🔖 chore(release): v1.136.10 [skip ci]

### [Version 1.136.10](https://github.com/lobehub/lobe-chat/compare/v1.136.9...v1.136.10)
<sup>Released on **2025-10-11**</sup>

#### 💄 Styles

- **misc**: Improve search experience.

<br/>

<details>
<summary><kbd>Improvements and Fixes</kbd></summary>

#### Styles

* **misc**: Improve search experience, closes [#9661](https://github.com/lobehub/lobe-chat/issues/9661) ([8624f84](https://github.com/lobehub/lobe-chat/commit/8624f84))

</details>

<div align="right">

[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)

</div>

.cursor/rules/backend-architecture.mdc

@@ -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。

.cursor/rules/code-review.mdc

@@ -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>

.cursor/rules/cursor-ux.mdc

@@ -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

.cursor/rules/define-database-model.mdc

@@ -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/`

.cursor/rules/project-introduce.mdc

@@ -4,41 +4,33 @@ 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: 🤯
+Supported 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
+- PGLite for client DB and Neon 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

.cursor/rules/project-structure.mdc

@@ -5,235 +5,118 @@ alwaysApply: false
 
 # LobeChat Project Structure
 
-## Directory Structure
+## Complete Project Structure
 
-note: some files are not shown for simplicity.
+This project uses common monorepo structure. The workspace packages name use `@lobechat/` namespace.
+
+**note**: some not very important files are not shown for simplicity.
 
 ```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/
+│   │   └── src/
+│   │       └── aiModels/
+│   ├── model-runtime/
+│   │   └── src/
+│   │       ├── core/
+│   │       └── providers/
+│   ├── 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/` cross-platform 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` server-used-only 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`
+- **Web with ClientDB**: React UI → Client Service → Direct Model Access → PGLite (Web WASM)
+- **Web with ServerDB**: 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)

.cursor/rules/rules-index.mdc

@@ -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

.cursor/rules/system-role.mdc

@@ -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

.cursor/rules/typescript.mdc

@@ -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
 
@@ -79,16 +29,11 @@ alwaysApply: false
 
 ## Code Structure and Readability
 
-- Refactor repeated logic into reusable functions.
 - Prefer object destructuring when accessing and using properties.
 - Use consistent, descriptive naming; avoid obscure abbreviations.
 - Use semantically meaningful variable, function, and class names.
 - Replace magic numbers or strings with well-named constants.
-- Keep meaningful code comments; do not remove them when applying edits. Update comments when behavior changes.
-- Ensure JSDoc comments accurately reflect the implementation.
-- Look for opportunities to simplify or modernize code with the latest JavaScript/TypeScript features where it improves clarity.
 - Defer formatting to tooling; ignore purely formatting-only issues and autofixable lint problems.
-- Respect project Prettier settings.
 
 ## UI and Theming
 
@@ -100,15 +45,14 @@ alwaysApply: false
 ## Performance
 
 - Prefer `for…of` loops to index-based `for` loops when feasible.
-- Decide whether callbacks should be debounced or throttled based on UX and performance needs.
-- Reuse existing npm packages rather than reinventing the wheel (e.g., `lodash-es/omit`).
+- Reuse existing utils inside `packages/utils` or installed npm packages rather than reinventing the wheel.
 - Query only the required columns from a database rather than selecting entire rows.
 
 ## Time and Consistency
 
 - Instead of calling `Date.now()` multiple times, assign it to a constant once and reuse it to ensure consistency and improve readability.
 
-## Some logging rules
+## Logging
 
 - Never log user private information like api key, etc
 - Don't use `import { log } from 'debug'` to log messages, because it will directly log the message to the console.

.github/ISSUE_TEMPLATE/1_bug_report_cn.yml

@@ -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。

.github/ISSUE_TEMPLATE/2_feature_request_cn.yml

@@ -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。

.github/ISSUE_TEMPLATE/config.yml

@@ -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.

.github/PULL_REQUEST_TEMPLATE.md

@@ -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. -->

.github/scripts/lock-closed-issues.js

@@ -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}`);
+};

.github/workflows/claude-translator.yml

@@ -0,0 +1,108 @@
+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@v5
+        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:
+                 [Translated content]
+
+                 ---
+                 > This issue/comment/review was translated by Claude.
+
+                 <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

.github/workflows/desktop-pr-build.yml

@@ -36,7 +36,7 @@ jobs:
       - name: Install bun
         uses: oven-sh/setup-bun@v2
         with:
-          bun-version: ${{ secrets.BUN_VERSION }}
+          bun-version: 1.2.23
 
       - name: Install deps
         run: bun i
@@ -95,7 +95,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        os: [macos-latest, macos-13, windows-2025, ubuntu-latest]
+        os: [macos-latest, macos-15-intel, windows-2025, ubuntu-latest]
     steps:
       - uses: actions/checkout@v5
         with:
@@ -129,11 +129,11 @@ jobs:
         run: npm run desktop:build
         env:
           # 设置更新通道，PR构建为nightly，否则为stable
-          UPDATE_CHANNEL: 'nightly'
+          UPDATE_CHANNEL: "nightly"
           APP_URL: http://localhost:3015
-          DATABASE_URL: 'postgresql://postgres@localhost:5432/postgres'
+          DATABASE_URL: "postgresql://postgres@localhost:5432/postgres"
           # 默认添加一个加密 SECRET
-          KEY_VAULTS_SECRET: 'oLXWIiR/AKF+rWaqy9lHkrYgzpATbW3CtJp3UfkVgpE='
+          KEY_VAULTS_SECRET: "oLXWIiR/AKF+rWaqy9lHkrYgzpATbW3CtJp3UfkVgpE="
           # macOS 签名和公证配置
           CSC_LINK: ${{ secrets.APPLE_CERTIFICATE_BASE64 }}
           CSC_KEY_PASSWORD: ${{ secrets.APPLE_CERTIFICATE_PASSWORD }}
@@ -152,10 +152,10 @@ jobs:
         run: npm run desktop:build
         env:
           # 设置更新通道，PR构建为nightly，否则为stable
-          UPDATE_CHANNEL: 'nightly'
+          UPDATE_CHANNEL: "nightly"
           APP_URL: http://localhost:3015
-          DATABASE_URL: 'postgresql://postgres@localhost:5432/postgres'
-          KEY_VAULTS_SECRET: 'oLXWIiR/AKF+rWaqy9lHkrYgzpATbW3CtJp3UfkVgpE='
+          DATABASE_URL: "postgresql://postgres@localhost:5432/postgres"
+          KEY_VAULTS_SECRET: "oLXWIiR/AKF+rWaqy9lHkrYgzpATbW3CtJp3UfkVgpE="
           NEXT_PUBLIC_DESKTOP_PROJECT_ID: ${{ secrets.UMAMI_NIGHTLY_DESKTOP_PROJECT_ID }}
           NEXT_PUBLIC_DESKTOP_UMAMI_BASE_URL: ${{ secrets.UMAMI_NIGHTLY_DESKTOP_BASE_URL }}
           # 将 TEMP 和 TMP 目录设置到 C 盘
@@ -168,10 +168,10 @@ jobs:
         run: npm run desktop:build
         env:
           # 设置更新通道，PR构建为nightly，否则为stable
-          UPDATE_CHANNEL: 'nightly'
+          UPDATE_CHANNEL: "nightly"
           APP_URL: http://localhost:3015
-          DATABASE_URL: 'postgresql://postgres@localhost:5432/postgres'
-          KEY_VAULTS_SECRET: 'oLXWIiR/AKF+rWaqy9lHkrYgzpATbW3CtJp3UfkVgpE='
+          DATABASE_URL: "postgresql://postgres@localhost:5432/postgres"
+          KEY_VAULTS_SECRET: "oLXWIiR/AKF+rWaqy9lHkrYgzpATbW3CtJp3UfkVgpE="
           NEXT_PUBLIC_DESKTOP_PROJECT_ID: ${{ secrets.UMAMI_NIGHTLY_DESKTOP_PROJECT_ID }}
           NEXT_PUBLIC_DESKTOP_UMAMI_BASE_URL: ${{ secrets.UMAMI_NIGHTLY_DESKTOP_BASE_URL }}
 
@@ -188,7 +188,7 @@ jobs:
             else
               ARCH_SUFFIX="x64"
             fi
-            
+
             mv latest-mac.yml "latest-mac-${ARCH_SUFFIX}.yml"
             echo "✅ Renamed latest-mac.yml to latest-mac-${ARCH_SUFFIX}.yml (detected: $SYSTEM_ARCH)"
             ls -la latest-mac-*.yml
@@ -234,7 +234,7 @@ jobs:
       - name: Install bun
         uses: oven-sh/setup-bun@v2
         with:
-          bun-version: ${{ secrets.BUN_VERSION }}
+          bun-version: 1.2.23
 
       # 下载所有平台的构建产物
       - name: Download artifacts

.github/workflows/docker-database.yml

@@ -1,4 +1,6 @@
 name: Publish Database Docker Image
+permissions:
+  contents: read
 
 on:
   workflow_dispatch:

.github/workflows/docker-pglite.yml

@@ -1,4 +1,6 @@
 name: Publish Docker Pglite Image
+permissions:
+  contents: read
 
 on:
   workflow_dispatch:

.github/workflows/docker.yml

@@ -1,4 +1,6 @@
 name: Publish Docker Image
+permissions:
+  contents: read
 
 on:
   workflow_dispatch:

.github/workflows/issue-auto-comments.yml

@@ -28,8 +28,7 @@ jobs:
             👀 @{{ author }}
 
             Thank you for raising an issue. We will investigate into the matter and get back to you as soon as possible.
-            Please make sure you have given us as much context as possible.\
-            非常感谢您提交 issue。我们会尽快调查此事，并尽快回复您。 请确保您已经提供了尽可能多的背景信息。
+            Please make sure you have given us as much context as possible.
       - name: Auto Comment on Issues Closed
         uses: wow-actions/auto-comment@v1
         with:
@@ -37,8 +36,7 @@ jobs:
           issuesClosed: |
             ✅ @{{ author }}
 
-            This issue is closed, If you have any questions, you can comment and reply.\
-            此问题已经关闭。如果您有任何问题，可以留言并回复。
+            This issue is closed, If you have any questions, you can comment and reply.
       - name: Auto Comment on Pull Request Opened
         uses: wow-actions/auto-comment@v1
         with:
@@ -48,9 +46,7 @@ jobs:
 
             Thank you for raising your pull request and contributing to our Community
             Please make sure you have followed our contributing guidelines. We will review it as soon as possible.
-            If you encounter any problems, please feel free to connect with us.\
-            非常感谢您提出拉取请求并为我们的社区做出贡献，请确保您已经遵循了我们的贡献指南，我们会尽快审查它。
-            如果您遇到任何问题，请随时与我们联系。
+            If you encounter any problems, please feel free to connect with us.
       - name: Auto Comment on Pull Request Merged
         uses: actions-cool/pr-welcome@main
         if: github.event.pull_request.merged == true
@@ -59,8 +55,7 @@ jobs:
           comment: |
             ❤️ Great PR @${{ github.event.pull_request.user.login }} ❤️
 
-            The growth of project is inseparable from user feedback and contribution, thanks for your contribution! If you are interesting with the lobehub developer community, please join our [discord](https://discord.com/invite/AYFPHvv2jT) and then dm @arvinxx or @canisminor1990. They will invite you to our private developer channel. We are talking about the lobe-chat development or sharing ai newsletter around the world.\
-            项目的成长离不开用户反馈和贡献，感谢您的贡献! 如果您对 LobeHub 开发者社区感兴趣，请加入我们的 [discord](https://discord.com/invite/AYFPHvv2jT)，然后私信 @arvinxx 或 @canisminor1990。他们会邀请您加入我们的私密开发者频道。我们将会讨论关于 Lobe Chat 的开发，分享和讨论全球范围内的 AI 消息。
+            The growth of project is inseparable from user feedback and contribution, thanks for your contribution! If you are interesting with the lobehub developer community, please join our [discord](https://discord.com/invite/AYFPHvv2jT) and then dm @arvinxx or @canisminor1990. They will invite you to our private developer channel. We are talking about the lobe-chat development or sharing ai newsletter around the world.
           emoji: 'hooray'
           pr-emoji: '+1, heart'
       - name: Remove inactive

.github/workflows/issue-close-require.yml

@@ -38,8 +38,7 @@ jobs:
           body: |
             👋 @{{ author }}
             <br/>
-            Since the issue was labeled with `✅ Fixed`, but no response in 3 days. This issue will be closed. If you have any questions, you can comment and reply.\
-            由于该 issue 被标记为已修复，同时 3 天未收到回应。现关闭 issue，若有任何问题，可评论回复。
+            Since the issue was labeled with `✅ Fixed`, but no response in 3 days. This issue will be closed. If you have any questions, you can comment and reply.
       - name: need reproduce
         uses: actions-cool/issues-helper@v3
         with:
@@ -50,8 +49,7 @@ jobs:
           body: |
             👋 @{{ author }}
             <br/>
-            Since the issue was labeled with `🤔 Need Reproduce`, but no response in 3 days. This issue will be closed. If you have any questions, you can comment and reply.\
-            由于该 issue 被标记为需要更多信息，却 3 天未收到回应。现关闭 issue，若有任何问题，可评论回复。
+            Since the issue was labeled with `🤔 Need Reproduce`, but no response in 3 days. This issue will be closed. If you have any questions, you can comment and reply.
       - name: need reproduce
         uses: actions-cool/issues-helper@v3
         with:
@@ -62,5 +60,4 @@ jobs:
           body: |
             👋 @{{ github.event.issue.user.login }}
             <br/>
-            Since the issue was labeled with `🙅🏻‍♀️ WON'T DO`, and no response in 3 days. This issue will be closed. If you have any questions, you can comment and reply.\
-            由于该 issue 被标记为暂不处理，同时 3 天未收到回应。现关闭 issue，若有任何问题，可评论回复。
+            Since the issue was labeled with `🙅🏻‍♀️ WON'T DO`, and no response in 3 days. This issue will be closed. If you have any questions, you can comment and reply.

.github/workflows/issues-translate.yml

@@ -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 }}

.github/workflows/lock-closed-issues.yml

@@ -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@v5
+
+      - name: Lock closed issues after 7 days of inactivity
+        uses: actions/github-script@v8
+        with:
+          script: |
+            const lockScript = require('./.github/scripts/lock-closed-issues.js');
+            await lockScript({ github, context });

.github/workflows/release-desktop-beta.yml

@@ -32,7 +32,7 @@ jobs:
       - name: Install bun
         uses: oven-sh/setup-bun@v2
         with:
-          bun-version: ${{ secrets.BUN_VERSION }}
+          bun-version: 1.2.23
 
       - name: Install deps
         run: bun i
@@ -82,7 +82,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        os: [macos-latest, macos-13, windows-2025, ubuntu-latest]
+        os: [macos-latest, macos-15-intel, windows-2025, ubuntu-latest]
     steps:
       - uses: actions/checkout@v5
         with:
@@ -116,9 +116,9 @@ jobs:
         run: npm run desktop:build
         env:
           APP_URL: http://localhost:3015
-          DATABASE_URL: 'postgresql://postgres@localhost:5432/postgres'
+          DATABASE_URL: "postgresql://postgres@localhost:5432/postgres"
           # 默认添加一个加密 SECRET
-          KEY_VAULTS_SECRET: 'oLXWIiR/AKF+rWaqy9lHkrYgzpATbW3CtJp3UfkVgpE='
+          KEY_VAULTS_SECRET: "oLXWIiR/AKF+rWaqy9lHkrYgzpATbW3CtJp3UfkVgpE="
           # macOS 签名和公证配置
           CSC_LINK: ${{ secrets.APPLE_CERTIFICATE_BASE64 }}
           CSC_KEY_PASSWORD: ${{ secrets.APPLE_CERTIFICATE_PASSWORD }}
@@ -137,8 +137,8 @@ jobs:
         run: npm run desktop:build
         env:
           APP_URL: http://localhost:3015
-          DATABASE_URL: 'postgresql://postgres@localhost:5432/postgres'
-          KEY_VAULTS_SECRET: 'oLXWIiR/AKF+rWaqy9lHkrYgzpATbW3CtJp3UfkVgpE='
+          DATABASE_URL: "postgresql://postgres@localhost:5432/postgres"
+          KEY_VAULTS_SECRET: "oLXWIiR/AKF+rWaqy9lHkrYgzpATbW3CtJp3UfkVgpE="
           NEXT_PUBLIC_DESKTOP_PROJECT_ID: ${{ secrets.UMAMI_BETA_DESKTOP_PROJECT_ID }}
           NEXT_PUBLIC_DESKTOP_UMAMI_BASE_URL: ${{ secrets.UMAMI_BETA_DESKTOP_BASE_URL }}
 
@@ -152,8 +152,8 @@ jobs:
         run: npm run desktop:build
         env:
           APP_URL: http://localhost:3015
-          DATABASE_URL: 'postgresql://postgres@localhost:5432/postgres'
-          KEY_VAULTS_SECRET: 'oLXWIiR/AKF+rWaqy9lHkrYgzpATbW3CtJp3UfkVgpE='
+          DATABASE_URL: "postgresql://postgres@localhost:5432/postgres"
+          KEY_VAULTS_SECRET: "oLXWIiR/AKF+rWaqy9lHkrYgzpATbW3CtJp3UfkVgpE="
           NEXT_PUBLIC_DESKTOP_PROJECT_ID: ${{ secrets.UMAMI_BETA_DESKTOP_PROJECT_ID }}
           NEXT_PUBLIC_DESKTOP_UMAMI_BASE_URL: ${{ secrets.UMAMI_BETA_DESKTOP_BASE_URL }}
 
@@ -170,7 +170,7 @@ jobs:
             else
               ARCH_SUFFIX="x64"
             fi
-            
+
             mv latest-mac.yml "latest-mac-${ARCH_SUFFIX}.yml"
             echo "✅ Renamed latest-mac.yml to latest-mac-${ARCH_SUFFIX}.yml (detected: $SYSTEM_ARCH)"
             ls -la latest-mac-*.yml
@@ -216,7 +216,7 @@ jobs:
       - name: Install bun
         uses: oven-sh/setup-bun@v2
         with:
-          bun-version: ${{ secrets.BUN_VERSION }}
+          bun-version: 1.2.23
 
       # 下载所有平台的构建产物
       - name: Download artifacts

.github/workflows/release.yml

@@ -1,4 +1,10 @@
 name: Release CI
+
+permissions:
+  contents: write
+  issues: write
+  pull-requests: write
+
 on:
   push:
     branches:
@@ -35,7 +41,7 @@ jobs:
       - name: Install bun
         uses: oven-sh/setup-bun@v2
         with:
-          bun-version: ${{ secrets.BUN_VERSION }}
+          bun-version: 1.2.23
 
       - name: Install deps
         run: bun i

.github/workflows/sync-database-schema.yml

@@ -1,4 +1,6 @@
 name: Database Schema Visualization CI
+permissions:
+  contents: read
 
 on:
   push:

.github/workflows/test.yml

@@ -18,6 +18,7 @@ jobs:
           - web-crawler
           - electron-server-ipc
           - utils
+          - python-interpreter
           - context-engine
           - agent-runtime
 
@@ -44,7 +45,7 @@ jobs:
         run: bun run --filter @lobechat/${{ matrix.package }} test:coverage
 
       - name: Upload ${{ matrix.package }} coverage to Codecov
-        uses: codecov/codecov-action@v4
+        uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
           files: ./packages/${{ matrix.package }}/coverage/lcov.info
@@ -70,7 +71,7 @@ jobs:
       - name: Install bun
         uses: oven-sh/setup-bun@v2
         with:
-          bun-version: ${{ secrets.BUN_VERSION }}
+          bun-version: 1.2.23
 
       - name: Install deps
         run: bun i
@@ -79,7 +80,7 @@ jobs:
         run: bun run --filter ${{ matrix.package }} test:coverage
 
       - name: Upload ${{ matrix.package }} coverage to Codecov
-        uses: codecov/codecov-action@v4
+        uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
           files: ./packages/${{ matrix.package }}/coverage/lcov.info
@@ -103,7 +104,7 @@ jobs:
       - name: Install bun
         uses: oven-sh/setup-bun@v2
         with:
-          bun-version: ${{ secrets.BUN_VERSION }}
+          bun-version: 1.2.23
 
       - name: Install deps
         run: bun i
@@ -112,7 +113,7 @@ jobs:
         run: bun run test-app:coverage
 
       - name: Upload App Coverage to Codecov
-        uses: codecov/codecov-action@v4
+        uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
           files: ./coverage/app/lcov.info
@@ -147,7 +148,7 @@ jobs:
       - name: Install bun
         uses: oven-sh/setup-bun@v2
         with:
-          bun-version: ${{ secrets.BUN_VERSION }}
+          bun-version: 1.2.23
 
       - name: Install deps
         run: bun i
@@ -173,7 +174,7 @@ jobs:
           APP_URL: https://home.com
 
       - name: Upload Database coverage to Codecov
-        uses: codecov/codecov-action@v4
+        uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
           files: ./packages/database/coverage/lcov.info

.i18nrc.js

@@ -25,7 +25,7 @@ module.exports = defineConfig({
   ],
   temperature: 0,
   saveImmediately: true,
-  modelName: 'gpt-4.1-mini',
+  modelName: 'chatgpt-4o-latest',
   experimental: {
     jsonMode: true,
   },

.vscode/settings.json

@@ -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",

AGENTS.md

@@ -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

CHANGELOG.md

@@ -2,6 +2,973 @@
 
 # Changelog
 
+### [Version 1.136.10](https://github.com/lobehub/lobe-chat/compare/v1.136.9...v1.136.10)
+
+<sup>Released on **2025-10-11**</sup>
+
+#### 💄 Styles
+
+- **misc**: Improve search experience.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Styles
+
+- **misc**: Improve search experience, closes [#9661](https://github.com/lobehub/lobe-chat/issues/9661) ([8624f84](https://github.com/lobehub/lobe-chat/commit/8624f84))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.136.9](https://github.com/lobehub/lobe-chat/compare/v1.136.8...v1.136.9)
+
+<sup>Released on **2025-10-11**</sup>
+
+#### 💄 Styles
+
+- **misc**: Add lab to support disable/enable rich text.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Styles
+
+- **misc**: Add lab to support disable/enable rich text, closes [#9652](https://github.com/lobehub/lobe-chat/issues/9652) ([658c294](https://github.com/lobehub/lobe-chat/commit/658c294))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.136.8](https://github.com/lobehub/lobe-chat/compare/v1.136.7...v1.136.8)
+
+<sup>Released on **2025-10-11**</sup>
+
+#### 🐛 Bug Fixes
+
+- **provider**: Add deepseek-v3.1-terminus to THINKING_MODELS.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **provider**: Add deepseek-v3.1-terminus to THINKING_MODELS, closes [#9653](https://github.com/lobehub/lobe-chat/issues/9653) [#9648](https://github.com/lobehub/lobe-chat/issues/9648) ([e9b5c69](https://github.com/lobehub/lobe-chat/commit/e9b5c69))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.136.7](https://github.com/lobehub/lobe-chat/compare/v1.136.6...v1.136.7)
+
+<sup>Released on **2025-10-11**</sup>
+
+#### 🐛 Bug Fixes
+
+- **misc**: Disable rich text in markdown editor.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **misc**: Disable rich text in markdown editor, closes [#9637](https://github.com/lobehub/lobe-chat/issues/9637) ([9349ce2](https://github.com/lobehub/lobe-chat/commit/9349ce2))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.136.6](https://github.com/lobehub/lobe-chat/compare/v1.136.5...v1.136.6)
+
+<sup>Released on **2025-10-11**</sup>
+
+#### 🐛 Bug Fixes
+
+- **bedrock**: Add parameter conflict handling for Claude 4+ models.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **bedrock**: Add parameter conflict handling for Claude 4+ models, closes [#9627](https://github.com/lobehub/lobe-chat/issues/9627) [#9523](https://github.com/lobehub/lobe-chat/issues/9523) ([54b6217](https://github.com/lobehub/lobe-chat/commit/54b6217))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.136.5](https://github.com/lobehub/lobe-chat/compare/v1.136.4...v1.136.5)
+
+<sup>Released on **2025-10-11**</sup>
+
+#### 🐛 Bug Fixes
+
+- **plugin-store**: Fix search functionality for old plugin store.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **plugin-store**: Fix search functionality for old plugin store, closes [#9651](https://github.com/lobehub/lobe-chat/issues/9651) [#9645](https://github.com/lobehub/lobe-chat/issues/9645) ([522fc09](https://github.com/lobehub/lobe-chat/commit/522fc09))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.136.4](https://github.com/lobehub/lobe-chat/compare/v1.136.3...v1.136.4)
+
+<sup>Released on **2025-10-10**</sup>
+
+#### 🐛 Bug Fixes
+
+- **misc**: Add 'gemini-2.5-flash-image' to disabled models Thinking.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **misc**: Add 'gemini-2.5-flash-image' to disabled models Thinking, closes [#9633](https://github.com/lobehub/lobe-chat/issues/9633) ([771b585](https://github.com/lobehub/lobe-chat/commit/771b585))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.136.3](https://github.com/lobehub/lobe-chat/compare/v1.136.2...v1.136.3)
+
+<sup>Released on **2025-10-10**</sup>
+
+#### 💄 Styles
+
+- **misc**: Add delete & regenerate hotkeys.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Styles
+
+- **misc**: Add delete & regenerate hotkeys, closes [#9538](https://github.com/lobehub/lobe-chat/issues/9538) ([d948580](https://github.com/lobehub/lobe-chat/commit/d948580))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.136.2](https://github.com/lobehub/lobe-chat/compare/v1.136.1...v1.136.2)
+
+<sup>Released on **2025-10-10**</sup>
+
+#### 💄 Styles
+
+- **misc**: Update i18n.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Styles
+
+- **misc**: Update i18n, closes [#9625](https://github.com/lobehub/lobe-chat/issues/9625) ([70d356d](https://github.com/lobehub/lobe-chat/commit/70d356d))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.136.1](https://github.com/lobehub/lobe-chat/compare/v1.136.0...v1.136.1)
+
+<sup>Released on **2025-10-09**</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 1.136.0](https://github.com/lobehub/lobe-chat/compare/v1.135.6...v1.136.0)
+
+<sup>Released on **2025-10-09**</sup>
+
+#### ✨ Features
+
+- **misc**: Add new provider Cerebras.
+
+#### 🐛 Bug Fixes
+
+- **misc**: Fix standalone plugin rerender issue.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's improved
+
+- **misc**: Add new provider Cerebras, closes [#9559](https://github.com/lobehub/lobe-chat/issues/9559) ([9cceaad](https://github.com/lobehub/lobe-chat/commit/9cceaad))
+
+#### What's fixed
+
+- **misc**: Fix standalone plugin rerender issue, closes [#9611](https://github.com/lobehub/lobe-chat/issues/9611) [#9396](https://github.com/lobehub/lobe-chat/issues/9396) ([7ab30fc](https://github.com/lobehub/lobe-chat/commit/7ab30fc))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.135.6](https://github.com/lobehub/lobe-chat/compare/v1.135.5...v1.135.6)
+
+<sup>Released on **2025-10-08**</sup>
+
+#### 🐛 Bug Fixes
+
+- **desktop**: Macos26 small icon.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **desktop**: Macos26 small icon, closes [#9421](https://github.com/lobehub/lobe-chat/issues/9421) ([ca03342](https://github.com/lobehub/lobe-chat/commit/ca03342))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.135.5](https://github.com/lobehub/lobe-chat/compare/v1.135.4...v1.135.5)
+
+<sup>Released on **2025-10-08**</sup>
+
+#### 💄 Styles
+
+- **misc**: Update i18n.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Styles
+
+- **misc**: Update i18n, closes [#9602](https://github.com/lobehub/lobe-chat/issues/9602) ([ed267a4](https://github.com/lobehub/lobe-chat/commit/ed267a4))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.135.4](https://github.com/lobehub/lobe-chat/compare/v1.135.3...v1.135.4)
+
+<sup>Released on **2025-10-07**</sup>
+
+#### ♻ Code Refactoring
+
+- **misc**: Refactor chat item.
+
+#### 💄 Styles
+
+- **misc**: Add GPT-5 pro model.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Code refactoring
+
+- **misc**: Refactor chat item, closes [#9599](https://github.com/lobehub/lobe-chat/issues/9599) ([1f36158](https://github.com/lobehub/lobe-chat/commit/1f36158))
+
+#### Styles
+
+- **misc**: Add GPT-5 pro model, closes [#9594](https://github.com/lobehub/lobe-chat/issues/9594) ([775f30b](https://github.com/lobehub/lobe-chat/commit/775f30b))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.135.3](https://github.com/lobehub/lobe-chat/compare/v1.135.2...v1.135.3)
+
+<sup>Released on **2025-10-07**</sup>
+
+#### 💄 Styles
+
+- **misc**: Improve Korean translate.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Styles
+
+- **misc**: Improve Korean translate, closes [#9597](https://github.com/lobehub/lobe-chat/issues/9597) ([319fbfb](https://github.com/lobehub/lobe-chat/commit/319fbfb))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.135.2](https://github.com/lobehub/lobe-chat/compare/v1.135.1...v1.135.2)
+
+<sup>Released on **2025-10-06**</sup>
+
+#### 💄 Styles
+
+- **image**: Optimize UX and fix fal pricing.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Styles
+
+- **image**: Optimize UX and fix fal pricing, closes [#9592](https://github.com/lobehub/lobe-chat/issues/9592) ([dddbfcd](https://github.com/lobehub/lobe-chat/commit/dddbfcd))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.135.1](https://github.com/lobehub/lobe-chat/compare/v1.135.0...v1.135.1)
+
+<sup>Released on **2025-10-06**</sup>
+
+#### 💄 Styles
+
+- **misc**: Improve styles and fix tools calling condition.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Styles
+
+- **misc**: Improve styles and fix tools calling condition, closes [#9591](https://github.com/lobehub/lobe-chat/issues/9591) ([1695f2f](https://github.com/lobehub/lobe-chat/commit/1695f2f))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+## [Version 1.135.0](https://github.com/lobehub/lobe-chat/compare/v1.134.7...v1.135.0)
+
+<sup>Released on **2025-10-06**</sup>
+
+#### ✨ Features
+
