Compare commits

..

45 Commits

Author SHA1 Message Date
Vaayne
a67a6cf1cd check uv and bun install 2025-08-06 00:06:45 +08:00
Vaayne
9bfe70219d Add UV installer to sidebar and refactor state management
The changes add an UV installer component to the sidebar and switch from
Redux to local state for managing UV/Bun installation status. The commit
includes layout adjustments to accommodate the new component.
2025-08-05 23:46:44 +08:00
Vaayne
f9c4acd1d7 remove unused i18n 2025-08-05 23:26:13 +08:00
Vaayne
139feb1bd5 Add agent editing and configuration features
This commit adds comprehensive agent editing capabilities, including: -
New edit modal with advanced configuration options - Expanded agent form
with description, avatar, and instructions - Tools and knowledge base
selection - Model configuration settings - UI improvements for agent
management
2025-08-05 23:22:51 +08:00
Vaayne
245812916f Replace delete icon and simplify session modal 2025-08-05 22:48:47 +08:00
Vaayne
9e473ee8ce 💫 ui: redesign agent chat UI with improved message hierarchy and tool display
- Create MessageGroup component for intelligent message organization and tool grouping
- Redesign tool calls to be compact, visually secondary with muted colors and smaller fonts
- Align tool messages with agent message content using consistent 44px offset
- Reduce message container gap from 20px to 12px for better conversation flow
- Fix hashCode TypeScript error with proper string-to-number hash function
- Add responsive design breakpoints for mobile compatibility (768px, 480px)
- Implement smooth transitions and proper collapse icon rotation (-90deg)
- Separate system messages from conversation flow for better organization
- Reduce tool content max-height to 200px with scroll for better space usage
- Apply consistent visual hierarchy: conversation primary, tools secondary
2025-08-05 22:19:14 +08:00
Vaayne
03183b4c50 Improve tool call message UI and expand behavior 2025-08-05 21:56:24 +08:00
Vaayne
66fa189474 ♻️ refactor: restructure CherryAgentPage into modular architecture
- Extract utilities into separate modules (formatters, parsers, validators, constants, logProcessors)
- Create custom hooks for state management (useAgents, useSessions, useSessionLogs, useCollapsibleMessages, useAgentExecution)
- Split UI into reusable components (Sidebar, ConversationArea, InputArea, message components, modals)
- Organize styled-components into themed style modules (layout, sidebar, conversation, messages, modals, buttons)
- Reduce main component from ~2400 lines to ~290 lines
- Improve code maintainability and testability with proper separation of concerns
- Follow React best practices with custom hooks and component composition
2025-08-05 20:20:54 +08:00
Vaayne
c19a501f66 Add tool call UI and raw log parsing support 2025-08-05 17:15:41 +08:00
Vaayne
1e78e2ee89 Add session configuration and management UI 2025-08-05 15:46:53 +08:00
Vaayne
845dc40334 Add session metrics and improve chat message filtering 2025-08-05 14:50:49 +08:00
Vaayne
3b472cf48b Redesign chat UI with improved styling and message display 2025-08-05 14:39:45 +08:00
Vaayne
6087cb687d feat: enhance agent logging system with structured events and improved UI
- Add structured logging for Claude assistant responses in agent.py
- Remove duplicate user query logging to prevent UI duplication
- Implement comprehensive message filtering and formatting in UI
- Add visual styling for different message types (errors, results, responses)
- Improve message content parsing with type-specific handlers
- Filter raw stdout/stderr logs from conversation display
- Add useCallback optimization for React Hook dependencies
- Fix ESLint and TypeScript issues in CherryAgentPage component
- Update test formatting and structure for consistency

This creates a clean conversation flow showing:
1. User prompts
2. Session initialization details
3. Claude assistant responses
4. Session results with cost/duration
5. Error messages with proper styling
2025-08-05 12:10:45 +08:00
Vaayne
24c3295393 Add structured logging support for agent execution 2025-08-05 11:54:32 +08:00
Vaayne
9d0c8ca223 enhance shell envs and fix continue conversations 2025-08-05 11:35:30 +08:00
Vaayne
4d38e82392 Add agent and session CRUD, chat UI to CherryAgentPage
- Implements agent/session creation, selection, and listing - Adds chat
interface with message input and session logs - Integrates IPC handlers
for agent/session CRUD and logs - Updates preload API for agent/session
operations - Restricts claude_code_agent.py to Python 3.10
2025-08-05 10:44:22 +08:00
Vaayne
a83f7baa72 Reorder BrowserWindow import and fix formatting issues 2025-08-05 09:03:53 +08:00
Vaayne
dca0cf488b ♻️ refactor: improve agent execution architecture and shell environment handling
- Refactor AgentExecutionService process execution from Promise-based to async/await pattern
- Separate process spawning from event handler setup for better error handling
- Add dependency injection support for shell environment provider (better testability)
- Consolidate Cherry Studio bin path logic into shell-env utility
- Use typed IPC channels for consistent agent communication
- Improve error handling with proper async/await in agent execution flow
- Update test mocks to use new testable AgentExecutionService architecture
- Enhance cross-platform shell detection (zsh default for macOS, bash for Linux)
2025-08-04 23:21:44 +08:00
Vaayne
e82aa2f061 feat: implement AgentExecutionService with process management and comprehensive testing
- Add complete runAgent and stopAgent implementation
- Implement child process spawning with uv for secure agent execution
- Add real-time stdout/stderr streaming to UI via IPC
- Implement comprehensive session logging to database
- Add graceful process termination with SIGTERM/SIGKILL fallback
- Track running processes with status reporting and management
- Handle all error scenarios with proper status updates and cleanup
- Create extensive test suite with 31 passing unit tests
- Add integration tests for end-to-end verification
- Include comprehensive documentation and testing guides

Features:
- Secure process execution without shell injection
- Session continuation support via Claude session IDs
- Working directory management and validation
- Real-time UI feedback through IPC streaming
- Database persistence of all execution events
- Comprehensive error handling and recovery
- Process lifecycle management and cleanup
2025-08-04 23:21:44 +08:00
Vaayne
823986bb11 🗃️ feat: enhance AgentService database migration system
- Refactor initialization to handle both fresh installs and migrations
- Replace createTables + migrateDatabase with unified createTablesAndMigrate approach
- Add comprehensive schema migration for sessions table with backwards compatibility
- Migrate user_prompt → user_goal column renaming
- Migrate claude_session_id → latest_claude_session_id column renaming
- Add migration for new columns: max_turns, permission_mode, accessible_paths
- Improve entity mapping to handle null values correctly
- Update database queries and indexes for new schema

Breaking changes:
- SessionEntity now uses user_goal instead of user_prompt
- SessionEntity now uses latest_claude_session_id instead of claude_session_id
- Added new required fields: max_turns, permission_mode
2025-08-04 23:21:44 +08:00
Vaayne
2fd2573a65 fix lint 2025-08-04 23:21:44 +08:00
Vaayne
8e0b6e369c clear code 2025-08-04 23:21:44 +08:00
Vaayne
8ab26e4e45 feat: implement secure AgentExecutionService for controlled agent.py execution
- Create new AgentExecutionService.ts with secure agent.py script execution
- Replace arbitrary shell command execution with controlled Python script calls
- Add claude_session_id field to session types for conversation continuity
- Update shared types between main and renderer processes
- Implement proper argument validation and sanitization
- Add comprehensive error handling and logging
- Export service through agent service index

Security improvements:
- Only executes predefined agent.py script (no arbitrary commands)
- Uses direct process spawning instead of shell execution
- Validates all arguments before execution
- Prevents command injection vulnerabilities

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-03 17:52:01 +08:00
Vaayne
b1a464fadc feat: enhance agent management with session log persistence and improved UX 2025-08-03 11:44:18 +08:00
Vaayne
8de2239eb6 fix .
fix issues
2025-08-03 11:43:02 +08:00
Vaayne
571f6c3ef3 feat: implement session-based message isolation and improve agent creation UX
- Add sessionId field to PocMessage interface for session isolation
- Filter messages by current session to prevent cross-session pollution
- Remove automatic agent creation - only manual creation by users
- Add beautiful empty state when no agents exist
- Enhance sidebar UX with prominent "Create Agent" button when empty
- Update message hooks to handle session-specific messaging
- Improve user control over agent lifecycle management

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-03 11:43:02 +08:00
Vaayne
dc603d9896 ♻️ refactor: use session-based working directory for command execution
- Remove working directory display from command input UI
- Commands now execute in session's accessible_paths directory
- Clean up unused props and styled components
- Simplify command input interface for better UX

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-03 11:43:02 +08:00
Vaayne
bbc0e9378a Redesign agent sidebar with avatar gradients 2025-08-03 11:43:02 +08:00
Vaayne
3d94740482 feat: add dynamic model and tool fetching for agent management
Replace hardcoded model and tool options with dynamic data fetched from API server:
- Update MCP API to return array format instead of object for consistency
- Add fetchAvailableModels() and fetchAvailableMCPTools() to AgentManagementService
- Modify AgentManagementModal to fetch and display dynamic options
- Add type definitions for FetchModelResponse and FetchMCPToolResponse

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-03 11:43:02 +08:00
Vaayne
4a5032520a feat: implement comprehensive agent and session management UI
- Add enhanced sidebar with agent and session controls
- Implement create/edit/delete operations for agents and sessions
- Add real-time session switching and auto-initialization
- Replace mock data with persistent database integration
- Include dropdown menus, tooltips, and confirmation dialogs
- Add responsive UI with proper styling and state management

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-03 11:43:02 +08:00
Vaayne
500831454b 🗃️ feat: implement comprehensive agent and session database management system
- Add complete database schema for agents, sessions, and session_logs tables
- Implement full CRUD operations with libsql database integration
- Create comprehensive AgentService with proper error handling and logging
- Add AgentManagementService for renderer-side IPC communication
- Implement useAgentManagement React hook for state management
- Add 12 new IPC channels for agent and session operations
- Update CherryAgentPage to use real database data instead of mock data
- Create shared TypeScript types between main and renderer processes
- Add auto-initialization for default agent and session creation
- Implement real-time agent name editing with database persistence
- Add comprehensive error handling with user feedback via Ant Design messages
- Create structured logging for all database operations
- Add tasks.md documentation for implementation progress tracking

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-03 11:43:02 +08:00
Vaayne
c8ea3407e6 💄 style: enhance Cherry Agent page design with modern UI improvements
- Restructure layout to match wireframe design with proper header/content sections
- Add agent name input field with elegant styling and focus effects
- Implement session management with interactive session items and hover animations
- Enhance sidebar design with improved spacing, shadows, and visual hierarchy
- Add modern styling with gradients, rounded corners, and smooth transitions
- Improve button interactions with scale effects and proper hover states
- Create responsive design that works when sidebar is collapsed
- Use mock session data for initial implementation

