: 'active',
      webPreferences: {
-        backgroundThrottling: false,
        contextIsolation: true,
        preload: join(preloadDir, 'index.js'),
      },
@@ -1,4 +1,52 @@
 [
+  {
+    "children": {
+      "improvements": ["Add minimap to chat list for quick navigation."]
+    },
+    "date": "2025-09-30",
+    "version": "1.133.2"
+  },
+  {
+    "children": {
+      "improvements": ["Update i18n."]
+    },
+    "date": "2025-09-30",
+    "version": "1.133.1"
+  },
+  {
+    "children": {
+      "features": ["Add builtin Python plugin, add Claude Sonnet 4.5 model to AI chat models."]
+    },
+    "date": "2025-09-29",
+    "version": "1.133.0"
+  },
+  {
+    "children": {},
+    "date": "2025-09-29",
+    "version": "1.132.19"
+  },
+  {
+    "children": {
+      "fixes": ["Refactor tools-engine and fix search token count."],
+      "improvements": ["Update i18n."]
+    },
+    "date": "2025-09-28",
+    "version": "1.132.18"
+  },
+  {
+    "children": {
+      "fixes": ["Fix input empty group name."]
+    },
+    "date": "2025-09-27",
+    "version": "1.132.17"
+  },
+  {
+    "children": {
+      "fixes": ["Resolve qwen-image-edit imageUrls conversion issue."]
+    },
+    "date": "2025-09-26",
+    "version": "1.132.16"
+  },
  {
    "children": {
      "fixes": ["Add proxyUrl configuration for NEW API provider."]
@@ -16,6 +16,7 @@ table agents {
  provider text
  system_role text
  tts jsonb
+  virtual boolean [default: false]
  opening_message text
  opening_questions text[] [default: `[]`]
  accessed_at "timestamp with time zone" [not null, default: `now()`]
@@ -150,6 +150,11 @@
      "total": "الإجمالي المستهلك"
    }
  },
+  "minimap": {
+    "jumpToMessage": "الانتقال إلى الرسالة رقم {{index}}",
+    "nextMessage": "الرسالة التالية",
+    "previousMessage": "الرسالة السابقة"
+  },
  "newAgent": "مساعد جديد",
  "pin": "تثبيت",
  "pinOff": "إلغاء التثبيت",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "وصف المحتوى الذي ترغب في إنشائه"
    },
+    "quality": {
+      "label": "جودة الصورة",
+      "options": {
+        "hd": "عالي الدقة",
+        "standard": "عادي"
+      }
+    },
    "seed": {
      "label": "البذرة",
      "random": "بذرة عشوائية"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4 يحسن بشكل كبير على قدرات Sonnet 3.7 الرائدة في الصناعة، ويظهر أداءً ممتازًا في الترميز، محققًا 72.7% في SWE-bench. يوازن النموذج بين الأداء والكفاءة، مناسب للحالات الداخلية والخارجية، ويحقق تحكمًا أكبر في التنفيذ من خلال قابلية تحكم محسنة."
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "كلود سونيت 4.5 هو أذكى نموذج قدمته شركة أنثروبيك حتى الآن."
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B هو نموذج لغة ضخم نادر التنشيط يحتوي على 72 مليار معلمة و16 مليار معلمة نشطة، يعتمد على بنية الخبراء المختلطين المجمعة (MoGE). في مرحلة اختيار الخبراء، يتم تجميع الخبراء وتقيد تنشيط عدد متساوٍ من الخبراء داخل كل مجموعة لكل رمز، مما يحقق توازنًا في تحميل الخبراء ويعزز بشكل كبير كفاءة نشر النموذج على منصة Ascend."
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "كلود سونيت 4 نموذج تفكيري يمكنه إنتاج استجابات شبه فورية أو تفكير تدريجي مطول، حيث يمكن للمستخدم رؤية هذه العمليات بوضوح."
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "كلود سونيت 4.5 هو أذكى نموذج قدمته شركة أنثروبيك حتى الآن."
+  },
  "codegeex-4": {
    "description": "CodeGeeX-4 هو مساعد برمجي قوي، يدعم مجموعة متنوعة من لغات البرمجة في الإجابة الذكية وإكمال الشيفرة، مما يعزز من كفاءة التطوير."
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "kimi-k2 هو نموذج أساسي بمعمارية MoE يتمتع بقدرات قوية للغاية في البرمجة وقدرات الوكيل (Agent)، بإجمالي معلمات يبلغ 1 تريليون والمعلمات المُفعَّلة 32 مليار. في اختبارات الأداء المعيارية للفئات الرئيسية مثل الاستدلال المعرفي العام والبرمجة والرياضيات والوكلاء (Agent)، تفوق أداء نموذج K2 على النماذج المفتوحة المصدر السائدة الأخرى."
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2 هو نموذج لغوي خبير هجين واسع النطاق (MoE) تم تطويره بواسطة AI جانب القمر المظلم، يحتوي على تريليون معلمة إجمالية و 32 مليار معلمة تنشيط في كل تمريرة أمامية. تم تحسينه لقدرات الوكيل، بما في ذلك استخدام الأدوات المتقدمة، الاستدلال، وتركيب الشيفرة."
+  },
  "kimi-latest": {
    "description": "يستخدم منتج كيمي المساعد الذكي أحدث نموذج كبير من كيمي، وقد يحتوي على ميزات لم تستقر بعد. يدعم فهم الصور، وسيختار تلقائيًا نموذج 8k/32k/128k كنموذج للتسعير بناءً على طول سياق الطلب."
  },
@@ -110,6 +110,9 @@
  "ollama": {
    "description": "تغطي نماذج Ollama مجموعة واسعة من مجالات توليد الشيفرة، والعمليات الرياضية، ومعالجة اللغات المتعددة، والتفاعل الحواري، وتدعم احتياجات النشر على مستوى المؤسسات والتخصيص المحلي."
  },
+  "ollamacloud": {
+    "description": "توفر Ollama Cloud خدمة استدلال مُدارة رسميًا، تتيح الوصول الفوري إلى مكتبة نماذج Ollama، وتدعم واجهة متوافقة مع OpenAI."
+  },
  "openai": {
    "description": "OpenAI هي مؤسسة رائدة عالميًا في أبحاث الذكاء الاصطناعي، حيث دفعت النماذج التي طورتها مثل سلسلة GPT حدود معالجة اللغة الطبيعية. تلتزم OpenAI بتغيير العديد من الصناعات من خلال حلول الذكاء الاصطناعي المبتكرة والفعالة. تتمتع منتجاتهم بأداء ملحوظ وفعالية من حيث التكلفة، وتستخدم على نطاق واسع في البحث والتجارة والتطبيقات الابتكارية."
  },
@@ -1,4 +1,11 @@
 {
+  "codeInterpreter": {
+    "error": "خطأ في التنفيذ",
+    "executing": "جارٍ التنفيذ...",
+    "files": "الملفات:",
+    "output": "الإخراج:",
+    "returnValue": "قيمة الإرجاع:"
+  },
  "dalle": {
    "autoGenerate": "توليد تلقائي",
    "downloading": "صلاحية روابط الصور المُولَّدة بواسطة DallE3 تدوم ساعة واحدة فقط، يتم تحميل الصور إلى الجهاز المحلي...",
@@ -150,6 +150,11 @@
      "total": "Общо разходи"
    }
  },
+  "minimap": {
+    "jumpToMessage": "Отиди до съобщение № {{index}}",
+    "nextMessage": "Следващо съобщение",
+    "previousMessage": "Предишно съобщение"
+  },
  "newAgent": "Нов агент",
  "pin": "Закачи",
  "pinOff": "Откачи",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "Опишете съдържанието, което искате да генерирате"
    },
+    "quality": {
+      "label": "Качество на изображението",
+      "options": {
+        "hd": "Висока резолюция",
+        "standard": "Стандартно"
+      }
+    },
    "seed": {
      "label": "Семена",
      "random": "Случаен семенен код"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4 значително подобрява водещите в индустрията възможности на Sonnet 3.7, с отлични резултати в кодиране и постига водещи 72.7% в SWE-bench. Моделът балансира производителност и ефективност, подходящ е за вътрешни и външни случаи и предлага по-голям контрол чрез подобрена управляемост."
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "Claude Sonnet 4.5 е най-интелигентният модел на Anthropic досега."
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B е голям езиков модел с 72 милиарда параметри и 16 милиарда активирани параметри, базиран на архитектурата с групирани смесени експерти (MoGE). Той групира експертите по време на избора им и ограничава активацията на токените да активират равен брой експерти във всяка група, което осигурява балансирано натоварване на експертите и значително подобрява ефективността на разгръщане на модела на платформата Ascend."
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "Claude Sonnet 4 мисловен модел може да генерира почти мигновени отговори или удължено стъпково мислене, като потребителите могат ясно да проследят тези процеси."
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "Claude Sonnet 4.5 е най-интелигентният модел на Anthropic досега."
+  },
  "codegeex-4": {
    "description": "CodeGeeX-4 е мощен AI помощник за програмиране, който поддържа интелигентни въпроси и отговори и автоматично допълване на код за различни програмни езици, повишавайки ефективността на разработката."
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "Kimi-k2 е базов модел с MoE архитектура, който притежава изключителни възможности за работа с код и агентни функции. Общият брой параметри е 1T, а активните параметри са 32B. В бенчмарковете за основни категории като общо знание и разсъждение, програмиране, математика и агентни задачи, моделът K2 превъзхожда другите водещи отворени модели."
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2 е голям мащабен смесен експертен (MoE) езиков модел, разработен от AI на тъмната страна на Луната, с общо 1 трилион параметри и 32 милиарда активирани параметри при всяко предно преминаване. Той е оптимизиран за агентски способности, включително усъвършенствано използване на инструменти, разсъждения и синтез на код."
+  },
  "kimi-latest": {
    "description": "Kimi интелигентен асистент използва най-новия Kimi голям модел, който може да съдържа нестабилни функции. Поддържа разбиране на изображения и автоматично избира 8k/32k/128k модел за таксуване в зависимост от дължината на контекста на заявката."
  },
@@ -110,6 +110,9 @@
  "ollama": {
    "description": "Моделите, предоставени от Ollama, обхващат широк спектър от области, включително генериране на код, математически операции, многоезично обработване и диалогова интеракция, отговарящи на разнообразните нужди на предприятията и локализирани внедрявания."
  },
+  "ollamacloud": {
+    "description": "Ollama Cloud предлага официално хоствана услуга за изчисления, която осигурява достъп до библиотеката с модели на Ollama веднага след изваждане от кутията и поддържа интерфейс, съвместим с OpenAI."
+  },
  "openai": {
    "description": "OpenAI е водеща световна изследователска институция в областта на изкуствения интелект, чийто модели, като серията GPT, напредват в границите на обработката на естествен език. OpenAI се стреми да трансформира множество индустрии чрез иновации и ефективни AI решения. Продуктите им предлагат значителна производителност и икономичност, широко използвани в изследвания, бизнес и иновационни приложения."