+- **misc**: Huanyuan text-to-image 3.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's improved
+
+- **misc**: Huanyuan text-to-image 3, closes [#9589](https://github.com/lobehub/lobe-chat/issues/9589) ([1dd0e5e](https://github.com/lobehub/lobe-chat/commit/1dd0e5e))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.134.7](https://github.com/lobehub/lobe-chat/compare/v1.134.6...v1.134.7)
+
+<sup>Released on **2025-10-06**</sup>
+
+#### 🐛 Bug Fixes
+
+- **security**: Sanitize Azure provider error responses to prevent API key exposure.
+
+#### 💄 Styles
+
+- **misc**: Update i18n.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **security**: Sanitize Azure provider error responses to prevent API key exposure, closes [#9583](https://github.com/lobehub/lobe-chat/issues/9583) ([af59bfe](https://github.com/lobehub/lobe-chat/commit/af59bfe))
+
+#### Styles
+
+- **misc**: Update i18n, closes [#9580](https://github.com/lobehub/lobe-chat/issues/9580) ([c0974ea](https://github.com/lobehub/lobe-chat/commit/c0974ea))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.134.6](https://github.com/lobehub/lobe-chat/compare/v1.134.5...v1.134.6)
+
+<sup>Released on **2025-10-05**</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 1.134.5](https://github.com/lobehub/lobe-chat/compare/v1.134.4...v1.134.5)
+
+<sup>Released on **2025-10-05**</sup>
+
+#### 🐛 Bug Fixes
+
+- **database**: Prevent empty array insertion in aiModel batch operations.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **database**: Prevent empty array insertion in aiModel batch operations, closes [#9491](https://github.com/lobehub/lobe-chat/issues/9491) [#9429](https://github.com/lobehub/lobe-chat/issues/9429) [#9429](https://github.com/lobehub/lobe-chat/issues/9429) ([eb50c8b](https://github.com/lobehub/lobe-chat/commit/eb50c8b))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.134.4](https://github.com/lobehub/lobe-chat/compare/v1.134.3...v1.134.4)
+
+<sup>Released on **2025-10-05**</sup>
+
+#### 💄 Styles
+
+- **misc**: Add promptfoo to improve prompts quality.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Styles
+
+- **misc**: Add promptfoo to improve prompts quality, closes [#9568](https://github.com/lobehub/lobe-chat/issues/9568) ([33874c2](https://github.com/lobehub/lobe-chat/commit/33874c2))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.134.3](https://github.com/lobehub/lobe-chat/compare/v1.134.2...v1.134.3)
+
+<sup>Released on **2025-10-05**</sup>
+
+#### 🐛 Bug Fixes
+
+- **misc**: Type not preserved when model is sorted.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **misc**: Type not preserved when model is sorted, closes [#9561](https://github.com/lobehub/lobe-chat/issues/9561) ([5fe2518](https://github.com/lobehub/lobe-chat/commit/5fe2518))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.134.2](https://github.com/lobehub/lobe-chat/compare/v1.134.1...v1.134.2)
+
+<sup>Released on **2025-10-05**</sup>
+
+#### 💄 Styles
+
+- **misc**: Allow switching model `type`.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Styles
+
+- **misc**: Allow switching model `type`, closes [#9529](https://github.com/lobehub/lobe-chat/issues/9529) ([9b62685](https://github.com/lobehub/lobe-chat/commit/9b62685))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.134.1](https://github.com/lobehub/lobe-chat/compare/v1.134.0...v1.134.1)
+
+<sup>Released on **2025-10-05**</sup>
+
+#### 💄 Styles
+
+- **misc**: Update i18n.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### Styles
+
+- **misc**: Update i18n, closes [#9546](https://github.com/lobehub/lobe-chat/issues/9546) ([ed8174f](https://github.com/lobehub/lobe-chat/commit/ed8174f))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+## [Version 1.134.0](https://github.com/lobehub/lobe-chat/compare/v1.133.6...v1.134.0)
+
+<sup>Released on **2025-10-04**</sup>
+
+#### ✨ Features
+
+- **misc**: Support double-click to open multi agent window on the desktop.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's improved
+
+- **misc**: Support double-click to open multi agent window on the desktop, closes [#9331](https://github.com/lobehub/lobe-chat/issues/9331) ([a060901](https://github.com/lobehub/lobe-chat/commit/a060901))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.133.6](https://github.com/lobehub/lobe-chat/compare/v1.133.5...v1.133.6)
+
+<sup>Released on **2025-10-04**</sup>
+
+#### 🐛 Bug Fixes
+
+- **misc**: `type` not preserved when model is disabled or sorted.
+
+#### 💄 Styles
+
+- **misc**: Nano banana support `aspect_ratio`.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **misc**: `type` not preserved when model is disabled or sorted, closes [#9530](https://github.com/lobehub/lobe-chat/issues/9530) ([476b897](https://github.com/lobehub/lobe-chat/commit/476b897))
+
+#### Styles
+
+- **misc**: Nano banana support `aspect_ratio`, closes [#9528](https://github.com/lobehub/lobe-chat/issues/9528) ([ae3ed6e](https://github.com/lobehub/lobe-chat/commit/ae3ed6e))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.133.5](https://github.com/lobehub/lobe-chat/compare/v1.133.4...v1.133.5)
+
+<sup>Released on **2025-10-04**</sup>
+
+#### 🐛 Bug Fixes
+
+- **misc**: Custom provider fails when client requests are enabled.
+
+#### 💄 Styles
+
+- **misc**: Optimized `extendParams` UI, update i18n.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **misc**: Custom provider fails when client requests are enabled, closes [#9534](https://github.com/lobehub/lobe-chat/issues/9534) ([8b12fdf](https://github.com/lobehub/lobe-chat/commit/8b12fdf))
+
+#### Styles
+
+- **misc**: Optimized `extendParams` UI, closes [#9457](https://github.com/lobehub/lobe-chat/issues/9457) ([582f6d1](https://github.com/lobehub/lobe-chat/commit/582f6d1))
+- **misc**: Update i18n, closes [#9514](https://github.com/lobehub/lobe-chat/issues/9514) ([6430f57](https://github.com/lobehub/lobe-chat/commit/6430f57))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [Version 1.133.4](https://github.com/lobehub/lobe-chat/compare/v1.133.3...v1.133.4)
+
+<sup>Released on **2025-10-01**</sup>
+
+#### 🐛 Bug Fixes
+
+- **misc**: OllamaCloud error.
+
+#### 💄 Styles
+
+- **misc**: Fix chat minimap overflow.
+
+<br/>
+
+<details>
+<summary><kbd>Improvements and Fixes</kbd></summary>
+
+#### What's fixed
+
+- **misc**: OllamaCloud error, closes [#9481](https://github.com/lobehub/lobe-chat/issues/9481) ([55c45a5](https://github.com/lobehub/lobe-chat/commit/55c45a5))
+
+#### Styles
+
+- **misc**: Fix chat minimap overflow, closes [#9507](https://github.com/lobehub/lobe-chat/issues/9507) ([d835c33](https://github.com/lobehub/lobe-chat/commit/d835c33))
+
+</details>
+
+<div align="right">
+
+[![](https://img.shields.io/badge/-BACK_TO_TOP-151515?style=flat-square)](#readme-top)
+
+</div>
+
+### [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>

CLAUDE.md

@@ -31,28 +31,18 @@ This repository adopts a monorepo structure.
 
 see @.cursor/rules/typescript.mdc
 
-### Modify Code Rules
-
-- **Code Language**:
-  - For files with existing Chinese comments: Continue using Chinese to maintain consistency
-  - For new files or files without Chinese comments: MUST use American English.
-    - eg: new react tsx file and new test file
-- Conservative for existing code, modern approaches for new features
-
 ### Testing
 
-Testing work follows the Rule-Aware Task Execution system above.
-
-- **Required Rule**: `testing-guide/testing-guide.mdc`
+- **Required Rule**: read `@.cursor/rules/testing-guide/testing-guide.mdc` before writing tests
 - **Command**:
   - web: `bunx vitest run --silent='passed-only' '[file-path-pattern]'`
   - packages(eg: database): `cd packages/database && bunx vitest run --silent='passed-only' '[file-path-pattern]'`
 
 **Important**:
 
-- wrapped the file path in single quotes to avoid shell expansion
+- wrap the file path in single quotes to avoid shell expansion
 - Never run `bun run test` etc to run tests, this will run all tests and cost about 10mins
-- If try to fix the same test twice, but still failed, stop and ask for help.
+- If trying to fix the same test twice, but still failed, stop and ask for help.
 
 ### Typecheck
 
@@ -61,40 +51,9 @@ Testing work follows the Rule-Aware Task Execution system above.
 ### i18n
 
 - **Keys**: Add to `src/locales/default/namespace.ts`
-- **Dev**: Translate `locales/zh-CN/namespace.json` locale file only for preview
+- **Dev**: Translate `locales/zh-CN/namespace.json` and `locales/en-US/namespace.json` locales file only for dev preview
 - DON'T run `pnpm i18n`, let CI auto handle it
 
 ## Rules Index
 
-Some useful rules of this project. Read them when needed.
-
-**IMPORTANT**: All rule files referenced in this document are located in the `.cursor/rules/` directory. Throughout this document, rule files are referenced by their filename only for brevity.
-
-### 📋 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

Dockerfile.database

@@ -301,7 +301,9 @@ ENV \
     # BFL
     BFL_API_KEY="" BFL_MODEL_LIST="" \
     # Vercel AI Gateway
-    VERCELAIGATEWAY_API_KEY="" VERCELAIGATEWAY_MODEL_LIST=""
+    VERCELAIGATEWAY_API_KEY="" VERCELAIGATEWAY_MODEL_LIST="" \
+    # Cerebras
+    CEREBRAS_API_KEY="" CEREBRAS_MODEL_LIST=""
 
 USER nextjs
 

README.md

@@ -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 -->
 

README.zh-CN.md

@@ -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 -->
 

apps/desktop/electron-builder.js

@@ -1,5 +1,7 @@
 const dotenv = require('dotenv');
+const fs = require('node:fs/promises');
 const os = require('node:os');
+const path = require('node:path');
 
 dotenv.config();
 
@@ -32,11 +34,50 @@ const getProtocolScheme = () => {
 
 const protocolScheme = getProtocolScheme();
 
+// Determine icon file based on version type
+const getIconFileName = () => {
+  if (isNightly) return 'Icon-nightly';
+  if (isBeta) return 'Icon-beta';
+  return 'Icon';
+};
+
 /**
  * @type {import('electron-builder').Configuration}
  * @see https://www.electron.build/configuration
  */
 const config = {
+  /**
+   * AfterPack hook to copy pre-generated Liquid Glass Assets.car for macOS 26+
+   * @see https://github.com/electron-userland/electron-builder/issues/9254
+   * @see https://github.com/MultiboxLabs/flow-browser/pull/159
+   * @see https://github.com/electron/packager/pull/1806
+   */
+  afterPack: async (context) => {
+    // Only process macOS builds
+    if (context.electronPlatformName !== 'darwin') {
+      return;
+    }
+
+    const iconFileName = getIconFileName();
+    const assetsCarSource = path.join(__dirname, 'build', `${iconFileName}.Assets.car`);
+    const resourcesPath = path.join(
+      context.appOutDir,
+      `${context.packager.appInfo.productFilename}.app`,
+      'Contents',
+      'Resources',
+    );
+    const assetsCarDest = path.join(resourcesPath, 'Assets.car');
+
+    try {
+      await fs.access(assetsCarSource);
+      await fs.copyFile(assetsCarSource, assetsCarDest);
+      console.log(`✅ Copied Liquid Glass icon: ${iconFileName}.Assets.car`);
+    } catch {
+      // Non-critical: Assets.car not found or copy failed
+      // App will use fallback .icns icon on all macOS versions
+      console.log(`⏭️  Skipping Assets.car (not found or copy failed)`);
+    }
+  },
   appId: isNightly
     ? 'com.lobehub.lobehub-desktop-nightly'
     : isBeta
@@ -81,6 +122,7 @@ const config = {
     compression: 'maximum',
     entitlementsInherit: 'build/entitlements.mac.plist',
     extendInfo: {
+      CFBundleIconName: 'AppIcon',
       CFBundleURLTypes: [
         {
           CFBundleURLName: 'LobeHub Protocol',

apps/desktop/src/main/appBrowsers.ts

@@ -46,4 +46,55 @@ export const appBrowsers = {
   },
 } satisfies Record<string, BrowserWindowOpts>;
 
+// Window templates for multi-instance windows
+export interface WindowTemplate {
+  allowMultipleInstances: boolean;
+  // Include common BrowserWindow options
+  autoHideMenuBar?: boolean;
+  baseIdentifier: string;
+  basePath: string;
+  devTools?: boolean;
+  height?: number;
+  keepAlive?: boolean;
+  minWidth?: number;
+  parentIdentifier?: string;
+  showOnInit?: boolean;
+  title?: string;
+  titleBarStyle?: 'hidden' | 'default' | 'hiddenInset' | 'customButtonsOnHover';
+  vibrancy?:
+    | 'appearance-based'
+    | 'content'
+    | 'fullscreen-ui'
+    | 'header'
+    | 'hud'
+    | 'menu'
+    | 'popover'
+    | 'selection'
+    | 'sheet'
+    | 'sidebar'
+    | 'titlebar'
+    | 'tooltip'
+    | 'under-page'
+    | 'under-window'
+    | 'window';
+  width?: number;
+}
+
+export const windowTemplates = {
+  chatSingle: {
+    allowMultipleInstances: true,
+    autoHideMenuBar: true,
+    baseIdentifier: 'chatSingle',
+    basePath: '/chat',
+    height: 600,
+    keepAlive: false, // Multi-instance windows don't need to stay alive
+    minWidth: 400,
+    parentIdentifier: 'chat',
+    titleBarStyle: 'hidden',
+    vibrancy: 'under-window',
+    width: 900,
+  },
+} satisfies Record<string, WindowTemplate>;
+
 export type AppBrowsersIdentifiers = keyof typeof appBrowsers;
+export type WindowTemplateIdentifiers = keyof typeof windowTemplates;

apps/desktop/src/main/controllers/BrowserWindowsCtr.ts

@@ -1,7 +1,7 @@
 import { InterceptRouteParams } from '@lobechat/electron-client-ipc';
 import { extractSubPath, findMatchingRoute } from '~common/routes';
 
-import { AppBrowsersIdentifiers, BrowsersIdentifiers } from '@/appBrowsers';
+import { AppBrowsersIdentifiers, BrowsersIdentifiers, WindowTemplateIdentifiers } from '@/appBrowsers';
 import { IpcClientEventSender } from '@/types/ipcClientEvent';
 
 import { ControllerModule, ipcClientEvent, shortcut } from './index';
@@ -100,6 +100,77 @@ export default class BrowserWindowsCtr extends ControllerModule {
     }
   }
 
+  /**
+   * Create a new multi-instance window
+   */
+  @ipcClientEvent('createMultiInstanceWindow')
+  async createMultiInstanceWindow(params: {
+    templateId: WindowTemplateIdentifiers;
+    path: string;
+    uniqueId?: string;
+  }) {
+    try {
+      console.log('[BrowserWindowsCtr] Creating multi-instance window:', params);
+
+      const result = this.app.browserManager.createMultiInstanceWindow(
+        params.templateId,
+        params.path,
+        params.uniqueId,
+      );
+
+      // Show the window
+      result.browser.show();
+
+      return {
+        success: true,
+        windowId: result.identifier,
+      };
+    } catch (error) {
+      console.error('[BrowserWindowsCtr] Failed to create multi-instance window:', error);
+      return {
+        error: error.message,
+        success: false,
+      };
+    }
+  }
+
+  /**
+   * Get all windows by template
+   */
+  @ipcClientEvent('getWindowsByTemplate')
+  async getWindowsByTemplate(templateId: string) {
+    try {
+      const windowIds = this.app.browserManager.getWindowsByTemplate(templateId);
+      return {
+        success: true,
+        windowIds,
+      };
+    } catch (error) {
+      console.error('[BrowserWindowsCtr] Failed to get windows by template:', error);
+      return {
+        error: error.message,
+        success: false,
+      };
+    }
+  }
+
+  /**
+   * Close all windows by template
+   */
+  @ipcClientEvent('closeWindowsByTemplate')
+  async closeWindowsByTemplate(templateId: string) {
+    try {
+      this.app.browserManager.closeWindowsByTemplate(templateId);
+      return { success: true };
+    } catch (error) {
+      console.error('[BrowserWindowsCtr] Failed to close windows by template:', error);
+      return {
+        error: error.message,
+        success: false,
+      };
+    }
+  }
+
   /**
    * Open target window and navigate to specified sub-path
    */

apps/desktop/src/main/core/browser/Browser.ts

@@ -336,7 +336,6 @@ export default class Browser {
       vibrancy: 'sidebar',
       visualEffectState: 'active',
       webPreferences: {
-        backgroundThrottling: false,
         contextIsolation: true,
         preload: join(preloadDir, 'index.js'),
       },

apps/desktop/src/main/core/browser/BrowserManager.ts

@@ -3,7 +3,7 @@ import { WebContents } from 'electron';
 
 import { createLogger } from '@/utils/logger';
 
-import { AppBrowsersIdentifiers, appBrowsers } from '../../appBrowsers';
+import { AppBrowsersIdentifiers, appBrowsers, WindowTemplate, WindowTemplateIdentifiers, windowTemplates } from '../../appBrowsers';
 import type { App } from '../App';
 import type { BrowserWindowOpts } from './Browser';
 import Browser from './Browser';
@@ -14,9 +14,9 @@ const logger = createLogger('core:BrowserManager');
 export class BrowserManager {
   app: App;
 
-  browsers: Map<AppBrowsersIdentifiers, Browser> = new Map();
+  browsers: Map<string, Browser> = new Map();
 
-  private webContentsMap = new Map<WebContents, AppBrowsersIdentifiers>();
+  private webContentsMap = new Map<WebContents, string>();
 
   constructor(app: App) {
     logger.debug('Initializing BrowserManager');
@@ -51,12 +51,12 @@ export class BrowserManager {
   };
 
   broadcastToWindow = <T extends MainBroadcastEventKey>(
-    identifier: AppBrowsersIdentifiers,
+    identifier: string,
     event: T,
     data: MainBroadcastParams<T>,
   ) => {
     logger.debug(`Broadcasting event ${event} to window: ${identifier}`);
-    this.browsers.get(identifier).broadcast(event, data);
+    this.browsers.get(identifier)?.broadcast(event, data);
   };
 
   /**
@@ -87,13 +87,21 @@ export class BrowserManager {
    * @param identifier Window identifier
    * @param subPath Sub-path, such as 'agent', 'about', etc.
    */
-  async redirectToPage(identifier: AppBrowsersIdentifiers, subPath?: string) {
+  async redirectToPage(identifier: string, subPath?: string) {
     try {
       // Ensure window is retrieved or created
       const browser = this.retrieveByIdentifier(identifier);
       browser.hide();
 
-      const baseRoute = appBrowsers[identifier].path;
+      // Handle both static and dynamic windows
+      let baseRoute: string;
+      if (identifier in appBrowsers) {
+        baseRoute = appBrowsers[identifier as AppBrowsersIdentifiers].path;
+      } else {
+        // For dynamic windows, extract base route from the browser options
+        const browserOptions = browser.options;
+        baseRoute = browserOptions.path;
+      }
 
       // Build complete URL path
       const fullPath = subPath ? `${baseRoute}/${subPath}` : baseRoute;
@@ -114,13 +122,75 @@ export class BrowserManager {
   /**
    * get Browser by identifier
    */
-  retrieveByIdentifier(identifier: AppBrowsersIdentifiers) {
+  retrieveByIdentifier(identifier: string) {
     const browser = this.browsers.get(identifier);
 
     if (browser) return browser;
 
-    logger.debug(`Browser ${identifier} not found, initializing new instance`);
-    return this.retrieveOrInitialize(appBrowsers[identifier]);
+    // Check if it's a static browser
+    if (identifier in appBrowsers) {
+      logger.debug(`Browser ${identifier} not found, initializing new instance`);
+      return this.retrieveOrInitialize(appBrowsers[identifier as AppBrowsersIdentifiers]);
+    }
+
+    throw new Error(`Browser ${identifier} not found and is not a static browser`);
+  }
+
+  /**
+   * Create a multi-instance window from template
+   * @param templateId Template identifier
+   * @param path Full path with query parameters
+   * @param uniqueId Optional unique identifier, will be generated if not provided
+   * @returns The window identifier and Browser instance
+   */
+  createMultiInstanceWindow(templateId: WindowTemplateIdentifiers, path: string, uniqueId?: string) {
+    const template = windowTemplates[templateId];
+    if (!template) {
+      throw new Error(`Window template ${templateId} not found`);
+    }
+
+    // Generate unique identifier
+    const windowId = uniqueId || `${template.baseIdentifier}_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`;
+
+    // Create browser options from template
+    const browserOpts: BrowserWindowOpts = {
+      ...template,
+      identifier: windowId,
+      path: path,
+    };
+
+    logger.debug(`Creating multi-instance window: ${windowId} with path: ${path}`);
+
+    const browser = this.retrieveOrInitialize(browserOpts);
+
+    return {
+      identifier: windowId,
+      browser: browser,
+    };
+  }
+
+  /**
+   * Get all windows based on template
+   * @param templateId Template identifier
+   * @returns Array of window identifiers matching the template
+   */
+  getWindowsByTemplate(templateId: string): string[] {
+    const prefix = `${templateId}_`;
+    return Array.from(this.browsers.keys()).filter(id => id.startsWith(prefix));
+  }
+
+  /**
+   * Close all windows based on template
+   * @param templateId Template identifier
+   */
+  closeWindowsByTemplate(templateId: string): void {
+    const windowIds = this.getWindowsByTemplate(templateId);
+    windowIds.forEach(id => {
+      const browser = this.browsers.get(id);
+      if (browser) {
+        browser.close();
+      }
+    });
   }
 
   /**
@@ -144,7 +214,7 @@ export class BrowserManager {
    * @param options Browser window options
    */
   private retrieveOrInitialize(options: BrowserWindowOpts) {
-    let browser = this.browsers.get(options.identifier as AppBrowsersIdentifiers);
+    let browser = this.browsers.get(options.identifier);
     if (browser) {
       logger.debug(`Retrieved existing browser: ${options.identifier}`);
       return browser;
@@ -153,7 +223,7 @@ export class BrowserManager {
     logger.debug(`Creating new browser: ${options.identifier}`);
     browser = new Browser(options, this.app);
 
-    const identifier = options.identifier as AppBrowsersIdentifiers;
+    const identifier = options.identifier;
     this.browsers.set(identifier, browser);
 
     // 记录 WebContents 和 identifier 的映射
@@ -166,32 +236,32 @@ export class BrowserManager {
 
     browser.browserWindow.on('show', () => {
       if (browser.webContents)
-        this.webContentsMap.set(browser.webContents, browser.identifier as AppBrowsersIdentifiers);
+        this.webContentsMap.set(browser.webContents, browser.identifier);
     });
 
     return browser;
   }
 
   closeWindow(identifier: string) {
-    const browser = this.browsers.get(identifier as AppBrowsersIdentifiers);
+    const browser = this.browsers.get(identifier);
     browser?.close();
   }
 
   minimizeWindow(identifier: string) {
-    const browser = this.browsers.get(identifier as AppBrowsersIdentifiers);
+    const browser = this.browsers.get(identifier);
     browser?.browserWindow.minimize();
   }
 
   maximizeWindow(identifier: string) {
-    const browser = this.browsers.get(identifier as AppBrowsersIdentifiers);
-    if (browser.browserWindow.isMaximized()) {
+    const browser = this.browsers.get(identifier);
+    if (browser?.browserWindow.isMaximized()) {
       browser?.browserWindow.unmaximize();
     } else {
       browser?.browserWindow.maximize();
     }
   }
 
-  getIdentifierByWebContents(webContents: WebContents): AppBrowsersIdentifiers | null {
+  getIdentifierByWebContents(webContents: WebContents): string | null {
     return this.webContentsMap.get(webContents) || null;
   }
 

changelog/v1.json

@@ -1,4 +1,244 @@
 [
+  {
+    "children": {
+      "improvements": ["Add lab to support disable/enable rich text."]
+    },
+    "date": "2025-10-11",
+    "version": "1.136.9"
+  },
+  {
+    "children": {},
+    "date": "2025-10-11",
+    "version": "1.136.8"
+  },
+  {
+    "children": {
+      "fixes": ["Disable rich text in markdown editor."]
+    },
+    "date": "2025-10-11",
+    "version": "1.136.7"
+  },
+  {
+    "children": {},
+    "date": "2025-10-11",
+    "version": "1.136.6"
+  },
+  {
+    "children": {},
+    "date": "2025-10-11",
+    "version": "1.136.5"
+  },
+  {
+    "children": {
+      "fixes": ["Add 'gemini-2.5-flash-image' to disabled models Thinking."]
+    },
+    "date": "2025-10-10",
+    "version": "1.136.4"
+  },
+  {
+    "children": {
+      "improvements": ["Add delete & regenerate hotkeys."]
+    },
+    "date": "2025-10-10",
+    "version": "1.136.3"
+  },
+  {
+    "children": {
+      "improvements": ["Update i18n."]
+    },
+    "date": "2025-10-10",
+    "version": "1.136.2"
+  },
+  {
+    "children": {},
+    "date": "2025-10-09",
+    "version": "1.136.1"
+  },
+  {
+    "children": {
+      "features": ["Add new provider Cerebras."],
+      "fixes": ["Fix standalone plugin rerender issue."]
+    },
+    "date": "2025-10-09",
+    "version": "1.136.0"
+  },
+  {
+    "children": {},
+    "date": "2025-10-08",
+    "version": "1.135.6"
+  },
+  {
+    "children": {
+      "improvements": ["Update i18n."]
+    },
+    "date": "2025-10-08",
+    "version": "1.135.5"
+  },
+  {
+    "children": {
+      "improvements": ["Add GPT-5 pro model."]
+    },
+    "date": "2025-10-07",
+    "version": "1.135.4"
+  },
+  {
+    "children": {
+      "improvements": ["Improve Korean translate."]
+    },
+    "date": "2025-10-07",
+    "version": "1.135.3"
+  },
+  {
+    "children": {},
+    "date": "2025-10-06",
+    "version": "1.135.2"
+  },
+  {
+    "children": {
+      "improvements": ["Improve styles and fix tools calling condition."]
+    },
+    "date": "2025-10-06",
+    "version": "1.135.1"
+  },
+  {
+    "children": {
+      "features": ["Huanyuan text-to-image 3."]
+    },
+    "date": "2025-10-06",
+    "version": "1.135.0"
+  },
+  {
+    "children": {
+      "improvements": ["Update i18n."]
+    },
+    "date": "2025-10-06",
+    "version": "1.134.7"
+  },
+  {
+    "children": {},
+    "date": "2025-10-05",
+    "version": "1.134.6"
+  },
+  {
+    "children": {},
+    "date": "2025-10-05",
+    "version": "1.134.5"
+  },
+  {
+    "children": {
+      "improvements": ["Add promptfoo to improve prompts quality."]
+    },
+    "date": "2025-10-05",
+    "version": "1.134.4"
+  },
+  {
+    "children": {
+      "fixes": ["Type not preserved when model is sorted."]
+    },
+    "date": "2025-10-05",
+    "version": "1.134.3"
+  },
+  {
+    "children": {
+      "improvements": ["Allow switching model type."]
+    },
+    "date": "2025-10-05",
+    "version": "1.134.2"
+  },
+  {
+    "children": {
+      "improvements": ["Update i18n."]
+    },
+    "date": "2025-10-05",
+    "version": "1.134.1"
+  },
+  {
+    "children": {
+      "features": ["Support double-click to open multi agent window on the desktop."]
+    },
+    "date": "2025-10-04",
+    "version": "1.134.0"
+  },
+  {
+    "children": {
+      "fixes": ["type not preserved when model is disabled or sorted."],
+      "improvements": ["Nano banana support aspect_ratio."]
+    },
+    "date": "2025-10-04",
+    "version": "1.133.6"
+  },
+  {
+    "children": {
+      "fixes": ["Custom provider fails when client requests are enabled."],
+      "improvements": ["Optimized extendParams UI, update i18n."]
+    },
+    "date": "2025-10-04",
+    "version": "1.133.5"
+  },
+  {
+    "children": {
+      "fixes": ["OllamaCloud error."],
+      "improvements": ["Fix chat minimap overflow."]
+    },
+    "date": "2025-10-01",
+    "version": "1.133.4"
+  },
+  {
+    "children": {
+      "improvements": ["Refactor a ssrf-safe-fetch module."],
+      "fixes": ["Fix frontend random API key config not work."]
+    },
+    "date": "2025-10-01",
+    "version": "1.133.3"
+  },
+  {
+    "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."]

docs/development/basic/feature-development-frontend.mdx

@@ -5,7 +5,9 @@ LobeChat is built on the Next.js framework and uses TypeScript as the primary de
 1. Routing: Define routes (`src/app`).
 2. Data Structure: Define data structures (`src/types`).
 3. Business Logic Implementation: Zustand store (`src/store`).
-4. Page Display: Write static components/pages (`src/app/<new-page>/features/<new-feature>.tsx`).
+4. Page Display: Write static components/pages. Create features in:
+   - `src/features/<feature-name>/` for **shared global features** (used across multiple pages)
+   - `src/app/<new-page>/features/<feature-name>/` for **page-specific features** (only used in this page)
 5. Function Binding: Bind the store with page triggers (`const [state, function] = useNewStore(s => [s.state, s.function])`).
 
 Taking the "Chat Messages" feature as an example, here are the brief steps to implement this feature:
@@ -60,7 +62,8 @@ export const useChatStore = create<ChatState>((set) => ({
 In `src/app/<new-page>/features/<new-feature>.tsx`, we need to create a new page or component to display "Chat Messages". In this file, we can use the Zustand Store created earlier and Ant Design components to build the UI:
 