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-03 11:43:02 +08:00
Vaayne
d2fdb8ab0f 💄 refactor: redesign cherry-agent input with enhanced terminal UI
- Replace separate PocCommandInput and PocStatusBar with unified EnhancedCommandInput
- Add terminal-style prompt with dynamic status indicators ($, , ✗)
- Integrate status bar functionality directly into input component
- Implement contextual tool buttons (history, clear, settings, send/cancel)
- Add color-coded visual states for idle/running/error states
- Enhance keyboard UX with Enter/Esc shortcuts and history navigation
- Remove unused components: PocCommandInput, PocStatusBar, PocHeader
- Clean up imports and styled components
- Improve accessibility with tooltips and proper ARIA labels

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-03 11:43:02 +08:00
Vaayne
3f6c884992 Improve agent UI responsiveness and add command cancellation
The UI changes include faster command output buffering, better error
handling, improved status bar with cancel button, and visual refinements
to command messages.
2025-08-03 11:43:02 +08:00
Vaayne
db418ef5f1 enhance layput 2025-08-03 11:43:02 +08:00
Vaayne
29318d5a06 basic layout of cherry agent ui 2025-08-03 11:43:02 +08:00
Vaayne
2df77b62f9 fix init shell with command 2025-08-03 11:43:02 +08:00
Vaayne
ea3598e194 Merge branch 'main' into feat/agents-1 2025-08-03 11:43:02 +08:00
Vaayne
4b0db10195 ... 2025-08-03 11:43:02 +08:00
Vaayne
9fe14311fc feat(agents): enhance POC interface styling with Cherry Studio design system
- Integrate complete Cherry Studio CSS variables and design patterns
- Implement proper light/dark theme support with system preference detection
- Enhance message bubbles to match Cherry Studio's chat interface styling
- Add Cherry Studio-compatible scrollbar styling with theme-aware colors
- Improve typography with Ubuntu font family and proper font stacks
- Add comprehensive hover states, transitions, and micro-interactions
- Implement accessibility improvements including focus states and reduced motion
- Add theme toggle functionality with persistent preferences
- Enhance header styling to match Cherry Studio's navbar design
- Add animation effects consistent with Cherry Studio's motion design
- Improve responsive design for mobile and tablet viewports
- Add high contrast mode support for better accessibility

The POC interface now provides a polished, professional appearance that
seamlessly integrates with Cherry Studio's design language and user experience.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-03 11:43:02 +08:00
Vaayne
2628f9b57e feat: integrate hooks with POC UI components for real-time command execution
- Update CommandPocPage.tsx to coordinate between all hooks and manage application state
- Integrate usePocMessages, usePocCommand, and useCommandHistory hooks for complete functionality
- Add auto-scrolling to PocMessageList with user scroll detection
- Implement command history navigation in PocCommandInput using arrow keys
- Connect real-time command status updates to PocStatusBar
- Pass current working directory to PocHeader for display
- Enable seamless command execution flow with proper loading states
- Add buffered output handling between command hook and message display
- Implement command count tracking and execution state management

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-03 11:43:02 +08:00
Vaayne
df23499679 feat: implement PoC command hooks for message management and command execution
- Add usePocMessages hook for managing message state with real-time streaming support
- Add usePocCommand hook for command execution with 100ms output buffering
- Add useCommandHistory hook for input history navigation with arrow keys
- Implement proper event handling from AgentCommandService
- Add comprehensive logging and error handling
- Support message completion tracking and buffered output streaming

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-03 11:43:02 +08:00
Vaayne
0860541b2d feat: implement AgentCommandService for POC command execution
- Add AgentCommandService.ts with singleton pattern following existing renderer service architecture
- Implement IPC communication with main process command executor using established patterns
- Add methods for executing commands, handling real-time output streaming, and command interruption
- Create proper TypeScript interfaces and event-driven architecture using Emittery
- Add POC API endpoints to preload script for secure renderer-main communication
- Include comprehensive test suite with 12 passing tests covering all major functionality
- Follow existing code patterns for error handling, logging, and resource cleanup
- Support command state tracking, process management, and event listeners

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-03 11:43:02 +08:00
Vaayne
ffa4b4fc04 feat: implement PocCommandExecutor for cross-platform shell command execution
- Created PocCommandExecutor class in src/main/poc/commandExecutor.ts
- Added cross-platform shell detection (cmd.exe on Windows, bash on Unix)
- Implemented real-time stdout/stderr streaming via IPC
- Added process management with activeProcesses Map
- Support for command interruption with graceful and force termination
- Proper error handling and process cleanup
- Added POC-related IPC channels: Poc_ExecuteCommand, Poc_CommandOutput, Poc_InterruptCommand, Poc_GetActiveProcesses
- Registered IPC handlers in main/ipc.ts for command execution integration
- Follows existing architecture patterns from PythonService and other main process services

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-03 11:43:02 +08:00
Vaayne
75766dbfdc feat: Add POC command page structure and routing
- Created CommandPocPage.tsx with basic layout structure
- Added POC-specific TypeScript interfaces and types
- Implemented basic UI components: PocHeader, PocMessageList, PocMessageBubble, PocCommandInput, PocStatusBar
- Added /command-poc route to Router.tsx
- Set up component folder structure following PRD specifications

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-03 11:43:02 +08:00
1230 changed files with 58551 additions and 116851 deletions

View File

@@ -1,8 +1 @@
NODE_OPTIONS=--max-old-space-size=8000
API_KEY="sk-xxx"
BASE_URL="https://api.siliconflow.cn/v1/"
MODEL="Qwen/Qwen3-235B-A22B-Instruct-2507"
CSLOGGER_MAIN_LEVEL=info
CSLOGGER_RENDERER_LEVEL=info
#CSLOGGER_MAIN_SHOW_MODULES=
#CSLOGGER_RENDERER_SHOW_MODULES=

4
.github/CODEOWNERS vendored
View File

@@ -1,4 +0,0 @@
/src/renderer/src/store/ @0xfullex
/src/main/services/ConfigManager.ts @0xfullex
/packages/shared/IpcChannel.ts @0xfullex
/src/main/ipc.ts @0xfullex

View File

@@ -0,0 +1,92 @@
name: 🐛 错误报告 (中文)
description: 创建一个报告以帮助我们改进
title: '[错误]: '
labels: ['kind/bug']
body:
- type: markdown
attributes:
value: |
感谢您花时间填写此错误报告!
在提交此问题之前,请确保您已经了解了[常见问题](https://docs.cherry-ai.com/question-contact/questions)和[知识科普](https://docs.cherry-ai.com/question-contact/knowledge)
- type: checkboxes
id: checklist
attributes:
label: 提交前检查
description: |
在提交 Issue 前请确保您已经完成了以下所有步骤
options:
- label: 我理解 Issue 是用于反馈和解决问题的,而非吐槽评论区,将尽可能提供更多信息帮助问题解决。
required: true
- label: 我的问题不是 [常见问题](https://github.com/CherryHQ/cherry-studio/issues/3881) 中的内容。
required: true
- label: 我已经查看了 **置顶 Issue** 并搜索了现有的 [开放Issue](https://github.com/CherryHQ/cherry-studio/issues)和[已关闭Issue](https://github.com/CherryHQ/cherry-studio/issues?q=is%3Aissue%20state%3Aclosed%20),没有找到类似的问题。
required: true
- label: 我填写了简短且清晰明确的标题,以便开发者在翻阅 Issue 列表时能快速确定大致问题。而不是“一个建议”、“卡住了”等。
required: true
- type: dropdown
id: platform
attributes:
label: 平台
description: 您正在使用哪个平台?
options:
- Windows
- macOS
- Linux
validations:
required: true
- type: input
id: version
attributes:
label: 版本
description: 您正在运行的 Cherry Studio 版本是什么?
placeholder: 例如 v1.0.0
validations:
required: true
- type: textarea
id: description
attributes:
label: 错误描述
description: 描述问题时请尽可能详细。请尽可能提供截图或屏幕录制,以帮助我们更好地理解问题。
placeholder: 告诉我们发生了什么...(记得附上截图/录屏,如果适用)
validations:
required: true
- type: textarea
id: reproduction
attributes:
label: 重现步骤
description: 提供详细的重现步骤,以便于我们的开发人员可以准确地重现问题。请尽可能为每个步骤提供截图或屏幕录制。
placeholder: |
1. 转到 '...'
2. 点击 '....'
3. 向下滚动到 '....'
4. 看到错误
记得尽可能为每个步骤附上截图/录屏!
validations:
required: true
- type: textarea
id: expected
attributes:
label: 预期行为
description: 清晰简洁地描述您期望发生的事情
validations:
required: true
- type: textarea
id: logs
attributes:
label: 相关日志输出
description: 请复制并粘贴任何相关的日志输出
render: shell
- type: textarea
id: additional
attributes:
label: 附加信息
description: 任何能让我们对你所遇到的问题有更多了解的东西

View File

@@ -0,0 +1,76 @@
name: 💡 功能建议 (中文)
description: 为项目提出新的想法
title: '[功能]: '
labels: ['kind/enhancement']
body:
- type: markdown
attributes:
value: |
感谢您花时间提出新的功能建议!
在提交此问题之前,请确保您已经了解了[项目规划](https://docs.cherry-ai.com/cherrystudio/planning)和[功能介绍](https://docs.cherry-ai.com/cherrystudio/preview)
- type: checkboxes
id: checklist
attributes:
label: 提交前检查
description: |
在提交 Issue 前请确保您已经完成了以下所有步骤
options:
- label: 我理解 Issue 是用于反馈和解决问题的,而非吐槽评论区,将尽可能提供更多信息帮助问题解决。
required: true
- label: 我已经查看了置顶 Issue 并搜索了现有的 [开放Issue](https://github.com/CherryHQ/cherry-studio/issues)和[已关闭Issue](https://github.com/CherryHQ/cherry-studio/issues?q=is%3Aissue%20state%3Aclosed%20),没有找到类似的建议。
required: true
- label: 我填写了简短且清晰明确的标题,以便开发者在翻阅 Issue 列表时能快速确定大致问题。而不是“一个建议”、“卡住了”等。
required: true
- label: 最新的 Cherry Studio 版本没有实现我所提出的功能。
required: true
- type: dropdown
id: platform
attributes:
label: 平台
description: 您正在使用哪个平台?
options:
- Windows
- macOS
- Linux
validations:
required: true
- type: input
id: version
attributes:
label: 版本
description: 您正在运行的 Cherry Studio 版本是什么?
placeholder: 例如 v1.0.0
validations:
required: true
- type: textarea
id: problem
attributes:
label: 您的功能建议是否与某个问题/issue相关?
description: 请简明扼要地描述您遇到的问题
placeholder: 我总是感到沮丧,因为...
validations:
required: true
- type: textarea
id: solution
attributes:
label: 请描述您希望实现的解决方案
description: 请简明扼要地描述您希望发生的情况
validations:
required: true
- type: textarea
id: alternatives
attributes:
label: 请描述您考虑过的其他方案
description: 请简明扼要地描述您考虑过的任何其他解决方案或功能
- type: textarea
id: additional
attributes:
label: 其他补充信息
description: 在此添加任何其他与功能建议相关的上下文或截图