  },
@@ -1,4 +1,11 @@
 {
+  "codeInterpreter": {
+    "error": "Грешка при изпълнение",
+    "executing": "Изпълнение...",
+    "files": "Файлове:",
+    "output": "Изход:",
+    "returnValue": "Върната стойност:"
+  },
  "dalle": {
    "autoGenerate": "Автоматично генериране",
    "downloading": "Връзките към изображенията, генерирани от DALL·E3, са валидни само за 1 час, кеширане на изображенията локално...",
@@ -150,6 +150,11 @@
      "total": "Gesamter Verbrauch"
    }
  },
+  "minimap": {
+    "jumpToMessage": "Zur Nachricht Nr. {{index}} springen",
+    "nextMessage": "Nächste Nachricht",
+    "previousMessage": "Vorherige Nachricht"
+  },
  "newAgent": "Neuer Assistent",
  "pin": "Anheften",
  "pinOff": "Anheften aufheben",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "Beschreiben Sie den Inhalt, den Sie generieren möchten"
    },
+    "quality": {
+      "label": "Bildqualität",
+      "options": {
+        "hd": "Hohe Auflösung",
+        "standard": "Standard"
+      }
+    },
    "seed": {
      "label": "Seed",
      "random": "Zufälliger Seed"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4 baut auf den branchenführenden Fähigkeiten von Sonnet 3.7 auf und zeigt herausragende Codierungsleistung mit einem Spitzenwert von 72,7 % bei SWE-bench. Das Modell bietet eine ausgewogene Kombination aus Leistung und Effizienz, geeignet für interne und externe Anwendungsfälle, und ermöglicht durch verbesserte Steuerbarkeit eine größere Kontrolle über die Ergebnisse."
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "Claude Sonnet 4.5 ist das bisher intelligenteste Modell von Anthropic."
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B ist ein spärlich besetztes großes Sprachmodell mit 72 Milliarden Parametern und 16 Milliarden aktivierten Parametern. Es basiert auf der gruppierten Mixture-of-Experts-Architektur (MoGE), bei der Experten in Gruppen eingeteilt werden und Tokens innerhalb jeder Gruppe eine gleiche Anzahl von Experten aktivieren, um eine ausgewogene Expertenauslastung zu gewährleisten. Dies verbessert die Effizienz der Modellausführung auf der Ascend-Plattform erheblich."
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "Claude Sonnet 4 Denkmodell kann nahezu sofortige Antworten oder verlängerte schrittweise Überlegungen erzeugen, die für den Nutzer klar nachvollziehbar sind."
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "Claude Sonnet 4.5 ist das bisher intelligenteste Modell von Anthropic."
+  },
  "codegeex-4": {
    "description": "CodeGeeX-4 ist ein leistungsstarker AI-Programmierassistent, der intelligente Fragen und Codevervollständigung in verschiedenen Programmiersprachen unterstützt und die Entwicklungseffizienz steigert."
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "kimi-k2 ist ein Basis-Modell mit MoE-Architektur und besonders starken Fähigkeiten im Bereich Code und Agenten. Es verfügt über insgesamt 1T Parameter und 32B aktivierte Parameter. In Benchmark-Tests der wichtigsten Kategorien – allgemeines Wissens-Reasoning, Programmierung, Mathematik und Agenten – übertrifft das K2-Modell die Leistung anderer gängiger Open‑Source‑Modelle."
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2 ist ein von Moon's Dark Side AI entwickeltes großes gemischtes Expertenmodell (MoE) mit insgesamt 1 Billion Parametern und 32 Milliarden aktivierten Parametern pro Vorwärtsdurchlauf. Es ist auf Agentenfähigkeiten optimiert, einschließlich fortgeschrittener Werkzeugnutzung, Schlussfolgerungen und Code-Synthese."
+  },
  "kimi-latest": {
    "description": "Das Kimi intelligente Assistenzprodukt verwendet das neueste Kimi Großmodell, das möglicherweise noch instabile Funktionen enthält. Es unterstützt die Bildverarbeitung und wählt automatisch das Abrechnungsmodell 8k/32k/128k basierend auf der Länge des angeforderten Kontexts aus."
  },
@@ -110,6 +110,9 @@
  "ollama": {
    "description": "Die von Ollama angebotenen Modelle decken ein breites Spektrum ab, darunter Code-Generierung, mathematische Berechnungen, mehrsprachige Verarbeitung und dialogbasierte Interaktionen, und unterstützen die vielfältigen Anforderungen an unternehmensgerechte und lokal angepasste Bereitstellungen."
  },
+  "ollamacloud": {
+    "description": "Ollama Cloud bietet offiziell gehostete Inferenzdienste, mit sofortigem Zugriff auf die Ollama-Modellbibliothek und Unterstützung für OpenAI-kompatible Schnittstellen."
+  },
  "openai": {
    "description": "OpenAI ist eine weltweit führende Forschungsinstitution im Bereich der künstlichen Intelligenz, deren entwickelte Modelle wie die GPT-Serie die Grenzen der Verarbeitung natürlicher Sprache vorantreiben. OpenAI setzt sich dafür ein, durch innovative und effiziente KI-Lösungen verschiedene Branchen zu transformieren. Ihre Produkte zeichnen sich durch herausragende Leistung und Wirtschaftlichkeit aus und finden breite Anwendung in Forschung, Wirtschaft und innovativen Anwendungen."
  },
@@ -1,4 +1,11 @@
 {
+  "codeInterpreter": {
+    "error": "Ausführungsfehler",
+    "executing": "Wird ausgeführt...",
+    "files": "Dateien:",
+    "output": "Ausgabe:",
+    "returnValue": "Rückgabewert:"
+  },
  "dalle": {
    "autoGenerate": "Automatisch generieren",
    "downloading": "Die von DallE3 generierten Bildlinks sind nur 1 Stunde lang gültig. Das Bild wird lokal zwischengespeichert...",
@@ -150,6 +150,11 @@
      "total": "Total Consumption"
    }
  },
+  "minimap": {
+    "jumpToMessage": "Jump to message {{index}}",
+    "nextMessage": "Next message",
+    "previousMessage": "Previous message"
+  },
  "newAgent": "New Assistant",
  "pin": "Pin",
  "pinOff": "Unpin",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "Describe what you want to generate"
    },
+    "quality": {
+      "label": "Image Quality",
+      "options": {
+        "hd": "High Definition",
+        "standard": "Standard"
+      }
+    },
    "seed": {
      "label": "Seed",
      "random": "Random Seed"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4 significantly improves upon the industry-leading capabilities of Sonnet 3.7, excelling in coding with state-of-the-art 72.7% on SWE-bench. The model balances performance and efficiency, suitable for both internal and external use cases, and offers enhanced controllability for greater command over outcomes."
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "Claude Sonnet 4.5 is Anthropic's most intelligent model to date."
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B is a sparse large language model with 72 billion parameters and 16 billion activated parameters. It is based on the Group Mixture of Experts (MoGE) architecture, which groups experts during the expert selection phase and constrains tokens to activate an equal number of experts within each group, achieving expert load balancing and significantly improving deployment efficiency on the Ascend platform."
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "Claude Sonnet 4 Thinking model can produce near-instant responses or extended step-by-step reasoning, enabling users to clearly see these processes."
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "Claude Sonnet 4.5 is Anthropic's most intelligent model to date."
+  },
  "codegeex-4": {
    "description": "CodeGeeX-4 is a powerful AI programming assistant that supports intelligent Q&A and code completion in various programming languages, enhancing development efficiency."
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "Kimi-K2 is a Mixture-of-Experts (MoE) foundation model with exceptional coding and agent capabilities, featuring 1T total parameters and 32B activated parameters. In benchmark evaluations across core categories — general knowledge reasoning, programming, mathematics, and agent tasks — the K2 model outperforms other leading open-source models."
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2 is a large-scale Mixture of Experts (MoE) language model developed by Moon's Dark Side AI, featuring a total of 1 trillion parameters and 32 billion activated parameters per forward pass. It is optimized for agent capabilities, including advanced tool usage, reasoning, and code synthesis."
+  },
  "kimi-latest": {
    "description": "The Kimi Smart Assistant product uses the latest Kimi large model, which may include features that are not yet stable. It supports image understanding and will automatically select the 8k/32k/128k model as the billing model based on the length of the request context."
  },
@@ -110,6 +110,9 @@
  "ollama": {
    "description": "Ollama provides models that cover a wide range of fields, including code generation, mathematical operations, multilingual processing, and conversational interaction, catering to diverse enterprise-level and localized deployment needs."
  },
+  "ollamacloud": {
+    "description": "Ollama Cloud offers officially hosted inference services, providing out-of-the-box access to the Ollama model library and supporting OpenAI-compatible interfaces."
+  },
  "openai": {
    "description": "OpenAI is a global leader in artificial intelligence research, with models like the GPT series pushing the frontiers of natural language processing. OpenAI is committed to transforming multiple industries through innovative and efficient AI solutions. Their products demonstrate significant performance and cost-effectiveness, widely used in research, business, and innovative applications."
  },
@@ -1,4 +1,11 @@
 {
+  "codeInterpreter": {
+    "error": "Execution Error",
+    "executing": "Executing...",
+    "files": "Files:",
+    "output": "Output:",
+    "returnValue": "Return Value:"
+  },
  "dalle": {
    "autoGenerate": "Auto Generate",
    "downloading": "The image links generated by DALL·E3 are only valid for 1 hour, caching the images locally...",
@@ -150,6 +150,11 @@
      "total": "Total consumido"
    }
  },
+  "minimap": {
+    "jumpToMessage": "Ir al mensaje número {{index}}",
+    "nextMessage": "Mensaje siguiente",
+    "previousMessage": "Mensaje anterior"
+  },
  "newAgent": "Nuevo asistente",
  "pin": "Fijar",
  "pinOff": "Desfijar",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "Describe el contenido que deseas generar"
    },
+    "quality": {
+      "label": "Calidad de imagen",
+      "options": {
+        "hd": "Alta definición",
+        "standard": "Estándar"
+      }
+    },
    "seed": {
      "label": "Semilla",
      "random": "Semilla aleatoria"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4 mejora significativamente las capacidades líderes de Sonnet 3.7, destacándose en codificación con un rendimiento de vanguardia del 72.7% en SWE-bench. El modelo equilibra rendimiento y eficiencia, adecuado para casos de uso internos y externos, y ofrece mayor control mediante una mejor capacidad de control."
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "Claude Sonnet 4.5 es el modelo más inteligente de Anthropic hasta la fecha."