 ```jsx
-// src/features/chat/index.tsx
+// src/app/chat/features/ChatPage/index.tsx
+// Note: Use src/app/<page>/features/ for page-specific components
 import { List, Typography } from 'antd';
 import { useChatStore } from 'src/store/chatStore';
 
@@ -82,6 +85,12 @@ const ChatPage = () => {
 export default ChatPage;
 ```
 
+> **Note on Feature Organization**: LobeChat uses two patterns for organizing features:
+> - **Global features** (`src/features/`): Shared components like `ChatInput`, `Conversation` used across the app
+> - **Page-specific features** (`src/app/<page>/features/`): Components used only within a specific page route
+>
+> Choose based on reusability. If unsure, start with page-specific and refactor to global if needed elsewhere.
+
 ## 5. Function Binding
 
 In a page or component, we need to bind the Zustand Store's state and methods to the UI. In the example above, we have already bound the `messages` state to the `dataSource` property of the list. Now, we also need a method to add new messages. We can define this method in the Zustand Store and then use it in the page or component:

docs/development/basic/feature-development-frontend.zh-CN.mdx

@@ -5,7 +5,9 @@ LobeChat 基于 Next.js 框架构建，使用 TypeScript 作为主要开发语
 1. 路由：定义路由 (`src/app`)
 2. 数据结构： 定义数据结构 ( `src/types` )
 3. 业务功能实现： zustand store (`src/store`)
-4. 页面展示：书写静态组件 / 页面 (`src/app/<new-page>/features/<new-feature>.tsx`)
+4. 页面展示：书写静态组件 / 页面。根据以下方式创建功能组件：
+   - `src/features/<feature-name>/` 用于 **全局共享功能**（跨多个页面使用）
+   - `src/app/<new-page>/features/<feature-name>/` 用于 **页面专属功能**（仅在当前页面使用）
 5. 功能绑定：绑定 store 与页面的触发 (`const  [state,function]= useNewStore(s=>[s.state,s.function])`)
 
 我们以 "会话消息" 功能为例，以下是实现这个功能的简要步骤：
@@ -42,7 +44,7 @@ export type ChatMessage = {
 
 ```ts
 // src/store/chatStore.ts
-import create from 'zustand';
+import { create } from 'zustand';
 
 type ChatState = {
   messages: ChatMessage[];
@@ -60,7 +62,8 @@ export const useChatStore = create<ChatState>((set) => ({
 在 `src/app/<new-page>/features/<new-feature>.tsx` 中，我们需要创建一个新的页面或组件来显示 "会话消息"。在这个文件中，我们可以使用上面创建的 Zustand Store，以及 Ant Design 的组件来构建 UI：
 
 ```jsx
-// src/features/chat/index.tsx
+// src/app/chat/features/ChatPage/index.tsx
+// 注意：使用 src/app/<page>/features/ 放置页面专属组件
 import { List, Typography } from 'antd';
 import { useChatStore } from 'src/store/chatStore';
 
@@ -82,6 +85,12 @@ const ChatPage = () => {
 export default ChatPage;
 ```
 
+> **关于功能组件组织方式的说明**：LobeChat 使用两种模式来组织功能组件：
+> - **全局功能**（`src/features/`）：跨应用共享的组件，如 `ChatInput`、`Conversation` 等
+> - **页面专属功能**（`src/app/<page>/features/`）：仅在特定页面路由中使用的组件
+>
+> 根据可复用性选择合适的方式。如果不确定，可以先放在页面专属位置，需要时再重构为全局共享。
+
 ## 5. 功能绑定
 
 在页面或组件中，我们需要将 Zustand Store 的状态和方法绑定到 UI 上。在上面的示例中，我们已经将 `messages` 状态绑定到了列表的 `dataSource` 属性上。现在，我们还需要一个方法来添加新的消息。我们可以在 Zustand Store 中定义这个方法，然后在页面或组件中使用它：

docs/development/basic/folder-structure.mdx

@@ -4,37 +4,88 @@ The directory structure of LobeChat is as follows:
 
 ```bash
 src
-├── app        # Main logic and state management related code for the application
+├── app        # Next.js App Router implementation with route groups and API routes
 ├── components # Reusable UI components
 ├── config     # Application configuration files, including client-side and server-side environment variables
-├── const      # Used to define constants, such as action types, route names, etc.
 ├── features   # Function modules related to business functions, such as agent settings, plugin development pop-ups, etc.
 ├── hooks      # Custom utility hooks reused throughout the application
 ├── layout     # Application layout components, such as navigation bars, sidebars, etc.
+├── libs       # Third-party integrations (analytics, OIDC, etc.)
 ├── locales    # Internationalization language files
+├── server     # Server-side modules and services
 ├── services   # Encapsulated backend service interfaces, such as HTTP requests
 ├── store      # Zustand store for state management
+├── styles     # Global styles and CSS-in-JS configurations
 ├── types      # TypeScript type definition files
 └── utils      # Common utility functions
 ```
 
 ## app
 
-In the `app` folder, we organize each route page according to the app router's [Route Groups](https://nextjs.org/docs/app/building-your-application/routing/route-groups) to separately handle the implementation of desktop and mobile code. Taking the file structure of the `welcome` page as an example:
+The `app` directory follows Next.js 13+ App Router conventions with a sophisticated architecture using [Route Groups](https://nextjs.org/docs/app/building-your-application/routing/route-groups) to organize backend services, platform variants, and application routes:
 
 ```bash
-welcome
-├── (desktop)               # Desktop implementation
-│   ├── features            # Desktop-specific features
-│   ├── index.tsx           # Main entry file for desktop
-│   └── layout.desktop.tsx  # Desktop layout component
-├── (mobile)                # Mobile implementation
-│   ├── features            # Mobile-specific features
-│   ├── index.tsx           # Main entry file for mobile
-│   └── layout.mobile.tsx   # Mobile layout component
-├── features                # This folder contains features code shared by both desktop and mobile, such as the Banner component
-│   └── Banner
-└── page.tsx                # This is the main entry file for the page, used to load desktop or mobile code based on the device type
+app
+├── (backend)/                    # Backend API routes and services
+│   ├── api/                      # REST API endpoints
+│   │   ├── auth/                 # Authentication routes
+│   │   └── webhooks/             # Webhook handlers
+│   ├── middleware/               # Request middleware
+│   ├── oidc/                     # OpenID Connect routes
+│   ├── trpc/                     # tRPC API endpoints
+│   │   ├── async/                # Async tRPC routes
+│   │   ├── desktop/              # Desktop-specific tRPC routes
+│   │   ├── edge/                 # Edge runtime tRPC routes
+│   │   ├── lambda/               # Lambda tRPC routes
+│   │   └── tools/                # Tools tRPC routes
+│   └── webapi/                   # Web API endpoints
+│       ├── chat/                 # Chat-related APIs
+│       ├── models/               # Model management APIs
+│       ├── tts/                  # Text-to-speech APIs
+│       └── ...
+├── [variants]/                   # Platform and device variants
+│   ├── (auth)/                   # Authentication pages
+│   │   ├── login/
+│   │   ├── signup/
+│   │   └── next-auth/
+│   ├── (main)/                   # Main application routes
+│   │   ├── (mobile)/             # Mobile-specific routes
+│   │   │   └── me/               # Mobile profile pages
+│   │   ├── _layout/              # Layout components
+│   │   ├── chat/                 # Chat interface
+│   │   ├── discover/             # Discovery pages
+│   │   ├── files/                # File management
+│   │   ├── image/                # Image generation
+│   │   ├── profile/              # User profile
+│   │   ├── repos/                # Repository management
+│   │   └── settings/             # Application settings
+│   └── @modal/                   # Parallel modal routes
+│       ├── (.)changelog/
+│       └── _layout/
+├── desktop/                      # Desktop-specific routes
+│   └── devtools/
+├── manifest.ts                   # PWA manifest
+├── robots.tsx                    # Robots.txt generation
+├── sitemap.tsx                   # Sitemap generation
+└── sw.ts                         # Service worker
 ```
 
-In this way, we can clearly distinguish and manage desktop and mobile code, while also easily reusing code required on both devices, thereby improving development efficiency and maintaining code cleanliness and maintainability.
+### Architecture Explanation
+
+**Route Groups:**
+- `(backend)` - Contains all server-side API routes, middleware, and backend services
+- `[variants]` - Dynamic route group handling different platform variants and main application pages
+- `@modal` - Parallel routes for modal dialogs using Next.js parallel routing
+
+**Platform Organization:**
+- The architecture supports multiple platforms (web, desktop, mobile) through route organization
+- Desktop-specific routes are in the `desktop/` directory
+- Mobile-specific routes are organized under `(main)/(mobile)/`
+- Shared layouts and components are in `_layout/` directories
+
+**API Architecture:**
+- REST APIs in `(backend)/api/` and `(backend)/webapi/`
+- tRPC endpoints organized by runtime environment (edge, lambda, async, desktop)
+- Authentication and OIDC handling in dedicated route groups
+
+This architecture provides clear separation of concerns while maintaining flexibility for different deployment targets and runtime environments.

docs/development/basic/folder-structure.zh-CN.mdx

@@ -4,37 +4,88 @@ LobeChat 的文件夹目录架构如下：
 
 ```bash
 src
-├── app        # 应用主要逻辑和状态管理相关的代码
+├── app        # Next.js App Router 实现，包含路由组和 API 路由
 ├── components # 可复用的 UI 组件
 ├── config     # 应用的配置文件，包含客户端环境变量与服务端环境变量
-├── const      # 用于定义常量，如 action 类型、路由名等
 ├── features   # 与业务功能相关的功能模块，如 Agent 设置、插件开发弹窗等
 ├── hooks      # 全应用复用自定义的工具 Hooks
 ├── layout     # 应用的布局组件，如导航栏、侧边栏等
+├── libs       # 第三方集成（分析、OIDC 等）
 ├── locales    # 国际化的语言文件
+├── server     # 服务端模块和服务
 ├── services   # 封装的后端服务接口，如 HTTP 请求
 ├── store      # 用于状态管理的 zustand store
+├── styles     # 全局样式和 CSS-in-JS 配置
 ├── types      # TypeScript 的类型定义文件
 └── utils      # 通用的工具函数
 ```
 
 ## app
 
-在 `app` 文件夹中，我们将每个路由页面按照 app router 的 [Route Groups](https://nextjs.org/docs/app/building-your-application/routing/route-groups) 进行组织，以此来分别处理桌面端和移动端的代码实现。以 `welcome` 页面的文件结构为例：
+`app` 目录遵循 Next.js 13+ App Router 约定，采用复杂的架构，使用 [路由组](https://nextjs.org/docs/app/building-your-application/routing/route-groups) 来组织后端服务、平台变体和应用路由：
 
 ```bash
-welcome
-├── (desktop)               # 桌面端实现
-│   ├── features            # 桌面端特有的功能
-│   ├── index.tsx           # 桌面端的主入口文件
-│   └── layout.desktop.tsx  # 桌面端的布局组件
-├── (mobile)                # 移动端实现
-│   ├── features            # 移动端特有的功能
-│   ├── index.tsx           # 移动端的主入口文件
-│   └── layout.mobile.tsx   # 移动端的布局组件
-├── features                # 此文件夹包含双端共享的特性代码，如 Banner 组件
-│   └── Banner
-└── page.tsx                # 此为页面的主入口文件，用于根据设备类型选择加载桌面端或移动端的代码
+app
+├── (backend)/                    # 后端 API 路由和服务
+│   ├── api/                      # REST API 端点
+│   │   ├── auth/                 # 身份验证路由
+│   │   └── webhooks/             # Webhook 处理器
+│   ├── middleware/               # 请求中间件
+│   ├── oidc/                     # OpenID Connect 路由
+│   ├── trpc/                     # tRPC API 端点
+│   │   ├── async/                # 异步 tRPC 路由
+│   │   ├── desktop/              # 桌面端专用 tRPC 路由
+│   │   ├── edge/                 # Edge 运行时 tRPC 路由
+│   │   ├── lambda/               # Lambda tRPC 路由
+│   │   └── tools/                # 工具 tRPC 路由
+│   └── webapi/                   # Web API 端点
+│       ├── chat/                 # 聊天相关 API
+│       ├── models/               # 模型管理 API
+│       ├── tts/                  # 文本转语音 API
+│       └── ...
+├── [variants]/                   # 平台和设备变体
+│   ├── (auth)/                   # 身份验证页面
+│   │   ├── login/
+│   │   ├── signup/
+│   │   └── next-auth/
+│   ├── (main)/                   # 主应用路由
+│   │   ├── (mobile)/             # 移动端专用路由
+│   │   │   └── me/               # 移动端个人资料页面
+│   │   ├── _layout/              # 布局组件
+│   │   ├── chat/                 # 聊天界面
+│   │   ├── discover/             # 发现页面
+│   │   ├── files/                # 文件管理
+│   │   ├── image/                # 图像生成
+│   │   ├── profile/              # 用户资料
+│   │   ├── repos/                # 仓库管理
+│   │   └── settings/             # 应用设置
+│   └── @modal/                   # 并行模态框路由
+│       ├── (.)changelog/
+│       └── _layout/
+├── desktop/                      # 桌面端专用路由
+│   └── devtools/
+├── manifest.ts                   # PWA 清单
+├── robots.tsx                    # Robots.txt 生成
+├── sitemap.tsx                   # 站点地图生成
+└── sw.ts                         # Service Worker
 ```
 
-通过这种方式，我们可以清晰地区分和管理桌面端和移动端的代码，同时也能方便地复用在两种设备上都需要的代码，从而提高开发效率并保持代码的整洁和可维护性。
+### 架构说明
+
+**路由组：**
+- `(backend)` - 包含所有服务端 API 路由、中间件和后端服务
+- `[variants]` - 处理不同平台变体和主应用页面的动态路由组
+- `@modal` - 使用 Next.js 并行路由的模态框对话框并行路由
+
+**平台组织：**
+- 架构通过路由组织支持多个平台（Web、桌面端、移动端）
+- 桌面端专用路由位于 `desktop/` 目录中
+- 移动端专用路由组织在 `(main)/(mobile)/` 下
+- 共享布局和组件位于 `_layout/` 目录中
+
+**API 架构：**
+- `(backend)/api/` 和 `(backend)/webapi/` 中的 REST API
+- 按运行时环境组织的 tRPC 端点（edge、lambda、async、desktop）
+- 专用路由组中的身份验证和 OIDC 处理
+
+这种架构在保持不同部署目标和运行时环境灵活性的同时，提供了清晰的关注点分离。

docs/development/database-schema.dbml

@@ -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()`]
@@ -317,6 +318,24 @@ table message_chunks {
   }
 }
 
+table message_groups {
+  id varchar(255) [pk, not null]
+  topic_id text
+  user_id text [not null]
+  parent_group_id varchar(255)
+  parent_message_id text
+  title varchar(255)
+  description text
+  client_id varchar(255)
+  accessed_at "timestamp with time zone" [not null, default: `now()`]
+  created_at "timestamp with time zone" [not null, default: `now()`]
+  updated_at "timestamp with time zone" [not null, default: `now()`]
+
+  indexes {
+    (client_id, user_id) [name: 'message_groups_client_id_user_id_unique', unique]
+  }
+}
+
 table message_plugins {
   id text [pk, not null]
   tool_call_id text
@@ -410,6 +429,7 @@ table messages {
   agent_id text
   group_id text
   target_id text
+  message_group_id varchar(255)
   accessed_at "timestamp with time zone" [not null, default: `now()`]
   created_at "timestamp with time zone" [not null, default: `now()`]
   updated_at "timestamp with time zone" [not null, default: `now()`]
@@ -945,6 +965,127 @@ table users {
   updated_at "timestamp with time zone" [not null, default: `now()`]
 }
 
+table user_memories {
+  id varchar(255) [pk, not null]
+  user_id text
+  memory_category varchar(255)
+  memory_layer varchar(255)
+  memory_type varchar(255)
+  title varchar(255)
+  summary text
+  summary_vector_1024 vector(1024)
+  details text
+  details_vector_1024 vector(1024)
+  status varchar(255)
+  accessed_count bigint [default: 0]
+  last_accessed_at "timestamp with time zone" [not null]
+  accessed_at "timestamp with time zone" [not null, default: `now()`]
+  created_at "timestamp with time zone" [not null, default: `now()`]
+  updated_at "timestamp with time zone" [not null, default: `now()`]
+
+  indexes {
+    summary_vector_1024 [name: 'user_memories_summary_vector_1024_index']
+    details_vector_1024 [name: 'user_memories_details_vector_1024_index']
+  }
+}
+
+table user_memories_contexts {
+  id varchar(255) [pk, not null]
+  user_memory_ids jsonb
+  labels jsonb
+  extracted_labels jsonb
+  associated_objects jsonb
+  associated_subjects jsonb
+  title text
+  title_vector vector(1024)
+  description text
+  description_vector vector(1024)
+  type varchar(255)
+  current_status text
+  score_impact numeric [default: 0]
+  score_urgency numeric [default: 0]
+  accessed_at "timestamp with time zone" [not null, default: `now()`]
+  created_at "timestamp with time zone" [not null, default: `now()`]
+  updated_at "timestamp with time zone" [not null, default: `now()`]
+
+  indexes {
+    title_vector [name: 'user_memories_contexts_title_vector_index']
+    description_vector [name: 'user_memories_contexts_description_vector_index']
+    type [name: 'user_memories_contexts_type_index']
+  }
+}
+
+table user_memories_experiences {
+  id varchar(255) [pk, not null]
+  user_memory_id text
+  labels jsonb
+  extracted_labels jsonb
+  type varchar(255)
+  situation text
+  situation_vector vector(1024)
+  reasoning text
+  possible_outcome text
+  action text
+  action_vector vector(1024)
+  key_learning text
+  key_learning_vector vector(1024)
+  metadata jsonb
+  score_confidence real [default: 0]
+  accessed_at "timestamp with time zone" [not null, default: `now()`]
+  created_at "timestamp with time zone" [not null, default: `now()`]
+  updated_at "timestamp with time zone" [not null, default: `now()`]
+
+  indexes {
+    situation_vector [name: 'user_memories_experiences_situation_vector_index']
+    action_vector [name: 'user_memories_experiences_action_vector_index']
+    key_learning_vector [name: 'user_memories_experiences_key_learning_vector_index']
+    type [name: 'user_memories_experiences_type_index']
+  }
+}
+
+table user_memories_identities {
+  current_focuses text
+  description text
+  description_vector vector(1024)
+  experience text
+  extracted_labels jsonb
+  id varchar(255) [pk, not null]
+  labels jsonb
+  relationship text
+  role text
+  type varchar(255)
+  user_memory_id text
+  accessed_at "timestamp with time zone" [not null, default: `now()`]
+  created_at "timestamp with time zone" [not null, default: `now()`]
+  updated_at "timestamp with time zone" [not null, default: `now()`]
+
+  indexes {
+    description_vector [name: 'user_memories_identities_description_vector_index']
+    type [name: 'user_memories_identities_type_index']
+  }
+}
+
+table user_memories_preferences {
+  id varchar(255) [pk, not null]
+  context_id varchar(255)
+  user_memory_id varchar(255)
+  labels jsonb
+  extracted_labels jsonb
+  extracted_scopes jsonb
+  conclusion_directives text
+  conclusion_directives_vector vector(1024)
+  type varchar(255)
+  suggestions text
+  score_priority numeric [default: 0]
+  accessed_at "timestamp with time zone" [not null, default: `now()`]
+  created_at "timestamp with time zone" [not null, default: `now()`]
+  updated_at "timestamp with time zone" [not null, default: `now()`]
+
+  indexes {
+    conclusion_directives_vector [name: 'user_memories_preferences_conclusion_directives_vector_index']
+  }
+}
+
 ref: agents_files.file_id > files.id
 
 ref: agents_files.agent_id > agents.id
@@ -995,6 +1136,12 @@ ref: generations.generation_batch_id > generation_batches.id
 
 ref: generations.async_task_id - async_tasks.id
 
+ref: message_groups.user_id - users.id
+
+ref: message_groups.topic_id - topics.id
+
+ref: message_groups.parent_group_id > message_groups.id
+
 ref: messages_files.file_id > files.id
 
 ref: messages_files.message_id > messages.id
@@ -1007,6 +1154,8 @@ ref: messages.topic_id - topics.id
 
 ref: threads.source_message_id - messages.id
 
+ref: messages.message_group_id > message_groups.id
+
 ref: sessions.group_id - session_groups.id
 
 ref: topic_documents.document_id > documents.id

docs/self-hosting/environment-variables/model-provider.mdx

@@ -717,4 +717,20 @@ NewAPI is a multi-provider model aggregation service that supports automatic mod
 - Default: `-`
 - Example: `-all,+vercel-model-1,+vercel-model-2=vercel-special`
 
+## Cerebras
+
+### `CEREBRAS_API_KEY`
+
+- Type: Required
+- Description: This is the API key you applied for in the Cerebras service.
+- Default: -
+- Example: `csk-xxxxxx...xxxxxx`
+
+### `CEREBRAS_MODEL_LIST`
+
+- Type: Optional
+- Description: Used to control the Cerebras model list. Use `+` to add a model, `-` to hide a model, and `model_name=display_name` to customize the display name of a model. Separate multiple entries with commas. The definition syntax follows the same rules as other providers' model lists.
+- Default: `-`
+- Example: `-all,+cerebras-model-1,+cerebras-model-2=cerebras-special`
+
 [model-list]: /docs/self-hosting/advanced/model-list

docs/self-hosting/environment-variables/model-provider.zh-CN.mdx

@@ -720,4 +720,20 @@ LobeChat 在部署时提供了丰富的模型服务商相关的环境变量，
 - 默认值：`-`
 - 示例：`-all,+vercel-model-1,+vercel-model-2=vercel-special`
 
+## Cerebras
+
+### `CEREBRAS_API_KEY`
+
+- 类型：必选
+- 描述：这是你在 Cerebras 服务中申请的 API 密钥
+- 默认值：-
+- 示例：`csk-xxxxxx...xxxxxx`
+
+### `CEREBRAS_MODEL_LIST`
+
+- 类型：可选
+- 描述：用来控制 Cerebras 模型列表，使用 `+` 增加一个模型，使用 `-` 来隐藏一个模型，使用 `模型名=展示名` 来自定义模型的展示名，用英文逗号隔开。模型定义语法规则与其他 provider 保持一致。
+- 默认值：`-`
+- 示例：`-all,+cerebras-model-1,+cerebras-model-2=cerebras-special`
+
 [model-list]: /zh/docs/self-hosting/advanced/model-list

docs/usage/features/auth.mdx

@@ -29,11 +29,6 @@ LobeChat integrates `next-auth`, a flexible and powerful identity verification l
 - **Social Login**: Support quick login via various social platforms.
 - **Data Security**: Ensure the security and privacy of user data.
 