77
.github/ISSUE_TEMPLATE/#2_question.yml vendored Normal file
View File

@@ -0,0 +1,77 @@
name: ❓ 提问 & 讨论 (中文)
description: 寻求帮助、讨论问题、提出疑问等...
title: '[讨论]: '
labels: ['kind/question']
body:
- type: markdown
attributes:
value: |
感谢您的提问!请尽可能详细地描述您的问题,这样我们才能更好地帮助您。
- type: checkboxes
id: checklist
attributes:
label: Issue 检查清单
description: |
在提交 Issue 前请确保您已经完成了以下所有步骤
options:
- label: 我理解 Issue 是用于反馈和解决问题的,而非吐槽评论区,将尽可能提供更多信息帮助问题解决。
required: true
- label: 我确认自己需要的是提出问题并且讨论问题,而不是 Bug 反馈或需求建议。
required: true
- type: dropdown
id: platform
attributes:
label: 平台
description: 您正在使用哪个平台?
options:
- Windows
- macOS
- Linux
validations:
required: true
- type: input
id: version
attributes:
label: 版本
description: 您正在运行的 Cherry Studio 版本是什么?
placeholder: 例如 v1.0.0
validations:
required: true
- type: textarea
id: question
attributes:
label: 您的问题
description: 请详细描述您的问题
placeholder: 请尽可能清楚地说明您的问题...
validations:
required: true
- type: textarea
id: context
attributes:
label: 相关背景
description: 请提供一些背景信息,帮助我们更好地理解您的问题
placeholder: 例如:使用场景、已尝试的解决方案等
- type: textarea
id: additional
attributes:
label: 补充信息
description: 任何其他相关的信息、截图或代码示例
render: shell
- type: dropdown
id: priority
attributes:
label: 优先级
description: 这个问题对您来说有多紧急?
options:
- 低 (有空再看)
- 中 (希望尽快得到答复)
- 高 (阻碍工作进行)
validations:
required: true

76
.github/ISSUE_TEMPLATE/#3_others.yml vendored Normal file
View File

@@ -0,0 +1,76 @@
name: 🤔 其他问题 (中文)
description: 提交不属于错误报告或功能需求的问题
title: '[其他]: '
body:
- type: markdown
attributes:
value: |
感谢您花时间提出问题!
在提交此问题之前,请确保您已经了解了[常见问题](https://docs.cherry-ai.com/question-contact/questions)和[知识科普](https://docs.cherry-ai.com/question-contact/knowledge)
- type: checkboxes
id: checklist
attributes:
label: 提交前检查
description: |
在提交 Issue 前请确保您已经完成了以下所有步骤
options:
- label: 我理解 Issue 是用于反馈和解决问题的,而非吐槽评论区,将尽可能提供更多信息帮助问题解决。
required: true
- label: 我已经查看了置顶 Issue 并搜索了现有的 [开放Issue](https://github.com/CherryHQ/cherry-studio/issues)和[已关闭Issue](https://github.com/CherryHQ/cherry-studio/issues?q=is%3Aissue%20state%3Aclosed%20),没有找到类似的问题。
required: true
- label: 我填写了简短且清晰明确的标题,以便开发者在翻阅 Issue 列表时能快速确定大致问题。而不是"一个问题"、"求助"等。
required: true
- label: 我的问题不属于错误报告或功能需求类别。
required: true
- type: dropdown
id: platform
attributes:
label: 平台
description: 您正在使用哪个平台?
options:
- Windows
- macOS
- Linux
validations:
required: true
- type: input
id: version
attributes:
label: 版本
description: 您正在运行的 Cherry Studio 版本是什么?
placeholder: 例如 v1.0.0
validations:
required: true
- type: textarea
id: question
attributes:
label: 问题描述
description: 请详细描述您的问题或疑问
placeholder: 我想了解有关...的更多信息
validations:
required: true
- type: textarea
id: context
attributes:
label: 相关背景
description: 请提供与您的问题相关的任何背景信息或上下文
placeholder: 我尝试实现...时遇到了疑问
validations:
required: true
- type: textarea
id: attempts
attributes:
label: 您已尝试的方法
description: 请描述您为解决问题已经尝试过的方法(如果有)
- type: textarea
id: additional
attributes:
label: 附加信息
description: 任何能让我们对您的问题有更多了解的信息,包括截图或相关链接

View File

@@ -1,7 +1,7 @@
name: 🐛 Bug Report (English)
description: Create a report to help us improve
title: '[Bug]: '
labels: ['BUG']
labels: ['kind/bug']
body:
- type: markdown
attributes:
@@ -24,8 +24,6 @@ body:
required: true
- label: I've filled in short, clear headings so that developers can quickly identify a rough idea of what to expect when flipping through the list of issues. And not "a suggestion", "stuck", etc.
required: true
- label: I've confirmed that I am using the latest version of Cherry Studio.
required: true
- type: dropdown
id: platform

View File

@@ -1,7 +1,7 @@
name: 💡 Feature Request (English)
description: Suggest an idea for this project
title: '[Feature]: '
labels: ['feature']
labels: ['kind/enhancement']
body:
- type: markdown
attributes:

View File

@@ -1,7 +1,7 @@
name: ❓ Questions & Discussion
description: Seeking help, discussing issues, asking questions, etc...
title: '[Discussion]: '
labels: ['discussion', 'help wanted']
labels: ['kind/question']
body:
- type: markdown
attributes:

View File

@@ -1,66 +0,0 @@
name: Auto I18N
env:
API_KEY: ${{ secrets.TRANSLATE_API_KEY }}
MODEL: ${{ vars.AUTO_I18N_MODEL || 'deepseek/deepseek-v3.1'}}
BASE_URL: ${{ vars.AUTO_I18N_BASE_URL || 'https://api.ppinfra.com/openai'}}
on:
pull_request:
types: [opened, synchronize, reopened]
workflow_dispatch:
jobs:
auto-i18n:
runs-on: ubuntu-latest
if: github.event.pull_request.head.repo.full_name == 'CherryHQ/cherry-studio'
name: Auto I18N
permissions:
contents: write
pull-requests: write
steps:
- name: 🐈‍⬛ Checkout
uses: actions/checkout@v5
with:
ref: ${{ github.event.pull_request.head.ref }}
- name: 📦 Setting Node.js
uses: actions/setup-node@v5
with:
node-version: 20
- name: 📦 Install dependencies in isolated directory
run: |
# 在临时目录安装依赖
mkdir -p /tmp/translation-deps
cd /tmp/translation-deps
echo '{"dependencies": {"openai": "^5.12.2", "cli-progress": "^3.12.0", "tsx": "^4.20.3", "@biomejs/biome": "2.2.4"}}' > package.json
npm install --no-package-lock
# 设置 NODE_PATH 让项目能找到这些依赖
echo "NODE_PATH=/tmp/translation-deps/node_modules" >> $GITHUB_ENV
- name: 🏃‍♀️ Translate
run: npx tsx scripts/auto-translate-i18n.ts
- name: 🔍 Format
run: cd /tmp/translation-deps && npx biome format --config-path /home/runner/work/cherry-studio/cherry-studio/biome.jsonc --write /home/runner/work/cherry-studio/cherry-studio/src/renderer/src/i18n/
- name: 🔄 Commit changes
run: |
git config --local user.email "action@github.com"
git config --local user.name "GitHub Action"
git add .
git reset -- package.json yarn.lock # 不提交 package.json 和 yarn.lock 的更改
if git diff --cached --quiet; then
echo "No changes to commit"
else
git commit -m "fix(i18n): Auto update translations for PR #${{ github.event.pull_request.number }}"
fi
- name: 🚀 Push changes
uses: ad-m/github-push-action@master
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
branch: ${{ github.event.pull_request.head.ref }}

View File

@@ -1,56 +0,0 @@
name: Claude Code Review
on:
pull_request:
types: [opened]
# Optional: Only run on specific file changes
# paths:
# - "src/**/*.ts"
# - "src/**/*.tsx"
# - "src/**/*.js"
# - "src/**/*.jsx"
jobs:
claude-review:
# Only trigger code review for PRs from the main repository due to upstream OIDC issues
# https://github.com/anthropics/claude-code-action/issues/542
if: |
(github.event.pull_request.head.repo.full_name == github.repository) &&
(github.event.pull_request.draft == false)
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: write
issues: read
id-token: write
actions: read
steps:
- name: Checkout repository
uses: actions/checkout@v5
with:
fetch-depth: 1
- name: Run Claude Code Review
id: claude-review
uses: anthropics/claude-code-action@v1
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
prompt: |
Please review this pull request and provide feedback on:
- Code quality and best practices
- Potential bugs or issues
- Performance considerations
- Security concerns
- Test coverage
PR number: ${{ github.event.number }}
Repo: ${{ github.repository }}
Use the repository's CLAUDE.md for guidance on style and conventions. Be constructive and helpful in your feedback.
Use `gh pr comment` with your Bash tool to leave your review as a comment on the PR.
# See https://github.com/anthropics/claude-code-action/blob/main/docs/usage.md
# or https://docs.anthropic.com/en/docs/claude-code/sdk#command-line for available options
claude_args: '--allowed-tools "Bash(gh issue view:*),Bash(gh search:*),Bash(gh issue list:*),Bash(gh pr comment:*),Bash(gh pr diff:*),Bash(gh pr view:*),Bash(gh pr list:*)"'