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B es un modelo de lenguaje grande disperso con 72 mil millones de parámetros y 16 mil millones de parámetros activados. Está basado en la arquitectura de expertos mixtos agrupados (MoGE), que agrupa expertos durante la selección y restringe la activación de un número igual de expertos por grupo para cada token, logrando un balance de carga entre expertos y mejorando significativamente la eficiencia de despliegue en la plataforma Ascend."
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "Modelo de pensamiento Claude Sonnet 4 que puede generar respuestas casi instantáneas o un pensamiento prolongado paso a paso, permitiendo a los usuarios ver claramente estos procesos."
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "Claude Sonnet 4.5 es el modelo más inteligente de Anthropic hasta la fecha."
+  },
  "codegeex-4": {
    "description": "CodeGeeX-4 es un potente asistente de programación AI, que admite preguntas y respuestas inteligentes y autocompletado de código en varios lenguajes de programación, mejorando la eficiencia del desarrollo."
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "kimi-k2 es un modelo base con arquitectura MoE que ofrece potentes capacidades para código y agentes, con 1T parámetros totales y 32B parámetros activados. En las pruebas de referencia en categorías principales como razonamiento de conocimiento general, programación, matemáticas y agentes, el rendimiento del modelo K2 supera al de otros modelos de código abierto más extendidos."
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2 es un modelo de lenguaje de expertos mixtos a gran escala (MoE) desarrollado por la IA del lado oscuro de la luna, con un total de un billón de parámetros y 32 mil millones de parámetros activados por cada pasada hacia adelante. Está optimizado para capacidades de agente, incluyendo el uso avanzado de herramientas, razonamiento y síntesis de código."
+  },
  "kimi-latest": {
    "description": "El producto asistente inteligente Kimi utiliza el último modelo grande de Kimi, que puede incluir características que aún no están estables. Soporta la comprensión de imágenes y seleccionará automáticamente el modelo de facturación de 8k/32k/128k según la longitud del contexto de la solicitud."
  },
@@ -110,6 +110,9 @@
  "ollama": {
    "description": "Los modelos ofrecidos por Ollama abarcan ampliamente áreas como la generación de código, cálculos matemáticos, procesamiento multilingüe e interacciones conversacionales, apoyando diversas necesidades de implementación empresarial y local."
  },
+  "ollamacloud": {
+    "description": "Ollama Cloud ofrece un servicio de inferencia alojado oficialmente, acceso inmediato a la biblioteca de modelos de Ollama y soporte para interfaces compatibles con OpenAI."
+  },
  "openai": {
    "description": "OpenAI es una de las principales instituciones de investigación en inteligencia artificial a nivel mundial, cuyos modelos, como la serie GPT, están a la vanguardia del procesamiento del lenguaje natural. OpenAI se dedica a transformar múltiples industrias a través de soluciones de IA innovadoras y eficientes. Sus productos ofrecen un rendimiento y una rentabilidad significativos, siendo ampliamente utilizados en investigación, negocios y aplicaciones innovadoras."
  },
@@ -1,4 +1,11 @@
 {
+  "codeInterpreter": {
+    "error": "Error de ejecución",
+    "executing": "Ejecutando...",
+    "files": "Archivos:",
+    "output": "Salida:",
+    "returnValue": "Valor devuelto:"
+  },
  "dalle": {
    "autoGenerate": "Auto-generar",
    "downloading": "El enlace de la imagen generada por DALL·E 3 solo es válido durante 1 hora, descargando la imagen al dispositivo local...",
@@ -150,6 +150,11 @@
      "total": "مجموع مصرف"
    }
  },
+  "minimap": {
+    "jumpToMessage": "رفتن به پیام شماره {{index}}",
+    "nextMessage": "پیام بعدی",
+    "previousMessage": "پیام قبلی"
+  },
  "newAgent": "دستیار جدید",
  "pin": "سنجاق کردن",
  "pinOff": "لغو سنجاق",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "توصیف محتوایی که می‌خواهید تولید شود"
    },
+    "quality": {
+      "label": "کیفیت تصویر",
+      "options": {
+        "hd": "وضوح بالا",
+        "standard": "استاندارد"
+      }
+    },
    "seed": {
      "label": "بذر",
      "random": "بذر تصادفی"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4 بهبود قابل توجهی بر توانایی‌های پیشرو در صنعت Sonnet 3.7 دارد و در کدنویسی عملکرد برجسته‌ای با 72.7% در SWE-bench ارائه می‌دهد. این مدل تعادل بین عملکرد و کارایی را حفظ کرده و برای موارد استفاده داخلی و خارجی مناسب است و با کنترل‌پذیری بهبود یافته، کنترل بیشتری بر نتایج فراهم می‌کند."
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "کلود سونت ۴.۵ هوشمندترین مدل تا به امروز شرکت Anthropic است."
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B یک مدل زبان بزرگ پراکنده با 72 میلیارد پارامتر و 16 میلیارد پارامتر فعال است که بر اساس معماری متخصصان ترکیبی گروه‌بندی شده (MoGE) ساخته شده است. در مرحله انتخاب متخصص، متخصصان به گروه‌هایی تقسیم می‌شوند و توکن‌ها در هر گروه به تعداد مساوی متخصصان فعال می‌شوند تا تعادل بار متخصصان حفظ شود، که به طور قابل توجهی کارایی استقرار مدل را در پلتفرم Ascend افزایش می‌دهد."
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "مدل تفکر Claude Sonnet 4 می‌تواند پاسخ‌های تقریباً فوری یا تفکر گام به گام طولانی‌مدت تولید کند که کاربران می‌توانند این فرآیندها را به وضوح مشاهده کنند."
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "کلود سونت ۴.۵ هوشمندترین مدل تا به امروز شرکت Anthropic است."
+  },
  "codegeex-4": {
    "description": "CodeGeeX-4 یک دستیار برنامه‌نویسی قدرتمند مبتنی بر هوش مصنوعی است که از پرسش و پاسخ هوشمند و تکمیل کد در زبان‌های برنامه‌نویسی مختلف پشتیبانی می‌کند و بهره‌وری توسعه را افزایش می‌دهد."
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "kimi-k2 یک مدل پایه با معماری MoE است که دارای توانمندی‌های بسیار قوی در حوزهٔ برنامه‌نویسی و عامل‌ها (Agent) می‌باشد. مجموع پارامترها 1T و پارامترهای فعال‌شده 32B است. در آزمون‌های بنچمارک در دسته‌های اصلی مانند استدلال دانش عمومی، برنامه‌نویسی، ریاضیات و Agent، عملکرد مدل K2 از سایر مدل‌های متن‌باز مرسوم پیشی گرفته است."
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2 یک مدل زبان متخصص ترکیبی بزرگ‌مقیاس (MoE) است که توسط هوش مصنوعی ماه تاریک توسعه یافته است، با مجموع ۱ تریلیون پارامتر و ۳۲ میلیارد پارامتر فعال در هر عبور رو به جلو. این مدل برای توانمندی‌های نمایندگی بهینه شده است، از جمله استفاده پیشرفته از ابزارها، استدلال و ترکیب کد."
+  },
  "kimi-latest": {
    "description": "محصول دستیار هوشمند کیمی از جدیدترین مدل بزرگ کیمی استفاده می‌کند و ممکن است شامل ویژگی‌های ناپایدار باشد. از درک تصویر پشتیبانی می‌کند و به‌طور خودکار بر اساس طول متن درخواست، مدل‌های 8k/32k/128k را به‌عنوان مدل محاسبه انتخاب می‌کند."
  },
@@ -110,6 +110,9 @@
  "ollama": {
    "description": "مدل‌های ارائه‌شده توسط Ollama طیف گسترده‌ای از تولید کد، محاسبات ریاضی، پردازش چندزبانه و تعاملات گفتگویی را پوشش می‌دهند و از نیازهای متنوع استقرار در سطح سازمانی و محلی پشتیبانی می‌کنند."
  },
+  "ollamacloud": {
+    "description": "Ollama Cloud خدمات استنتاج میزبانی شده رسمی را ارائه می‌دهد که به‌صورت آماده استفاده به کتابخانه مدل‌های Ollama دسترسی می‌دهد و از رابط‌های سازگار با OpenAI پشتیبانی می‌کند."
+  },
  "openai": {
    "description": "OpenAI یک موسسه پیشرو در تحقیقات هوش مصنوعی در سطح جهان است که مدل‌هایی مانند سری GPT را توسعه داده و مرزهای پردازش زبان طبیعی را پیش برده است. OpenAI متعهد به تغییر صنایع مختلف از طریق راه‌حل‌های نوآورانه و کارآمد هوش مصنوعی است. محصولات آن‌ها دارای عملکرد برجسته و اقتصادی بوده و به طور گسترده در تحقیقات، تجارت و کاربردهای نوآورانه استفاده می‌شوند."
  },
@@ -1,4 +1,11 @@
 {
+  "codeInterpreter": {
+    "error": "خطا در اجرا",
+    "executing": "در حال اجرا...",
+    "files": "فایل‌ها:",
+    "output": "خروجی:",
+    "returnValue": "مقدار بازگشتی:"
+  },
  "dalle": {
    "autoGenerate": "تولید خودکار",
    "downloading": "لینک‌های تصاویر تولید شده توسط DallE3 فقط به مدت ۱ ساعت معتبر هستند، در حال ذخیره‌سازی تصاویر به صورت محلی...",
@@ -150,6 +150,11 @@
      "total": "Total consommé"
    }
  },
+  "minimap": {
+    "jumpToMessage": "Aller au message n° {{index}}",
+    "nextMessage": "Message suivant",
+    "previousMessage": "Message précédent"
+  },
  "newAgent": "Nouvel agent",
  "pin": "Épingler",
  "pinOff": "Désépingler",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "Décrivez ce que vous souhaitez générer"
    },
+    "quality": {
+      "label": "Qualité de l'image",
+      "options": {
+        "hd": "Haute définition",
+        "standard": "Standard"
+      }
+    },
    "seed": {
      "label": "Graine",
      "random": "Graine aléatoire"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4 améliore significativement les capacités de Sonnet 3.7, excelle en codage avec un score de pointe de 72,7 % sur SWE-bench. Ce modèle équilibre performance et efficacité, adapté aux cas d'usage internes et externes, avec un contrôle accru grâce à une meilleure contrôlabilité."
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "Claude Sonnet 4.5 est le modèle le plus intelligent d'Anthropic à ce jour."
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B est un grand modèle de langage sparse à 72 milliards de paramètres, avec 16 milliards de paramètres activés. Il repose sur une architecture Mixture of Experts groupée (MoGE), qui regroupe les experts lors de la sélection et contraint chaque token à activer un nombre égal d'experts dans chaque groupe, assurant ainsi un équilibre de charge entre les experts et améliorant considérablement l'efficacité de déploiement sur la plateforme Ascend."
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "Le modèle de réflexion Claude Sonnet 4 produit des réponses quasi instantanées ou des raisonnements prolongés étape par étape, clairement visibles par l'utilisateur."