-<Callout type={'warning'}>
-  Due to workload constraints, integration of next-auth with a server-side database has not been
-  implemented yet. If you need to use a server-side database, please use Clerk.
-</Callout>
-
 <Callout type={'info'}>
   For information on using Next-Auth, you can refer to [Authentication Services - Next
   Auth](/docs/self-hosting/advanced/authentication#next-auth).

docs/usage/features/auth.zh-CN.mdx

@@ -25,11 +25,6 @@ LobeChat 集成了 `next-auth`，一个灵活且强大的身份验证库，支
 - **社交登录**：支持多种社交平台的快捷登录。
 - **数据安全**：保障用户数据的安全性和隐私性。
 
-<Callout type={'warning'}>
-  由于工作量原因，目前还没有实现 next-auth 与服务端数据库的集成，如果需要使用服务端数据库，请使用
-  Clerk 。
-</Callout>
-
 <Callout type={'info'}>
   关于 Next-Auth 的使用，可以查阅 [身份验证服务 - Next
   Auth](/zh/docs/self-hosting/advanced/authentication#next-auth)。

locales/ar/chat.json

@@ -3,8 +3,8 @@
     "title": "النموذج"
   },
   "agentDefaultMessage": "مرحبًا، أنا **{{name}}**، يمكنك بدء المحادثة معي على الفور، أو يمكنك الذهاب إلى [إعدادات المساعد]({{url}}) لإكمال معلوماتي.",
-  "agentDefaultMessageWithSystemRole": "مرحبًا، أنا **{{name}}**، {{systemRole}}، دعنا نبدأ الدردشة!",
-  "agentDefaultMessageWithoutEdit": "مرحبًا، أنا **{{name}}**، دعنا نبدأ المحادثة!",
+  "agentDefaultMessageWithSystemRole": "مرحبًا، أنا **{{name}}**، كيف يمكنني مساعدتك؟",
+  "agentDefaultMessageWithoutEdit": "مرحبًا، أنا **{{name}}**، كيف يمكنني مساعدتك؟",
   "agents": "مساعد",
   "artifact": {
     "generating": "جاري الإنشاء",
@@ -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",

locales/ar/common.json

@@ -236,6 +236,7 @@
   },
   "information": "المجتمع والمعلومات",
   "installPWA": "تثبيت تطبيق المتصفح",
+  "labs": "المختبرات",
   "lang": {
     "ar": "العربية",
     "bg-BG": "البلغارية",

locales/ar/hotkey.json

@@ -7,6 +7,14 @@
     "desc": "مسح الرسائل والملفات المرفوعة في المحادثة الحالية",
     "title": "مسح رسائل المحادثة"
   },
+  "deleteAndRegenerateMessage": {
+    "desc": "حذف الرسالة الأخيرة وإعادة إنشائها",
+    "title": "حذف وإعادة إنشاء"
+  },
+  "deleteLastMessage": {
+    "desc": "حذف الرسالة الأخيرة",
+    "title": "حذف الرسالة الأخيرة"
+  },
   "desktop": {
     "openSettings": {
       "desc": "افتح صفحة إعدادات التطبيق",

locales/ar/image.json

@@ -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"

locales/ar/labs.json

@@ -0,0 +1,14 @@
+{
+  "desc": "سنقوم بتحديث الميزات الجديدة التي نستكشفها من وقت لآخر، ندعوك لتجربتها!",
+  "features": {
+    "groupChat": {
+      "desc": "تفعيل إمكانية تنسيق المحادثات الجماعية متعددة الوكلاء.",
+      "title": "دردشة جماعية (متعددة الوكلاء)"
+    },
+    "inputMarkdown": {
+      "desc": "عرض Markdown في منطقة الإدخال بشكل فوري (مثل النص العريض، كتل الشيفرة، الجداول، وغيرها).",
+      "title": "عرض Markdown في حقل الإدخال"
+    }
+  },
+  "title": "المختبر"
+}

locales/ar/modelProvider.json

@@ -294,6 +294,21 @@
           "title": "أقصى نافذة سياق",
           "unlimited": "غير محدود"
         },
+        "type": {
+          "extra": "أنواع النماذج المختلفة تمتلك سيناريوهات استخدام وقدرات مميزة",
+          "options": {
+            "chat": "محادثة",
+            "embedding": "تضمين",
+            "image": "توليد الصور",
+            "realtime": "محادثة فورية",
+            "stt": "تحويل الصوت إلى نص",
+            "text2music": "تحويل النص إلى موسيقى",
+            "text2video": "تحويل النص إلى فيديو",
+            "tts": "تحويل النص إلى كلام"
+          },
+          "placeholder": "يرجى اختيار نوع النموذج",
+          "title": "نوع النموذج"
+        },
         "vision": {
           "extra": "سيؤدي هذا التكوين إلى فتح إعدادات تحميل الصور في التطبيق، ما إذا كان يدعم التعرف يعتمد بالكامل على النموذج نفسه، يرجى اختبار قابلية استخدام التعرف البصري لهذا النموذج بنفسك",
           "title": "دعم التعرف البصري"

locales/ar/models.json

@@ -92,6 +92,12 @@
   "DeepSeek-V3.1-Think": {
     "description": "DeepSeek-V3.1 - وضع التفكير؛ DeepSeek-V3.1 هو نموذج استدلال هجين جديد من DeepSeek يدعم وضعين للاستدلال: التفكير وعدم التفكير، مع كفاءة تفكير أعلى مقارنة بـ DeepSeek-R1-0528. بعد تحسين ما بعد التدريب، تحسنت بشكل كبير أداء استخدام أدوات الوكيل ومهام الوكيل الذكي."
   },
+  "DeepSeek-V3.2-Exp": {
+    "description": "DeepSeek V3.2 هو أحدث نموذج عام أصدرته DeepSeek، يدعم بنية استدلال هجينة، ويتميز بقدرات وكيل أقوى."
+  },
+  "DeepSeek-V3.2-Exp-Think": {
+    "description": "وضع التفكير في DeepSeek V3.2. قبل إخراج الإجابة النهائية، يقوم النموذج أولاً بإخراج سلسلة من الأفكار لتحسين دقة الإجابة النهائية."
+  },
   "Doubao-lite-128k": {
     "description": "Doubao-lite يتميز بسرعة استجابة فائقة وقيمة أفضل مقابل المال، ويوفر خيارات أكثر مرونة للعملاء في سيناريوهات مختلفة. يدعم الاستدلال والتخصيص مع نافذة سياق 128k."
   },
@@ -287,6 +293,9 @@
   "Pro/deepseek-ai/DeepSeek-V3.1": {
     "description": "DeepSeek-V3.1 هو نموذج لغة كبير بنمط هجين أصدرته DeepSeek AI، وقد شهد ترقيات مهمة متعددة مقارنة بالإصدارات السابقة. من الابتكارات الرئيسية في هذا النموذج دمج \"وضع التفكير\" و\"وضع عدم التفكير\" في نموذج واحد، حيث يمكن للمستخدمين التبديل بينهما بسهولة عبر تعديل قالب المحادثة لتلبية متطلبات المهام المختلفة. من خلال تحسينات ما بعد التدريب المخصصة، تم تعزيز أداء V3.1 في استدعاء الأدوات ومهام الوكيل بشكل ملحوظ، مما يمكنه من دعم أدوات البحث الخارجية وتنفيذ مهام معقدة متعددة الخطوات بشكل أفضل. يعتمد النموذج على DeepSeek-V3.1-Base مع تدريب إضافي، حيث تم توسيع حجم بيانات التدريب بشكل كبير عبر طريقة التوسيع النصي الطويل على مرحلتين، مما يحسن أدائه في معالجة المستندات الطويلة والرموز البرمجية الطويلة. كنموذج مفتوح المصدر، يظهر DeepSeek-V3.1 قدرة تنافسية مع أفضل النماذج المغلقة في مجالات الترميز والرياضيات والاستدلال، وبفضل هيكله المختلط للخبراء (MoE)، يحافظ على سعة نموذج ضخمة مع تقليل تكلفة الاستدلال بفعالية."
   },
+  "Pro/deepseek-ai/DeepSeek-V3.1-Terminus": {
+    "description": "DeepSeek-V3.1-Terminus هو نسخة محدثة من نموذج V3.1 الذي أصدرته DeepSeek، ويصنف كنموذج لغة كبير لوكيل هجين. يركز هذا التحديث على إصلاح المشكلات التي أبلغ عنها المستخدمون وتحسين الاستقرار مع الحفاظ على القدرات الأصلية للنموذج. لقد حسّن بشكل ملحوظ اتساق اللغة، وقلل من الاستخدام المختلط للغة الصينية والإنجليزية والرموز غير الطبيعية. يدمج النموذج \"وضع التفكير\" و\"الوضع غير التفكيري\"، حيث يمكن للمستخدمين التبديل بينهما بسهولة عبر قوالب الدردشة لتناسب مهام مختلفة. كتحسين مهم، عزز V3.1-Terminus أداء وكيل الكود ووكيل البحث، مما يجعله أكثر موثوقية في استدعاء الأدوات وتنفيذ المهام المعقدة متعددة الخطوات."
+  },
   "Pro/moonshotai/Kimi-K2-Instruct-0905": {
     "description": "Kimi K2-Instruct-0905 هو أحدث وأقوى إصدار من Kimi K2. إنه نموذج لغوي من نوع الخبراء المختلطين (MoE) من الطراز الأول، يحتوي على تريليون معلمة إجمالية و32 مليار معلمة مفعلة. تشمل الميزات الرئيسية للنموذج: تعزيز ذكاء التكويد للوكيل، مع تحسينات ملحوظة في الأداء في اختبارات المعيار المفتوحة ومهام التكويد الواقعية للوكيل؛ تحسين تجربة التكويد في الواجهة الأمامية، مع تقدم في الجمالية والعملية في برمجة الواجهة الأمامية."
   },
@@ -680,6 +689,9 @@
   "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 +785,9 @@
   "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."
   },
@@ -920,6 +935,9 @@
   "deepseek-ai/DeepSeek-V3.1": {
     "description": "DeepSeek-V3.1 هو نموذج لغة كبير بنمط هجين أصدرته DeepSeek AI، وقد شهد ترقيات مهمة متعددة مقارنة بالإصدارات السابقة. من الابتكارات الرئيسية في هذا النموذج دمج \"وضع التفكير\" و\"وضع عدم التفكير\" في نموذج واحد، حيث يمكن للمستخدمين التبديل بينهما بسهولة عبر تعديل قالب المحادثة لتلبية متطلبات المهام المختلفة. من خلال تحسينات ما بعد التدريب المخصصة، تم تعزيز أداء V3.1 في استدعاء الأدوات ومهام الوكيل بشكل ملحوظ، مما يمكنه من دعم أدوات البحث الخارجية وتنفيذ مهام معقدة متعددة الخطوات بشكل أفضل. يعتمد النموذج على DeepSeek-V3.1-Base مع تدريب إضافي، حيث تم توسيع حجم بيانات التدريب بشكل كبير عبر طريقة التوسيع النصي الطويل على مرحلتين، مما يحسن أدائه في معالجة المستندات الطويلة والرموز البرمجية الطويلة. كنموذج مفتوح المصدر، يظهر DeepSeek-V3.1 قدرة تنافسية مع أفضل النماذج المغلقة في مجالات الترميز والرياضيات والاستدلال، وبفضل هيكله المختلط للخبراء (MoE)، يحافظ على سعة نموذج ضخمة مع تقليل تكلفة الاستدلال بفعالية."
   },
+  "deepseek-ai/DeepSeek-V3.1-Terminus": {
+    "description": "DeepSeek-V3.1-Terminus هو نسخة محدثة من نموذج V3.1 الذي أصدرته DeepSeek، ويصنف كنموذج لغة كبير لوكيل هجين. يركز هذا التحديث على إصلاح المشكلات التي أبلغ عنها المستخدمون وتحسين الاستقرار مع الحفاظ على القدرات الأصلية للنموذج. لقد حسّن بشكل ملحوظ اتساق اللغة، وقلل من الاستخدام المختلط للغة الصينية والإنجليزية والرموز غير الطبيعية. يدمج النموذج \"وضع التفكير\" و\"الوضع غير التفكيري\"، حيث يمكن للمستخدمين التبديل بينهما بسهولة عبر قوالب الدردشة لتناسب مهام مختلفة. كتحسين مهم، عزز V3.1-Terminus أداء وكيل الكود ووكيل البحث، مما يجعله أكثر موثوقية في استدعاء الأدوات وتنفيذ المهام المعقدة متعددة الخطوات."
+  },
   "deepseek-ai/deepseek-llm-67b-chat": {
     "description": "DeepSeek 67B هو نموذج متقدم تم تدريبه للحوار المعقد."
   },
@@ -929,6 +947,9 @@
   "deepseek-ai/deepseek-v3.1": {
     "description": "DeepSeek V3.1: نموذج استدلال من الجيل التالي يعزز القدرات على الاستدلال المعقد والتفكير التسلسلي، مناسب للمهام التي تتطلب تحليلاً عميقًا."
   },
+  "deepseek-ai/deepseek-v3.1-terminus": {
+    "description": "DeepSeek V3.1: نموذج الاستدلال من الجيل التالي، يعزز القدرة على الاستنتاج المعقد والتفكير المتسلسل، ومناسب للمهام التي تتطلب تحليلاً عميقاً."
+  },
   "deepseek-ai/deepseek-vl2": {
     "description": "DeepSeek-VL2 هو نموذج لغوي بصري مختلط الخبراء (MoE) تم تطويره بناءً على DeepSeekMoE-27B، يستخدم بنية MoE ذات تفعيل نادر، محققًا أداءً ممتازًا مع تفعيل 4.5 مليار معلمة فقط. يقدم هذا النموذج أداءً ممتازًا في مهام مثل الأسئلة البصرية، التعرف الضوئي على الأحرف، فهم الوثائق/الجداول/الرسوم البيانية، وتحديد المواقع البصرية."
   },
@@ -993,7 +1014,7 @@
     "description": "DeepSeek R1 النسخة الكاملة، تحتوي على 671 مليار معلمة، تدعم البحث المتصل في الوقت الحقيقي، وتتمتع بقدرات فهم وتوليد أقوى."
   },
   "deepseek-reasoner": {
-    "description": "وضع التفكير في DeepSeek V3.1. قبل إخراج الإجابة النهائية، يقوم النموذج أولاً بإخراج سلسلة من التفكير لتحسين دقة الإجابة النهائية."
+    "description": "وضع التفكير في DeepSeek V3.2. قبل إخراج الإجابة النهائية، يقوم النموذج أولاً بإخراج سلسلة من الأفكار لتحسين دقة الإجابة النهائية."
   },
   "deepseek-v2": {
     "description": "DeepSeek V2 هو نموذج لغوي فعال من نوع Mixture-of-Experts، مناسب لاحتياجات المعالجة الاقتصادية."
@@ -1013,6 +1034,9 @@
   "deepseek-v3.1:671b": {
     "description": "DeepSeek V3.1: نموذج استدلال من الجيل التالي يعزز القدرات على الاستدلال المعقد والتفكير التسلسلي، مناسب للمهام التي تتطلب تحليلاً عميقًا."
   },
+  "deepseek-v3.2-exp": {
+    "description": "deepseek-v3.2-exp يُدخل آلية الانتباه المتفرق، بهدف تحسين كفاءة التدريب والاستدلال عند معالجة النصوص الطويلة، بسعر أقل من deepseek-v3.1."
+  },
   "deepseek/deepseek-chat-v3-0324": {
     "description": "DeepSeek V3 هو نموذج مختلط خبير يحتوي على 685B من المعلمات، وهو أحدث إصدار من سلسلة نماذج الدردشة الرائدة لفريق DeepSeek.\n\nيستفيد من نموذج [DeepSeek V3](/deepseek/deepseek-chat-v3) ويظهر أداءً ممتازًا في مجموعة متنوعة من المهام."
   },
@@ -1232,6 +1256,9 @@
   "fal-ai/flux/schnell": {
     "description": "FLUX.1 [schnell] هو نموذج توليد صور يحتوي على 12 مليار معلمة، يركز على توليد صور عالية الجودة بسرعة."
   },
+  "fal-ai/hunyuan-image/v3": {
+    "description": "نموذج قوي لتوليد الصور متعددة الوسائط الأصلية"
+  },
   "fal-ai/imagen4/preview": {
     "description": "نموذج توليد صور عالي الجودة مقدم من جوجل."
   },
@@ -1343,24 +1370,36 @@
   "gemini-2.5-flash": {
     "description": "Gemini 2.5 Flash هو نموذج Google الأكثر فعالية من حيث التكلفة، ويوفر وظائف شاملة."
   },
+  "gemini-2.5-flash-image": {
+    "description": "Nano Banana هو أحدث وأسرع وأكثر نموذج متعدد الوسائط أصلي كفاءة من Google، يتيح لك إنشاء وتحرير الصور من خلال المحادثة."
+  },
   "gemini-2.5-flash-image-preview": {
     "description": "Nano Banana هو أحدث وأسرع وأكثر نموذج متعدد الوسائط أصلي كفاءة من Google، يتيح لك إنشاء وتحرير الصور من خلال المحادثة."
   },
   "gemini-2.5-flash-image-preview:image": {
     "description": "Nano Banana هو أحدث وأسرع وأكثر نموذج متعدد الوسائط أصلي كفاءة من Google، يتيح لك إنشاء وتحرير الصور من خلال المحادثة."
   },
+  "gemini-2.5-flash-image:image": {
+    "description": "Nano Banana هو أحدث وأسرع وأكثر نموذج متعدد الوسائط أصلي كفاءة من Google، يتيح لك إنشاء وتحرير الصور من خلال المحادثة."
+  },
   "gemini-2.5-flash-lite": {
     "description": "Gemini 2.5 Flash-Lite هو أصغر وأفضل نموذج من حيث التكلفة من Google، مصمم للاستخدام على نطاق واسع."
   },
   "gemini-2.5-flash-lite-preview-06-17": {
     "description": "Gemini 2.5 Flash-Lite Preview هو أصغر وأكفأ نموذج من Google، مصمم للاستخدام واسع النطاق."
   },
+  "gemini-2.5-flash-lite-preview-09-2025": {
+    "description": "إصدار معاينة (25 سبتمبر 2025) من Gemini 2.5 Flash-Lite"
+  },
   "gemini-2.5-flash-preview-04-17": {
     "description": "معاينة فلاش جمنّي 2.5 هي النموذج الأكثر كفاءة من جوجل، حيث تقدم مجموعة شاملة من الميزات."
   },
   "gemini-2.5-flash-preview-05-20": {
     "description": "Gemini 2.5 Flash Preview هو نموذج Google الأكثر فعالية من حيث التكلفة، يقدم وظائف شاملة."
   },
+  "gemini-2.5-flash-preview-09-2025": {
+    "description": "إصدار معاينة (25 سبتمبر 2025) من Gemini 2.5 Flash"
+  },
   "gemini-2.5-pro": {
     "description": "Gemini 2.5 Pro هو نموذج التفكير الأكثر تقدمًا من Google، قادر على استدلال المشكلات المعقدة في البرمجة والرياضيات ومجالات STEM، بالإضافة إلى تحليل مجموعات البيانات الكبيرة ومستودعات الأكواد والوثائق باستخدام سياق طويل."
   },
@@ -1373,6 +1412,15 @@
   "gemini-2.5-pro-preview-06-05": {
     "description": "جيميني 2.5 برو بريڤيو هو أحدث نموذج تفكيري من جوجل، قادر على استنتاج حلول للمشكلات المعقدة في مجالات البرمجة، الرياضيات، والعلوم والتكنولوجيا والهندسة والرياضيات (STEM)، بالإضافة إلى تحليل مجموعات بيانات كبيرة، قواعد بيانات البرمجة، والوثائق باستخدام سياق طويل."
   },
+  "gemini-flash-latest": {
+    "description": "أحدث إصدار من Gemini Flash"
+  },
+  "gemini-flash-lite-latest": {
+    "description": "أحدث إصدار من Gemini Flash-Lite"
+  },
+  "gemini-pro-latest": {
+    "description": "أحدث إصدار من Gemini Pro"
+  },
   "gemma-7b-it": {
     "description": "Gemma 7B مناسب لمعالجة المهام المتوسطة والصغيرة، ويجمع بين الكفاءة من حيث التكلفة."
   },
@@ -1437,7 +1485,7 @@
     "description": "سلسلة نماذج GLM-4.1V-Thinking هي أقوى نماذج اللغة البصرية المعروفة على مستوى 10 مليارات معلمة، وتدمج مهام اللغة البصرية المتقدمة من نفس المستوى، بما في ذلك فهم الفيديو، الأسئلة والأجوبة على الصور، حل المسائل العلمية، التعرف على النصوص OCR، تفسير الوثائق والرسوم البيانية، وكلاء واجهة المستخدم الرسومية، ترميز صفحات الويب الأمامية، والتثبيت الأرضي، وغيرها. تتفوق قدرات هذه المهام على نموذج Qwen2.5-VL-72B الذي يحتوي على أكثر من 8 أضعاف عدد المعلمات. من خلال تقنيات التعلم المعزز الرائدة، يتقن النموذج تحسين دقة وإثراء الإجابات عبر استدلال سلسلة التفكير، متفوقًا بشكل ملحوظ على النماذج التقليدية غير المعتمدة على التفكير من حيث النتائج النهائية وقابلية التفسير."
   },
   "glm-4.5": {
-    "description": "أحدث نموذج رائد من Zhizhu، يدعم تبديل وضع التفكير، ويحقق مستوى SOTA بين النماذج المفتوحة المصدر في القدرات الشاملة، مع طول سياق يصل إلى 128 ألف رمز."
+    "description": "نموذج الذكاء الاصطناعي الرائد من Zhipu، يدعم تبديل أوضاع التفكير، ويحقق مستوى متقدمًا في القدرات الشاملة مقارنة بالنماذج مفتوحة المصدر، مع طول سياق يصل إلى 128 ألف."
   },
   "glm-4.5-air": {
     "description": "نسخة خفيفة من GLM-4.5، تجمع بين الأداء والقيمة، وتدعم التبديل المرن بين نماذج التفكير المختلطة."
@@ -1454,6 +1502,9 @@
   "glm-4.5v": {
     "description": "نموذج استدلال بصري من الجيل الجديد لشركة Zhipu مبني على بنية MOE، بإجمالي 106 مليار معامل و12 مليار معامل نشط، وقد بلغ مستوى الأداء الأعلى (SOTA) بين نماذج التعدد الوسائط مفتوحة المصدر المماثلة على مستوى العالم في عدة اختبارات معيارية، ويغطي مهامًا شائعة مثل فهم الصور والفيديو والمستندات وواجهات المستخدم الرسومية (GUI)."
   },
+  "glm-4.6": {
+    "description": "أحدث نموذج رائد من Zhipu GLM-4.6 (355B) يتفوق بشكل شامل على الأجيال السابقة في الترميز المتقدم، معالجة النصوص الطويلة، الاستدلال، وقدرات الوكيل الذكي، وخاصة في قدرات البرمجة التي تتوافق مع Claude Sonnet 4، ليصبح نموذج الترميز الرائد محليًا."
+  },
   "glm-4v": {
     "description": "GLM-4V يوفر قدرات قوية في فهم الصور والاستدلال، ويدعم مجموعة متنوعة من المهام البصرية."
   },
@@ -1481,6 +1532,9 @@
   "glm-zero-preview": {
     "description": "يمتلك GLM-Zero-Preview قدرة قوية على الاستدلال المعقد، ويظهر أداءً ممتازًا في مجالات الاستدلال المنطقي، والرياضيات، والبرمجة."
   },
+  "glm4.6:355b": {
+    "description": "نموذج GLM-4.6 (355B) الرائد الأحدث من Zhipu يتفوق بشكل شامل على الجيل السابق في الترميز المتقدم، ومعالجة النصوص الطويلة، والاستدلال، وقدرات الوكلاء الذكيين، لا سيما في مجال البرمجة حيث يتماشى مع Claude Sonnet 4، ليصبح من أفضل نماذج الترميز في الصين."
+  },
   "google/gemini-2.0-flash": {
     "description": "Gemini 2.0 Flash يقدم ميزات الجيل التالي وتحسينات تشمل سرعة فائقة، استخدام أدوات مدمجة، توليد متعدد الوسائط، ونافذة سياق تصل إلى مليون رمز."
   },
@@ -1682,12 +1736,18 @@
   "gpt-5-nano": {
     "description": "أسرع وأكفأ نسخة من GPT-5 من حيث التكلفة. مثالية للتطبيقات التي تتطلب استجابة سريعة وحساسة للتكلفة."
   },
+  "gpt-5-pro": {
+    "description": "يستخدم GPT-5 pro قدرة حسابية أكبر للتفكير بشكل أعمق، ويواصل تقديم إجابات أفضل باستمرار."
+  },
   "gpt-audio": {
     "description": "GPT Audio هو نموذج دردشة عام موجه لإدخال وإخراج الصوت، ويدعم استخدام الصوت في واجهة برمجة تطبيقات Chat Completions."
   },
   "gpt-image-1": {
     "description": "نموذج توليد الصور متعدد الوسائط الأصلي من ChatGPT"
   },
+  "gpt-image-1-mini": {
+    "description": "نسخة منخفضة التكلفة من GPT Image 1، تدعم إدخال النصوص والصور بشكل أصلي وتوليد مخرجات على شكل صور."
+  },
   "gpt-oss-120b": {
     "description": "GPT-OSS-120B MXFP4: هيكل Transformer محسّن بالكمية، يحافظ على أداء قوي حتى في ظل محدودية الموارد."
   },
@@ -1700,9 +1760,6 @@
   "gpt-realtime": {
     "description": "نموذج عام في الوقت الحقيقي يدعم الإدخال والإخراج النصي والصوتي، ويدعم أيضًا إدخال الصور."
   },
-  "grok-2-1212": {
-    "description": "لقد تم تحسين هذا النموذج في الدقة، والامتثال للتعليمات، والقدرة على التعامل مع لغات متعددة."
-  },
   "grok-2-image-1212": {
     "description": "نموذج توليد الصور الأحدث لدينا قادر على توليد صور حيوية وواقعية بناءً على الأوامر النصية. يبرع في مجالات التسويق، وسائل التواصل الاجتماعي، والترفيه."
   },
@@ -1712,15 +1769,9 @@
   "grok-3": {
     "description": "نموذج رائد، بارع في استخراج البيانات، البرمجة، وتلخيص النصوص لتطبيقات المؤسسات، يمتلك معرفة عميقة في مجالات المالية، الطب، القانون، والعلوم."
   },
-  "grok-3-fast": {
-    "description": "نموذج رائد، بارع في استخراج البيانات، البرمجة، وتلخيص النصوص لتطبيقات المؤسسات، يمتلك معرفة عميقة في مجالات المالية، الطب، القانون، والعلوم."
-  },
   "grok-3-mini": {
     "description": "نموذج خفيف الوزن، يفكر قبل المحادثة. سريع وذكي، مناسب للمهام المنطقية التي لا تتطلب معرفة متخصصة عميقة، ويستطيع تتبع مسار التفكير الأصلي."
   },
-  "grok-3-mini-fast": {
-    "description": "نموذج خفيف الوزن، يفكر قبل المحادثة. سريع وذكي، مناسب للمهام المنطقية التي لا تتطلب معرفة متخصصة عميقة، ويستطيع تتبع مسار التفكير الأصلي."
-  },
   "grok-4": {
     "description": "نموذجنا الرائد الأحدث والأقوى، يتميز بأداء ممتاز في معالجة اللغة الطبيعية، الحسابات الرياضية، والاستدلال — إنه لاعب شامل مثالي."
   },
@@ -1799,12 +1850,12 @@
   "hunyuan-t1-latest": {
     "description": "تحسين كبير لقدرات نموذج التفكير البطيء الرئيسي في الرياضيات الصعبة، الاستدلال المعقد، الشيفرة الصعبة، الالتزام بالتعليمات، وجودة إنشاء النصوص."
   },
-  "hunyuan-t1-vision": {
-    "description": "نموذج تفكير عميق متعدد الوسائط من Hunyuan، يدعم سلاسل التفكير الأصلية متعددة الوسائط، بارع في معالجة مختلف سيناريوهات الاستدلال على الصور، ويحقق تحسينًا شاملاً مقارنة بنموذج التفكير السريع في مسائل العلوم."
-  },
   "hunyuan-t1-vision-20250619": {
     "description": "أحدث نموذج تفكير عميق متعدد الوسائط t1-vision من Hunyuan، يدعم سلسلة التفكير الأصلية متعددة الوسائط، مع تحسين شامل مقارنة بالإصدار الافتراضي السابق."
   },
+  "hunyuan-t1-vision-20250916": {
+    "description": "أحدث إصدار من نموذج Hunyuan t1-vision للتفكير البصري العميق، يقدم تحسينات شاملة مقارنة بالإصدار السابق في مهام الأسئلة والأجوبة العامة على الصور والنصوص، التحديد البصري، التعرف البصري على الحروف (OCR)، الرسوم البيانية، حل المسائل المصورة، والإبداع البصري، مع تحسين ملحوظ في دعم اللغة الإنجليزية واللغات الأقل استخدامًا."
+  },
   "hunyuan-turbo": {
     "description": "نسخة المعاينة من الجيل الجديد من نموذج اللغة الكبير، يستخدم هيكل نموذج الخبراء المختلط (MoE) الجديد، مما يوفر كفاءة استدلال أسرع وأداء أقوى مقارنة بـ hunyuan-pro."
   },
@@ -1826,6 +1877,9 @@
   "hunyuan-turbos-20250604": {
     "description": "ترقية قاعدة التدريب المسبق، مع تحسينات في مهارات الكتابة وفهم القراءة، وزيادة كبيرة في القدرات البرمجية والعلمية، وتحسين مستمر في اتباع التعليمات المعقدة."
   },
+  "hunyuan-turbos-20250926": {
+    "description": "ترقية جودة بيانات قاعدة التدريب المسبق. تحسين استراتيجية التدريب في مرحلة ما بعد التدريب، مع استمرار تحسين قدرات الوكيل، واللغات الإنجليزية واللغات الصغيرة، والامتثال للتعليمات، والبرمجة، والعلوم."
+  },
   "hunyuan-turbos-latest": {
     "description": "hunyuan-TurboS هو أحدث إصدار من نموذج هونيان الرائد، يتمتع بقدرات تفكير أقوى وتجربة أفضل."
   },
@@ -1916,6 +1970,9 @@
   "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."
   },
@@ -1958,6 +2015,9 @@
   "llama-3.2-vision-instruct": {
     "description": "تم تحسين نموذج Llama 3.2-Vision المعدل للتعليمات للتعرف البصري، والاستدلال على الصور، ووصف الصور، والإجابة على الأسئلة العامة المتعلقة بالصور."
   },
+  "llama-3.3-70b": {
+    "description": "Llama 3.3 70B: نموذج Llama متوسط إلى كبير الحجم، يوازن بين قدرات الاستدلال والكفاءة الإنتاجية."
+  },
   "llama-3.3-70b-instruct": {
     "description": "Llama 3.3 هو النموذج الأكثر تقدمًا في سلسلة Llama، وهو نموذج لغوي مفتوح المصدر متعدد اللغات، يوفر تجربة أداء تنافس نموذج 405B بتكلفة منخفضة للغاية. يعتمد على هيكل Transformer، وتم تحسين فائدته وأمانه من خلال التعديل الدقيق تحت الإشراف (SFT) والتعلم المعزز من خلال التغذية الراجعة البشرية (RLHF). تم تحسين نسخة التعديل الخاصة به لتكون مثالية للحوار متعدد اللغات، حيث يتفوق في العديد من المعايير الصناعية على العديد من نماذج الدردشة المفتوحة والمغلقة. تاريخ انتهاء المعرفة هو ديسمبر 2023."
   },
@@ -1967,6 +2027,12 @@
   "llama-3.3-instruct": {
     "description": "تم تحسين نموذج Llama 3.3 المعدل للتعليمات خصيصًا لسيناريوهات المحادثة، حيث تفوق على العديد من نماذج الدردشة مفتوحة المصدر الحالية في اختبارات المعايير الصناعية الشائعة."
   },
+  "llama-4-maverick-17b-128e-instruct": {
+    "description": "Llama 4 Maverick: نموذج عالي الأداء من سلسلة Llama، مناسب لمهام الاستدلال المتقدم، حل المشكلات المعقدة، وتنفيذ التعليمات."
+  },
+  "llama-4-scout-17b-16e-instruct": {
+    "description": "Llama 4 Scout: نموذج عالي الأداء من سلسلة Llama، مثالي للسيناريوهات التي تتطلب إنتاجية عالية وزمن استجابة منخفض."
+  },
   "llama3-70b-8192": {
     "description": "Meta Llama 3 70B يوفر قدرة معالجة معقدة لا مثيل لها، مصمم خصيصًا للمشاريع ذات المتطلبات العالية."
   },
@@ -1982,6 +2048,9 @@
   "llama3.1": {
     "description": "Llama 3.1 هو النموذج الرائد الذي أطلقته Meta، يدعم ما يصل إلى 405B من المعلمات، ويمكن تطبيقه في مجالات الحوار المعقد، والترجمة متعددة اللغات، وتحليل البيانات."
   },
+  "llama3.1-8b": {
+    "description": "Llama 3.1 8B: إصدار خفيف ومنخفض التأخير من Llama، مناسب للاستدلال التفاعلي الخفيف عبر الإنترنت."
+  },
   "llama3.1:405b": {
     "description": "Llama 3.1 هو النموذج الرائد الذي أطلقته Meta، يدعم ما يصل إلى 405B من المعلمات، ويمكن تطبيقه في مجالات الحوار المعقد، والترجمة متعددة اللغات، وتحليل البيانات."
   },
@@ -2579,6 +2648,12 @@
   "qvq-plus": {
     "description": "نموذج استدلال بصري يدعم الإدخال البصري وإخراج سلسلة التفكير. النسخة بلس التي تلت نموذج qvq-max، تتميز بسرعة استدلال أعلى وتوازن أفضل بين الأداء والتكلفة مقارنة بنموذج qvq-max."
   },
+  "qwen-3-32b": {
+    "description": "Qwen 3 32B: نموذج من سلسلة Qwen يتميز بأداء ممتاز في المهام متعددة اللغات والبرمجة، مناسب للاستخدام الإنتاجي متوسط النطاق."
+  },
+  "qwen-3-coder-480b": {
+    "description": "Qwen 3 Coder 480B: نموذج طويل السياق مخصص لتوليد الشيفرات والمهام البرمجية المعقدة."
+  },
   "qwen-coder-plus": {
     "description": "نموذج Tongyi Qianwen للبرمجة."
   },
@@ -3131,6 +3206,9 @@
   "zai-org/GLM-4.5V": {
     "description": "GLM-4.5V هو نموذج لغوي بصري (VLM) من الجيل الأحدث صدر عن Zhipu AI (智谱 AI). بُني النموذج على نموذج النص الرائد GLM-4.5-Air الذي يحتوي على 106B من المعاملات الإجمالية و12B من معاملات التنشيط، ويعتمد على بنية الخبراء المختلطين (MoE) بهدف تحقيق أداء متميز بتكلفة استدلال أقل. من الناحية التقنية، يواصل GLM-4.5V نهج GLM-4.1V-Thinking ويقدّم ابتكارات مثل ترميز المواقع الدوراني ثلاثي الأبعاد (3D-RoPE)، مما عزّز بشكل ملحوظ قدرته على إدراك واستنتاج العلاقات المكانية ثلاثية الأبعاد. وبفضل تحسينات في مراحل ما قبل التدريب، والتعديل بالإشراف، والتعلّم المعزّز، أصبح النموذج قادراً على معالجة محتوى بصري متنوّع مثل الصور والفيديوهات والمستندات الطويلة، وقد حقق مستوى متقدماً ضمن أفضل نماذج المصدر المفتوح في 41 معياراً متعدد الوسائط منشوراً. بالإضافة إلى ذلك، أضاف النموذج مفتاح \"وضع التفكير\" الذي يتيح للمستخدمين التبديل بين الاستجابة السريعة والاستدلال العميق بحرية لتوازن أفضل بين الكفاءة والفعالية."
   },
+  "zai-org/GLM-4.6": {
+    "description": "مقارنةً بـ GLM-4.5، قدم GLM-4.6 عدة تحسينات رئيسية. تم توسيع نافذة السياق من 128 ألف إلى 200 ألف رمز، مما يمكن النموذج من التعامل مع مهام وكيل أكثر تعقيدًا. حقق النموذج درجات أعلى في اختبارات معيارية للبرمجة، وأظهر أداءً أقوى في تطبيقات مثل Claude Code وCline وRoo Code وKilo Code، بما في ذلك تحسينات في إنشاء صفحات أمامية ذات تأثيرات بصرية متقنة. أظهر GLM-4.6 تحسنًا واضحًا في أداء الاستدلال ويدعم استخدام الأدوات أثناء الاستدلال، مما يعزز قدراته الشاملة. كما أنه أقوى في استخدام الأدوات والوكيل المعتمد على البحث، وأكثر فعالية في التكامل ضمن أطر الوكلاء. من حيث الكتابة، يتوافق النموذج بشكل أفضل مع تفضيلات البشر من حيث الأسلوب وقابلية القراءة، ويظهر سلوكًا أكثر طبيعية في سيناريوهات تمثيل الأدوار."
+  },
   "zai/glm-4.5": {
     "description": "سلسلة نماذج GLM-4.5 هي نماذج أساسية مصممة خصيصًا للوكلاء. النموذج الرائد GLM-4.5 يدمج 355 مليار معلمة إجمالية (32 مليار نشطة)، موحدًا الاستدلال، الترميز، وقدرات الوكيل لتلبية متطلبات التطبيقات المعقدة. كنظام استدلال مختلط، يوفر وضعين تشغيليين."
   },