View File

@@ -1,107 +0,0 @@
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
issues: write # 编辑issues/comments
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.TOKEN_GITHUB_WRITE }}
allowed_non_write_users: "*"
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
claude_args: "--allowed-tools Bash(gh issue:*),Bash(gh api:repos/*/issues:*),Bash(gh api:repos/*/pulls/*/reviews/*),Bash(gh api:repos/*/pulls/comments/*)"
prompt: |
你是一个多语言翻译助手。你需要响应 GitHub Webhooks 中的以下四种事件:
- issues
- issue_comment
- pull_request_review
- pull_request_review_comment
请完成以下任务:
1. 获取当前事件的完整信息。
- 如果当前事件是 issues就获取该 issues 的信息。
- 如果当前事件是 issue_comment就获取该 comment 的信息。
- 如果当前事件是 pull_request_review就获取该 review 的信息。
- 如果当前事件是 pull_request_review_comment就获取该 comment 的信息。
2. 智能检测内容。
- 如果获取到的信息是已经遵循格式要求翻译过的内容,则检查翻译内容和原始内容是否匹配。若不匹配,则重新翻译一次令其匹配,并遵循格式要求;
- 如果获取到的信息是未翻译过的内容,检查其内容语言。若不是英文,则翻译成英文;
- 如果获取到的信息是部分翻译为英文的内容,则将其翻译为英文;
- 如果获取到的信息包含了对已翻译内容的引用,则将引用内容清理为仅含英文的内容。引用的内容不能够包含"This xxx was translated by Claude"和"Original Content`等内容。
- 如果获取到的信息包含了其他类型的引用,即对非 Claude 翻译的内容的引用,则直接照原样引用,不进行翻译。
- 如果获取到的信息是通过邮件回复的内容,则在翻译时应当将邮件内容的引用放到最后。在原始内容和翻译内容中只需要回复的内容本身,不要包含对邮件内容的引用。
- 如果获取到的信息本身不需要任何处理,则跳过任务。
3. 格式要求:
- 标题:英文翻译(如果非英文)
- 内容格式:
> [!NOTE]
> This issue/comment/review was translated by Claude.
[翻译内容]
---
<details>
<summary>Original Content</summary>
[原始内容]
</details>
4. 使用gh工具更新
- 根据环境信息中的Event类型选择正确的命令
- 如果 Event 是 'issues': gh issue edit [ISSUE_NUMBER] --title "[英文标题]" --body "[翻译内容 + 原始内容]"
- 如果 Event 是 'issue_comment': gh api -X PATCH /repos/${{ github.repository }}/issues/comments/${{ github.event.comment.id }} -f body="[翻译内容 + 原始内容]"
- 如果 Event 是 'pull_request_review': gh api -X PUT /repos/${{ github.repository }}/pulls/${{ github.event.pull_request.number }}/reviews/${{ github.event.review.id }} -f body="[翻译内容]"
- 如果 Event 是 'pull_request_review_comment': gh api -X PATCH /repos/${{ github.repository }}/pulls/comments/${{ github.event.comment.id }} -f body="[翻译内容 + 原始内容]"
环境信息:
- 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' }}
使用以下命令获取完整信息:
gh issue view ${{ github.event.issue.number }} --json title,body,comments

View File

@@ -1,60 +0,0 @@
name: Claude Code
on:
issue_comment:
types: [created]
pull_request_review_comment:
types: [created]
issues:
types: [opened]
pull_request_review:
types: [submitted]
jobs:
claude:
if: |
(github.event_name == 'issue_comment'
&& contains(github.event.comment.body, '@claude')
&& contains(fromJSON('["COLLABORATOR","MEMBER","OWNER"]'), github.event.comment.author_association))
||
(github.event_name == 'pull_request_review_comment'
&& contains(github.event.comment.body, '@claude')
&& contains(fromJSON('["COLLABORATOR","MEMBER","OWNER"]'), github.event.comment.author_association))
||
(github.event_name == 'pull_request_review'
&& contains(github.event.review.body, '@claude')
&& contains(fromJSON('["COLLABORATOR","MEMBER","OWNER"]'), github.event.review.author_association))
||
(github.event_name == 'issues'
&& (contains(github.event.issue.body, '@claude') || contains(github.event.issue.title, '@claude'))
&& contains(fromJSON('["COLLABORATOR","MEMBER","OWNER"]'), github.event.issue.author_association))
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: read
issues: read
id-token: write
actions: read # Required for Claude to read CI results on PRs
steps:
- name: Checkout repository
uses: actions/checkout@v5
with:
fetch-depth: 1
- name: Run Claude Code
id: claude
uses: anthropics/claude-code-action@v1
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
# This is an optional setting that allows Claude to read CI results on PRs
additional_permissions: |
actions: read
# Optional: Give a custom prompt to Claude. If this is not specified, Claude will perform the instructions specified in the comment that tagged it.
# prompt: 'Update the pull request description to include a summary of changes.'
# Optional: Add claude_args to customize behavior and configuration
# See https://github.com/anthropics/claude-code-action/blob/main/docs/usage.md
# or https://docs.anthropic.com/en/docs/claude-code/sdk#command-line for available options
# claude_args: '--model claude-opus-4-1-20250805 --allowed-tools Bash(gh pr:*)'

View File

@@ -1,22 +0,0 @@
name: Delete merged branch
on:
pull_request:
types:
- closed
jobs:
delete-branch:
runs-on: ubuntu-latest
permissions:
contents: write
if: github.event.pull_request.merged == true && github.event.pull_request.head.repo.full_name == github.repository
steps:
- name: Delete merged branch
uses: actions/github-script@v8
with:
script: |
github.rest.git.deleteRef({
owner: context.repo.owner,
repo: context.repo.repo,
ref: `heads/${context.payload.pull_request.head.ref}`,
})

View File

@@ -51,12 +51,12 @@ jobs:
steps:
- name: Check out Git repository
uses: actions/checkout@v5
uses: actions/checkout@v4
with:
ref: main
- name: Install Node.js
uses: actions/setup-node@v5
uses: actions/setup-node@v4
with:
node-version: 20
@@ -93,44 +93,37 @@ jobs:
- name: Build Linux
if: matrix.os == 'ubuntu-latest'
run: |
sudo apt-get install -y rpm
yarn build:npm linux
yarn build:linux
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ vars.RENDERER_VITE_AIHUBMIX_SECRET }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_CHERRYAI_CLIENT_SECRET: ${{ secrets.MAIN_VITE_CHERRYAI_CLIENT_SECRET }}
MAIN_VITE_MINERU_API_KEY: ${{ secrets.MAIN_VITE_MINERU_API_KEY }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ secrets.RENDERER_VITE_AIHUBMIX_SECRET }}
RENDERER_VITE_PPIO_APP_SECRET: ${{ secrets.RENDERER_VITE_PPIO_APP_SECRET }}
- name: Build Mac
if: matrix.os == 'macos-latest'
run: |
yarn build:npm mac
yarn build:mac
env:
CSC_LINK: ${{ secrets.CSC_LINK }}
CSC_KEY_PASSWORD: ${{ secrets.CSC_KEY_PASSWORD }}
APPLE_ID: ${{ secrets.APPLE_ID }}
APPLE_APP_SPECIFIC_PASSWORD: ${{ secrets.APPLE_APP_SPECIFIC_PASSWORD }}
APPLE_TEAM_ID: ${{ secrets.APPLE_TEAM_ID }}
APPLE_ID: ${{ vars.APPLE_ID }}
APPLE_APP_SPECIFIC_PASSWORD: ${{ vars.APPLE_APP_SPECIFIC_PASSWORD }}
APPLE_TEAM_ID: ${{ vars.APPLE_TEAM_ID }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ vars.RENDERER_VITE_AIHUBMIX_SECRET }}
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_CHERRYAI_CLIENT_SECRET: ${{ secrets.MAIN_VITE_CHERRYAI_CLIENT_SECRET }}
MAIN_VITE_MINERU_API_KEY: ${{ secrets.MAIN_VITE_MINERU_API_KEY }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ secrets.RENDERER_VITE_AIHUBMIX_SECRET }}
RENDERER_VITE_PPIO_APP_SECRET: ${{ secrets.RENDERER_VITE_PPIO_APP_SECRET }}
- name: Build Windows
if: matrix.os == 'windows-latest'
run: |
yarn build:npm windows
yarn build:win
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ vars.RENDERER_VITE_AIHUBMIX_SECRET }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_CHERRYAI_CLIENT_SECRET: ${{ secrets.MAIN_VITE_CHERRYAI_CLIENT_SECRET }}
MAIN_VITE_MINERU_API_KEY: ${{ secrets.MAIN_VITE_MINERU_API_KEY }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ secrets.RENDERER_VITE_AIHUBMIX_SECRET }}
RENDERER_VITE_PPIO_APP_SECRET: ${{ secrets.RENDERER_VITE_PPIO_APP_SECRET }}
- name: Rename artifacts with nightly format
shell: bash
@@ -226,7 +219,7 @@ jobs:
shell: bash
- name: Download all artifacts
uses: actions/download-artifact@v5
uses: actions/download-artifact@v4
with:
path: all-artifacts
merge-multiple: false

View File

@@ -1,30 +1,24 @@
name: Pull Request CI
permissions:
contents: read
on:
workflow_dispatch:
pull_request:
branches:
- main
- develop
- v2
types: [ready_for_review, synchronize, opened]
jobs:
build:
runs-on: ubuntu-latest
env:
PRCI: true
if: github.event.pull_request.draft == false
steps:
- name: Check out Git repository
uses: actions/checkout@v5
uses: actions/checkout@v4
- name: Install Node.js
uses: actions/setup-node@v5
uses: actions/setup-node@v4
with:
node-version: 20
@@ -48,17 +42,8 @@ jobs:
- name: Install Dependencies
run: yarn install
- name: Build Check
run: yarn build:check
- name: Lint Check
run: yarn test:lint
- name: Format Check
run: yarn format:check
- name: Type Check
run: yarn typecheck
- name: i18n Check
run: yarn check:i18n
- name: Test
run: yarn test