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "Claude Sonnet 4.5 est le modèle le plus intelligent d'Anthropic à ce jour."
+  },
  "codegeex-4": {
    "description": "CodeGeeX-4 est un puissant assistant de programmation AI, prenant en charge des questions intelligentes et l'achèvement de code dans divers langages de programmation, améliorant l'efficacité du développement."
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "kimi-k2 est un modèle de base à architecture MoE doté de capacités remarquables en programmation et en agents autonomes, avec 1T de paramètres au total et 32B de paramètres activés. Dans les principaux tests de référence couvrant le raisonnement général, la programmation, les mathématiques et les agents, le modèle K2 surpasse les autres modèles open source majeurs."
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2 est un modèle de langage à experts mixtes à grande échelle (MoE) développé par l'IA de la face cachée de la Lune, avec un total de 1 000 milliards de paramètres et 32 milliards de paramètres activés par passage avant. Il est optimisé pour les capacités d'agent, incluant l'utilisation avancée d'outils, le raisonnement et la synthèse de code."
+  },
  "kimi-latest": {
    "description": "Le produit d'assistant intelligent Kimi utilise le dernier modèle Kimi, qui peut inclure des fonctionnalités encore instables. Il prend en charge la compréhension des images et choisit automatiquement le modèle de facturation 8k/32k/128k en fonction de la longueur du contexte de la demande."
  },
@@ -110,6 +110,9 @@
  "ollama": {
    "description": "Les modèles proposés par Ollama couvrent largement des domaines tels que la génération de code, les calculs mathématiques, le traitement multilingue et les interactions conversationnelles, répondant à des besoins diversifiés pour le déploiement en entreprise et la localisation."
  },
+  "ollamacloud": {
+    "description": "Ollama Cloud offre un service d'inférence hébergé officiellement, permettant un accès prêt à l'emploi à la bibliothèque de modèles Ollama, avec prise en charge d'une interface compatible OpenAI."
+  },
  "openai": {
    "description": "OpenAI est un institut de recherche en intelligence artificielle de premier plan au monde, dont les modèles, tels que la série GPT, font progresser les frontières du traitement du langage naturel. OpenAI s'engage à transformer plusieurs secteurs grâce à des solutions IA innovantes et efficaces. Leurs produits offrent des performances et une rentabilité remarquables, largement utilisés dans la recherche, le commerce et les applications innovantes."
  },
@@ -1,4 +1,11 @@
 {
+  "codeInterpreter": {
+    "error": "Erreur d'exécution",
+    "executing": "Exécution en cours...",
+    "files": "Fichiers :",
+    "output": "Sortie :",
+    "returnValue": "Valeur de retour :"
+  },
  "dalle": {
    "autoGenerate": "Auto-générer",
    "downloading": "Les liens d'image générés par DallE3 ne sont valides que pendant 1 heure. Le téléchargement de l'image est en cours...",
@@ -150,6 +150,11 @@
      "total": "Totale consumato"
    }
  },
+  "minimap": {
+    "jumpToMessage": "Vai al messaggio n. {{index}}",
+    "nextMessage": "Messaggio successivo",
+    "previousMessage": "Messaggio precedente"
+  },
  "newAgent": "Nuovo assistente",
  "pin": "Fissa in alto",
  "pinOff": "Annulla fissaggio in alto",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "Descrivi ciò che desideri generare"
    },
+    "quality": {
+      "label": "Qualità immagine",
+      "options": {
+        "hd": "Alta definizione",
+        "standard": "Standard"
+      }
+    },
    "seed": {
      "label": "Seed",
      "random": "Seme casuale"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4 migliora significativamente le capacità leader del settore di Sonnet 3.7, eccellendo nella codifica con un punteggio all'avanguardia del 72,7% su SWE-bench. Il modello bilancia prestazioni ed efficienza, adatto a casi d'uso interni ed esterni, e offre un controllo maggiore sull'implementazione grazie a una controllabilità migliorata."
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "Claude Sonnet 4.5 è il modello più intelligente di Anthropic fino ad oggi."
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B è un modello linguistico di grandi dimensioni a parametri sparsi con 72 miliardi di parametri totali e 16 miliardi di parametri attivati, basato sull'architettura Mixture of Group Experts (MoGE). Durante la fase di selezione degli esperti, gli esperti sono raggruppati e il token attiva un numero uguale di esperti all'interno di ogni gruppo, garantendo un bilanciamento del carico degli esperti e migliorando significativamente l'efficienza di distribuzione del modello sulla piattaforma Ascend."
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "Modello di pensiero Claude Sonnet 4 che può generare risposte quasi istantanee o un pensiero graduale prolungato, permettendo all'utente di vedere chiaramente questi processi."
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "Claude Sonnet 4.5 è il modello più intelligente di Anthropic fino ad oggi."
+  },
  "codegeex-4": {
    "description": "CodeGeeX-4 è un potente assistente di programmazione AI, supporta domande intelligenti e completamento del codice in vari linguaggi di programmazione, migliorando l'efficienza dello sviluppo."
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "kimi-k2 è un modello di base con architettura MoE che offre potenti capacità di programmazione e di agent, con 1T di parametri totali e 32B di parametri attivi. Nei benchmark delle principali categorie — ragionamento su conoscenze generali, programmazione, matematica e agent — il modello K2 supera gli altri modelli open source più diffusi."
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2 è un modello linguistico esperto ibrido su larga scala (MoE) sviluppato da Moon's Dark Side AI, con un totale di 1 trilione di parametri e 32 miliardi di parametri attivati per ogni passaggio in avanti. È ottimizzato per capacità di agente, inclusi l'uso avanzato di strumenti, il ragionamento e la sintesi del codice."
+  },
  "kimi-latest": {
    "description": "Il prodotto Kimi Smart Assistant utilizza il più recente modello Kimi, che potrebbe includere funzionalità non ancora stabili. Supporta la comprensione delle immagini e selezionerà automaticamente il modello di fatturazione 8k/32k/128k in base alla lunghezza del contesto della richiesta."
  },
@@ -110,6 +110,9 @@
  "ollama": {
    "description": "I modelli forniti da Ollama coprono ampiamente aree come generazione di codice, operazioni matematiche, elaborazione multilingue e interazioni conversazionali, supportando esigenze diversificate per implementazioni aziendali e localizzate."
  },
+  "ollamacloud": {
+    "description": "Ollama Cloud offre un servizio di inferenza ospitato ufficialmente, con accesso immediato alla libreria di modelli Ollama e supporto per interfacce compatibili con OpenAI."
+  },
  "openai": {
    "description": "OpenAI è un'agenzia di ricerca sull'intelligenza artificiale leader a livello globale, i cui modelli come la serie GPT hanno spinto in avanti il campo dell'elaborazione del linguaggio naturale. OpenAI si impegna a trasformare diversi settori attraverso soluzioni AI innovative ed efficienti. I loro prodotti offrono prestazioni e costi notevoli, trovando ampio utilizzo nella ricerca, nel commercio e nelle applicazioni innovative."
  },
@@ -1,4 +1,11 @@
 {
+  "codeInterpreter": {
+    "error": "Errore di esecuzione",
+    "executing": "In esecuzione...",
+    "files": "File:",
+    "output": "Output:",
+    "returnValue": "Valore di ritorno:"
+  },
  "dalle": {
    "autoGenerate": "Auto-generato",
    "downloading": "Il link dell'immagine generata da DALL·E3 è valido solo per 1 ora, sta scaricando l'immagine in locale...",
@@ -150,6 +150,11 @@
      "total": "合計消費"
    }
  },
+  "minimap": {
+    "jumpToMessage": "メッセージ {{index}} へジャンプ",
+    "nextMessage": "次のメッセージ",
+    "previousMessage": "前のメッセージ"
+  },
  "newAgent": "新しいエージェント",
  "pin": "ピン留め",
  "pinOff": "ピン留め解除",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "生成したい内容を記述してください"
    },
+    "quality": {
+      "label": "画像品質",
+      "options": {
+        "hd": "高精細",
+        "standard": "標準"
+      }
+    },
    "seed": {
      "label": "シード",
      "random": "ランダムシード"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4 は Sonnet 3.7 の業界トップの能力を大幅に向上させ、コーディングで優れた性能を発揮し、SWE-bench で最先端の72.7%を達成しました。性能と効率のバランスが取れており、内部および外部のユースケースに適し、強化された制御性により実装の管理性が向上しています。"
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "Claude Sonnet 4.5 は Anthropic のこれまでで最も賢いモデルです。"
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B は、720億パラメータ、160億アクティベーションパラメータのスパース大規模言語モデルであり、グループ化された混合エキスパート（MoGE）アーキテクチャに基づいています。エキスパート選択段階でエキスパートをグループ化し、各グループ内でトークンが均等にエキスパートをアクティベートするよう制約を設けることで、エキスパートの負荷バランスを実現し、昇騰プラットフォーム上でのモデル展開効率を大幅に向上させています。"
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "Claude Sonnet 4 思考モデルは、ほぼ即時の応答や段階的な思考の延長を生成でき、ユーザーはこれらの過程を明確に見ることができます。"
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "Claude Sonnet 4.5 は Anthropic のこれまでで最も賢いモデルです。"
+  },
  "codegeex-4": {
    "description": "CodeGeeX-4は強力なAIプログラミングアシスタントで、さまざまなプログラミング言語のインテリジェントな質問応答とコード補完をサポートし、開発効率を向上させます。"
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "kimi-k2 は高度なコード処理能力とエージェント機能を備えた MoE（Mixture of Experts）アーキテクチャの基盤モデルで、総パラメータ数は1T、アクティブパラメータは32Bです。一般的な知識推論、プログラミング、数学、エージェントなどの主要カテゴリにおけるベンチマークで、K2モデルは他の主要なオープンソースモデルを上回る性能を示しています。"
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2 は、月の裏側 AI によって開発された大規模混合専門家（MoE）言語モデルで、総パラメータ数は1兆、1回のフォワードパスで320億の活性化パラメータを持ちます。エージェント能力に最適化されており、高度なツール使用、推論、コード合成を含みます。"
+  },
  "kimi-latest": {
    "description": "Kimi スマートアシスタント製品は最新の Kimi 大モデルを使用しており、まだ安定していない機能が含まれている可能性があります。画像理解をサポートし、リクエストのコンテキストの長さに応じて 8k/32k/128k モデルを請求モデルとして自動的に選択します。"
  },
@@ -110,6 +110,9 @@
  "ollama": {
    "description": "Ollamaが提供するモデルは、コード生成、数学演算、多言語処理、対話インタラクションなどの分野を広くカバーし、企業向けおよびローカライズされた展開の多様なニーズに対応しています。"
  },
+  "ollamacloud": {
+    "description": "Ollama Cloud は公式にホストされた推論サービスを提供し、すぐに使える Ollama モデルライブラリへのアクセスと OpenAI 互換インターフェースをサポートします。"
+  },
  "openai": {
    "description": "OpenAIは、世界をリードする人工知能研究機関であり、GPTシリーズなどのモデルを開発し、自然言語処理の最前線を推進しています。OpenAIは、革新と効率的なAIソリューションを通じて、さまざまな業界を変革することに取り組んでいます。彼らの製品は、顕著な性能と経済性を持ち、研究、ビジネス、革新アプリケーションで広く使用されています。"
  },
@@ -1,4 +1,11 @@
 {
+  "codeInterpreter": {
+    "error": "実行エラー",
+    "executing": "実行中...",
+    "files": "ファイル：",
+    "output": "出力：",
+    "returnValue": "戻り値："
+  },
  "dalle": {
    "autoGenerate": "自動生成",
    "downloading": "DallE3 で生成された画像リンクは有効期間が1時間しかありません。画像をローカルにキャッシュしています...",
@@ -150,6 +150,11 @@
      "total": "총 소모"
    }
  },
+  "minimap": {
+    "jumpToMessage": "{{index}}번째 메시지로 이동",
+    "nextMessage": "다음 메시지",
+    "previousMessage": "이전 메시지"
+  },
  "newAgent": "새 도우미",
  "pin": "고정",
  "pinOff": "고정 해제",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "생성하고 싶은 내용을 설명하세요"
    },
+    "quality": {
+      "label": "이미지 품질",
+      "options": {
+        "hd": "고화질",
+        "standard": "표준"
+      }
+    },
    "seed": {
      "label": "시드",
      "random": "무작위 시드"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4는 Sonnet 3.7의 업계 선도 능력을 크게 향상시켰으며, 코딩에서 뛰어난 성능을 보이고 SWE-bench에서 최첨단 72.7%를 달성했습니다. 이 모델은 성능과 효율성 사이의 균형을 이루며, 내부 및 외부 사용 사례에 적합하고 향상된 제어성을 통해 구현에 대한 더 큰 통제를 제공합니다."