locales/ar/providers.json

@@ -32,6 +32,9 @@
   "bfl": {
     "description": "مختبر أبحاث رائد في مقدمة الذكاء الاصطناعي، يبني البنية التحتية البصرية للمستقبل."
   },
+  "cerebras": {
+    "description": "Cerebras هو نظام استدلال ذكاء اصطناعي يعتمد على نظام CS-3 المخصص، ويهدف إلى تقديم أسرع خدمات النماذج اللغوية الكبيرة (LLM) في العالم مع استجابة فورية وقدرة معالجة عالية. تم تصميمه خصيصًا للقضاء على التأخير وتسريع سير العمل المعقد للذكاء الاصطناعي مثل توليد الشيفرات في الوقت الحقيقي والمهام التفاعلية."
+  },
   "cloudflare": {
     "description": "تشغيل نماذج التعلم الآلي المدفوعة بوحدات معالجة الرسوميات بدون خادم على شبكة Cloudflare العالمية."
   },
@@ -110,6 +113,9 @@
   "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."
   },

locales/ar/tool.json

@@ -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...",

locales/bg-BG/chat.json

@@ -3,8 +3,8 @@
     "title": "Модел"
   },
   "agentDefaultMessage": "Здравейте, аз съм **{{name}}**, можете да започнете разговор с мен веднага или да отидете на [Настройки на асистента]({{url}}), за да попълните информацията ми.",
-  "agentDefaultMessageWithSystemRole": "Здравей, аз съм **{{name}}**, {{systemRole}}. Нека започнем да чатим!",
-  "agentDefaultMessageWithoutEdit": "Здравей, аз съм **{{name}}** и нека започнем разговора!",
+  "agentDefaultMessageWithSystemRole": "Здравейте, аз съм **{{name}}**. Как мога да ви помогна?",
+  "agentDefaultMessageWithoutEdit": "Здравейте, аз съм **{{name}}**. Как мога да ви помогна?",
   "agents": "Асистент",
   "artifact": {
     "generating": "Генериране",
@@ -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",

locales/bg-BG/common.json

@@ -236,6 +236,7 @@
   },
   "information": "Общност и информация",
   "installPWA": "Инсталиране на PWA",
+  "labs": "Лаборатория",
   "lang": {
     "ar": "Арабски",
     "bg-BG": "български",

locales/bg-BG/hotkey.json

@@ -7,6 +7,14 @@
     "desc": "Изтриване на текущите съобщения и качените файлове в сесията",
     "title": "Изтриване на съобщенията в сесията"
   },
+  "deleteAndRegenerateMessage": {
+    "desc": "Изтриване на последното съобщение и повторно генериране",
+    "title": "Изтрий и генерирай отново"
+  },
+  "deleteLastMessage": {
+    "desc": "Изтриване на последното съобщение",
+    "title": "Изтрий последното съобщение"
+  },
   "desktop": {
     "openSettings": {
       "desc": "Отворете страницата с настройки на приложението",

locales/bg-BG/image.json

@@ -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"

locales/bg-BG/labs.json

@@ -0,0 +1,14 @@
+{
+  "desc": "Тук периодично ще актуализираме новите функции, които изследваме. Добре дошли да ги изпробвате!",
+  "features": {
+    "groupChat": {
+      "desc": "Активиране на възможността за координация в групов чат с множество интелигентни агенти.",
+      "title": "Групов чат (множество агенти)"
+    },
+    "inputMarkdown": {
+      "desc": "Реално време визуализация на Markdown в полето за въвеждане (удебелен текст, кодови блокове, таблици и др.).",
+      "title": "Markdown визуализация в полето за въвеждане"
+    }
+  },
+  "title": "Лаборатория"
+}

locales/bg-BG/modelProvider.json

@@ -294,6 +294,21 @@
           "title": "Максимален контекстуален прозорец",
           "unlimited": "Без ограничения"
         },
+        "type": {
+          "extra": "Различните типове модели имат различни сценарии на използване и възможности",
+          "options": {
+            "chat": "Чат",
+            "embedding": "Векторизация",
+            "image": "Генериране на изображения",
+            "realtime": "Реално време чат",
+            "stt": "Гласов текст",
+            "text2music": "Текст към музика",
+            "text2video": "Текст към видео",
+            "tts": "Гласово синтезиране"
+          },
+          "placeholder": "Моля, изберете тип модел",
+          "title": "Тип модел"
+        },
         "vision": {
           "extra": "Тази конфигурация ще активира само конфигурацията за качване на изображения в приложението, дали поддържа разпознаване зависи изцяло от самия модел, моля, тествайте наличността на визуалната разпознаваемост на този модел.",
           "title": "Поддръжка на визуално разпознаване"