View File

@@ -25,7 +25,7 @@ jobs:
steps:
- name: Check out Git repository
uses: actions/checkout@v5
uses: actions/checkout@v4
with:
fetch-depth: 0
@@ -39,15 +39,8 @@ jobs:
echo "tag=${GITHUB_REF#refs/tags/}" >> $GITHUB_OUTPUT
fi
- name: Set package.json version
shell: bash
run: |
TAG="${{ steps.get-tag.outputs.tag }}"
VERSION="${TAG#v}"
npm version "$VERSION" --no-git-tag-version --allow-same-version
- name: Install Node.js
uses: actions/setup-node@v5
uses: actions/setup-node@v4
with:
node-version: 20
@@ -79,46 +72,45 @@ jobs:
- name: Build Linux
if: matrix.os == 'ubuntu-latest'
run: |
sudo apt-get install -y rpm
yarn build:npm linux
yarn build:linux
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_CHERRYAI_CLIENT_SECRET: ${{ secrets.MAIN_VITE_CHERRYAI_CLIENT_SECRET }}
MAIN_VITE_MINERU_API_KEY: ${{ secrets.MAIN_VITE_MINERU_API_KEY }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ secrets.RENDERER_VITE_AIHUBMIX_SECRET }}
RENDERER_VITE_PPIO_APP_SECRET: ${{ secrets.RENDERER_VITE_PPIO_APP_SECRET }}
MAIN_VITE_MINERU_API_KEY: ${{ vars.MAIN_VITE_MINERU_API_KEY }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ vars.RENDERER_VITE_AIHUBMIX_SECRET }}
RENDERER_VITE_PPIO_APP_SECRET: ${{ vars.RENDERER_VITE_PPIO_APP_SECRET }}
- name: Build Mac
if: matrix.os == 'macos-latest'
run: |
sudo -H pip install setuptools
yarn build:npm mac
yarn build:mac
env:
CSC_LINK: ${{ secrets.CSC_LINK }}
CSC_KEY_PASSWORD: ${{ secrets.CSC_KEY_PASSWORD }}
APPLE_ID: ${{ secrets.APPLE_ID }}
APPLE_APP_SPECIFIC_PASSWORD: ${{ secrets.APPLE_APP_SPECIFIC_PASSWORD }}
APPLE_TEAM_ID: ${{ secrets.APPLE_TEAM_ID }}
APPLE_ID: ${{ vars.APPLE_ID }}
APPLE_APP_SPECIFIC_PASSWORD: ${{ vars.APPLE_APP_SPECIFIC_PASSWORD }}
APPLE_TEAM_ID: ${{ vars.APPLE_TEAM_ID }}
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_CHERRYAI_CLIENT_SECRET: ${{ secrets.MAIN_VITE_CHERRYAI_CLIENT_SECRET }}
MAIN_VITE_MINERU_API_KEY: ${{ secrets.MAIN_VITE_MINERU_API_KEY }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ secrets.RENDERER_VITE_AIHUBMIX_SECRET }}
RENDERER_VITE_PPIO_APP_SECRET: ${{ secrets.RENDERER_VITE_PPIO_APP_SECRET }}
MAIN_VITE_MINERU_API_KEY: ${{ vars.MAIN_VITE_MINERU_API_KEY }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ vars.RENDERER_VITE_AIHUBMIX_SECRET }}
RENDERER_VITE_PPIO_APP_SECRET: ${{ vars.RENDERER_VITE_PPIO_APP_SECRET }}
- name: Build Windows
if: matrix.os == 'windows-latest'
run: |
yarn build:npm windows
yarn build:win
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
NODE_OPTIONS: --max-old-space-size=8192
MAIN_VITE_CHERRYAI_CLIENT_SECRET: ${{ secrets.MAIN_VITE_CHERRYAI_CLIENT_SECRET }}
MAIN_VITE_MINERU_API_KEY: ${{ secrets.MAIN_VITE_MINERU_API_KEY }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ secrets.RENDERER_VITE_AIHUBMIX_SECRET }}
RENDERER_VITE_PPIO_APP_SECRET: ${{ secrets.RENDERER_VITE_PPIO_APP_SECRET }}
MAIN_VITE_MINERU_API_KEY: ${{ vars.MAIN_VITE_MINERU_API_KEY }}
RENDERER_VITE_AIHUBMIX_SECRET: ${{ vars.RENDERER_VITE_AIHUBMIX_SECRET }}
RENDERER_VITE_PPIO_APP_SECRET: ${{ vars.RENDERER_VITE_PPIO_APP_SECRET }}
- name: Release
uses: ncipollo/release-action@v1
@@ -127,5 +119,5 @@ jobs:
allowUpdates: true
makeLatest: false
tag: ${{ steps.get-tag.outputs.tag }}
artifacts: 'dist/*.exe,dist/*.zip,dist/*.dmg,dist/*.AppImage,dist/*.snap,dist/*.deb,dist/*.rpm,dist/*.tar.gz,dist/latest*.yml,dist/rc*.yml,dist/beta*.yml,dist/*.blockmap'
artifacts: 'dist/*.exe,dist/*.zip,dist/*.dmg,dist/*.AppImage,dist/*.snap,dist/*.deb,dist/*.rpm,dist/*.tar.gz,dist/latest*.yml,dist/rc*.yml,dist/*.blockmap'
token: ${{ secrets.GITHUB_TOKEN }}

7
.gitignore vendored
View File

@@ -37,7 +37,6 @@ dist
out
mcp_server
stats.html
.eslintcache
# ENV
.env
@@ -54,18 +53,12 @@ local
.qwen/*
.trae/*
.claude-code-router/*
.codebuddy/*
.zed/*
CLAUDE.local.md
# vitest
coverage
.vitest-cache
vitest.config.*.timestamp-*
# TypeScript incremental build
.tsbuildinfo
# playwright
playwright-report
test-results

View File

@@ -1,215 +0,0 @@
{
"$schema": "./node_modules/oxlint/configuration_schema.json",
"categories": {},
"env": {
"es2022": true
},
"globals": {},
"ignorePatterns": [
"node_modules/**",
"build/**",
"dist/**",
"out/**",
"local/**",
".yarn/**",
".gitignore",
"scripts/cloudflare-worker.js",
"src/main/integration/nutstore/sso/lib/**",
"src/main/integration/cherryai/index.js",
"src/main/integration/nutstore/sso/lib/**",
"src/renderer/src/ui/**",
"packages/**/dist",
"eslint.config.mjs"
],
"overrides": [
// set different env
{
"env": {
"node": true
},
"files": ["src/main/**", "resources/scripts/**", "scripts/**", "playwright.config.ts", "electron.vite.config.ts"]
},
{
"env": {
"browser": true
},
"files": [
"src/renderer/**/*.{ts,tsx}",
"packages/aiCore/**",
"packages/extension-table-plus/**",
"resources/js/**"
]
},
{
"env": {
"node": true,
"vitest": true
},
"files": ["**/__tests__/*.test.{ts,tsx}", "tests/**"]
},
{
"env": {
"browser": true,
"node": true
},
"files": ["src/preload/**"]
}
],
// We don't use the React plugin here because its behavior differs slightly from that of ESLint's React plugin.
"plugins": ["unicorn", "typescript", "oxc", "import"],
"rules": {
"constructor-super": "error",
"for-direction": "error",
"getter-return": "error",
"no-array-constructor": "off",
// "import/no-cycle": "error", // tons of error, bro
"no-async-promise-executor": "error",
"no-caller": "warn",
"no-case-declarations": "error",
"no-class-assign": "error",
"no-compare-neg-zero": "error",
"no-cond-assign": "error",
"no-const-assign": "error",
"no-constant-binary-expression": "error",
"no-constant-condition": "error",
"no-control-regex": "error",
"no-debugger": "error",
"no-delete-var": "error",
"no-dupe-args": "error",
"no-dupe-class-members": "error",
"no-dupe-else-if": "error",
"no-dupe-keys": "error",
"no-duplicate-case": "error",
"no-empty": "error",
"no-empty-character-class": "error",
"no-empty-pattern": "error",
"no-empty-static-block": "error",
"no-eval": "warn",
"no-ex-assign": "error",
"no-extra-boolean-cast": "error",
"no-fallthrough": "warn",
"no-func-assign": "error",
"no-global-assign": "error",
"no-import-assign": "error",
"no-invalid-regexp": "error",
"no-irregular-whitespace": "error",
"no-loss-of-precision": "error",
"no-misleading-character-class": "error",
"no-new-native-nonconstructor": "error",
"no-nonoctal-decimal-escape": "error",
"no-obj-calls": "error",
"no-octal": "error",
"no-prototype-builtins": "error",
"no-redeclare": "error",
"no-regex-spaces": "error",
"no-self-assign": "error",
"no-setter-return": "error",
"no-shadow-restricted-names": "error",
"no-sparse-arrays": "error",
"no-this-before-super": "error",
"no-unassigned-vars": "warn",
"no-undef": "error",
"no-unexpected-multiline": "error",
"no-unreachable": "error",
"no-unsafe-finally": "error",
"no-unsafe-negation": "error",
"no-unsafe-optional-chaining": "error",
"no-unused-expressions": "off", // this rule disallow us to use expression to call function, like `condition && fn()`
"no-unused-labels": "error",
"no-unused-private-class-members": "error",
"no-unused-vars": ["error", { "caughtErrors": "none" }],
"no-useless-backreference": "error",
"no-useless-catch": "error",
"no-useless-escape": "error",
"no-useless-rename": "warn",
"no-with": "error",
"oxc/bad-array-method-on-arguments": "warn",
"oxc/bad-char-at-comparison": "warn",
"oxc/bad-comparison-sequence": "warn",
"oxc/bad-min-max-func": "warn",
"oxc/bad-object-literal-comparison": "warn",
"oxc/bad-replace-all-arg": "warn",
"oxc/const-comparisons": "warn",
"oxc/double-comparisons": "warn",
"oxc/erasing-op": "warn",
"oxc/missing-throw": "warn",
"oxc/number-arg-out-of-range": "warn",
"oxc/only-used-in-recursion": "off", // manually off bacause of existing warning. may turn it on in the future
"oxc/uninvoked-array-callback": "warn",
"require-yield": "error",
"typescript/await-thenable": "warn",
// "typescript/ban-ts-comment": "error",
"typescript/no-array-constructor": "error",
// "typescript/consistent-type-imports": "error",
"typescript/no-array-delete": "warn",
"typescript/no-base-to-string": "warn",
"typescript/no-duplicate-enum-values": "error",
"typescript/no-duplicate-type-constituents": "warn",
"typescript/no-empty-object-type": "off",
"typescript/no-explicit-any": "off", // not safe but too many errors
"typescript/no-extra-non-null-assertion": "error",
"typescript/no-floating-promises": "warn",
"typescript/no-for-in-array": "warn",
"typescript/no-implied-eval": "warn",
"typescript/no-meaningless-void-operator": "warn",
"typescript/no-misused-new": "error",
"typescript/no-misused-spread": "warn",
"typescript/no-namespace": "error",
"typescript/no-non-null-asserted-optional-chain": "off", // it's off now. but may turn it on.
"typescript/no-redundant-type-constituents": "warn",
"typescript/no-require-imports": "off",
"typescript/no-this-alias": "error",
"typescript/no-unnecessary-parameter-property-assignment": "warn",
"typescript/no-unnecessary-type-constraint": "error",
"typescript/no-unsafe-declaration-merging": "error",
"typescript/no-unsafe-function-type": "error",
"typescript/no-unsafe-unary-minus": "warn",
"typescript/no-useless-empty-export": "warn",
"typescript/no-wrapper-object-types": "error",
"typescript/prefer-as-const": "error",
"typescript/prefer-namespace-keyword": "error",
"typescript/require-array-sort-compare": "warn",
"typescript/restrict-template-expressions": "warn",
"typescript/triple-slash-reference": "error",
"typescript/unbound-method": "warn",
"unicorn/no-await-in-promise-methods": "warn",
"unicorn/no-empty-file": "off", // manually off bacause of existing warning. may turn it on in the future
"unicorn/no-invalid-fetch-options": "warn",
"unicorn/no-invalid-remove-event-listener": "warn",
"unicorn/no-new-array": "off", // manually off bacause of existing warning. may turn it on in the future
"unicorn/no-single-promise-in-promise-methods": "warn",
"unicorn/no-thenable": "off", // manually off bacause of existing warning. may turn it on in the future
"unicorn/no-unnecessary-await": "warn",
"unicorn/no-useless-fallback-in-spread": "warn",
"unicorn/no-useless-length-check": "warn",
"unicorn/no-useless-spread": "off", // manually off bacause of existing warning. may turn it on in the future
"unicorn/prefer-set-size": "warn",
"unicorn/prefer-string-starts-ends-with": "warn",
"use-isnan": "error",
"valid-typeof": "error"
},
"settings": {
"jsdoc": {
"augmentsExtendsReplacesDocs": false,
"exemptDestructuredRootsFromChecks": false,
"ignoreInternal": false,
"ignorePrivate": false,
"ignoreReplacesDocs": true,
"implementsReplacesDocs": false,
"overrideReplacesDocs": true,
"tagNamePreference": {}
},
"jsx-a11y": {
"attributes": {},
"components": {},
"polymorphicPropName": null
},
"next": {
"rootDir": []
},
"react": {
"formComponents": [],
"linkComponents": []
}
}
}