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "Claude Sonnet 4.5는 Anthropic의 지금까지 가장 지능적인 모델입니다."
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B는 720억 개의 파라미터와 160억 활성 파라미터를 가진 희소 대형 언어 모델로, 그룹 혼합 전문가(MoGE) 아키텍처를 기반으로 합니다. 전문가 선택 단계에서 전문가를 그룹화하고 각 그룹 내에서 토큰이 동일 수의 전문가를 활성화하도록 제한하여 전문가 부하 균형을 달성함으로써 Ascend 플랫폼에서의 모델 배포 효율성을 크게 향상시켰습니다."
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "Claude Sonnet 4 사고 모델은 거의 즉각적인 응답 또는 확장된 단계별 사고를 생성할 수 있으며, 사용자가 이 과정을 명확히 볼 수 있습니다."
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "Claude Sonnet 4.5는 Anthropic의 지금까지 가장 지능적인 모델입니다."
+  },
  "codegeex-4": {
    "description": "CodeGeeX-4는 강력한 AI 프로그래밍 도우미로, 다양한 프로그래밍 언어에 대한 스마트 Q&A 및 코드 완성을 지원하여 개발 효율성을 높입니다."
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "kimi-k2는 강력한 코드 처리 및 에이전트(Agent) 기능을 갖춘 MoE(혼합 전문가) 아키텍처 기반 모델로, 총 파라미터 수는 1T(1조), 활성화 파라미터는 32B(320억)입니다. 일반 지식 추론, 프로그래밍, 수학, 에이전트 등 주요 분야의 벤치마크 성능 테스트에서 K2 모델은 다른 주요 오픈 소스 모델들을 능가합니다."
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2는 월면 AI가 개발한 대규모 혼합 전문가(MoE) 언어 모델로, 총 1조 개의 파라미터와 매 전방 전달 시 320억 개의 활성화 파라미터를 보유하고 있습니다. 이 모델은 고급 도구 사용, 추론 및 코드 합성을 포함한 에이전트 능력에 최적화되어 있습니다."
+  },
  "kimi-latest": {
    "description": "Kimi 스마트 어시스턴트 제품은 최신 Kimi 대형 모델을 사용하며, 아직 안정되지 않은 기능이 포함될 수 있습니다. 이미지 이해를 지원하며, 요청의 맥락 길이에 따라 8k/32k/128k 모델을 청구 모델로 자동 선택합니다."
  },
@@ -110,6 +110,9 @@
  "ollama": {
    "description": "Ollama가 제공하는 모델은 코드 생성, 수학 연산, 다국어 처리 및 대화 상호작용 등 다양한 분야를 포괄하며, 기업급 및 로컬 배포의 다양한 요구를 지원합니다."
  },
+  "ollamacloud": {
+    "description": "Ollama Cloud는 공식 호스팅 추론 서비스를 제공하며, 즉시 사용 가능한 Ollama 모델 라이브러리에 접근할 수 있고 OpenAI 호환 인터페이스를 지원합니다."
+  },
  "openai": {
    "description": "OpenAI는 세계 최고의 인공지능 연구 기관으로, 개발한 모델인 GPT 시리즈는 자연어 처리의 최전선에서 혁신을 이끌고 있습니다. OpenAI는 혁신적이고 효율적인 AI 솔루션을 통해 여러 산업을 변화시키는 데 전념하고 있습니다. 그들의 제품은 뛰어난 성능과 경제성을 갖추고 있어 연구, 비즈니스 및 혁신적인 응용 프로그램에서 널리 사용됩니다."
  },
@@ -1,4 +1,11 @@
 {
+  "codeInterpreter": {
+    "error": "실행 오류",
+    "executing": "실행 중...",
+    "files": "파일:",
+    "output": "출력:",
+    "returnValue": "반환 값:"
+  },
  "dalle": {
    "autoGenerate": "자동 생성",
    "downloading": "DallE3로 생성된 이미지 링크는 1시간 동안 유효하며, 로컬에 이미지를 캐시하는 중입니다...",
@@ -150,6 +150,11 @@
      "total": "Totaal verbruik"
    }
  },
+  "minimap": {
+    "jumpToMessage": "Ga naar bericht {{index}}",
+    "nextMessage": "Volgend bericht",
+    "previousMessage": "Vorig bericht"
+  },
  "newAgent": "Nieuwe assistent",
  "pin": "Vastzetten",
  "pinOff": "Vastzetten uitschakelen",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "Beschrijf wat je wilt genereren"
    },
+    "quality": {
+      "label": "Beeldkwaliteit",
+      "options": {
+        "hd": "Hoge resolutie",
+        "standard": "Standaard"
+      }
+    },
    "seed": {
      "label": "Zaad",
      "random": "Willekeurige zaad"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4 bouwt voort op de toonaangevende capaciteiten van Sonnet 3.7 en blinkt uit in codering met een geavanceerde score van 72,7% op SWE-bench. Het model balanceert prestaties en efficiëntie, geschikt voor interne en externe toepassingen, en biedt grotere controle via verbeterde beheersbaarheid."
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "Claude Sonnet 4.5 is het slimste model van Anthropic tot nu toe."
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B is een sparsely activated groot taalmodel met 72 miljard parameters en 16 miljard geactiveerde parameters. Het is gebaseerd op de Group Mixture of Experts (MoGE) architectuur, waarbij experts worden gegroepeerd tijdens de selectie en tokens binnen elke groep een gelijk aantal experts activeren, wat zorgt voor een gebalanceerde expertbelasting en de efficiëntie van modelimplementatie op het Ascend-platform aanzienlijk verbetert."
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "Claude Sonnet 4 denkmodel kan bijna onmiddellijke reacties genereren of uitgebreide stapsgewijze overwegingen, waarbij gebruikers deze processen duidelijk kunnen volgen."
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "Claude Sonnet 4.5 is het slimste model van Anthropic tot nu toe."
+  },
  "codegeex-4": {
    "description": "CodeGeeX-4 is een krachtige AI-programmeerassistent die slimme vraag- en antwoordmogelijkheden en code-aanvulling ondersteunt voor verschillende programmeertalen, waardoor de ontwikkelingssnelheid wordt verhoogd."
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "kimi-k2 is een basismodel met een MoE-architectuur dat beschikt over zeer sterke codeer- en agentcapaciteiten. Het heeft in totaal 1T parameters en 32B actieve parameters. In benchmarktests op belangrijke categorieën zoals algemene kennisredenering, programmeren, wiskunde en agenttaken overtreft het K2-model de prestaties van andere gangbare open-sourcemodellen."
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2 is een grootschalig gemengd expertsysteem (MoE) taalmodel ontwikkeld door Moon's Dark Side AI, met in totaal 1 biljoen parameters en 32 miljard geactiveerde parameters per voorwaartse doorgang. Het is geoptimaliseerd voor agentcapaciteiten, waaronder geavanceerd gebruik van tools, redeneren en code-synthese."
+  },
  "kimi-latest": {
    "description": "Kimi slimme assistent product maakt gebruik van het nieuwste Kimi grote model, dat mogelijk nog niet stabiele functies bevat. Ondersteunt beeldbegrip en kiest automatisch het 8k/32k/128k model als factureringsmodel op basis van de lengte van de context van het verzoek."
  },
@@ -110,6 +110,9 @@
  "ollama": {
    "description": "De modellen van Ollama bestrijken een breed scala aan gebieden, waaronder codegeneratie, wiskundige berekeningen, meertalige verwerking en interactieve dialogen, en voldoen aan de diverse behoeften van bedrijfs- en lokale implementaties."
  },
+  "ollamacloud": {
+    "description": "Ollama Cloud biedt officieel beheerde inferentiediensten, waarmee u direct toegang krijgt tot de Ollama-modelbibliotheek en ondersteuning voor OpenAI-compatibele interfaces."
+  },
  "openai": {
    "description": "OpenAI is 's werelds toonaangevende onderzoeksinstituut op het gebied van kunstmatige intelligentie, wiens ontwikkelde modellen zoals de GPT-serie de grenzen van natuurlijke taalverwerking verleggen. OpenAI streeft ernaar verschillende industrieën te transformeren door middel van innovatieve en efficiënte AI-oplossingen. Hun producten bieden opmerkelijke prestaties en kosteneffectiviteit, en worden op grote schaal gebruikt in onderzoek, commercie en innovatieve toepassingen."