locales/bg-BG/models.json

@@ -92,6 +92,12 @@
   "DeepSeek-V3.1-Think": {
     "description": "DeepSeek-V3.1 - режим с мислене; DeepSeek-V3.1 е нов хибриден модел за разсъждения, пуснат от DeepSeek, който поддържа два режима на разсъждения - с и без мислене, с по-висока ефективност на мислене в сравнение с DeepSeek-R1-0528. След оптимизация след обучение, използването на инструменти от агенти и изпълнението на задачи с агенти са значително подобрени."
   },
+  "DeepSeek-V3.2-Exp": {
+    "description": "DeepSeek V3.2 е най-новият универсален голям модел на DeepSeek, който поддържа хибридна архитектура за извод и притежава по-силни възможности на агент."
+  },
+  "DeepSeek-V3.2-Exp-Think": {
+    "description": "Режим на мислене на DeepSeek V3.2. Преди да изведе окончателния отговор, моделът първо генерира мисловна верига, за да подобри точността на крайния отговор."
+  },
   "Doubao-lite-128k": {
     "description": "Doubao-lite предлага изключително бърза реакция и по-добро съотношение цена-качество, осигурявайки по-гъвкави опции за различни сценарии на клиентите. Поддържа разсъждения и финна настройка с контекстен прозорец от 128k."
   },
@@ -287,6 +293,9 @@
   "Pro/deepseek-ai/DeepSeek-V3.1": {
     "description": "DeepSeek-V3.1 е хибриден голям езиков модел, пуснат от DeepSeek AI, който включва множество важни подобрения спрямо предишните версии. Основната иновация на модела е интеграцията на „режим на мислене“ (Thinking Mode) и „режим без мислене“ (Non-thinking Mode), които потребителите могат гъвкаво да превключват чрез настройка на чат шаблони, за да отговарят на различни задачи. След специална пост-тренировка, V3.1 значително подобрява производителността при използване на инструменти и задачи на агенти, като по-добре поддържа външни търсачки и изпълнение на сложни многостъпкови задачи. Моделът е дообучен върху DeepSeek-V3.1-Base чрез двуфазен метод за разширяване на дълги текстове, което значително увеличава обема на тренировъчните данни и подобрява работата с дълги документи и кодове. Като отворен модел, DeepSeek-V3.1 демонстрира способности, сравними с водещи затворени модели в области като кодиране, математика и разсъждение, като същевременно с хибридната си експертна (MoE) архитектура поддържа голям капацитет на модела и ефективно намалява разходите за изчисления."
   },
+  "Pro/deepseek-ai/DeepSeek-V3.1-Terminus": {
+    "description": "DeepSeek-V3.1-Terminus е обновена версия на модела V3.1, пусната от DeepSeek, позиционирана като хибриден интелигентен голям езиков модел. Тази актуализация запазва оригиналните възможности на модела, като се фокусира върху отстраняване на проблеми, посочени от потребителите, и подобряване на стабилността. Значително е подобрена езиковата последователност, намалено е смесването на китайски и английски и появата на аномални символи. Моделът интегрира „режим на мислене“ и „режим без мислене“, като потребителите могат гъвкаво да превключват между тях чрез чат шаблони за различни задачи. Като важна оптимизация, V3.1-Terminus подобрява производителността на кодовия агент и търсещия агент, което ги прави по-надеждни при извикване на инструменти и изпълнение на многократни сложни задачи."
+  },
   "Pro/moonshotai/Kimi-K2-Instruct-0905": {
     "description": "Kimi K2-Instruct-0905 е най-новата и най-мощна версия на Kimi K2. Това е водещ езиков модел с хибридна експертна архитектура (MoE), с общо 1 трилион параметри и 32 милиарда активни параметри. Основните характеристики на модела включват: подобрена интелигентност при кодиране на агенти, с изразително подобрение в производителността при публични бенчмаркове и реални задачи за кодиране на агенти; усъвършенстван опит при фронтенд кодиране, с напредък както в естетиката, така и в практичността на фронтенд програмирането."
   },
@@ -680,6 +689,9 @@
   "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 +785,9 @@
   "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."
   },
@@ -920,6 +935,9 @@
   "deepseek-ai/DeepSeek-V3.1": {
     "description": "DeepSeek-V3.1 е хибриден голям езиков модел, пуснат от DeepSeek AI, който включва множество важни подобрения спрямо предишните версии. Основната иновация на модела е интеграцията на „режим на мислене“ (Thinking Mode) и „режим без мислене“ (Non-thinking Mode), които потребителите могат гъвкаво да превключват чрез настройка на чат шаблони, за да отговарят на различни задачи. След специална пост-тренировка, V3.1 значително подобрява производителността при използване на инструменти и задачи на агенти, като по-добре поддържа външни търсачки и изпълнение на сложни многостъпкови задачи. Моделът е дообучен върху DeepSeek-V3.1-Base чрез двуфазен метод за разширяване на дълги текстове, което значително увеличава обема на тренировъчните данни и подобрява работата с дълги документи и кодове. Като отворен модел, DeepSeek-V3.1 демонстрира способности, сравними с водещи затворени модели в области като кодиране, математика и разсъждение, като същевременно с хибридната си експертна (MoE) архитектура поддържа голям капацитет на модела и ефективно намалява разходите за изчисления."
   },
+  "deepseek-ai/DeepSeek-V3.1-Terminus": {
+    "description": "DeepSeek-V3.1-Terminus е обновена версия на модела V3.1, пусната от DeepSeek, позиционирана като хибриден интелигентен голям езиков модел. Тази актуализация запазва оригиналните възможности на модела, като се фокусира върху отстраняване на проблеми, посочени от потребителите, и подобряване на стабилността. Значително е подобрена езиковата последователност, намалено е смесването на китайски и английски и появата на аномални символи. Моделът интегрира „режим на мислене“ и „режим без мислене“, като потребителите могат гъвкаво да превключват между тях чрез чат шаблони за различни задачи. Като важна оптимизация, V3.1-Terminus подобрява производителността на кодовия агент и търсещия агент, което ги прави по-надеждни при извикване на инструменти и изпълнение на многократни сложни задачи."
+  },
   "deepseek-ai/deepseek-llm-67b-chat": {
     "description": "DeepSeek 67B е напреднал модел, обучен за диалози с висока сложност."
   },
@@ -929,6 +947,9 @@
   "deepseek-ai/deepseek-v3.1": {
     "description": "DeepSeek V3.1: следващо поколение модел за разсъждение, подобряващ способностите за сложни разсъждения и свързано мислене, подходящ за задачи, изискващи задълбочен анализ."
   },
+  "deepseek-ai/deepseek-v3.1-terminus": {
+    "description": "DeepSeek V3.1: следващо поколение модел за разсъждение, с подобрени способности за сложни логически връзки и аналитично мислене, подходящ за задачи, изискващи задълбочен анализ."
+  },
   "deepseek-ai/deepseek-vl2": {
     "description": "DeepSeek-VL2 е визуален езиков модел, разработен на базата на DeepSeekMoE-27B, който използва архитектура на смесени експерти (MoE) с рядка активация, постигайки изключителна производителност с активирани само 4.5B параметри. Моделът показва отлични резултати в множество задачи, включително визуални въпроси и отговори, оптично разпознаване на символи, разбиране на документи/таблици/графики и визуална локализация."
   },
@@ -993,7 +1014,7 @@
     "description": "DeepSeek R1 пълна версия, с 671B параметри, поддържаща търсене в реално време, с по-силни способности за разбиране и генериране."
   },
   "deepseek-reasoner": {
-    "description": "DeepSeek V3.1 режим на мислене. Преди да изведе окончателния отговор, моделът първо генерира мисловна верига, за да повиши точността на крайния отговор."
+    "description": "Режим на мислене на DeepSeek V3.2. Преди да изведе окончателния отговор, моделът първо генерира мисловна верига, за да подобри точността на крайния отговор."
   },
   "deepseek-v2": {
     "description": "DeepSeek V2 е ефективен модел на Mixture-of-Experts, подходящ за икономически ефективни нужди от обработка."
@@ -1013,6 +1034,9 @@
   "deepseek-v3.1:671b": {
     "description": "DeepSeek V3.1: следващо поколение модел за разсъждение, подобряващ способностите за сложни разсъждения и свързано мислене, подходящ за задачи, изискващи задълбочен анализ."
   },
+  "deepseek-v3.2-exp": {
+    "description": "deepseek-v3.2-exp въвежда механизъм за разредено внимание, с цел подобряване на ефективността при обучение и извод при обработка на дълги текстове, като цената е по-ниска от тази на deepseek-v3.1."
+  },
   "deepseek/deepseek-chat-v3-0324": {
     "description": "DeepSeek V3 е експертен смесен модел с 685B параметри, последната итерация на флагманската серия чат модели на екипа DeepSeek.\n\nТой наследява модела [DeepSeek V3](/deepseek/deepseek-chat-v3) и показва отлични резултати в различни задачи."
   },
@@ -1232,6 +1256,9 @@
   "fal-ai/flux/schnell": {
     "description": "FLUX.1 [schnell] е модел за генериране на изображения с 12 милиарда параметри, фокусиран върху бързото създаване на висококачествени изображения."
   },
+  "fal-ai/hunyuan-image/v3": {
+    "description": "Мощен оригинален мултимодален модел за генериране на изображения"
+  },
   "fal-ai/imagen4/preview": {
     "description": "Висококачествен модел за генериране на изображения, предоставен от Google."
   },
@@ -1343,24 +1370,36 @@
   "gemini-2.5-flash": {
     "description": "Gemini 2.5 Flash е най-ефективният модел на Google, предлагащ пълна функционалност."
   },
+  "gemini-2.5-flash-image": {
+    "description": "Nano Banana е най-новият, най-бързият и най-ефективният роден мултимодален модел на Google, който ви позволява да генерирате и редактирате изображения чрез диалог."
+  },
   "gemini-2.5-flash-image-preview": {
     "description": "Nano Banana е най-новият, най-бързият и най-ефективният роден мултимодален модел на Google, който ви позволява да генерирате и редактирате изображения чрез диалог."
   },
   "gemini-2.5-flash-image-preview:image": {
     "description": "Nano Banana е най-новият, най-бързият и най-ефективният роден мултимодален модел на Google, който ви позволява да генерирате и редактирате изображения чрез диалог."
   },
+  "gemini-2.5-flash-image:image": {
+    "description": "Nano Banana е най-новият, най-бързият и най-ефективният роден мултимодален модел на Google, който ви позволява да генерирате и редактирате изображения чрез диалог."
+  },
   "gemini-2.5-flash-lite": {
     "description": "Gemini 2.5 Flash-Lite е най-малкият и най-ефективен модел на Google, създаден специално за масово използване."
   },
   "gemini-2.5-flash-lite-preview-06-17": {
     "description": "Gemini 2.5 Flash-Lite Preview е най-малкият и най-ефективен модел на Google, проектиран за мащабна употреба."
   },
+  "gemini-2.5-flash-lite-preview-09-2025": {
+    "description": "Прегледна версия (25 септември 2025 г.) на Gemini 2.5 Flash-Lite"
+  },
   "gemini-2.5-flash-preview-04-17": {
     "description": "Gemini 2.5 Flash Preview е моделът с най-добро съотношение цена-качество на Google, предлагащ пълна функционалност."
   },
   "gemini-2.5-flash-preview-05-20": {
     "description": "Gemini 2.5 Flash Preview е най-ефективният модел на Google, предлагащ пълна функционалност."
   },
+  "gemini-2.5-flash-preview-09-2025": {
+    "description": "Прегледна версия (25 септември 2025 г.) на Gemini 2.5 Flash"
+  },
   "gemini-2.5-pro": {
     "description": "Gemini 2.5 Pro е най-напредналият мисловен модел на Google, способен да разсъждава върху сложни проблеми в областта на кода, математиката и STEM, както и да анализира големи набори от данни, кодови бази и документи с дълъг контекст."
   },
@@ -1373,6 +1412,15 @@
   "gemini-2.5-pro-preview-06-05": {
     "description": "Gemini 2.5 Pro Preview е най-напредналият мисловен модел на Google, способен да разсъждава върху сложни проблеми в областта на кодирането, математиката и STEM, както и да анализира големи набори от данни, кодови бази и документи с дълъг контекст."
   },
+  "gemini-flash-latest": {
+    "description": "Последно издание на Gemini Flash"
+  },
+  "gemini-flash-lite-latest": {
+    "description": "Последно издание на Gemini Flash-Lite"
+  },
+  "gemini-pro-latest": {
+    "description": "Последно издание на Gemini Pro"
+  },
   "gemma-7b-it": {
     "description": "Gemma 7B е подходяща за обработка на средни и малки задачи, съчетаваща икономичност."
   },
@@ -1437,7 +1485,7 @@
     "description": "Серията модели GLM-4.1V-Thinking е най-мощният визуален модел сред известните VLM модели с размер около 10 милиарда параметри, обединяващ водещи в класа си задачи за визуално-езиково разбиране, включително видео разбиране, въпроси и отговори върху изображения, решаване на предметни задачи, OCR разпознаване на текст, интерпретация на документи и графики, GUI агент, кодиране на уеб страници, Grounding и други. Някои от задачите дори превъзхождат модели с 8 пъти повече параметри като Qwen2.5-VL-72B. Чрез водещи техники за подсилено обучение моделът овладява разсъждения чрез вериги на мисълта, което значително подобрява точността и богатството на отговорите, превъзхождайки традиционните модели без мисловен процес по отношение на крайния резултат и обяснимостта."
   },
   "glm-4.5": {
-    "description": "Най-новият флагмански модел на Zhizhu, поддържащ режим на мислене, с общи способности на ниво SOTA сред отворените модели и контекстова дължина до 128K."
+    "description": "Флагманският модел на Zhipu, поддържа превключване на режим на мислене, с общи възможности, достигащи нивото на SOTA за отворени модели, с контекстова дължина до 128K."
   },
   "glm-4.5-air": {
     "description": "Леката версия на GLM-4.5, балансираща между производителност и цена, с възможност за гъвкаво превключване на смесен мисловен режим."
@@ -1454,6 +1502,9 @@
   "glm-4.5v": {
     "description": "Новото поколение визуален модел за разсъждение на Zhipu, базиран на MOE архитектура, с общо 106B параметри и 12B активни параметри, постига SOTA сред отворените мултимодални модели в своя клас в различни бенчмаркове, обхващайки често срещани задачи като обработка на изображения, видео, разбиране на документи и GUI задачи."
   },
+  "glm-4.6": {
+    "description": "Най-новият флагмански модел на Zhipu GLM-4.6 (355B) превъзхожда предишното поколение във високо ниво на кодиране, обработка на дълги текстове, извод и интелигентни агенти, особено в програмирането, където е съпоставим с Claude Sonnet 4, ставайки водещият модел за кодиране в страната."
+  },
   "glm-4v": {
     "description": "GLM-4V предлага мощни способности за разбиране и разсъждение на изображения, поддържаща множество визуални задачи."
   },
@@ -1481,6 +1532,9 @@
   "glm-zero-preview": {
     "description": "GLM-Zero-Preview притежава мощни способности за сложни разсъждения, показвайки отлични резултати в логическото разсъждение, математиката и програмирането."
   },
+  "glm4.6:355b": {
+    "description": "Най-новият флагмански модел на Zhipu — GLM-4.6 (355B) — значително надминава предшествениците си в напреднало програмиране, обработка на дълги текстове, логическо разсъждение и способности на интелигентни агенти. Особено в програмирането се изравнява с Claude Sonnet 4, превръщайки се в водещ модел за кодиране в Китай."
+  },
   "google/gemini-2.0-flash": {
     "description": "Gemini 2.0 Flash предлага следващо поколение функции и подобрения, включително изключителна скорост, вградена употреба на инструменти, мултимодално генериране и контекстен прозорец от 1 милион токена."
   },
@@ -1682,12 +1736,18 @@
   "gpt-5-nano": {
     "description": "Най-бързата и най-икономична версия на GPT-5. Отлично подходяща за приложения, изискващи бърз отговор и чувствителни към разходите."
   },
+  "gpt-5-pro": {
+    "description": "GPT-5 pro използва повече изчислителна мощност за по-задълбочено мислене и постоянно предоставя по-добри отговори."
+  },
   "gpt-audio": {
     "description": "GPT Audio е универсален чат модел, ориентиран към аудио вход и изход, поддържащ използване на аудио I/O в Chat Completions API."
   },
   "gpt-image-1": {
     "description": "Роден мултимодален модел за генериране на изображения ChatGPT."
   },
+  "gpt-image-1-mini": {
+    "description": "По-икономична версия на GPT Image 1, с вградена поддръжка за вход от текст и изображение и генериране на изходно изображение."
+  },
   "gpt-oss-120b": {
     "description": "GPT-OSS-120B MXFP4 квантизиран трансформър модел, който запазва силна производителност при ограничени ресурси."
   },
@@ -1700,9 +1760,6 @@
   "gpt-realtime": {
     "description": "Универсален модел в реално време, поддържащ текстов и аудио вход и изход, както и вход на изображения."
   },
-  "grok-2-1212": {
-    "description": "Този модел е подобрен по отношение на точност, спазване на инструкции и многоезични способности."
-  },
   "grok-2-image-1212": {
     "description": "Нашият най-нов модел за генериране на изображения може да създава живи и реалистични изображения въз основа на текстови подсказки. Той се представя отлично в маркетинг, социални медии и развлекателни области."
   },
@@ -1712,15 +1769,9 @@
   "grok-3": {
     "description": "Флагмански модел, експертен в извличане на данни, програмиране и обобщаване на текст за корпоративни приложения, с дълбоки знания в областите финанси, медицина, право и наука."
   },
-  "grok-3-fast": {
-    "description": "Флагмански модел, експертен в извличане на данни, програмиране и обобщаване на текст за корпоративни приложения, с дълбоки знания в областите финанси, медицина, право и наука."
-  },
   "grok-3-mini": {
     "description": "Лек модел, който мисли преди разговор. Работи бързо и интелигентно, подходящ за логически задачи без нужда от дълбоки специализирани знания и позволява проследяване на оригиналния мисловен процес."
   },
-  "grok-3-mini-fast": {
-    "description": "Лек модел, който мисли преди разговор. Работи бързо и интелигентно, подходящ за логически задачи без нужда от дълбоки специализирани знания и позволява проследяване на оригиналния мисловен процес."
-  },
   "grok-4": {
     "description": "Нашият най-нов и най-мощен флагмански модел, който се отличава с изключителни резултати в обработката на естествен език, математическите изчисления и разсъжденията — перфектен универсален играч."
   },
@@ -1799,12 +1850,12 @@
   "hunyuan-t1-latest": {
     "description": "Значително подобрява способностите на основния модел за бавно мислене при сложна математика, комплексни разсъждения, труден код, спазване на инструкции и качество на текстовото творчество."
   },
-  "hunyuan-t1-vision": {
-    "description": "Модел за дълбоко мултимодално разбиране Hunyuan, поддържащ естествени мултимодални вериги на мислене, експертен в различни сценарии за разсъждение върху изображения, с цялостно подобрение спрямо бързите мисловни модели при научни задачи."
-  },
   "hunyuan-t1-vision-20250619": {
     "description": "Най-новият мултимодален дълбок мислещ модел t1-vision на Hunyuan, който поддържа оригинални мултимодални вериги на мисълта и предлага цялостно подобрение спрямо предишната версия по подразбиране."
   },
+  "hunyuan-t1-vision-20250916": {
+    "description": "Най-новият модел за визуално дълбоко мислене Hunyuan t1-vision предлага цялостни подобрения спрямо предишната версия в задачи като общи въпроси и отговори по изображения, визуално локализиране, OCR, графики, решаване на задачи по снимка и творческо писане по изображение. Значително е подобрена и поддръжката на английски и по-малко разпространени езици."
+  },
   "hunyuan-turbo": {
     "description": "Предварителна версия на новото поколение голям езиков модел на HunYuan, използваща нова структура на смесен експертен модел (MoE), с по-бърза скорост на извеждане и по-силни резултати в сравнение с hunyuan-pro."
   },
@@ -1826,6 +1877,9 @@
   "hunyuan-turbos-20250604": {
     "description": "Актуализирана предварително обучена основа, подобрени умения за писане и разбиране на текст, значително подобрени способности в кодирането и точните науки, както и непрекъснато усъвършенстване в следването на сложни инструкции."
   },
+  "hunyuan-turbos-20250926": {
+    "description": "Актуализация на качеството на данните за предварително обучение. Оптимизирана стратегия за обучение в посттренировъчния етап, с непрекъснато подобряване на възможностите на агента, английския и малките езици, спазването на инструкции, кода и научните способности."
+  },
   "hunyuan-turbos-latest": {
     "description": "hunyuan-TurboS е последната версия на флагманския модел Hunyuan, с по-силни способности за разсъждение и по-добро потребителско изживяване."
   },
@@ -1916,6 +1970,9 @@
   "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."
   },
@@ -1958,6 +2015,9 @@
   "llama-3.2-vision-instruct": {
     "description": "Моделът Llama 3.2-Vision с инструкции е оптимизиран за визуално разпознаване, изводи от изображения, описание на изображения и отговаряне на общи въпроси, свързани с изображения."
   },
+  "llama-3.3-70b": {
+    "description": "Llama 3.3 70B: средно до голямо Llama решение, съчетаващо логическо разсъждение и висока производителност."
+  },
   "llama-3.3-70b-instruct": {
     "description": "Llama 3.3 е най-напредналият многоезичен отворен езиков модел от серията Llama, който предлага производителност, сравнима с 405B моделите, на изключително ниска цена. Базиран на структурата Transformer и подобрен чрез супервизирано фино настройване (SFT) и обучение с човешка обратна връзка (RLHF) за повишаване на полезността и безопасността. Неговата версия, оптимизирана за инструкции, е специално проектирана за многоезични диалози и показва по-добри резултати от много от отворените и затворените чат модели в множество индустриални бенчмаркове. Краен срок за знания: декември 2023."
   },
@@ -1967,6 +2027,12 @@
   "llama-3.3-instruct": {
     "description": "Моделата Llama 3.3 с фина настройка за инструкции е оптимизирана за диалогови сценарии и надминава много съществуващи модели с отворен код в общи отраслови бенчмарк тестове."
   },
+  "llama-4-maverick-17b-128e-instruct": {
+    "description": "Llama 4 Maverick: високопроизводителен модел от серията Llama, подходящ за напреднало разсъждение, решаване на сложни задачи и следване на инструкции."
+  },
+  "llama-4-scout-17b-16e-instruct": {
+    "description": "Llama 4 Scout: високопроизводителен модел от серията Llama, оптимизиран за сценарии с висока пропускателна способност и ниска латентност."
+  },
   "llama3-70b-8192": {
     "description": "Meta Llama 3 70B предлага ненадмината способност за обработка на сложност, проектирана за високи изисквания."
   },
@@ -1982,6 +2048,9 @@
   "llama3.1": {
     "description": "Llama 3.1 е водещ модел, представен от Meta, поддържащ до 405B параметри, приложим в области като сложни диалози, многоезичен превод и анализ на данни."
   },
+  "llama3.1-8b": {
+    "description": "Llama 3.1 8B: лек и с ниска латентност вариант на Llama, идеален за онлайн разсъждение и интерактивни приложения."
+  },
   "llama3.1:405b": {
     "description": "Llama 3.1 е водещ модел, представен от Meta, поддържащ до 405B параметри, приложим в области като сложни диалози, многоезичен превод и анализ на данни."
   },
@@ -2579,6 +2648,12 @@
   "qvq-plus": {
     "description": "Модел за визуално разсъждение. Поддържа визуален вход и изход на мисловни вериги. Версия plus, пусната след модела qvq-max, предлага по-бързо разсъждение и по-добър баланс между ефективност и разходи в сравнение с qvq-max."
   },
+  "qwen-3-32b": {
+    "description": "Qwen 3 32B: модел от серията Qwen с отлична производителност при многоезични и програмни задачи, подходящ за средномащабна продукционна употреба."
+  },
+  "qwen-3-coder-480b": {
+    "description": "Qwen 3 Coder 480B: модел с дълъг контекст, предназначен за генериране на код и сложни програмни задачи."
+  },
   "qwen-coder-plus": {
     "description": "Tongyi Qianwen модел за кодиране."
   },
@@ -3131,6 +3206,9 @@
   "zai-org/GLM-4.5V": {
     "description": "GLM-4.5V е най-новото поколение визуално-езиков модел (VLM), публикуван от Zhipu AI (智谱 AI). Моделът е изграден върху водещия текстов модел GLM-4.5-Air, който разполага с общо 106 милиарда параметри и 12 милиарда активационни параметри, и използва архитектура с разбъркани експерти (Mixture of Experts, MoE), целяща постигане на висока производителност при по-ниски разходи за инференция. Технически GLM-4.5V продължава линията на GLM-4.1V-Thinking и въвежда иновации като триизмерно ротационно позиционно кодиране (3D-RoPE), което значително засилва възприемането и разсъжденията относно триизмерните пространствени взаимовръзки. Чрез оптимизации в етапите на предварително обучение, супервизирано фино настройване и подсилено обучение, моделът може да обработва различни визуални формати — изображения, видео и дълги документи — и в 41 публични мултимодални бенчмарка достига водещи резултати сред отворените модели от същия клас. Освен това моделът добавя превключвател за 'режим на мислене', който позволява на потребителите гъвкаво да избират между бърз отговор и дълбоко разсъждение, за да балансират ефективността и качеството."
   },
+  "zai-org/GLM-4.6": {
+    "description": "В сравнение с GLM-4.5, GLM-4.6 предлага множество ключови подобрения. Контекстният прозорец е разширен от 128K до 200K токена, което позволява на модела да обработва по-сложни задачи на агенти. Моделът постига по-високи резултати в кодовите бенчмаркове и демонстрира по-силна реална производителност в приложения като Claude Code, Cline, Roo Code и Kilo Code, включително подобрения в генерирането на визуално изискани фронтенд страници. GLM-4.6 показва значително подобрение в производителността на извод и поддържа използването на инструменти по време на извод, което води до по-силни интегрирани възможности. Той е по-добър в използването на инструменти и базирани на търсене агенти и може по-ефективно да се интегрира в агентски рамки. В писането моделът е по-съобразен със стиловите и четивни предпочитания на хората и се представя по-естествено в ролеви игри."
+  },
   "zai/glm-4.5": {
     "description": "Серията модели GLM-4.5 е специално проектирана за агенти. Флагманът GLM-4.5 интегрира 355 милиарда общи параметри (32 милиарда активни), обединявайки разсъждения, кодиране и агентски способности за решаване на сложни приложения. Като хибридна разсъдъчна система, той предлага двойни режими на работа."
   },

locales/bg-BG/providers.json

@@ -32,6 +32,9 @@
   "bfl": {
     "description": "Водеща изследователска лаборатория за авангарден изкуствен интелект, която изгражда визуалната инфраструктура на утрешния ден."
   },
+  "cerebras": {
+    "description": "Cerebras е AI платформа за извеждане, базирана на специализираната си система CS-3, създадена да предоставя най-бързите в света услуги за големи езикови модели (LLM) с незабавен отговор и висок капацитет на обработка. Тя е проектирана да елиминира закъсненията и да ускори сложни AI работни процеси, като генериране на код в реално време и изпълнение на агентски задачи."
+  },
   "cloudflare": {
     "description": "Работа с модели на машинно обучение, задвижвани от безсървърни GPU, в глобалната мрежа на Cloudflare."
   },
@@ -110,6 +113,9 @@
   "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."
   },

locales/bg-BG/tool.json

@@ -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...",

locales/de-DE/chat.json

@@ -3,8 +3,8 @@
     "title": "Modell"
   },
   "agentDefaultMessage": "Hallo, ich bin **{{name}}**. Du kannst sofort mit mir sprechen oder zu den [Assistenteneinstellungen]({{url}}) gehen, um meine Informationen zu vervollständigen.",
-  "agentDefaultMessageWithSystemRole": "Hallo, ich bin **{{name}}**, {{systemRole}}. Lass uns chatten!",
-  "agentDefaultMessageWithoutEdit": "Hallo, ich bin **{{name}}**. Lassen Sie uns ins Gespräch kommen!",
+  "agentDefaultMessageWithSystemRole": "Hallo, ich bin **{{name}}**. Wie kann ich Ihnen behilflich sein?",
+  "agentDefaultMessageWithoutEdit": "Hallo, ich bin **{{name}}**. Wie kann ich Ihnen behilflich sein?",
   "agents": "Assistent",
   "artifact": {
     "generating": "Wird generiert",
@@ -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",

locales/de-DE/common.json

@@ -236,6 +236,7 @@
   },
   "information": "Community und Informationen",
   "installPWA": "Installiere die Browser-App",
+  "labs": "Labore",
   "lang": {
     "ar": "Arabisch",
     "bg-BG": "Bulgarisch",

locales/de-DE/hotkey.json

@@ -7,6 +7,14 @@
     "desc": "Aktuelle Nachrichten und hochgeladene Dateien im Gespräch löschen",
     "title": "Gesprächsnachrichten löschen"
   },
+  "deleteAndRegenerateMessage": {
+    "desc": "Letzte Nachricht löschen und neu generieren",
+    "title": "Löschen und neu generieren"
+  },
+  "deleteLastMessage": {
+    "desc": "Letzte Nachricht löschen",
+    "title": "Letzte Nachricht löschen"
+  },
   "desktop": {
     "openSettings": {
       "desc": "Öffnet die Anwendungseinstellungsseite",

locales/de-DE/image.json

@@ -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"

locales/de-DE/labs.json

@@ -0,0 +1,14 @@
+{
+  "desc": "Hier werden wir regelmäßig neue Funktionen vorstellen, die wir gerade erforschen – probieren Sie sie gerne aus!",
+  "features": {
+    "groupChat": {
+      "desc": "Aktivieren Sie die Koordination von Gruppenchats mit mehreren KI-Agenten.",
+      "title": "Gruppenchats (mehrere Agenten)"
+    },
+    "inputMarkdown": {
+      "desc": "Echtzeit-Rendering von Markdown im Eingabefeld (Fettdruck, Codeblöcke, Tabellen usw.).",
+      "title": "Markdown-Rendering im Eingabefeld"
+    }
+  },
+  "title": "Labor"
+}

locales/de-DE/modelProvider.json

@@ -294,6 +294,21 @@
           "title": "Maximales Kontextfenster",
           "unlimited": "Unbegrenzt"
         },
+        "type": {
+          "extra": "Verschiedene Modelltypen haben unterschiedliche Anwendungsbereiche und Fähigkeiten",
+          "options": {
+            "chat": "Chat",
+            "embedding": "Vektorisierung",
+            "image": "Bildgenerierung",
+            "realtime": "Echtzeit-Chat",
+            "stt": "Spracherkennung",
+            "text2music": "Text zu Musik",
+            "text2video": "Text zu Video",
+            "tts": "Sprachsynthese"
+          },
+          "placeholder": "Bitte Modelltyp auswählen",
+          "title": "Modelltyp"
+        },
         "vision": {
           "extra": "Diese Konfiguration aktiviert nur die Bild-Upload-Funktionalität in der Anwendung. Ob die Erkennung unterstützt wird, hängt vollständig vom Modell selbst ab. Bitte testen Sie die Verwendbarkeit der visuellen Erkennungsfähigkeit des Modells selbst.",
           "title": "Visuelle Erkennung unterstützen"