9
.prettierignore Normal file
View File

@@ -0,0 +1,9 @@
out
dist
pnpm-lock.yaml
LICENSE.md
tsconfig.json
tsconfig.*.json
CHANGELOG*.md
agents.json
src/renderer/src/integration/nutstore/sso/lib

11
.prettierrc Normal file
View File

@@ -0,0 +1,11 @@
{
"bracketSameLine": true,
"endOfLine": "lf",
"jsonRecursiveSort": true,
"jsonSortOrder": "{\"*\": \"lexical\"}",
"plugins": ["prettier-plugin-sort-json"],
"printWidth": 120,
"semi": false,
"singleQuote": true,
"trailingComma": "none"
}

View File

@@ -1,11 +1,8 @@
{
"recommendations": [
"dbaeumer.vscode-eslint",
"esbenp.prettier-vscode",
"editorconfig.editorconfig",
"lokalise.i18n-ally",
"bradlc.vscode-tailwindcss",
"vitest.explorer",
"oxc.oxc-vscode",
"biomejs.biome"
"lokalise.i18n-ally"
]
}

45
.vscode/launch.json vendored
View File

@@ -1,40 +1,39 @@
{
"compounds": [
{
"configurations": ["Debug Main Process", "Debug Renderer Process"],
"name": "Debug All",
"presentation": {
"order": 1
}
}
],
"version": "0.2.0",
"configurations": [
{
"cwd": "${workspaceRoot}",
"env": {
"REMOTE_DEBUGGING_PORT": "9222"
},
"envFile": "${workspaceFolder}/.env",
"name": "Debug Main Process",
"request": "launch",
"runtimeArgs": ["--inspect", "--sourcemap"],
"runtimeExecutable": "${workspaceRoot}/node_modules/.bin/electron-vite",
"type": "node",
"request": "launch",
"cwd": "${workspaceRoot}",
"runtimeExecutable": "${workspaceRoot}/node_modules/.bin/electron-vite",
"windows": {
"runtimeExecutable": "${workspaceRoot}/node_modules/.bin/electron-vite.cmd"
},
"runtimeArgs": ["--inspect", "--sourcemap"],
"env": {
"REMOTE_DEBUGGING_PORT": "9222"
}
},
{
"name": "Debug Renderer Process",
"port": 9222,
"request": "attach",
"type": "chrome",
"webRoot": "${workspaceFolder}/src/renderer",
"timeout": 3000000,
"presentation": {
"hidden": true
},
"request": "attach",
"timeout": 3000000,
"type": "chrome",
"webRoot": "${workspaceFolder}/src/renderer"
}
}
],
"version": "0.2.0"
"compounds": [
{
"name": "Debug All",
"configurations": ["Debug Main Process", "Debug Renderer Process"],
"presentation": {
"order": 1
}
}
]
}

19
.vscode/settings.json vendored
View File

@@ -1,38 +1,33 @@
{
"[css]": {
"editor.defaultFormatter": "biomejs.biome"
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[javascript]": {
"editor.defaultFormatter": "biomejs.biome"
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[json]": {
"editor.defaultFormatter": "biomejs.biome"
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[jsonc]": {
"editor.defaultFormatter": "biomejs.biome"
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[markdown]": {
"files.trimTrailingWhitespace": false
},
"[scss]": {
"editor.defaultFormatter": "biomejs.biome"
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[typescript]": {
"editor.defaultFormatter": "biomejs.biome"
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"[typescriptreact]": {
"editor.defaultFormatter": "biomejs.biome"
"editor.defaultFormatter": "esbenp.prettier-vscode"
},
"editor.codeActionsOnSave": {
"source.fixAll.biome": "explicit",
"source.fixAll.eslint": "explicit",
"source.fixAll.oxc": "explicit",
"source.organizeImports": "never"
},
"editor.formatOnSave": true,
"files.associations": {
"*.css": "tailwindcss"
},
"files.eol": "\n",
"i18n-ally.displayLanguage": "zh-cn",
"i18n-ally.enabledFrameworks": ["react-i18next", "i18next"],

View File

@@ -1,13 +0,0 @@
diff --git a/dist/index.mjs b/dist/index.mjs
index b957cb824faa79cf01ba3a504f221870bd8e306a..4d71d30f655775d61537d9d8b73f6e17d41fa67e 100644
--- a/dist/index.mjs
+++ b/dist/index.mjs
@@ -452,7 +452,7 @@ function convertToGoogleGenerativeAIMessages(prompt, options) {
// src/get-model-path.ts
function getModelPath(modelId) {
- return modelId.includes("/") ? modelId : `models/${modelId}`;
+ return modelId?.includes("models/") ? modelId : `models/${modelId}`;
}
// src/google-generative-ai-options.ts

View File

@@ -1,30 +0,0 @@
diff --git a/index.js b/index.js
index dc071739e79876dff88e1be06a9168e294222d13..b9df7525c62bdf777e89e732e1b0c81f84d872f2 100644
--- a/index.js
+++ b/index.js
@@ -380,7 +380,7 @@ if (!nativeBinding || process.env.NAPI_RS_FORCE_WASI) {
}
}
-if (!nativeBinding) {
+if (!nativeBinding && process.platform !== 'linux') {
if (loadErrors.length > 0) {
throw new Error(
`Cannot find native binding. ` +
@@ -392,6 +392,13 @@ if (!nativeBinding) {
throw new Error(`Failed to load native binding`)
}
-module.exports = nativeBinding
-module.exports.OcrAccuracy = nativeBinding.OcrAccuracy
-module.exports.recognize = nativeBinding.recognize
+if (process.platform === 'linux') {
+ module.exports = {OcrAccuracy: {
+ Fast: 0,
+ Accurate: 1
+ }, recognize: () => Promise.resolve({text: '', confidence: 1.0})}
+}else{
+ module.exports = nativeBinding
+ module.exports.OcrAccuracy = nativeBinding.OcrAccuracy
+ module.exports.recognize = nativeBinding.recognize
+}

View File

@@ -1,48 +0,0 @@
diff --git a/dist/index.cjs b/dist/index.cjs
index 8e560a4406c5cc616c11bb9fd5455ac0dcf47fa3..c7cd0d65ddc971bff71e89f610de82cfdaa5a8c7 100644
--- a/dist/index.cjs
+++ b/dist/index.cjs
@@ -413,6 +413,19 @@ var DragHandlePlugin = ({
}
return false;
},
+ scroll(view) {
+ if (!element || locked) {
+ return false;
+ }
+ if (view.hasFocus()) {
+ hideHandle();
+ currentNode = null;
+ currentNodePos = -1;
+ onNodeChange == null ? void 0 : onNodeChange({ editor, node: null, pos: -1 });
+ return false;
+ }
+ return false;
+ },
mouseleave(_view, e) {
if (locked) {
return false;
diff --git a/dist/index.js b/dist/index.js
index 39e4c3ef9986cd25544d9d3994cf6a9ada74b145..378d9130abbfdd0e1e4f743b5b537743c9ab07d0 100644
--- a/dist/index.js
+++ b/dist/index.js
@@ -387,6 +387,19 @@ var DragHandlePlugin = ({
}
return false;
},
+ scroll(view) {
+ if (!element || locked) {
+ return false;
+ }
+ if (view.hasFocus()) {
+ hideHandle();
+ currentNode = null;
+ currentNodePos = -1;
+ onNodeChange == null ? void 0 : onNodeChange({ editor, node: null, pos: -1 });
+ return false;
+ }
+ return false;
+ },
mouseleave(_view, e) {
if (locked) {
return false;

View File

@@ -1,5 +1,5 @@
diff --git a/es/dropdown/dropdown.js b/es/dropdown/dropdown.js
index 2e45574398ff68450022a0078e213cc81fe7454e..58ba7789939b7805a89f92b93d222f8fb1168bdf 100644
index 986877a762b9ad0aca596a8552732cd12d2eaabb..1f18aa2ea745e68950e4cee16d4d655f5c835fd5 100644
--- a/es/dropdown/dropdown.js
+++ b/es/dropdown/dropdown.js
@@ -2,7 +2,7 @@
@@ -11,7 +11,7 @@ index 2e45574398ff68450022a0078e213cc81fe7454e..58ba7789939b7805a89f92b93d222f8f
import classNames from 'classnames';
import RcDropdown from 'rc-dropdown';
import useEvent from "rc-util/es/hooks/useEvent";
@@ -160,8 +160,10 @@ const Dropdown = props => {
@@ -158,8 +158,10 @@ const Dropdown = props => {
className: `${prefixCls}-menu-submenu-arrow`
}, direction === 'rtl' ? (/*#__PURE__*/React.createElement(LeftOutlined, {
className: `${prefixCls}-menu-submenu-arrow-icon`
@@ -24,8 +24,22 @@ index 2e45574398ff68450022a0078e213cc81fe7454e..58ba7789939b7805a89f92b93d222f8f
}))),
mode: "vertical",
selectable: false,
diff --git a/es/dropdown/style/index.js b/es/dropdown/style/index.js
index 768c01783002c6901c85a73061ff6b3e776a60ce..39b1b95a56cdc9fb586a193c3adad5141f5cf213 100644
--- a/es/dropdown/style/index.js
+++ b/es/dropdown/style/index.js
@@ -240,7 +240,8 @@ const genBaseStyle = token => {
marginInlineEnd: '0 !important',
color: token.colorTextDescription,
fontSize: fontSizeIcon,
- fontStyle: 'normal'
+ fontStyle: 'normal',
+ marginTop: 3,
}
}
}),
diff --git a/es/select/useIcons.js b/es/select/useIcons.js
index 572aaaa0899f429cbf8a7181f2eeada545f76dcb..4e175c8d7713dd6422f8bcdc74ee671a835de6ce 100644
index 959115be936ef8901548af2658c5dcfdc5852723..c812edd52123eb0faf4638b1154fcfa1b05b513b 100644
--- a/es/select/useIcons.js
+++ b/es/select/useIcons.js
@@ -4,10 +4,10 @@ import * as React from 'react';
@@ -37,10 +51,10 @@ index 572aaaa0899f429cbf8a7181f2eeada545f76dcb..4e175c8d7713dd6422f8bcdc74ee671a
import SearchOutlined from "@ant-design/icons/es/icons/SearchOutlined";
import { devUseWarning } from '../_util/warning';
+import { ChevronDown } from 'lucide-react';
export default function useIcons({
suffixIcon,
clearIcon,
@@ -54,8 +54,10 @@ export default function useIcons({
export default function useIcons(_ref) {
let {
suffixIcon,
@@ -56,8 +56,10 @@ export default function useIcons(_ref) {
className: iconCls
}));
}