  },
@@ -1,4 +1,11 @@
 {
+  "codeInterpreter": {
+    "error": "Fout bij uitvoering",
+    "executing": "Bezig met uitvoeren...",
+    "files": "Bestanden:",
+    "output": "Uitvoer:",
+    "returnValue": "Retourwaarde:"
+  },
  "dalle": {
    "autoGenerate": "Automatisch genereren",
    "downloading": "De link naar de afbeelding gegenereerd door DallE3 is slechts 1 uur geldig. De afbeelding wordt lokaal in de cache opgeslagen...",
@@ -150,6 +150,11 @@
      "total": "Całkowite zużycie"
    }
  },
+  "minimap": {
+    "jumpToMessage": "Przejdź do wiadomości nr {{index}}",
+    "nextMessage": "Następna wiadomość",
+    "previousMessage": "Poprzednia wiadomość"
+  },
  "newAgent": "Nowy asystent",
  "pin": "Przypnij",
  "pinOff": "Odepnij",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "Opisz, co chcesz wygenerować"
    },
+    "quality": {
+      "label": "Jakość obrazu",
+      "options": {
+        "hd": "Wysoka rozdzielczość",
+        "standard": "Standardowa"
+      }
+    },
    "seed": {
      "label": "Ziarno",
      "random": "Losowy seed"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4 to znacząca poprawa w stosunku do Sonnet 3.7, oferująca doskonałą wydajność w kodowaniu z rekordowym wynikiem 72,7% w SWE-bench. Model osiąga równowagę między wydajnością a efektywnością, nadaje się do zastosowań wewnętrznych i zewnętrznych oraz zapewnia większą kontrolę dzięki ulepszonej sterowalności."
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "Claude Sonnet 4.5 to jak dotąd najbardziej inteligentny model Anthropic."
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B to rzadki, duży model językowy o 72 miliardach parametrów i 16 miliardach aktywowanych parametrów, oparty na architekturze grupowanych ekspertów (MoGE). W fazie wyboru ekspertów model grupuje ekspertów i ogranicza aktywację tokenów do równej liczby ekspertów w każdej grupie, co zapewnia równomierne obciążenie ekspertów i znacznie poprawia efektywność wdrożenia modelu na platformie Ascend."
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "Model myślenia Claude Sonnet 4 może generować niemal natychmiastowe odpowiedzi lub wydłużone, stopniowe rozważania, które użytkownik może wyraźnie obserwować."
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "Claude Sonnet 4.5 to jak dotąd najbardziej inteligentny model Anthropic."
+  },
  "codegeex-4": {
    "description": "CodeGeeX-4 to potężny asystent programowania AI, obsługujący inteligentne pytania i odpowiedzi oraz uzupełnianie kodu w różnych językach programowania, zwiększając wydajność programistów."
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "kimi-k2 to bazowy model z architekturą MoE, dysponujący wyjątkowymi możliwościami w zakresie kodowania i agentów, z łączną liczbą parametrów 1T oraz 32B parametrów aktywacyjnych. W standardowych testach wydajności (benchmarkach) dla głównych kategorii takich jak wnioskowanie z wiedzy ogólnej, programowanie, matematyka i agenty, model K2 przewyższa inne popularne otwarte modele."
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2 to duży, hybrydowy model ekspertowy (MoE) języka opracowany przez AI z Ciemnej Strony Księżyca, posiadający 1 bilion parametrów ogółem oraz 32 miliardy aktywowanych parametrów na pojedyncze przejście w przód. Model jest zoptymalizowany pod kątem zdolności agentowych, w tym zaawansowanego korzystania z narzędzi, wnioskowania i syntezy kodu."
+  },
  "kimi-latest": {
    "description": "Produkt Kimi Smart Assistant korzysta z najnowszego modelu Kimi, który może zawierać cechy jeszcze niestabilne. Obsługuje zrozumienie obrazów i automatycznie wybiera model 8k/32k/128k jako model rozliczeniowy w zależności od długości kontekstu żądania."
  },
@@ -110,6 +110,9 @@
  "ollama": {
    "description": "Modele oferowane przez Ollama obejmują szeroki zakres zastosowań, w tym generowanie kodu, obliczenia matematyczne, przetwarzanie wielojęzyczne i interakcje konwersacyjne, wspierając różnorodne potrzeby wdrożeń na poziomie przedsiębiorstw i lokalnych."
  },
+  "ollamacloud": {
+    "description": "Ollama Cloud oferuje oficjalnie hostowaną usługę inferencji, umożliwiającą natychmiastowy dostęp do biblioteki modeli Ollama oraz obsługę interfejsu zgodnego z OpenAI."
+  },
  "openai": {
    "description": "OpenAI jest wiodącą na świecie instytucją badawczą w dziedzinie sztucznej inteligencji, której modele, takie jak seria GPT, przesuwają granice przetwarzania języka naturalnego. OpenAI dąży do zmiany wielu branż poprzez innowacyjne i efektywne rozwiązania AI. Ich produkty charakteryzują się znaczną wydajnością i opłacalnością, znajdując szerokie zastosowanie w badaniach, biznesie i innowacyjnych aplikacjach."
  },
@@ -1,4 +1,11 @@
 {
+  "codeInterpreter": {
+    "error": "Błąd wykonania",
+    "executing": "Wykonywanie...",
+    "files": "Pliki:",
+    "output": "Wynik:",
+    "returnValue": "Wartość zwracana:"
+  },
  "dalle": {
    "autoGenerate": "Automatyczne generowanie",
    "downloading": "Linki do obrazów wygenerowanych przez DallE3 są ważne tylko przez 1 godzinę. Trwa pobieranie obrazów do lokalnego bufora...",
@@ -150,6 +150,11 @@
      "total": "Total consumido"
    }
  },
+  "minimap": {
+    "jumpToMessage": "Ir para a mensagem nº {{index}}",
+    "nextMessage": "Próxima mensagem",
+    "previousMessage": "Mensagem anterior"
+  },
  "newAgent": "Novo Assistente",
  "pin": "Fixar",
  "pinOff": "Desafixar",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "Descreva o conteúdo que deseja gerar"
    },
+    "quality": {
+      "label": "Qualidade da imagem",
+      "options": {
+        "hd": "Alta definição",
+        "standard": "Padrão"
+      }
+    },
    "seed": {
      "label": "Semente",
      "random": "Semente aleatória"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4 apresenta melhorias significativas sobre a capacidade líder do setor do Sonnet 3.7, destacando-se em codificação com um desempenho de ponta de 72,7% no SWE-bench. O modelo equilibra desempenho e eficiência, adequado para casos de uso internos e externos, e oferece maior controle sobre as implementações por meio de controlabilidade aprimorada."
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "Claude Sonnet 4.5 é o modelo mais inteligente da Anthropic até agora."
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B é um modelo de linguagem grande esparso com 72 bilhões de parâmetros e 16 bilhões de parâmetros ativados, baseado na arquitetura Mixture of Experts em grupos (MoGE). Ele agrupa especialistas na fase de seleção e restringe a ativação de um número igual de especialistas dentro de cada grupo para cada token, alcançando equilíbrio na carga dos especialistas e melhorando significativamente a eficiência de implantação do modelo na plataforma Ascend."
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "Modelo de pensamento Claude Sonnet 4 pode gerar respostas quase instantâneas ou um pensamento gradual prolongado, permitindo que o usuário veja claramente esses processos."
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "Claude Sonnet 4.5 é o modelo mais inteligente da Anthropic até agora."
+  },
  "codegeex-4": {
    "description": "O CodeGeeX-4 é um poderoso assistente de programação AI, suportando perguntas e respostas inteligentes e autocompletar em várias linguagens de programação, aumentando a eficiência do desenvolvimento."
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "kimi-k2 é um modelo base com arquitetura MoE que oferece capacidades avançadas para programação e agentes, com 1T de parâmetros totais e 32B de parâmetros ativados. Em testes de benchmark nas principais categorias — raciocínio de conhecimento geral, programação, matemática e agentes — o desempenho do modelo K2 supera outros modelos de código aberto mais populares."
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2 é um modelo de linguagem de especialistas híbridos em larga escala (MoE) desenvolvido pela AI do Lado Escuro da Lua, com um total de 1 trilhão de parâmetros e 32 bilhões de parâmetros ativados por passagem. Ele é otimizado para capacidades de agente, incluindo uso avançado de ferramentas, raciocínio e síntese de código."
+  },
  "kimi-latest": {
    "description": "O produto assistente inteligente Kimi utiliza o mais recente modelo Kimi, que pode conter recursos ainda não estáveis. Suporta compreensão de imagens e seleciona automaticamente o modelo de cobrança de 8k/32k/128k com base no comprimento do contexto da solicitação."
  },
@@ -110,6 +110,9 @@
  "ollama": {
    "description": "Os modelos oferecidos pela Ollama abrangem amplamente áreas como geração de código, operações matemáticas, processamento multilíngue e interações de diálogo, atendendo a diversas necessidades de implantação em nível empresarial e local."
  },
+  "ollamacloud": {
+    "description": "Ollama Cloud oferece um serviço de inferência hospedado oficialmente, com acesso imediato à biblioteca de modelos Ollama e suporte à interface compatível com OpenAI."
+  },
  "openai": {
    "description": "OpenAI é uma das principais instituições de pesquisa em inteligência artificial do mundo, cujos modelos, como a série GPT, estão na vanguarda do processamento de linguagem natural. A OpenAI se dedica a transformar vários setores por meio de soluções de IA inovadoras e eficientes. Seus produtos apresentam desempenho e custo-benefício significativos, sendo amplamente utilizados em pesquisa, negócios e aplicações inovadoras."
  },
@@ -1,4 +1,11 @@
 {
+  "codeInterpreter": {
+    "error": "Erro de execução",
+    "executing": "Executando...",
+    "files": "Arquivos:",
+    "output": "Saída:",
+    "returnValue": "Valor de retorno:"
+  },
  "dalle": {
    "autoGenerate": "Auto gerar",
    "downloading": "O link da imagem gerada pelo DALL·E3 é válido apenas por 1 hora, está baixando a imagem para o armazenamento local...",
@@ -150,6 +150,11 @@
      "total": "Общее потребление"
    }
  },
+  "minimap": {
+    "jumpToMessage": "Перейти к сообщению № {{index}}",
+    "nextMessage": "Следующее сообщение",
+    "previousMessage": "Предыдущее сообщение"
+  },
  "newAgent": "Создать помощника",
  "pin": "Закрепить",
  "pinOff": "Открепить",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "Опишите, что вы хотите сгенерировать"
    },
+    "quality": {
+      "label": "Качество изображения",
+      "options": {
+        "hd": "Высокое разрешение",
+        "standard": "Стандартное"
+      }
+    },
    "seed": {
      "label": "Сид",
      "random": "Случайное начальное значение"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4 значительно улучшен по сравнению с Sonnet 3.7, демонстрируя выдающиеся результаты в кодировании с передовым показателем 72,7% в SWE-bench. Модель сбалансирована по производительности и эффективности, подходит для внутренних и внешних сценариев и обеспечивает большую управляемость благодаря расширенным возможностям контроля."
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "Claude Sonnet 4.5 — самая интеллектуальная модель Anthropic на сегодняшний день."
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B — это разреженная большая языковая модель с 72 миллиардами параметров и 16 миллиардами активных параметров, основанная на архитектуре группового смешанного эксперта (MoGE). В фазе выбора экспертов эксперты группируются, и токен активирует равное количество экспертов в каждой группе, что обеспечивает баланс нагрузки между экспертами и значительно повышает эффективность развертывания модели на платформе Ascend."