locales/de-DE/models.json

@@ -92,6 +92,12 @@
   "DeepSeek-V3.1-Think": {
     "description": "DeepSeek-V3.1 - Denkmodus; DeepSeek-V3.1 ist ein neu eingeführtes hybrides Inferenzmodell von DeepSeek, das zwei Inferenzmodi unterstützt: Denk- und Nicht-Denkmodus, mit höherer Denkeffizienz im Vergleich zu DeepSeek-R1-0528. Durch Post-Training-Optimierung wurde die Leistung bei Agenten-Werkzeugnutzung und Agentenaufgaben deutlich verbessert."
   },
+  "DeepSeek-V3.2-Exp": {
+    "description": "DeepSeek V3.2 ist das neueste universelle Großmodell von DeepSeek, das eine hybride Inferenzarchitektur unterstützt und über stärkere Agentenfähigkeiten verfügt."
+  },
+  "DeepSeek-V3.2-Exp-Think": {
+    "description": "DeepSeek V3.2 Denkmodus. Bevor die endgültige Antwort ausgegeben wird, gibt das Modell zunächst eine Gedankenkette aus, um die Genauigkeit der finalen Antwort zu verbessern."
+  },
   "Doubao-lite-128k": {
     "description": "Doubao-lite bietet extrem schnelle Reaktionszeiten und ein hervorragendes Preis-Leistungs-Verhältnis, um Kunden in verschiedenen Szenarien flexiblere Optionen zu bieten. Unterstützt Inferenz und Feintuning mit einem Kontextfenster von 128k."
   },
@@ -287,6 +293,9 @@
   "Pro/deepseek-ai/DeepSeek-V3.1": {
     "description": "DeepSeek-V3.1 ist ein hybrides großes Sprachmodell, das von DeepSeek AI veröffentlicht wurde und auf dem Vorgängermodell in vielerlei Hinsicht bedeutende Verbesserungen aufweist. Eine wesentliche Innovation dieses Modells ist die Integration des „Denkmodus“ und des „Nicht-Denkmodus“ in einem System, wobei Nutzer durch Anpassung der Chat-Vorlagen flexibel zwischen den Modi wechseln können, um unterschiedlichen Aufgabenanforderungen gerecht zu werden. Durch spezielles Post-Training wurde die Leistung von V3.1 bei Tool-Aufrufen und Agentenaufgaben deutlich gesteigert, was eine bessere Unterstützung externer Suchwerkzeuge und die Ausführung komplexer mehrstufiger Aufgaben ermöglicht. Das Modell basiert auf DeepSeek-V3.1-Base und wurde durch eine zweistufige Langtext-Erweiterungsmethode nachtrainiert, wodurch das Trainingsdatenvolumen erheblich erhöht wurde und es sich besonders bei der Verarbeitung langer Dokumente und umfangreicher Codes bewährt. Als Open-Source-Modell zeigt DeepSeek-V3.1 in Benchmarks zu Codierung, Mathematik und logischem Denken Fähigkeiten, die mit führenden Closed-Source-Modellen vergleichbar sind. Gleichzeitig senkt seine hybride Expertenarchitektur (MoE) die Inferenzkosten bei gleichzeitiger Beibehaltung einer enormen Modellkapazität."
   },
+  "Pro/deepseek-ai/DeepSeek-V3.1-Terminus": {
+    "description": "DeepSeek-V3.1-Terminus ist eine aktualisierte Version des V3.1-Modells von DeepSeek, positioniert als hybrides Agenten-Großsprachmodell. Dieses Update konzentriert sich darauf, auf Nutzerfeedback basierende Probleme zu beheben und die Stabilität zu verbessern, während die ursprünglichen Modellfähigkeiten erhalten bleiben. Es verbessert deutlich die Sprachkonsistenz und reduziert das Vermischen von Chinesisch und Englisch sowie das Auftreten ungewöhnlicher Zeichen. Das Modell integriert den „Denkmodus“ (Thinking Mode) und den „Nicht-Denkmodus“ (Non-thinking Mode), zwischen denen Nutzer flexibel über Chatvorlagen wechseln können, um unterschiedlichen Aufgaben gerecht zu werden. Als wichtige Optimierung verbessert V3.1-Terminus die Leistung des Code-Agenten und des Such-Agenten, wodurch diese bei Werkzeugaufrufen und der Ausführung mehrstufiger komplexer Aufgaben zuverlässiger sind."
+  },
   "Pro/moonshotai/Kimi-K2-Instruct-0905": {
     "description": "Kimi K2-Instruct-0905 ist die neueste und leistungsstärkste Version von Kimi K2. Es handelt sich um ein erstklassiges Mixture-of-Experts (MoE) Sprachmodell mit insgesamt 1 Billion Parametern und 32 Milliarden aktivierten Parametern. Die Hauptmerkmale dieses Modells umfassen: verbesserte Agenten-Codierungsintelligenz, die in öffentlichen Benchmark-Tests und realen Agenten-Codierungsaufgaben eine signifikante Leistungssteigerung zeigt; verbesserte Frontend-Codierungserfahrung mit Fortschritten in Ästhetik und Praktikabilität der Frontend-Programmierung."
   },
@@ -680,6 +689,9 @@
   "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 +785,9 @@
   "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."
   },
@@ -920,6 +935,9 @@
   "deepseek-ai/DeepSeek-V3.1": {
     "description": "DeepSeek-V3.1 ist ein hybrides großes Sprachmodell, das von DeepSeek AI veröffentlicht wurde und auf dem Vorgängermodell in vielerlei Hinsicht bedeutende Verbesserungen aufweist. Eine wesentliche Innovation dieses Modells ist die Integration des „Denkmodus“ und des „Nicht-Denkmodus“ in einem System, wobei Nutzer durch Anpassung der Chat-Vorlagen flexibel zwischen den Modi wechseln können, um unterschiedlichen Aufgabenanforderungen gerecht zu werden. Durch spezielles Post-Training wurde die Leistung von V3.1 bei Tool-Aufrufen und Agentenaufgaben deutlich gesteigert, was eine bessere Unterstützung externer Suchwerkzeuge und die Ausführung komplexer mehrstufiger Aufgaben ermöglicht. Das Modell basiert auf DeepSeek-V3.1-Base und wurde durch eine zweistufige Langtext-Erweiterungsmethode nachtrainiert, wodurch das Trainingsdatenvolumen erheblich erhöht wurde und es sich besonders bei der Verarbeitung langer Dokumente und umfangreicher Codes bewährt. Als Open-Source-Modell zeigt DeepSeek-V3.1 in Benchmarks zu Codierung, Mathematik und logischem Denken Fähigkeiten, die mit führenden Closed-Source-Modellen vergleichbar sind. Gleichzeitig senkt seine hybride Expertenarchitektur (MoE) die Inferenzkosten bei gleichzeitiger Beibehaltung einer enormen Modellkapazität."
   },
+  "deepseek-ai/DeepSeek-V3.1-Terminus": {
+    "description": "DeepSeek-V3.1-Terminus ist eine aktualisierte Version des V3.1-Modells von DeepSeek, positioniert als hybrides Agenten-Großsprachmodell. Dieses Update konzentriert sich darauf, auf Nutzerfeedback basierende Probleme zu beheben und die Stabilität zu verbessern, während die ursprünglichen Modellfähigkeiten erhalten bleiben. Es verbessert deutlich die Sprachkonsistenz und reduziert das Vermischen von Chinesisch und Englisch sowie das Auftreten ungewöhnlicher Zeichen. Das Modell integriert den „Denkmodus“ (Thinking Mode) und den „Nicht-Denkmodus“ (Non-thinking Mode), zwischen denen Nutzer flexibel über Chatvorlagen wechseln können, um unterschiedlichen Aufgaben gerecht zu werden. Als wichtige Optimierung verbessert V3.1-Terminus die Leistung des Code-Agenten und des Such-Agenten, wodurch diese bei Werkzeugaufrufen und der Ausführung mehrstufiger komplexer Aufgaben zuverlässiger sind."
+  },
   "deepseek-ai/deepseek-llm-67b-chat": {
     "description": "DeepSeek 67B ist ein fortschrittliches Modell, das für komplexe Dialoge trainiert wurde."
   },
@@ -929,6 +947,9 @@
   "deepseek-ai/deepseek-v3.1": {
     "description": "DeepSeek V3.1: Ein Inferenzmodell der nächsten Generation, das komplexe Schlussfolgerungen und verknüpfte Denkfähigkeiten verbessert und sich für Aufgaben eignet, die tiefgehende Analysen erfordern."
   },
+  "deepseek-ai/deepseek-v3.1-terminus": {
+    "description": "DeepSeek V3.1: Das nächste Generation von Inferenzmodellen mit verbesserter Fähigkeit zum komplexen Schlussfolgern und vernetztem Denken – ideal für Aufgaben, die tiefgehende Analysen erfordern."
+  },
   "deepseek-ai/deepseek-vl2": {
     "description": "DeepSeek-VL2 ist ein hybrides Expertenmodell (MoE) für visuelle Sprache, das auf DeepSeekMoE-27B basiert und eine spärliche Aktivierung der MoE-Architektur verwendet, um außergewöhnliche Leistungen bei der Aktivierung von nur 4,5 Milliarden Parametern zu erzielen. Dieses Modell zeigt hervorragende Leistungen in mehreren Aufgaben, darunter visuelle Fragenbeantwortung, optische Zeichenerkennung, Dokument-/Tabellen-/Diagrammverständnis und visuelle Lokalisierung."
   },
@@ -993,7 +1014,7 @@
     "description": "DeepSeek R1 Vollversion mit 671B Parametern, die Echtzeit-Online-Suche unterstützt und über verbesserte Verständnis- und Generierungsfähigkeiten verfügt."
   },
   "deepseek-reasoner": {
-    "description": "DeepSeek V3.1 Denkmodus. Bevor die endgültige Antwort ausgegeben wird, generiert das Modell eine Kette von Überlegungen, um die Genauigkeit der finalen Antwort zu verbessern."
+    "description": "DeepSeek V3.2 Denkmodus. Bevor die endgültige Antwort ausgegeben wird, gibt das Modell zunächst eine Gedankenkette aus, um die Genauigkeit der finalen Antwort zu verbessern."
   },
   "deepseek-v2": {
     "description": "DeepSeek V2 ist ein effizientes Mixture-of-Experts-Sprachmodell, das für wirtschaftliche Verarbeitungsanforderungen geeignet ist."
@@ -1013,6 +1034,9 @@
   "deepseek-v3.1:671b": {
     "description": "DeepSeek V3.1: Ein Inferenzmodell der nächsten Generation, das komplexe Schlussfolgerungen und verknüpfte Denkfähigkeiten verbessert und sich für Aufgaben eignet, die tiefgehende Analysen erfordern."
   },
+  "deepseek-v3.2-exp": {
+    "description": "deepseek-v3.2-exp führt einen sparsamen Aufmerksamkeitsmechanismus ein, um die Effizienz beim Training und der Inferenz bei der Verarbeitung langer Texte zu verbessern. Der Preis liegt unter dem von deepseek-v3.1."
+  },
   "deepseek/deepseek-chat-v3-0324": {
     "description": "DeepSeek V3 ist ein Experten-Mischmodell mit 685B Parametern und die neueste Iteration der Flaggschiff-Chatmodellreihe des DeepSeek-Teams.\n\nEs erbt das [DeepSeek V3](/deepseek/deepseek-chat-v3) Modell und zeigt hervorragende Leistungen in verschiedenen Aufgaben."
   },
@@ -1232,6 +1256,9 @@
   "fal-ai/flux/schnell": {
     "description": "FLUX.1 [schnell] ist ein bildgenerierendes Modell mit 12 Milliarden Parametern, das sich auf die schnelle Erzeugung hochwertiger Bilder konzentriert."
   },
+  "fal-ai/hunyuan-image/v3": {
+    "description": "Ein leistungsstarkes natives multimodales Bildgenerierungsmodell"
+  },
   "fal-ai/imagen4/preview": {
     "description": "Hochwertiges Bildgenerierungsmodell von Google."
   },
@@ -1343,24 +1370,36 @@
   "gemini-2.5-flash": {
     "description": "Gemini 2.5 Flash ist Googles kosteneffizientestes Modell und bietet umfassende Funktionen."
   },
+  "gemini-2.5-flash-image": {
+    "description": "Nano Banana ist Googles neuestes, schnellstes und effizientestes natives multimodales Modell, das es Ihnen ermöglicht, Bilder durch Dialog zu generieren und zu bearbeiten."
+  },
   "gemini-2.5-flash-image-preview": {
     "description": "Nano Banana ist Googles neuestes, schnellstes und effizientestes natives multimodales Modell, das es Ihnen ermöglicht, Bilder durch Dialog zu generieren und zu bearbeiten."
   },
   "gemini-2.5-flash-image-preview:image": {
     "description": "Nano Banana ist Googles neuestes, schnellstes und effizientestes natives multimodales Modell, das es Ihnen ermöglicht, Bilder durch Dialog zu generieren und zu bearbeiten."
   },
+  "gemini-2.5-flash-image:image": {
+    "description": "Nano Banana ist Googles neuestes, schnellstes und effizientestes natives multimodales Modell, das es Ihnen ermöglicht, Bilder durch Dialog zu generieren und zu bearbeiten."
+  },
   "gemini-2.5-flash-lite": {
     "description": "Gemini 2.5 Flash-Lite ist Googles kleinstes und kosteneffizientestes Modell, das speziell für den großflächigen Einsatz entwickelt wurde."
   },
   "gemini-2.5-flash-lite-preview-06-17": {
     "description": "Gemini 2.5 Flash-Lite Preview ist Googles kleinstes und kosteneffizientestes Modell, speziell für den großflächigen Einsatz konzipiert."
   },
+  "gemini-2.5-flash-lite-preview-09-2025": {
+    "description": "Vorschauversion (25. September 2025) von Gemini 2.5 Flash-Lite"
+  },
   "gemini-2.5-flash-preview-04-17": {
     "description": "Gemini 2.5 Flash Preview ist das kosteneffizienteste Modell von Google und bietet umfassende Funktionen."
   },
   "gemini-2.5-flash-preview-05-20": {
     "description": "Gemini 2.5 Flash Preview ist Googles kosteneffizientestes Modell mit umfassenden Funktionen."
   },
+  "gemini-2.5-flash-preview-09-2025": {
+    "description": "Vorschauversion (25. September 2025) von Gemini 2.5 Flash"
+  },
   "gemini-2.5-pro": {
     "description": "Gemini 2.5 Pro ist Googles fortschrittlichstes Denkmodell, das komplexe Probleme in den Bereichen Code, Mathematik und MINT-Fächer lösen kann und große Datensätze, Codebasen und Dokumente mit langem Kontext analysiert."
   },
@@ -1373,6 +1412,15 @@
   "gemini-2.5-pro-preview-06-05": {
     "description": "Gemini 2.5 Pro Preview ist Googles fortschrittlichstes Denkmodell, das komplexe Probleme in den Bereichen Code, Mathematik und MINT-Fächer lösen kann und große Datensätze, Codebasen und Dokumente mit langem Kontext analysiert."
   },
+  "gemini-flash-latest": {
+    "description": "Neueste Version von Gemini Flash"
+  },
+  "gemini-flash-lite-latest": {
+    "description": "Neueste Version von Gemini Flash-Lite"
+  },
+  "gemini-pro-latest": {
+    "description": "Neueste Version von Gemini Pro"
+  },
   "gemma-7b-it": {
     "description": "Gemma 7B eignet sich für die Verarbeitung von mittelgroßen Aufgaben und bietet ein gutes Kosten-Nutzen-Verhältnis."
   },
@@ -1437,7 +1485,7 @@
     "description": "Die GLM-4.1V-Thinking-Serie ist das leistungsstärkste visuelle Modell unter den bekannten 10-Milliarden-Parameter-VLMs und integriert SOTA-Leistungen auf diesem Niveau in verschiedenen visuellen Sprachaufgaben, darunter Videoverstehen, Bildfragen, Fachaufgaben, OCR-Texterkennung, Dokumenten- und Diagramminterpretation, GUI-Agenten, Frontend-Web-Coding und Grounding. In vielen Aufgaben übertrifft es sogar das Qwen2.5-VL-72B mit achtmal so vielen Parametern. Durch fortschrittliche Verstärkungslernverfahren beherrscht das Modell die Chain-of-Thought-Schlussfolgerung, was die Genauigkeit und Detailtiefe der Antworten deutlich verbessert und in Bezug auf Endergebnis und Erklärbarkeit traditionelle Nicht-Thinking-Modelle übertrifft."
   },
   "glm-4.5": {
-    "description": "Das neueste Flaggschiff-Modell von Zhipu, unterstützt den Denkmoduswechsel und erreicht eine umfassende Leistungsfähigkeit auf SOTA-Niveau für Open-Source-Modelle mit einer Kontextlänge von bis zu 128K."
+    "description": "Das Flaggschiff-Modell von Zhipu unterstützt den Wechsel zwischen Denkmodi und erreicht eine umfassende Leistungsfähigkeit auf dem Niveau der besten Open-Source-Modelle. Die Kontextlänge beträgt bis zu 128K."
   },
   "glm-4.5-air": {
     "description": "Die leichtgewichtige Version von GLM-4.5, die Leistung und Kosten-Nutzen-Verhältnis ausbalanciert und flexibel zwischen hybriden Denkmodellen wechseln kann."
@@ -1454,6 +1502,9 @@
   "glm-4.5v": {
     "description": "Das neue visuelle Inferenzmodell der nächsten Generation von Zhipu, basierend auf der MOE-Architektur, verfügt über 106B Gesamtparameter und 12B aktivierte Parameter und erzielt in verschiedenen Benchmarks State-of-the-Art‑Ergebnisse (SOTA) unter weltweit vergleichbaren Open‑Source‑multimodalen Modellen. Es deckt gängige Aufgaben wie Bild-, Video- und Dokumentenverständnis sowie GUI‑Aufgaben ab."
   },
+  "glm-4.6": {
+    "description": "Das neueste Flaggschiff-Modell von Zhipu, GLM-4.6 (355B), übertrifft die Vorgängergeneration in fortgeschrittener Codierung, Langtextverarbeitung, Inferenz und Agentenfähigkeiten umfassend. Besonders in der Programmierfähigkeit ist es mit Claude Sonnet 4 vergleichbar und gilt als eines der besten Coding-Modelle im Inland."
+  },
   "glm-4v": {
     "description": "GLM-4V bietet starke Fähigkeiten zur Bildverständnis und -schlussfolgerung und unterstützt eine Vielzahl visueller Aufgaben."
   },
@@ -1481,6 +1532,9 @@
   "glm-zero-preview": {
     "description": "GLM-Zero-Preview verfügt über starke Fähigkeiten zur komplexen Schlussfolgerung und zeigt hervorragende Leistungen in den Bereichen logisches Denken, Mathematik und Programmierung."
   },
+  "glm4.6:355b": {
+    "description": "Das neueste Flaggschiffmodell GLM-4.6 (355B) von Zhipu übertrifft seinen Vorgänger in den Bereichen fortgeschrittenes Codieren, Verarbeitung langer Texte, logisches Schlussfolgern und Agentenfähigkeiten deutlich. Besonders im Bereich Programmierung erreicht es das Niveau von Claude Sonnet 4 und zählt damit zu den führenden Coding-Modellen in China."
+  },
   "google/gemini-2.0-flash": {
     "description": "Gemini 2.0 Flash bietet Funktionen der nächsten Generation und Verbesserungen, darunter herausragende Geschwindigkeit, integrierte Werkzeugnutzung, multimodale Generierung und ein Kontextfenster von 1 Million Tokens."
   },
@@ -1682,12 +1736,18 @@
   "gpt-5-nano": {
     "description": "Die schnellste und kostengünstigste Version von GPT-5. Besonders geeignet für Anwendungen, die schnelle Reaktionen und Kostenbewusstsein erfordern."
   },
+  "gpt-5-pro": {
+    "description": "GPT-5 Pro nutzt mehr Rechenleistung für tiefgreifendere Überlegungen und liefert kontinuierlich bessere Antworten."
+  },
   "gpt-audio": {
     "description": "GPT Audio ist ein universelles Chatmodell für Audioeingabe und -ausgabe, das Audio-I/O in der Chat Completions API unterstützt."
   },
   "gpt-image-1": {
     "description": "ChatGPT natives multimodales Bildgenerierungsmodell"
   },
+  "gpt-image-1-mini": {
+    "description": "Kostengünstigere Version von GPT Image 1 mit nativer Unterstützung für Text- und Bildeingaben sowie Bildausgaben."
+  },
   "gpt-oss-120b": {
     "description": "GPT-OSS-120B MXFP4 quantisierte Transformer-Struktur, die auch bei begrenzten Ressourcen starke Leistung beibehält."
   },
@@ -1700,9 +1760,6 @@
   "gpt-realtime": {
     "description": "Universelles Echtzeitmodell, das Echtzeit-Text- und Audioeingabe/-ausgabe unterstützt und zudem Bildinput ermöglicht."
   },
-  "grok-2-1212": {
-    "description": "Dieses Modell hat Verbesserungen in Bezug auf Genauigkeit, Befolgung von Anweisungen und Mehrsprachigkeit erfahren."
-  },
   "grok-2-image-1212": {
     "description": "Unser neuestes Bildgenerierungsmodell kann lebendige und realistische Bilder basierend auf Text-Prompts erzeugen. Es zeigt hervorragende Leistungen in den Bereichen Marketing, soziale Medien und Unterhaltung."
   },
@@ -1712,15 +1769,9 @@
   "grok-3": {
     "description": "Ein Flaggschiffmodell, spezialisiert auf Datenextraktion, Programmierung und Textzusammenfassung für Unternehmensanwendungen, mit tiefgreifendem Wissen in den Bereichen Finanzen, Medizin, Recht und Wissenschaft."
   },
-  "grok-3-fast": {
-    "description": "Ein Flaggschiffmodell, spezialisiert auf Datenextraktion, Programmierung und Textzusammenfassung für Unternehmensanwendungen, mit tiefgreifendem Wissen in den Bereichen Finanzen, Medizin, Recht und Wissenschaft."
-  },
   "grok-3-mini": {
     "description": "Ein leichtgewichtiges Modell, das vor der Antwort nachdenkt. Es arbeitet schnell und intelligent, eignet sich für logische Aufgaben ohne tiefgehendes Fachwissen und ermöglicht die Nachverfolgung des ursprünglichen Denkprozesses."
   },
-  "grok-3-mini-fast": {
-    "description": "Ein leichtgewichtiges Modell, das vor der Antwort nachdenkt. Es arbeitet schnell und intelligent, eignet sich für logische Aufgaben ohne tiefgehendes Fachwissen und ermöglicht die Nachverfolgung des ursprünglichen Denkprozesses."
-  },
   "grok-4": {
     "description": "Unser neuestes und leistungsstärkstes Flaggschiffmodell, das in der Verarbeitung natürlicher Sprache, mathematischen Berechnungen und logischem Denken herausragende Leistungen erbringt – ein perfekter Allrounder."
   },
@@ -1799,12 +1850,12 @@
   "hunyuan-t1-latest": {
     "description": "Erhebliche Verbesserung der Fähigkeiten des Hauptmodells im langsamen Denkmodus bei anspruchsvoller Mathematik, komplexen Schlussfolgerungen, anspruchsvollem Code, Befolgung von Anweisungen und Textkreation."
   },
-  "hunyuan-t1-vision": {
-    "description": "Hunyuan ist ein multimodales Verständnis- und Tiefdenkmodell, das native multimodale lange Denkprozesse unterstützt. Es ist spezialisiert auf verschiedene Bildinferenzszenarien und zeigt im Vergleich zu Schnelldenkmodellen umfassende Verbesserungen bei naturwissenschaftlichen Problemen."
-  },
   "hunyuan-t1-vision-20250619": {
     "description": "Die neueste Version des hunyuan t1-vision multimodalen tiefen Denkmodells unterstützt native multimodale Chain-of-Thought-Mechanismen und bietet im Vergleich zur vorherigen Standardversion umfassende Verbesserungen."
   },
+  "hunyuan-t1-vision-20250916": {
+    "description": "Die neueste Version des Hunyuan t1-vision Modells für visuelles, tiefes Denken bietet im Vergleich zur Vorgängerversion umfassende Verbesserungen bei allgemeinen Bild-Text-Fragen, visueller Lokalisierung, OCR, Diagrammverarbeitung, Aufgabenlösung per Foto und kreativer Bildinterpretation. Die Fähigkeiten in Englisch und kleineren Sprachen wurden deutlich optimiert."
+  },
   "hunyuan-turbo": {
     "description": "Die Vorschauversion des neuen großen Sprachmodells von Hunyuan verwendet eine neuartige hybride Expertenmodellstruktur (MoE) und bietet im Vergleich zu Hunyuan-Pro eine schnellere Inferenz und bessere Leistung."
   },
@@ -1826,6 +1877,9 @@
   "hunyuan-turbos-20250604": {
     "description": "Upgrade der vortrainierten Basis, verbessert Schreib- und Leseverständnisfähigkeiten, steigert deutlich die Programmier- und naturwissenschaftlichen Kompetenzen und verbessert kontinuierlich die Befolgung komplexer Anweisungen."
   },
+  "hunyuan-turbos-20250926": {
+    "description": "Qualitätsverbesserung der Pretraining-Basisdaten. Optimierung der Trainingsstrategie in der Posttrain-Phase, kontinuierliche Verbesserung der Agenten-, Englisch- und kleinen Sprachfähigkeiten, Befolgung von Anweisungen, Code- und naturwissenschaftlichen Fähigkeiten."
+  },
   "hunyuan-turbos-latest": {
     "description": "hunyuan-TurboS ist die neueste Version des Hunyuan-Flaggschiffmodells, das über verbesserte Denkfähigkeiten und ein besseres Nutzungserlebnis verfügt."
   },
@@ -1916,6 +1970,9 @@
   "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."
   },
@@ -1958,6 +2015,9 @@
   "llama-3.2-vision-instruct": {
     "description": "Das Llama 3.2-Vision-Instruct-Modell ist optimiert für visuelle Erkennung, Bildschlussfolgerungen, Bildbeschreibungen und das Beantworten von allgemeinen Fragen, die mit Bildern zusammenhängen."
   },
+  "llama-3.3-70b": {
+    "description": "Llama 3.3 70B: Ein mittelgroßes Llama-Modell, das eine ausgewogene Kombination aus logischem Denken und hoher Verarbeitungskapazität bietet."
+  },
   "llama-3.3-70b-instruct": {
     "description": "Llama 3.3 ist das fortschrittlichste mehrsprachige Open-Source-Sprachmodell der Llama-Serie, das eine Leistung bietet, die mit einem 405B-Modell vergleichbar ist, und das zu extrem niedrigen Kosten. Es basiert auf der Transformer-Architektur und verbessert die Nützlichkeit und Sicherheit durch überwachte Feinabstimmung (SFT) und verstärkendes Lernen mit menschlichem Feedback (RLHF). Die auf Anweisungen optimierte Version ist speziell für mehrsprachige Dialoge optimiert und übertrifft in mehreren Branchenbenchmarks viele Open-Source- und geschlossene Chat-Modelle. Das Wissensdatum endet im Dezember 2023."
   },
@@ -1967,6 +2027,12 @@
   "llama-3.3-instruct": {
     "description": "Das Llama 3.3 Instruct-Modell ist für Dialogszenarien optimiert und übertrifft in gängigen Branchenbenchmarks viele bestehende Open-Source-Chatmodelle."
   },
+  "llama-4-maverick-17b-128e-instruct": {
+    "description": "Llama 4 Maverick: Ein leistungsstarkes Modell der Llama-Serie, ideal für fortgeschrittenes logisches Denken, komplexe Problemlösungen und Aufgaben mit Anweisungsbefolgung."
+  },
+  "llama-4-scout-17b-16e-instruct": {
+    "description": "Llama 4 Scout: Ein leistungsstarkes Modell der Llama-Serie, optimiert für Szenarien mit hoher Verarbeitungsgeschwindigkeit und niedriger Latenz."
+  },
   "llama3-70b-8192": {
     "description": "Meta Llama 3 70B bietet unvergleichliche Fähigkeiten zur Verarbeitung von Komplexität und ist maßgeschneidert für Projekte mit hohen Anforderungen."
   },
@@ -1982,6 +2048,9 @@
   "llama3.1": {
     "description": "Llama 3.1 ist ein führendes Modell von Meta, das bis zu 405B Parameter unterstützt und in den Bereichen komplexe Dialoge, mehrsprachige Übersetzungen und Datenanalysen eingesetzt werden kann."
   },
+  "llama3.1-8b": {
+    "description": "Llama 3.1 8B: Eine kompakte, latenzarme Variante des Llama-Modells, ideal für leichte Online-Inferenz- und Interaktionsszenarien."
+  },
   "llama3.1:405b": {
     "description": "Llama 3.1 ist ein führendes Modell von Meta, das bis zu 405B Parameter unterstützt und in den Bereichen komplexe Dialoge, mehrsprachige Übersetzungen und Datenanalysen eingesetzt werden kann."
   },
@@ -2579,6 +2648,12 @@
   "qvq-plus": {
     "description": "Visuelles Schlussfolgerungsmodell. Unterstützt visuelle Eingaben und Denkprozess-Ausgaben. Die Plus-Version, die auf dem qvq-max-Modell basiert, bietet schnellere Inferenzgeschwindigkeit sowie ein ausgewogeneres Verhältnis von Leistung und Kosten."
   },
+  "qwen-3-32b": {
+    "description": "Qwen 3 32B: Ein Modell der Qwen-Serie mit starker Leistung bei mehrsprachigen und Programmieraufgaben, geeignet für mittelgroße produktive Einsätze."
+  },
+  "qwen-3-coder-480b": {
+    "description": "Qwen 3 Coder 480B: Ein Modell mit langem Kontext, das für Codegenerierung und komplexe Programmieraufgaben entwickelt wurde."
+  },
   "qwen-coder-plus": {
     "description": "Tongyi Qianwen Codierungsmodell."
   },
@@ -3131,6 +3206,9 @@
   "zai-org/GLM-4.5V": {
     "description": "GLM-4.5V ist das neueste visuell-sprachliche Modell (VLM), das von Zhipu AI veröffentlicht wurde. Das Modell basiert auf dem Flaggschiff-Textmodell GLM-4.5-Air mit insgesamt 106 Milliarden Parametern und 12 Milliarden Aktivierungsparametern und verwendet eine Mixture-of-Experts-(MoE)-Architektur. Es zielt darauf ab, bei geringeren Inferenzkosten herausragende Leistung zu erzielen. Technisch setzt es die Entwicklungslinie von GLM-4.1V-Thinking fort und führt Innovationen wie die dreidimensionale Rotations-Positionskodierung (3D-RoPE) ein, wodurch die Wahrnehmung und das Schließen über dreidimensionale Raumbeziehungen deutlich verbessert werden. Durch Optimierungen in den Phasen des Pre-Trainings, der überwachten Feinabstimmung und des Reinforcement Learnings ist das Modell in der Lage, verschiedene visuelle Inhalte wie Bilder, Videos und lange Dokumente zu verarbeiten; in 41 öffentlichen multimodalen Benchmarks erreichte es Spitzenwerte unter frei verfügbaren Modellen derselben Klasse. Zudem wurde ein \"Denkmodus\"-Schalter hinzugefügt, der es Nutzern erlaubt, flexibel zwischen schneller Reaktion und tiefgehendem Schlussfolgern zu wählen, um Effizienz und Ergebnisqualität auszubalancieren."
   },
+  "zai-org/GLM-4.6": {
+    "description": "Im Vergleich zu GLM-4.5 bringt GLM-4.6 mehrere wichtige Verbesserungen. Das Kontextfenster wurde von 128K auf 200K Tokens erweitert, wodurch das Modell komplexere Agentenaufgaben bewältigen kann. Das Modell erzielte höhere Werte in Code-Benchmark-Tests und zeigte in Anwendungen wie Claude Code, Cline, Roo Code und Kilo Code eine stärkere Leistung in realen Szenarien, einschließlich verbesserter Generierung visuell ansprechender Frontend-Seiten. GLM-4.6 zeigt eine deutliche Steigerung der Inferenzleistung und unterstützt die Nutzung von Werkzeugen während der Inferenz, was zu einer stärkeren Gesamtkapazität führt. Es zeigt bessere Leistungen bei der Werkzeugnutzung und suchbasierten Agenten und lässt sich effektiver in Agentenframeworks integrieren. Im Bereich des Schreibens entspricht das Modell stilistisch und in der Lesbarkeit stärker menschlichen Präferenzen und verhält sich in Rollenspielszenarien natürlicher."
+  },
   "zai/glm-4.5": {
     "description": "Die GLM-4.5 Modellreihe sind speziell für Agenten entwickelte Basismodelle. Das Flaggschiff GLM-4.5 integriert 355 Milliarden Gesamtparameter (32 Milliarden aktiv) und vereint Inferenz-, Codierungs- und Agentenfähigkeiten zur Lösung komplexer Anwendungsanforderungen. Als hybrides Inferenzsystem bietet es zwei Betriebsmodi."
   },

locales/de-DE/providers.json

@@ -32,6 +32,9 @@
   "bfl": {
     "description": "Ein führendes, an vorderster Front tätiges KI-Forschungslabor, das die visuelle Infrastruktur von morgen gestaltet."
   },
+  "cerebras": {
+    "description": "Cerebras ist eine KI-Inferenzplattform, die auf dem spezialisierten CS-3-System basiert. Sie wurde entwickelt, um weltweit die schnellsten, in Echtzeit reagierenden und hochdurchsatzfähigen LLM-Dienste bereitzustellen. Ziel ist es, Latenzen zu eliminieren und komplexe KI-Workflows wie die Echtzeit-Codegenerierung und Agentenaufgaben zu beschleunigen."
+  },
   "cloudflare": {
     "description": "Führen Sie von serverlosen GPUs betriebene Machine-Learning-Modelle im globalen Netzwerk von Cloudflare aus."
   },
@@ -110,6 +113,9 @@
   "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."
   },

locales/de-DE/tool.json

@@ -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...",

locales/en-US/chat.json

@@ -3,8 +3,8 @@
     "title": "Model"
   },
   "agentDefaultMessage": "Hello, I am **{{name}}**. You can start a conversation with me right away, or you can go to [Assistant Settings]({{url}}) to complete my information.",
-  "agentDefaultMessageWithSystemRole": "Hello, I'm **{{name}}**, {{systemRole}}. Let's start chatting!",
-  "agentDefaultMessageWithoutEdit": "Hello, I'm **{{name}}**, let's start chatting!",
+  "agentDefaultMessageWithSystemRole": "Hello, I am **{{name}}**. How can I assist you today?",
+  "agentDefaultMessageWithoutEdit": "Hello, I am **{{name}}**. How can I assist you today?",
   "agents": "Assistants",
   "artifact": {
     "generating": "Generating",
@@ -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",