View File

@@ -0,0 +1,279 @@
diff --git a/client.js b/client.js
index 33b4ff6309d5f29187dab4e285d07dac20340bab..8f568637ee9e4677585931fb0284c8165a933f69 100644
--- a/client.js
+++ b/client.js
@@ -433,7 +433,7 @@ class OpenAI {
'User-Agent': this.getUserAgent(),
'X-Stainless-Retry-Count': String(retryCount),
...(options.timeout ? { 'X-Stainless-Timeout': String(Math.trunc(options.timeout / 1000)) } : {}),
- ...(0, detect_platform_1.getPlatformHeaders)(),
+ // ...(0, detect_platform_1.getPlatformHeaders)(),
'OpenAI-Organization': this.organization,
'OpenAI-Project': this.project,
},
diff --git a/client.mjs b/client.mjs
index c34c18213073540ebb296ea540b1d1ad39527906..1ce1a98256d7e90e26ca963582f235b23e996e73 100644
--- a/client.mjs
+++ b/client.mjs
@@ -430,7 +430,7 @@ export class OpenAI {
'User-Agent': this.getUserAgent(),
'X-Stainless-Retry-Count': String(retryCount),
...(options.timeout ? { 'X-Stainless-Timeout': String(Math.trunc(options.timeout / 1000)) } : {}),
- ...getPlatformHeaders(),
+ // ...getPlatformHeaders(),
'OpenAI-Organization': this.organization,
'OpenAI-Project': this.project,
},
diff --git a/core/error.js b/core/error.js
index a12d9d9ccd242050161adeb0f82e1b98d9e78e20..fe3a5462480558bc426deea147f864f12b36f9bd 100644
--- a/core/error.js
+++ b/core/error.js
@@ -40,7 +40,7 @@ class APIError extends OpenAIError {
if (!status || !headers) {
return new APIConnectionError({ message, cause: (0, errors_1.castToError)(errorResponse) });
}
- const error = errorResponse?.['error'];
+ const error = errorResponse?.['error'] || errorResponse;
if (status === 400) {
return new BadRequestError(status, error, message, headers);
}
diff --git a/core/error.mjs b/core/error.mjs
index 83cefbaffeb8c657536347322d8de9516af479a2..63334b7972ec04882aa4a0800c1ead5982345045 100644
--- a/core/error.mjs
+++ b/core/error.mjs
@@ -36,7 +36,7 @@ export class APIError extends OpenAIError {
if (!status || !headers) {
return new APIConnectionError({ message, cause: castToError(errorResponse) });
}
- const error = errorResponse?.['error'];
+ const error = errorResponse?.['error'] || errorResponse;
if (status === 400) {
return new BadRequestError(status, error, message, headers);
}
diff --git a/resources/embeddings.js b/resources/embeddings.js
index 2404264d4ba0204322548945ebb7eab3bea82173..8f1bc45cc45e0797d50989d96b51147b90ae6790 100644
--- a/resources/embeddings.js
+++ b/resources/embeddings.js
@@ -5,52 +5,64 @@ exports.Embeddings = void 0;
const resource_1 = require("../core/resource.js");
const utils_1 = require("../internal/utils.js");
class Embeddings extends resource_1.APIResource {
- /**
- * Creates an embedding vector representing the input text.
- *
- * @example
- * ```ts
- * const createEmbeddingResponse =
- * await client.embeddings.create({
- * input: 'The quick brown fox jumped over the lazy dog',
- * model: 'text-embedding-3-small',
- * });
- * ```
- */
- create(body, options) {
- const hasUserProvidedEncodingFormat = !!body.encoding_format;
- // No encoding_format specified, defaulting to base64 for performance reasons
- // See https://github.com/openai/openai-node/pull/1312
- let encoding_format = hasUserProvidedEncodingFormat ? body.encoding_format : 'base64';
- if (hasUserProvidedEncodingFormat) {
- (0, utils_1.loggerFor)(this._client).debug('embeddings/user defined encoding_format:', body.encoding_format);
- }
- const response = this._client.post('/embeddings', {
- body: {
- ...body,
- encoding_format: encoding_format,
- },
- ...options,
- });
- // if the user specified an encoding_format, return the response as-is
- if (hasUserProvidedEncodingFormat) {
- return response;
- }
- // in this stage, we are sure the user did not specify an encoding_format
- // and we defaulted to base64 for performance reasons
- // we are sure then that the response is base64 encoded, let's decode it
- // the returned result will be a float32 array since this is OpenAI API's default encoding
- (0, utils_1.loggerFor)(this._client).debug('embeddings/decoding base64 embeddings from base64');
- return response._thenUnwrap((response) => {
- if (response && response.data) {
- response.data.forEach((embeddingBase64Obj) => {
- const embeddingBase64Str = embeddingBase64Obj.embedding;
- embeddingBase64Obj.embedding = (0, utils_1.toFloat32Array)(embeddingBase64Str);
- });
- }
- return response;
- });
- }
+ /**
+ * Creates an embedding vector representing the input text.
+ *
+ * @example
+ * ```ts
+ * const createEmbeddingResponse =
+ * await client.embeddings.create({
+ * input: 'The quick brown fox jumped over the lazy dog',
+ * model: 'text-embedding-3-small',
+ * });
+ * ```
+ */
+ create(body, options) {
+ const hasUserProvidedEncodingFormat = !!body.encoding_format;
+ // No encoding_format specified, defaulting to base64 for performance reasons
+ // See https://github.com/openai/openai-node/pull/1312
+ let encoding_format = hasUserProvidedEncodingFormat
+ ? body.encoding_format
+ : "base64";
+ if (body.model.includes("jina")) {
+ encoding_format = undefined;
+ }
+ if (hasUserProvidedEncodingFormat) {
+ (0, utils_1.loggerFor)(this._client).debug(
+ "embeddings/user defined encoding_format:",
+ body.encoding_format
+ );
+ }
+ const response = this._client.post("/embeddings", {
+ body: {
+ ...body,
+ encoding_format: encoding_format,
+ },
+ ...options,
+ });
+ // if the user specified an encoding_format, return the response as-is
+ if (hasUserProvidedEncodingFormat || body.model.includes("jina")) {
+ return response;
+ }
+ // in this stage, we are sure the user did not specify an encoding_format
+ // and we defaulted to base64 for performance reasons
+ // we are sure then that the response is base64 encoded, let's decode it
+ // the returned result will be a float32 array since this is OpenAI API's default encoding
+ (0, utils_1.loggerFor)(this._client).debug(
+ "embeddings/decoding base64 embeddings from base64"
+ );
+ return response._thenUnwrap((response) => {
+ if (response && response.data && typeof response.data[0]?.embedding === 'string') {
+ response.data.forEach((embeddingBase64Obj) => {
+ const embeddingBase64Str = embeddingBase64Obj.embedding;
+ embeddingBase64Obj.embedding = (0, utils_1.toFloat32Array)(
+ embeddingBase64Str
+ );
+ });
+ }
+ return response;
+ });
+ }
}
exports.Embeddings = Embeddings;
//# sourceMappingURL=embeddings.js.map
diff --git a/resources/embeddings.mjs b/resources/embeddings.mjs
index 19dcaef578c194a89759c4360073cfd4f7dd2cbf..0284e9cc615c900eff508eb595f7360a74bd9200 100644
--- a/resources/embeddings.mjs
+++ b/resources/embeddings.mjs
@@ -2,51 +2,61 @@
import { APIResource } from "../core/resource.mjs";
import { loggerFor, toFloat32Array } from "../internal/utils.mjs";
export class Embeddings extends APIResource {
- /**
- * Creates an embedding vector representing the input text.
- *
- * @example
- * ```ts
- * const createEmbeddingResponse =
- * await client.embeddings.create({
- * input: 'The quick brown fox jumped over the lazy dog',
- * model: 'text-embedding-3-small',
- * });
- * ```
- */
- create(body, options) {
- const hasUserProvidedEncodingFormat = !!body.encoding_format;
- // No encoding_format specified, defaulting to base64 for performance reasons
- // See https://github.com/openai/openai-node/pull/1312
- let encoding_format = hasUserProvidedEncodingFormat ? body.encoding_format : 'base64';
- if (hasUserProvidedEncodingFormat) {
- loggerFor(this._client).debug('embeddings/user defined encoding_format:', body.encoding_format);
- }
- const response = this._client.post('/embeddings', {
- body: {
- ...body,
- encoding_format: encoding_format,
- },
- ...options,
- });
- // if the user specified an encoding_format, return the response as-is
- if (hasUserProvidedEncodingFormat) {
- return response;
- }
- // in this stage, we are sure the user did not specify an encoding_format
- // and we defaulted to base64 for performance reasons
- // we are sure then that the response is base64 encoded, let's decode it
- // the returned result will be a float32 array since this is OpenAI API's default encoding
- loggerFor(this._client).debug('embeddings/decoding base64 embeddings from base64');
- return response._thenUnwrap((response) => {
- if (response && response.data) {
- response.data.forEach((embeddingBase64Obj) => {
- const embeddingBase64Str = embeddingBase64Obj.embedding;
- embeddingBase64Obj.embedding = toFloat32Array(embeddingBase64Str);
- });
- }
- return response;
- });
- }
+ /**
+ * Creates an embedding vector representing the input text.
+ *
+ * @example
+ * ```ts
+ * const createEmbeddingResponse =
+ * await client.embeddings.create({
+ * input: 'The quick brown fox jumped over the lazy dog',
+ * model: 'text-embedding-3-small',
+ * });
+ * ```
+ */
+ create(body, options) {
+ const hasUserProvidedEncodingFormat = !!body.encoding_format;
+ // No encoding_format specified, defaulting to base64 for performance reasons
+ // See https://github.com/openai/openai-node/pull/1312
+ let encoding_format = hasUserProvidedEncodingFormat
+ ? body.encoding_format
+ : "base64";
+ if (body.model.includes("jina")) {
+ encoding_format = undefined;
+ }
+ if (hasUserProvidedEncodingFormat) {
+ loggerFor(this._client).debug(
+ "embeddings/user defined encoding_format:",
+ body.encoding_format
+ );
+ }
+ const response = this._client.post("/embeddings", {
+ body: {
+ ...body,
+ encoding_format: encoding_format,
+ },
+ ...options,
+ });
+ // if the user specified an encoding_format, return the response as-is
+ if (hasUserProvidedEncodingFormat || body.model.includes("jina")) {
+ return response;
+ }
+ // in this stage, we are sure the user did not specify an encoding_format
+ // and we defaulted to base64 for performance reasons
+ // we are sure then that the response is base64 encoded, let's decode it
+ // the returned result will be a float32 array since this is OpenAI API's default encoding
+ loggerFor(this._client).debug(
+ "embeddings/decoding base64 embeddings from base64"
+ );
+ return response._thenUnwrap((response) => {
+ if (response && response.data && typeof response.data[0]?.embedding === 'string') {
+ response.data.forEach((embeddingBase64Obj) => {
+ const embeddingBase64Str = embeddingBase64Obj.embedding;
+ embeddingBase64Obj.embedding = toFloat32Array(embeddingBase64Str);
+ });
+ }
+ return response;
+ });
+ }
}
//# sourceMappingURL=embeddings.mjs.map

Binary file not shown.