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "Модель мышления Claude Sonnet 4 способна генерировать почти мгновенные ответы или длительные пошаговые размышления, которые пользователь может ясно видеть."
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "Claude Sonnet 4.5 — самая интеллектуальная модель Anthropic на сегодняшний день."
+  },
  "codegeex-4": {
    "description": "CodeGeeX-4 — это мощный AI помощник по программированию, поддерживающий интеллектуальные ответы и автозаполнение кода на различных языках программирования, повышая эффективность разработки."
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "kimi-k2 — это базовая модель архитектуры MoE с выдающимися возможностями в области программирования и агентов. Общий объём параметров — 1 трлн, активируемые параметры — 32 млрд. В бенчмарках по основным категориям (общее знание и рассуждение, программирование, математика, агенты и пр.) модель K2 демонстрирует результаты выше, чем у других ведущих открытых моделей."
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2 — это крупномасштабная смешанная экспертная (MoE) языковая модель, разработанная ИИ с обратной стороны Луны, с общим количеством параметров в 1 триллион и 32 миллиардами активных параметров на один проход вперёд. Она оптимизирована для агентских возможностей, включая продвинутое использование инструментов, рассуждения и синтез кода."
+  },
  "kimi-latest": {
    "description": "Продукт Kimi Smart Assistant использует последнюю модель Kimi, которая может содержать нестабильные функции. Поддерживает понимание изображений и автоматически выбирает модель 8k/32k/128k в качестве модели для выставления счетов в зависимости от длины контекста запроса."
  },
@@ -110,6 +110,9 @@
  "ollama": {
    "description": "Модели, предлагаемые Ollama, охватывают широкий спектр областей, включая генерацию кода, математические вычисления, многоязыковую обработку и диалоговое взаимодействие, поддерживая разнообразные потребности в развертывании на уровне предприятий и локализации."
  },
+  "ollamacloud": {
+    "description": "Ollama Cloud предоставляет официально управляемые сервисы вывода, обеспечивая мгновенный доступ к библиотеке моделей Ollama и поддерживая интерфейс, совместимый с OpenAI."
+  },
  "openai": {
    "description": "OpenAI является ведущим мировым исследовательским институтом в области искусственного интеллекта, чьи модели, такие как серия GPT, продвигают границы обработки естественного языка. OpenAI стремится изменить множество отраслей с помощью инновационных и эффективных AI-решений. Их продукты обладают выдающимися характеристиками и экономичностью, широко используются в исследованиях, бизнесе и инновационных приложениях."
  },
@@ -1,4 +1,11 @@
 {
+  "codeInterpreter": {
+    "error": "Ошибка выполнения",
+    "executing": "Выполнение...",
+    "files": "Файлы:",
+    "output": "Вывод:",
+    "returnValue": "Возвращаемое значение:"
+  },
  "dalle": {
    "autoGenerate": "Автогенерация",
    "downloading": "Ссылка на изображение, созданное DALL·E3, действительна только в течение 1 часа. Идет кэширование изображения локально...",
@@ -150,6 +150,11 @@
      "total": "Toplam tüketim"
    }
  },
+  "minimap": {
+    "jumpToMessage": "{{index}} numaralı mesaja atla",
+    "nextMessage": "Sonraki mesaj",
+    "previousMessage": "Önceki mesaj"
+  },
  "newAgent": "Yeni Asistan",
  "pin": "Pin",
  "pinOff": "Unpin",
@@ -30,6 +30,13 @@
    "prompt": {
      "placeholder": "Oluşturmak istediğiniz içeriği tanımlayın"
    },
+    "quality": {
+      "label": "Görüntü Kalitesi",
+      "options": {
+        "hd": "Yüksek Çözünürlük",
+        "standard": "Standart"
+      }
+    },
    "seed": {
      "label": "Tohum",
      "random": "Rastgele Tohum"
@@ -680,6 +680,9 @@
  "anthropic/claude-sonnet-4": {
    "description": "Claude Sonnet 4, Sonnet 3.7'nin sektör lideri yetenekleri üzerine önemli geliştirmeler yapmış olup, kodlama alanında mükemmel performans sergiler ve SWE-bench'te en ileri %72.7 skoruna ulaşır. Model, performans ve verimlilik arasında denge sağlar, hem dahili hem de harici kullanım durumları için uygundur ve geliştirilmiş kontrol edilebilirlik ile uygulama üzerinde daha fazla hakimiyet sunar."
  },
+  "anthropic/claude-sonnet-4.5": {
+    "description": "Claude Sonnet 4.5, Anthropic'in şimdiye kadarki en akıllı modelidir."
+  },
  "ascend-tribe/pangu-pro-moe": {
    "description": "Pangu-Pro-MoE 72B-A16B, 72 milyar parametreli ve 16 milyar parametre aktive eden seyrek büyük bir dil modelidir. Bu model, grup tabanlı uzman karışımı (MoGE) mimarisine dayanır; uzman seçim aşamasında uzmanları gruplar halinde düzenler ve her grupta token başına eşit sayıda uzmanı aktive ederek uzman yük dengesini sağlar. Bu sayede Ascend platformunda modelin dağıtım verimliliği önemli ölçüde artırılmıştır."
  },
@@ -773,6 +776,9 @@
  "claude-sonnet-4-20250514-thinking": {
    "description": "Claude Sonnet 4 düşünme modeli, neredeyse anında yanıtlar veya uzatılmış adım adım düşünme süreçleri üretebilir; kullanıcılar bu süreçleri net bir şekilde görebilir."
  },
+  "claude-sonnet-4-5-20250929": {
+    "description": "Claude Sonnet 4.5, Anthropic'in şimdiye kadarki en akıllı modelidir."
+  },
  "codegeex-4": {
    "description": "CodeGeeX-4, çeşitli programlama dillerinde akıllı soru-cevap ve kod tamamlama desteği sunan güçlü bir AI programlama asistanıdır, geliştirme verimliliğini artırır."
  },
@@ -1916,6 +1922,9 @@
  "kimi-k2-turbo-preview": {
    "description": "kimi-k2, son derece güçlü kod yazma ve Agent yeteneklerine sahip MoE mimarisine dayanan bir temel modeldir; toplam parametre sayısı 1T, aktif (etkin) parametre sayısı 32B. Genel bilgi çıkarımı, programlama, matematik ve Agent gibi ana kategorilerde yapılan karşılaştırmalı performans testlerinde K2 modelinin performansı diğer önde gelen açık kaynak modellerinin üzerindedir."
  },
+  "kimi-k2:1t": {
+    "description": "Kimi K2, Ay'ın Karanlık Yüzü AI tarafından geliştirilen, toplamda 1 trilyon parametreye ve her ileri geçişte 32 milyar aktif parametreye sahip büyük ölçekli bir Karışık Uzman (MoE) dil modelidir. Gelişmiş araç kullanımı, muhakeme ve kod sentezi dahil olmak üzere ajan yetenekleri için optimize edilmiştir."
+  },
  "kimi-latest": {
    "description": "Kimi akıllı asistan ürünü, en son Kimi büyük modelini kullanır ve henüz kararlı olmayan özellikler içerebilir. Görüntü anlayışını desteklerken, isteğin bağlam uzunluğuna göre 8k/32k/128k modelini faturalama modeli olarak otomatik olarak seçecektir."
  },
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
semantic-release-bot	1e9b05d7ce	🔖 chore(release): v1.133.3 [skip ci] ### [Version 1.133.3](https://github.com/lobehub/lobe-chat/compare/v1.133.2...v1.133.3) <sup>Released on 2025-10-01</sup> #### ♻ Code Refactoring - misc: Refactor a `ssrf-safe-fetch` module. #### 🐛 Bug Fixes - misc: Fix frontend random API key config not work. <br/> <details> <summary><kbd>Improvements and Fixes</kbd></summary> #### Code refactoring * misc: Refactor a `ssrf-safe-fetch` module, closes [#9474](https://github.com/lobehub/lobe-chat/issues/9474) ([`92da716`](https://github.com/lobehub/lobe-chat/commit/92da716)) #### What's fixed * misc: Fix frontend random API key config not work, closes [#9477](https://github.com/lobehub/lobe-chat/issues/9477) [#9255](https://github.com/lobehub/lobe-chat/issues/9255) ([`a194d48`](https://github.com/lobehub/lobe-chat/commit/a194d48)) </details> <div align="right"> [![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top) </div>	2025-10-01 19:40:38 +00:00
Arvin Xu	92da716028	♻️ refactor: refactor a `ssrf-safe-fetch` module (#9474 ) * add ssrf-safe-fetch * fix web-crawler * add tests * revert * Update index.ts * fix tests	2025-10-02 03:31:20 +08:00
renovate[bot]	635d0d649b	Update dependency @opentelemetry/exporter-trace-otlp-http to ^0.205.0 (#9455 ) Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>	2025-10-01 14:54:05 +08:00
renovate[bot]	3ae352b79e	Update dependency @opentelemetry/instrumentation-http to ^0.205.0 (#9458 ) Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>	2025-10-01 14:53:58 +08:00
Arvin Xu	a194d48545	🐛 fix: fix frontend random API key config not work (#9477 ) * ✨ feat: add frontend random API key selection support - Implement ClientApiKeyManager for random selection from comma-separated keys - Update getProviderAuthPayload to use random key picking for all providers - Add comprehensive tests for the new functionality - Mirror existing server-side implementation for consistency Closes #9255 🤖 Generated with [Claude Code](https://claude.ai/code) Co-authored-by: LobeHub Bot <lobehubbot@users.noreply.github.com> * fix tests * fix implement * fix test * fix test	2025-10-01 05:46:24 +08:00
YuTengjing	0ee4f18d89	📝 docs(i18n): add image quality translations for multiple languages (#9495 )	2025-09-30 21:17:47 +08:00
YuTengjing	49ea508cc4	🔨 chore: support chat api and create image cost caculate (#9492 )	2025-09-30 21:09:56 +08:00
lobehubbot	88592d3f08	📝 docs(bot): Auto sync agents & plugin to readme	2025-09-30 09:05:58 +00:00
semantic-release-bot	7e0b715e22	🔖 chore(release): v1.133.2 [skip ci] ### [Version 1.133.2](https://github.com/lobehub/lobe-chat/compare/v1.133.1...v1.133.2) <sup>Released on 2025-09-30</sup> #### 💄 Styles - misc: Add minimap to chat list for quick navigation. <br/> <details> <summary><kbd>Improvements and Fixes</kbd></summary> #### Styles * misc: Add minimap to chat list for quick navigation, closes [#9470](https://github.com/lobehub/lobe-chat/issues/9470) ([`8db47eb`](https://github.com/lobehub/lobe-chat/commit/8db47eb)) </details> <div align="right"> [![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top) </div>	2025-09-30 09:04:58 +00:00