locales/en-US/common.json

@@ -236,6 +236,7 @@
   },
   "information": "Community and News",
   "installPWA": "Install browser app",
+  "labs": "Labs",
   "lang": {
     "ar": "Arabic",
     "bg-BG": "Bulgarian",

locales/en-US/hotkey.json

@@ -7,6 +7,14 @@
     "desc": "Clear the messages and uploaded files from the current conversation",
     "title": "Clear Conversation Messages"
   },
+  "deleteAndRegenerateMessage": {
+    "desc": "Delete the last message and regenerate",
+    "title": "Delete and Regenerate"
+  },
+  "deleteLastMessage": {
+    "desc": "Delete the last message",
+    "title": "Delete Last Message"
+  },
   "desktop": {
     "openSettings": {
       "desc": "Open the application settings page",

locales/en-US/image.json

@@ -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"

locales/en-US/labs.json

@@ -0,0 +1,14 @@
+{
+  "desc": "Here you'll find occasional updates on new features we're exploring—feel free to try them out!",
+  "features": {
+    "groupChat": {
+      "desc": "Enable multi-agent group chat coordination.",
+      "title": "Group Chat (Multi-Agent)"
+    },
+    "inputMarkdown": {
+      "desc": "Render Markdown in the input area in real time (bold text, code blocks, tables, etc.).",
+      "title": "Input Markdown Rendering"
+    }
+  },
+  "title": "Labs"
+}

locales/en-US/modelProvider.json

@@ -294,6 +294,21 @@
           "title": "Maximum Context Window",
           "unlimited": "Unlimited"
         },
+        "type": {
+          "extra": "Different model types have distinct use cases and capabilities",
+          "options": {
+            "chat": "Chat",
+            "embedding": "Embedding",
+            "image": "Image Generation",
+            "realtime": "Real-time Chat",
+            "stt": "Speech-to-Text",
+            "text2music": "Text-to-Music",
+            "text2video": "Text-to-Video",
+            "tts": "Text-to-Speech"
+          },
+          "placeholder": "Please select a model type",
+          "title": "Model Type"
+        },
         "vision": {
           "extra": "This configuration will only enable image upload capabilities in the application. Whether recognition is supported depends entirely on the model itself. Please test the visual recognition capabilities of the model yourself.",
           "title": "Support Vision"

locales/en-US/models.json

@@ -92,6 +92,12 @@
   "DeepSeek-V3.1-Think": {
     "description": "DeepSeek-V3.1 - Thinking Mode; DeepSeek-V3.1 is a newly launched hybrid reasoning model by DeepSeek, supporting both thinking and non-thinking reasoning modes, with higher thinking efficiency compared to DeepSeek-R1-0528. Post-training optimization significantly enhances agent tool usage and agent task performance."
   },
+  "DeepSeek-V3.2-Exp": {
+    "description": "DeepSeek V3.2 is the latest general-purpose large model released by DeepSeek, supporting a hybrid inference architecture and featuring enhanced Agent capabilities."
+  },
+  "DeepSeek-V3.2-Exp-Think": {
+    "description": "DeepSeek V3.2 Thinking Mode. Before outputting the final answer, the model first generates a chain of thought to improve the accuracy of the final response."
+  },
   "Doubao-lite-128k": {
     "description": "Doubao-lite offers ultra-fast response times and better cost-effectiveness, providing customers with more flexible options for different scenarios. Supports inference and fine-tuning with a 128k context window."
   },
@@ -287,6 +293,9 @@
   "Pro/deepseek-ai/DeepSeek-V3.1": {
     "description": "DeepSeek-V3.1 is a hybrid large language model released by DeepSeek AI, featuring multiple significant upgrades over its predecessor. A key innovation of this model is the integration of both \"Thinking Mode\" and \"Non-thinking Mode,\" allowing users to flexibly switch between modes by adjusting chat templates to suit different task requirements. Through dedicated post-training optimization, V3.1 significantly enhances performance in tool invocation and Agent tasks, better supporting external search tools and executing complex multi-step tasks. Based on DeepSeek-V3.1-Base, it employs a two-stage long-text extension method to greatly increase training data volume, improving its handling of long documents and extensive code. As an open-source model, DeepSeek-V3.1 demonstrates capabilities comparable to top closed-source models across benchmarks in coding, mathematics, and reasoning. Its Mixture of Experts (MoE) architecture maintains a massive model capacity while effectively reducing inference costs."
   },
+  "Pro/deepseek-ai/DeepSeek-V3.1-Terminus": {
+    "description": "DeepSeek-V3.1-Terminus is an updated version of the V3.1 model released by DeepSeek, positioned as a hybrid agent large language model. This update focuses on fixing user-reported issues and improving stability while maintaining the model's original capabilities. It significantly enhances language consistency, reducing the mixing of Chinese and English and the occurrence of abnormal characters. The model integrates both \"Thinking Mode\" and \"Non-thinking Mode,\" allowing users to switch flexibly between chat templates to suit different tasks. As a key optimization, V3.1-Terminus improves the performance of the Code Agent and Search Agent, making tool invocation and multi-step complex task execution more reliable."
+  },
   "Pro/moonshotai/Kimi-K2-Instruct-0905": {
     "description": "Kimi K2-Instruct-0905 is the latest and most powerful version of Kimi K2. It is a top-tier Mixture of Experts (MoE) language model with a total of 1 trillion parameters and 32 billion activated parameters. Key features of this model include enhanced agent coding intelligence, demonstrating significant performance improvements in public benchmark tests and real-world agent coding tasks; and an improved frontend coding experience, with advancements in both aesthetics and practicality for frontend programming."
   },
@@ -680,6 +689,9 @@
   "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 +785,9 @@
   "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."
   },
@@ -920,6 +935,9 @@
   "deepseek-ai/DeepSeek-V3.1": {
     "description": "DeepSeek-V3.1 is a hybrid large language model released by DeepSeek AI, featuring multiple significant upgrades over its predecessor. A key innovation of this model is the integration of both \"Thinking Mode\" and \"Non-thinking Mode,\" allowing users to flexibly switch between modes by adjusting chat templates to suit different task requirements. Through dedicated post-training optimization, V3.1 significantly enhances performance in tool invocation and Agent tasks, better supporting external search tools and executing complex multi-step tasks. Based on DeepSeek-V3.1-Base, it employs a two-stage long-text extension method to greatly increase training data volume, improving its handling of long documents and extensive code. As an open-source model, DeepSeek-V3.1 demonstrates capabilities comparable to top closed-source models across benchmarks in coding, mathematics, and reasoning. Its Mixture of Experts (MoE) architecture maintains a massive model capacity while effectively reducing inference costs."
   },
+  "deepseek-ai/DeepSeek-V3.1-Terminus": {
+    "description": "DeepSeek-V3.1-Terminus is an updated version of the V3.1 model released by DeepSeek, positioned as a hybrid agent large language model. This update focuses on fixing user-reported issues and improving stability while maintaining the model's original capabilities. It significantly enhances language consistency, reducing the mixing of Chinese and English and the occurrence of abnormal characters. The model integrates both \"Thinking Mode\" and \"Non-thinking Mode,\" allowing users to switch flexibly between chat templates to suit different tasks. As a key optimization, V3.1-Terminus improves the performance of the Code Agent and Search Agent, making tool invocation and multi-step complex task execution more reliable."
+  },
   "deepseek-ai/deepseek-llm-67b-chat": {
     "description": "DeepSeek 67B is an advanced model trained for highly complex conversations."
   },
@@ -929,6 +947,9 @@
   "deepseek-ai/deepseek-v3.1": {
     "description": "DeepSeek V3.1: The next-generation reasoning model that enhances complex reasoning and chain-of-thought capabilities, suitable for tasks requiring in-depth analysis."
   },
+  "deepseek-ai/deepseek-v3.1-terminus": {
+    "description": "DeepSeek V3.1: A next-generation reasoning model designed to enhance complex reasoning and chain-of-thought capabilities, ideal for tasks requiring in-depth analysis."
+  },
   "deepseek-ai/deepseek-vl2": {
     "description": "DeepSeek-VL2 is a mixture of experts (MoE) visual language model developed based on DeepSeekMoE-27B, employing a sparsely activated MoE architecture that achieves outstanding performance while activating only 4.5 billion parameters. This model excels in various tasks, including visual question answering, optical character recognition, document/table/chart understanding, and visual localization."
   },
@@ -993,7 +1014,7 @@
     "description": "DeepSeek R1 full version, with 671B parameters, supporting real-time online search, offering enhanced understanding and generation capabilities."
   },
   "deepseek-reasoner": {
-    "description": "DeepSeek V3.1 Thinking Mode. Before outputting the final answer, the model first generates a chain of thought to improve the accuracy of the final response."
+    "description": "DeepSeek V3.2 Thinking Mode. Before outputting the final answer, the model first generates a chain of thought to improve the accuracy of the final response."
   },
   "deepseek-v2": {
     "description": "DeepSeek V2 is an efficient Mixture-of-Experts language model, suitable for cost-effective processing needs."
@@ -1013,6 +1034,9 @@
   "deepseek-v3.1:671b": {
     "description": "DeepSeek V3.1: The next-generation reasoning model that enhances complex reasoning and chain-of-thought capabilities, suitable for tasks requiring in-depth analysis."
   },
+  "deepseek-v3.2-exp": {
+    "description": "deepseek-v3.2-exp introduces a sparse attention mechanism designed to enhance training and inference efficiency when processing long texts, priced lower than deepseek-v3.1."
+  },
   "deepseek/deepseek-chat-v3-0324": {
     "description": "DeepSeek V3 is a 685B parameter expert mixture model, the latest iteration in the DeepSeek team's flagship chat model series.\n\nIt inherits from the [DeepSeek V3](/deepseek/deepseek-chat-v3) model and performs excellently across various tasks."
   },
@@ -1232,6 +1256,9 @@
   "fal-ai/flux/schnell": {
     "description": "FLUX.1 [schnell] is a 12-billion-parameter image generation model focused on fast generation of high-quality images."
   },
+  "fal-ai/hunyuan-image/v3": {
+    "description": "A powerful native multimodal image generation model"
+  },
   "fal-ai/imagen4/preview": {
     "description": "High-quality image generation model provided by Google."
   },
@@ -1343,24 +1370,36 @@
   "gemini-2.5-flash": {
     "description": "Gemini 2.5 Flash is Google's most cost-effective model, offering comprehensive capabilities."
   },
+  "gemini-2.5-flash-image": {
+    "description": "Nano Banana is Google's latest, fastest, and most efficient native multimodal model, allowing you to generate and edit images through conversation."
+  },
   "gemini-2.5-flash-image-preview": {
     "description": "Nano Banana is Google's latest, fastest, and most efficient native multimodal model, enabling you to generate and edit images through conversation."
   },
   "gemini-2.5-flash-image-preview:image": {
     "description": "Nano Banana is Google's latest, fastest, and most efficient native multimodal model, enabling you to generate and edit images through conversation."
   },
+  "gemini-2.5-flash-image:image": {
+    "description": "Nano Banana is Google's latest, fastest, and most efficient native multimodal model, allowing you to generate and edit images through conversation."
+  },
   "gemini-2.5-flash-lite": {
     "description": "Gemini 2.5 Flash-Lite is Google's smallest and most cost-effective model, designed for large-scale use."
   },
   "gemini-2.5-flash-lite-preview-06-17": {
     "description": "Gemini 2.5 Flash-Lite Preview is Google's smallest and most cost-efficient model, designed for large-scale usage."
   },
+  "gemini-2.5-flash-lite-preview-09-2025": {
+    "description": "Preview release (September 25th, 2025) of Gemini 2.5 Flash-Lite"
+  },
   "gemini-2.5-flash-preview-04-17": {
     "description": "Gemini 2.5 Flash Preview is Google's most cost-effective model, offering a comprehensive set of features."
   },
   "gemini-2.5-flash-preview-05-20": {
     "description": "Gemini 2.5 Flash Preview is Google's most cost-effective model, offering comprehensive capabilities."
   },
+  "gemini-2.5-flash-preview-09-2025": {
+    "description": "Preview release (September 25th, 2025) of Gemini 2.5 Flash"
+  },
   "gemini-2.5-pro": {
     "description": "Gemini 2.5 Pro is Google's most advanced reasoning model, capable of tackling complex problems in coding, mathematics, and STEM fields, as well as analyzing large datasets, codebases, and documents using long-context processing."
   },
@@ -1373,6 +1412,15 @@
   "gemini-2.5-pro-preview-06-05": {
     "description": "Gemini 2.5 Pro Preview is Google's most advanced cognitive model, capable of reasoning through complex problems in code, mathematics, and STEM fields, as well as analyzing large datasets, codebases, and documents using long-context understanding."
   },
+  "gemini-flash-latest": {
+    "description": "Latest release of Gemini Flash"
+  },
+  "gemini-flash-lite-latest": {
+    "description": "Latest release of Gemini Flash-Lite"
+  },
+  "gemini-pro-latest": {
+    "description": "Latest release of Gemini Pro"
+  },
   "gemma-7b-it": {
     "description": "Gemma 7B is suitable for medium to small-scale task processing, offering cost-effectiveness."
   },
@@ -1437,7 +1485,7 @@
     "description": "The GLM-4.1V-Thinking series represents the most powerful vision-language models known at the 10B parameter scale, integrating state-of-the-art capabilities across various vision-language tasks such as video understanding, image question answering, academic problem solving, OCR text recognition, document and chart interpretation, GUI agents, front-end web coding, and grounding. Its performance in many tasks even surpasses that of Qwen2.5-VL-72B, which has over eight times the parameters. Leveraging advanced reinforcement learning techniques, the model masters Chain-of-Thought reasoning to improve answer accuracy and richness, significantly outperforming traditional non-thinking models in final results and interpretability."
   },
   "glm-4.5": {
-    "description": "Zhipu's latest flagship model supports thinking mode switching, achieving state-of-the-art comprehensive capabilities among open-source models, with a context length of up to 128K."
+    "description": "Zhipu's flagship model supports thinking mode switching, with comprehensive capabilities reaching the state-of-the-art level among open-source models, and a context length of up to 128K."
   },
   "glm-4.5-air": {
     "description": "A lightweight version of GLM-4.5 balancing performance and cost-effectiveness, capable of flexibly switching hybrid thinking models."
@@ -1454,6 +1502,9 @@
   "glm-4.5v": {
     "description": "Zhipu's next-generation visual reasoning model is built on a Mixture-of-Experts (MoE) architecture. With 106B total parameters and 12B activated parameters, it achieves state-of-the-art performance among open-source multimodal models of similar scale across various benchmarks, supporting common tasks such as image, video, document understanding, and GUI-related tasks."
   },
+  "glm-4.6": {
+    "description": "Zhipu's latest flagship model GLM-4.6 (355B) surpasses its predecessor comprehensively in advanced encoding, long text processing, reasoning, and agent capabilities, especially aligning with Claude Sonnet 4 in programming skills, making it a top-tier coding model in China."
+  },
   "glm-4v": {
     "description": "GLM-4V provides strong image understanding and reasoning capabilities, supporting various visual tasks."
   },
@@ -1481,6 +1532,9 @@
   "glm-zero-preview": {
     "description": "GLM-Zero-Preview possesses strong complex reasoning abilities, excelling in logical reasoning, mathematics, programming, and other fields."
   },
+  "glm4.6:355b": {
+    "description": "GLM-4.6 (355B), the latest flagship model from Zhipu, delivers comprehensive improvements over its predecessor in advanced coding, long-text processing, reasoning, and agent capabilities. It is particularly aligned with Claude Sonnet 4 in programming performance, making it one of the top coding models in China."
+  },
   "google/gemini-2.0-flash": {
     "description": "Gemini 2.0 Flash offers next-generation features and improvements, including exceptional speed, built-in tool usage, multimodal generation, and a 1 million token context window."
   },
@@ -1682,12 +1736,18 @@
   "gpt-5-nano": {
     "description": "The fastest and most cost-efficient version of GPT-5. Perfectly suited for applications requiring rapid responses and cost sensitivity."
   },
+  "gpt-5-pro": {
+    "description": "GPT-5 Pro leverages greater computational power for deeper reasoning and consistently delivers improved answers."
+  },
   "gpt-audio": {
     "description": "GPT Audio is a general-purpose chat model designed for audio input and output, supporting audio I/O in the Chat Completions API."
   },
   "gpt-image-1": {
     "description": "ChatGPT native multimodal image generation model."
   },
+  "gpt-image-1-mini": {
+    "description": "A more cost-effective version of GPT Image 1, natively supporting both text and image inputs with image generation output."
+  },
   "gpt-oss-120b": {
     "description": "GPT-OSS-120B MXFP4 quantized Transformer architecture, delivering strong performance even under resource constraints."
   },
@@ -1700,9 +1760,6 @@
   "gpt-realtime": {
     "description": "A general-purpose real-time model supporting real-time text and audio input/output, as well as image input."
   },
-  "grok-2-1212": {
-    "description": "This model has improved in accuracy, instruction adherence, and multilingual capabilities."
-  },
   "grok-2-image-1212": {
     "description": "Our latest image generation model can create vivid and realistic images based on text prompts. It performs excellently in image generation for marketing, social media, and entertainment."
   },
@@ -1712,15 +1769,9 @@
   "grok-3": {
     "description": "A flagship model skilled in data extraction, programming, and text summarization for enterprise applications, with deep knowledge in finance, healthcare, law, and science."
   },
-  "grok-3-fast": {
-    "description": "A flagship model skilled in data extraction, programming, and text summarization for enterprise applications, with deep knowledge in finance, healthcare, law, and science."
-  },
   "grok-3-mini": {
     "description": "A lightweight model that thinks before responding. It runs fast and intelligently, suitable for logical tasks that do not require deep domain knowledge, and can provide raw thought trajectories."
   },
-  "grok-3-mini-fast": {
-    "description": "A lightweight model that thinks before responding. It runs fast and intelligently, suitable for logical tasks that do not require deep domain knowledge, and can provide raw thought trajectories."
-  },
   "grok-4": {
     "description": "Our latest and most powerful flagship model, excelling in natural language processing, mathematical computation, and reasoning — a perfect all-rounder."
   },
@@ -1799,12 +1850,12 @@
   "hunyuan-t1-latest": {
     "description": "Significantly enhances the main model's slow-thinking capabilities in advanced mathematics, complex reasoning, difficult coding, instruction adherence, and text creation quality."
   },
-  "hunyuan-t1-vision": {
-    "description": "Hunyuan is a multimodal deep thinking model supporting native multimodal chain-of-thought reasoning, excelling in various image reasoning scenarios and significantly outperforming fast-thinking models on science problems."
-  },
   "hunyuan-t1-vision-20250619": {
     "description": "The latest Hunyuan t1-vision multimodal deep thinking model supports native long Chain-of-Thought reasoning across modalities, comprehensively improving over the previous default version."
   },
+  "hunyuan-t1-vision-20250916": {
+    "description": "The latest Hunyuan t1-vision model excels in visual deep reasoning. Compared to the previous version, it offers significant enhancements in general image-text Q&A, visual localization, OCR, chart interpretation, problem-solving from photos, and image-based creative tasks, with notable improvements in English and low-resource language capabilities."
+  },
   "hunyuan-turbo": {
     "description": "The preview version of the next-generation Hunyuan large language model, featuring a brand-new mixed expert model (MoE) structure, which offers faster inference efficiency and stronger performance compared to Hunyuan Pro."
   },
@@ -1826,6 +1877,9 @@
   "hunyuan-turbos-20250604": {
     "description": "Upgraded pretraining foundation with improved writing and reading comprehension skills, significantly enhanced coding and STEM abilities, and continuous improvements in following complex instructions."
   },
+  "hunyuan-turbos-20250926": {
+    "description": "Pre-training base data quality upgrade. Optimized post-training phase strategies to continuously enhance Agent capabilities, English and minor language proficiency, instruction compliance, coding, and scientific reasoning."
+  },
   "hunyuan-turbos-latest": {
     "description": "The latest version of hunyuan-TurboS, the flagship model of Hunyuan, features enhanced reasoning capabilities and improved user experience."
   },
@@ -1916,6 +1970,9 @@
   "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."
   },
@@ -1958,6 +2015,9 @@
   "llama-3.2-vision-instruct": {
     "description": "The Llama 3.2-Vision instruction-tuned model is optimized for visual recognition, image reasoning, image captioning, and answering general questions related to images."
   },
+  "llama-3.3-70b": {
+    "description": "Llama 3.3 70B: A mid-to-large scale Llama model that balances reasoning power and throughput."
+  },
   "llama-3.3-70b-instruct": {
     "description": "Llama 3.3 is the most advanced multilingual open-source large language model in the Llama series, offering performance comparable to a 405B model at an extremely low cost. Based on the Transformer architecture, it enhances usability and safety through supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF). Its instruction-tuned version is optimized for multilingual dialogue and outperforms many open-source and closed chat models on various industry benchmarks. Knowledge cutoff date is December 2023."
   },
@@ -1967,6 +2027,12 @@
   "llama-3.3-instruct": {
     "description": "The Llama 3.3 instruction-tuned model is optimized for conversational scenarios, outperforming many existing open-source chat models on common industry benchmarks."
   },
+  "llama-4-maverick-17b-128e-instruct": {
+    "description": "Llama 4 Maverick: A high-performance model in the Llama series, ideal for advanced reasoning, complex problem-solving, and instruction-following tasks."
+  },
+  "llama-4-scout-17b-16e-instruct": {
+    "description": "Llama 4 Scout: A high-performance Llama model optimized for scenarios requiring high throughput and low latency."
+  },
   "llama3-70b-8192": {
     "description": "Meta Llama 3 70B provides unparalleled complexity handling capabilities, tailored for high-demand projects."
   },
@@ -1982,6 +2048,9 @@
   "llama3.1": {
     "description": "Llama 3.1 is a leading model launched by Meta, supporting up to 405B parameters, applicable in complex dialogues, multilingual translation, and data analysis."
   },
+  "llama3.1-8b": {
+    "description": "Llama 3.1 8B: A lightweight, low-latency variant of Llama, well-suited for real-time inference and interactive applications."
+  },
   "llama3.1:405b": {
     "description": "Llama 3.1 is a leading model launched by Meta, supporting up to 405B parameters, applicable in complex dialogues, multilingual translation, and data analysis."
   },
@@ -2579,6 +2648,12 @@
   "qvq-plus": {
     "description": "A visual reasoning model supporting visual inputs and chain-of-thought outputs. The plus version, succeeding the qvq-max model, offers faster reasoning speed and a more balanced trade-off between performance and cost."
   },
+  "qwen-3-32b": {
+    "description": "Qwen 3 32B: A strong performer in multilingual and coding tasks, suitable for medium-scale production use."
+  },
+  "qwen-3-coder-480b": {
+    "description": "Qwen 3 Coder 480B: A long-context model designed for code generation and complex programming tasks."
+  },
   "qwen-coder-plus": {
     "description": "Tongyi Qianwen coding model."
   },
@@ -3131,6 +3206,9 @@
   "zai-org/GLM-4.5V": {
     "description": "GLM-4.5V is the latest-generation vision-language model (VLM) released by Zhipu AI. It is built on the flagship text model GLM-4.5-Air, which has 106B total parameters and 12B active parameters, and adopts a Mixture-of-Experts (MoE) architecture to deliver outstanding performance at reduced inference cost. Technically, GLM-4.5V continues the trajectory of GLM-4.1V-Thinking and introduces innovations such as three-dimensional rotary position encoding (3D-RoPE), significantly improving perception and reasoning of three-dimensional spatial relationships. Through optimizations across pretraining, supervised fine-tuning, and reinforcement learning stages, the model can handle a wide range of visual content including images, video, and long documents, and has achieved top-tier performance among comparable open-source models across 41 public multimodal benchmarks. The model also adds a \"Thinking Mode\" toggle that lets users flexibly choose between fast responses and deep reasoning to balance efficiency and effectiveness."
   },
+  "zai-org/GLM-4.6": {
+    "description": "Compared to GLM-4.5, GLM-4.6 introduces several key improvements. Its context window expands from 128K to 200K tokens, enabling the model to handle more complex agent tasks. The model achieves higher scores on code benchmarks and demonstrates stronger real-world performance in applications such as Claude Code, Cline, Roo Code, and Kilo Code, including improvements in generating visually refined front-end pages. GLM-4.6 shows significant enhancements in inference performance and supports tool usage during inference, resulting in stronger overall capabilities. It excels in tool utilization and search-based agents and integrates more effectively into agent frameworks. In writing, the model better aligns with human preferences in style and readability and performs more naturally in role-playing scenarios."
+  },
   "zai/glm-4.5": {
     "description": "The GLM-4.5 series models are foundational models specifically designed for agents. The flagship GLM-4.5 integrates 355 billion total parameters (32 billion active), unifying reasoning, coding, and agent capabilities to address complex application needs. As a hybrid reasoning system, it offers dual operating modes."
   },

locales/en-US/providers.json

@@ -32,6 +32,9 @@
   "bfl": {
     "description": "A leading, cutting-edge artificial intelligence research lab building the visual infrastructure of tomorrow."
   },
+  "cerebras": {
+    "description": "Cerebras is an AI inference platform built on its dedicated CS-3 system, designed to deliver the world's fastest, real-time, high-throughput LLM services. It is specifically engineered to eliminate latency and accelerate complex AI workflows such as real-time code generation and agent-based tasks."
+  },
   "cloudflare": {
     "description": "Run serverless GPU-powered machine learning models on Cloudflare's global network."
   },
@@ -110,6 +113,9 @@
   "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."
   },

locales/en-US/tool.json

@@ -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...",

locales/es-ES/chat.json

@@ -3,8 +3,8 @@
     "title": "Cambiar modelo"
   },
   "agentDefaultMessage": "Hola, soy **{{name}}**. Puedes comenzar a hablar conmigo de inmediato o ir a [Configuración del asistente]({{url}}) para completar mi información.",
-  "agentDefaultMessageWithSystemRole": "Hola, soy **{{name}}**, {{systemRole}}, ¡comencemos a chatear!",
-  "agentDefaultMessageWithoutEdit": "¡Hola, soy **{{name}}**! Comencemos nuestra conversación.",
+  "agentDefaultMessageWithSystemRole": "Hola, soy **{{name}}**, ¿en qué puedo ayudarte?",
+  "agentDefaultMessageWithoutEdit": "Hola, soy **{{name}}**, ¿en qué puedo ayudarte?",
   "agents": "Asistente",
   "artifact": {
     "generating": "Generando",
@@ -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",

locales/es-ES/common.json

@@ -236,6 +236,7 @@
   },
   "information": "Comunidad e Información",
   "installPWA": "Instalar la aplicación del navegador",
+  "labs": "Laboratorio",
   "lang": {
     "ar": "árabe",
     "bg-BG": "búlgaro",

locales/es-ES/hotkey.json

@@ -7,6 +7,14 @@
     "desc": "Eliminar los mensajes y archivos subidos de la conversación actual",
     "title": "Eliminar mensajes de la conversación"
   },
+  "deleteAndRegenerateMessage": {
+    "desc": "Eliminar el último mensaje y volver a generarlo",
+    "title": "Eliminar y regenerar"
+  },
+  "deleteLastMessage": {
+    "desc": "Eliminar el último mensaje",
+    "title": "Eliminar el último mensaje"
+  },
   "desktop": {
     "openSettings": {
       "desc": "Abrir la página de configuración de la aplicación",

locales/es-ES/image.json

@@ -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"