René Wang	8db47eb816	💄 style: Add minimap to chat list for quick navigation (#9470 ) * feat: Add minimap to chat list * style: Tweak style * style: Hover to reveal the arrow * style: Hover to reveal the arrow * feat: Message anchor detection * fix: Type error * style: Remove drag handle for topic panel * fix: type error * fix: Anchor position * fix: Scroll * feat: Add missing translation * fix: Offset * fix: Offset * feat: Remove test files	2025-09-30 16:55:17 +08:00
YuTengjing	6325602480	📝 docs(rules): optimize agent rules and documentation structure (#9486 )	2025-09-30 16:07:32 +08:00
lobehubbot	b745f11873	📝 docs(bot): Auto sync agents & plugin to readme	2025-09-30 04:46:57 +00:00
semantic-release-bot	7f31eba0d9	🔖 chore(release): v1.133.1 [skip ci] ### [Version 1.133.1](https://github.com/lobehub/lobe-chat/compare/v1.133.0...v1.133.1) <sup>Released on 2025-09-30</sup> #### 💄 Styles - misc: Update i18n. <br/> <details> <summary><kbd>Improvements and Fixes</kbd></summary> #### Styles * misc: Update i18n, closes [#9480](https://github.com/lobehub/lobe-chat/issues/9480) ([`dfeb42c`](https://github.com/lobehub/lobe-chat/commit/dfeb42c)) </details> <div align="right"> [![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top) </div>	2025-09-30 04:45:58 +00:00
LobeHub Bot	dfeb42ce1c	🤖 style: update i18n (#9480 ) 💄 style: update i18n Co-authored-by: canisminor1990 <17870709+canisminor1990@users.noreply.github.com>	2025-09-30 12:36:35 +08:00
renovate[bot]	138071d0e3	Update dependency ollama to ^0.6.0 (#9461 ) Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>	2025-09-30 12:32:00 +08:00
lobehubbot	1aaa5f5152	📝 docs(bot): Auto sync agents & plugin to readme	2025-09-29 20:33:43 +00:00
semantic-release-bot	e1acbf21fd	🔖 chore(release): v1.133.0 [skip ci] ## [Version 1.133.0](https://github.com/lobehub/lobe-chat/compare/v1.132.19...v1.133.0) <sup>Released on 2025-09-29</sup> #### ✨ Features - misc: Add builtin Python plugin, add Claude Sonnet 4.5 model to AI chat models. <br/> <details> <summary><kbd>Improvements and Fixes</kbd></summary> #### What's improved * misc: Add builtin Python plugin, closes [#8873](https://github.com/lobehub/lobe-chat/issues/8873) ([`fa6ef94`](https://github.com/lobehub/lobe-chat/commit/fa6ef94)) * misc: Add Claude Sonnet 4.5 model to AI chat models, closes [#9476](https://github.com/lobehub/lobe-chat/issues/9476) ([`a30a65c`](https://github.com/lobehub/lobe-chat/commit/a30a65c)) </details> <div align="right"> [![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top) </div>	2025-09-29 20:32:18 +00:00
Arvin Xu	79bc08a076	🔨 chore: add claude translator and improve issue template (#9479 ) * add translator * use claude translator	2025-09-30 04:22:01 +08:00
Aloxaf	fa6ef94067	✨ feat: add builtin Python plugin (#8873 ) * feat: 初步完成 * chore: type * feat: 图片功能 * feat: 文件下载功能 * refactor: 简化代码 * chore: 清理代码 * chore: clean * chore: 清理代码 * chore: 清理代码 * chore: 小改进 * fix: 上传完成前图片无法显示 * refactor: 增加 python-interpreter package * chore: 清理 * feat: 传入上下文中的文件 * chore: 小优化 * chore: 中文字体 * chore: clean * fix: 服务端部署 * fix: 重复文件检查 * test: 增加 interpreter.test.ts * test: add worker.test.ts * style: fix import * test: fix * style: fix import * style: move env file to envs * style: 限制代码框高度 * style: 重命名 * misc: 小修小补 * refactor: 重命名为 code-interpreter --------- Co-authored-by: Arvin Xu <arvinx@foxmail.com>	2025-09-30 04:20:57 +08:00
YuTengjing	a30a65cd4c	✨ feat: add Claude Sonnet 4.5 model to AI chat models (#9476 )	2025-09-30 04:20:51 +08:00
Arvin Xu	2e6018a496	🔨 chore: fix types (#9478 ) fix types	2025-09-30 03:54:12 +08:00
Arvin Xu	1776a24943	🔨 chore: add auto close issues workflow (#9473 ) * add auto close issues * update	2025-09-30 02:14:47 +08:00
renovate[bot]	27d133a417	Update dependency @opentelemetry/exporter-metrics-otlp-http to ^0.205.0 (#9454 ) Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>	2025-09-29 18:49:24 +08:00
renovate[bot]	de3478b17a	Update dependency @opentelemetry/instrumentation to ^0.205.0 (#9456 ) Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>	2025-09-29 18:49:05 +08:00
renovate[bot]	694cdbea8f	Update dependency @opentelemetry/sdk-node to ^0.205.0 (#9460 ) Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>	2025-09-29 18:48:26 +08:00
lobehubbot	ffbb804b3f	📝 docs(bot): Auto sync agents & plugin to readme	2025-09-29 08:18:20 +00:00
semantic-release-bot	5947148c01	🔖 chore(release): v1.132.19 [skip ci] ### [Version 1.132.19](https://github.com/lobehub/lobe-chat/compare/v1.132.18...v1.132.19) <sup>Released on 2025-09-29</sup> <br/> <details> <summary><kbd>Improvements and Fixes</kbd></summary> </details> <div align="right"> [![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top) </div>	2025-09-29 08:17:23 +00:00
René Wang	b0cb96e5c2	👷 build: Add `virtual` column to agent table (#9464 )	2025-09-29 10:07:19 +02:00
lobehubbot	f1d732d166	📝 docs(bot): Auto sync agents & plugin to readme	2025-09-28 05:29:59 +00:00
semantic-release-bot	c6de50e385	🔖 chore(release): v1.132.18 [skip ci] ### [Version 1.132.18](https://github.com/lobehub/lobe-chat/compare/v1.132.17...v1.132.18) <sup>Released on 2025-09-28</sup> #### 🐛 Bug Fixes - misc: Refactor tools-engine and fix search token count. #### 💄 Styles - misc: Update i18n. <br/> <details> <summary><kbd>Improvements and Fixes</kbd></summary> #### What's fixed * misc: Refactor tools-engine and fix search token count, closes [#9448](https://github.com/lobehub/lobe-chat/issues/9448) ([`e82d4b7`](https://github.com/lobehub/lobe-chat/commit/e82d4b7)) #### Styles * misc: Update i18n, closes [#9449](https://github.com/lobehub/lobe-chat/issues/9449) ([`b04a5d7`](https://github.com/lobehub/lobe-chat/commit/b04a5d7)) </details> <div align="right"> [![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top) </div>	2025-09-28 05:28:51 +00:00
LobeHub Bot	b04a5d7906	🤖 style: update i18n (#9449 ) 💄 style: update i18n Co-authored-by: canisminor1990 <17870709+canisminor1990@users.noreply.github.com>	2025-09-28 13:18:26 +08:00
renovate[bot]	088cc2c56c	Update pnpm to v10.17.1 (#9450 ) Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>	2025-09-28 13:13:23 +08:00
renovate[bot]	acb49c1393	Update dependency @anthropic-ai/sdk to ^0.64.0 (#9451 ) Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>	2025-09-28 13:12:25 +08:00
Arvin Xu	e82d4b7274	🐛 fix: refactor tools-engine and fix search token count (#9448 ) * init toolsEngine * clean implement * refactor with tools-engine * add more tests * update * rename * refactor the tools engine * refactor code * refactor helpers * fix tools is empty issue * fix tests * refactor to remove enabledSchema * support defaultToolIds * fix tests * fix tests	2025-09-28 13:12:14 +08:00
lobehubbot	2dc03b47d6	📝 docs(bot): Auto sync agents & plugin to readme	2025-09-27 05:58:05 +00:00
semantic-release-bot	3e64ee659e	🔖 chore(release): v1.132.17 [skip ci] ### [Version 1.132.17](https://github.com/lobehub/lobe-chat/compare/v1.132.16...v1.132.17) <sup>Released on 2025-09-27</sup> #### 🐛 Bug Fixes - misc: Fix input empty group name. <br/> <details> <summary><kbd>Improvements and Fixes</kbd></summary> #### What's fixed * misc: Fix input empty group name, closes [#9441](https://github.com/lobehub/lobe-chat/issues/9441) ([`f653ce1`](https://github.com/lobehub/lobe-chat/commit/f653ce1)) </details> <div align="right"> [![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top) </div>	2025-09-27 05:57:02 +00:00
huangkairan	f653ce1737	🐛 fix: fix input empty group name (#9441 ) fix: cant input empty group name	2025-09-27 07:47:21 +02:00
Arvin Xu	eeabb69088	⚡️ perf: fix battery usage (#9444 )	2025-09-27 07:46:18 +02:00
sxjeru	356cf029dd	✨ feat: Add new provider Ollama Cloud (#9435 )	2025-09-27 07:45:47 +02:00
lobehubbot	6e7b420347	📝 docs(bot): Auto sync agents & plugin to readme	2025-09-26 15:43:27 +00:00
semantic-release-bot	ee464838ac	🔖 chore(release): v1.132.16 [skip ci] ### [Version 1.132.16](https://github.com/lobehub/lobe-chat/compare/v1.132.15...v1.132.16) <sup>Released on 2025-09-26</sup> #### 🐛 Bug Fixes - misc: Resolve qwen-image-edit imageUrls conversion issue. <br/> <details> <summary><kbd>Improvements and Fixes</kbd></summary> #### What's fixed * misc: Resolve qwen-image-edit imageUrls conversion issue, closes [#9414](https://github.com/lobehub/lobe-chat/issues/9414) ([`ec5af1b`](https://github.com/lobehub/lobe-chat/commit/ec5af1b)) </details> <div align="right"> [![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top) </div>	2025-09-26 15:42:22 +00:00
Maple Gao	ec5af1b4c7	🐛 fix: resolve qwen-image-edit imageUrls conversion issue (#9414 ) * 🔧 fix: resolve missing imageurls convertion * ✅ test: add comprehensive tests for qwen-image-edit imageUrls conversion - Add tests for imageUrls array to imageUrl conversion - Add tests for multiple elements using first element - Add tests for empty array error handling - Add tests for imageUrl priority over imageUrls - Add tests for missing parameters error handling - All 20 test cases pass (5 new + 15 existing) --------- Co-authored-by: Arvin Xu <arvinx@foxmail.com>	2025-09-26 17:32:18 +02:00