View File

@@ -1,348 +0,0 @@
diff --git a/src/constants/languages.d.ts b/src/constants/languages.d.ts
new file mode 100644
index 0000000000000000000000000000000000000000..6a2ba5086187622b8ca8887bcc7406018fba8a89
--- /dev/null
+++ b/src/constants/languages.d.ts
@@ -0,0 +1,43 @@
+/**
+ * Languages with existing tesseract traineddata
+ * https://tesseract-ocr.github.io/tessdoc/Data-Files#data-files-for-version-400-november-29-2016
+ */
+
+// Define the language codes as string literals
+type LanguageCode =
+ | 'afr' | 'amh' | 'ara' | 'asm' | 'aze' | 'aze_cyrl' | 'bel' | 'ben' | 'bod' | 'bos'
+ | 'bul' | 'cat' | 'ceb' | 'ces' | 'chi_sim' | 'chi_tra' | 'chr' | 'cym' | 'dan' | 'deu'
+ | 'dzo' | 'ell' | 'eng' | 'enm' | 'epo' | 'est' | 'eus' | 'fas' | 'fin' | 'fra'
+ | 'frk' | 'frm' | 'gle' | 'glg' | 'grc' | 'guj' | 'hat' | 'heb' | 'hin' | 'hrv'
+ | 'hun' | 'iku' | 'ind' | 'isl' | 'ita' | 'ita_old' | 'jav' | 'jpn' | 'kan' | 'kat'
+ | 'kat_old' | 'kaz' | 'khm' | 'kir' | 'kor' | 'kur' | 'lao' | 'lat' | 'lav' | 'lit'
+ | 'mal' | 'mar' | 'mkd' | 'mlt' | 'msa' | 'mya' | 'nep' | 'nld' | 'nor' | 'ori'
+ | 'pan' | 'pol' | 'por' | 'pus' | 'ron' | 'rus' | 'san' | 'sin' | 'slk' | 'slv'
+ | 'spa' | 'spa_old' | 'sqi' | 'srp' | 'srp_latn' | 'swa' | 'swe' | 'syr' | 'tam' | 'tel'
+ | 'tgk' | 'tgl' | 'tha' | 'tir' | 'tur' | 'uig' | 'ukr' | 'urd' | 'uzb' | 'uzb_cyrl'
+ | 'vie' | 'yid';
+
+// Define the language keys as string literals
+type LanguageKey =
+ | 'AFR' | 'AMH' | 'ARA' | 'ASM' | 'AZE' | 'AZE_CYRL' | 'BEL' | 'BEN' | 'BOD' | 'BOS'
+ | 'BUL' | 'CAT' | 'CEB' | 'CES' | 'CHI_SIM' | 'CHI_TRA' | 'CHR' | 'CYM' | 'DAN' | 'DEU'
+ | 'DZO' | 'ELL' | 'ENG' | 'ENM' | 'EPO' | 'EST' | 'EUS' | 'FAS' | 'FIN' | 'FRA'
+ | 'FRK' | 'FRM' | 'GLE' | 'GLG' | 'GRC' | 'GUJ' | 'HAT' | 'HEB' | 'HIN' | 'HRV'
+ | 'HUN' | 'IKU' | 'IND' | 'ISL' | 'ITA' | 'ITA_OLD' | 'JAV' | 'JPN' | 'KAN' | 'KAT'
+ | 'KAT_OLD' | 'KAZ' | 'KHM' | 'KIR' | 'KOR' | 'KUR' | 'LAO' | 'LAT' | 'LAV' | 'LIT'
+ | 'MAL' | 'MAR' | 'MKD' | 'MLT' | 'MSA' | 'MYA' | 'NEP' | 'NLD' | 'NOR' | 'ORI'
+ | 'PAN' | 'POL' | 'POR' | 'PUS' | 'RON' | 'RUS' | 'SAN' | 'SIN' | 'SLK' | 'SLV'
+ | 'SPA' | 'SPA_OLD' | 'SQI' | 'SRP' | 'SRP_LATN' | 'SWA' | 'SWE' | 'SYR' | 'TAM' | 'TEL'
+ | 'TGK' | 'TGL' | 'THA' | 'TIR' | 'TUR' | 'UIG' | 'UKR' | 'URD' | 'UZB' | 'UZB_CYRL'
+ | 'VIE' | 'YID';
+
+// Create a mapped type to ensure each key maps to its specific value
+type LanguagesMap = {
+ [K in LanguageKey]: LanguageCode;
+};
+
+// Declare the exported constant with the specific type
+export const LANGUAGES: LanguagesMap;
+
+// Export the individual types for use in other modules
+export type { LanguageCode, LanguageKey, LanguagesMap };
\ No newline at end of file
diff --git a/src/index.d.ts b/src/index.d.ts
index 1f5a9c8094fe4de7983467f9efb43bdb4de535f2..16dc95cf68663673e37e189b719cb74897b7735f 100644
--- a/src/index.d.ts
+++ b/src/index.d.ts
@@ -1,31 +1,74 @@
+// Import the languages types
+import { LanguagesMap } from "./constants/languages";
+
+/// <reference types="node" />
+
declare namespace Tesseract {
- function createScheduler(): Scheduler
- function createWorker(langs?: string | string[] | Lang[], oem?: OEM, options?: Partial<WorkerOptions>, config?: string | Partial<InitOptions>): Promise<Worker>
- function setLogging(logging: boolean): void
- function recognize(image: ImageLike, langs?: string, options?: Partial<WorkerOptions>): Promise<RecognizeResult>
- function detect(image: ImageLike, options?: Partial<WorkerOptions>): any
+ function createScheduler(): Scheduler;
+ function createWorker(
+ langs?: LanguageCode | LanguageCode[] | Lang[],
+ oem?: OEM,
+ options?: Partial<WorkerOptions>,
+ config?: string | Partial<InitOptions>
+ ): Promise<Worker>;
+ function setLogging(logging: boolean): void;
+ function recognize(
+ image: ImageLike,
+ langs?: LanguageCode,
+ options?: Partial<WorkerOptions>
+ ): Promise<RecognizeResult>;
+ function detect(image: ImageLike, options?: Partial<WorkerOptions>): any;
+
+ // Export languages constant
+ const languages: LanguagesMap;
+
+ type LanguageCode = import("./constants/languages").LanguageCode;
+ type LanguageKey = import("./constants/languages").LanguageKey;
interface Scheduler {
- addWorker(worker: Worker): string
- addJob(action: 'recognize', ...args: Parameters<Worker['recognize']>): Promise<RecognizeResult>
- addJob(action: 'detect', ...args: Parameters<Worker['detect']>): Promise<DetectResult>
- terminate(): Promise<any>
- getQueueLen(): number
- getNumWorkers(): number
+ addWorker(worker: Worker): string;
+ addJob(
+ action: "recognize",
+ ...args: Parameters<Worker["recognize"]>
+ ): Promise<RecognizeResult>;
+ addJob(
+ action: "detect",
+ ...args: Parameters<Worker["detect"]>
+ ): Promise<DetectResult>;
+ terminate(): Promise<any>;
+ getQueueLen(): number;
+ getNumWorkers(): number;
}
interface Worker {
- load(jobId?: string): Promise<ConfigResult>
- writeText(path: string, text: string, jobId?: string): Promise<ConfigResult>
- readText(path: string, jobId?: string): Promise<ConfigResult>
- removeText(path: string, jobId?: string): Promise<ConfigResult>
- FS(method: string, args: any[], jobId?: string): Promise<ConfigResult>
- reinitialize(langs?: string | Lang[], oem?: OEM, config?: string | Partial<InitOptions>, jobId?: string): Promise<ConfigResult>
- setParameters(params: Partial<WorkerParams>, jobId?: string): Promise<ConfigResult>
- getImage(type: imageType): string
- recognize(image: ImageLike, options?: Partial<RecognizeOptions>, output?: Partial<OutputFormats>, jobId?: string): Promise<RecognizeResult>
- detect(image: ImageLike, jobId?: string): Promise<DetectResult>
- terminate(jobId?: string): Promise<ConfigResult>
+ load(jobId?: string): Promise<ConfigResult>;
+ writeText(
+ path: string,
+ text: string,
+ jobId?: string
+ ): Promise<ConfigResult>;
+ readText(path: string, jobId?: string): Promise<ConfigResult>;
+ removeText(path: string, jobId?: string): Promise<ConfigResult>;
+ FS(method: string, args: any[], jobId?: string): Promise<ConfigResult>;
+ reinitialize(
+ langs?: string | Lang[],
+ oem?: OEM,
+ config?: string | Partial<InitOptions>,
+ jobId?: string
+ ): Promise<ConfigResult>;
+ setParameters(
+ params: Partial<WorkerParams>,
+ jobId?: string
+ ): Promise<ConfigResult>;
+ getImage(type: imageType): string;
+ recognize(
+ image: ImageLike,
+ options?: Partial<RecognizeOptions>,
+ output?: Partial<OutputFormats>,
+ jobId?: string
+ ): Promise<RecognizeResult>;
+ detect(image: ImageLike, jobId?: string): Promise<DetectResult>;
+ terminate(jobId?: string): Promise<ConfigResult>;
}
interface Lang {
@@ -34,43 +77,43 @@ declare namespace Tesseract {
}
interface InitOptions {
- load_system_dawg: string
- load_freq_dawg: string
- load_unambig_dawg: string
- load_punc_dawg: string
- load_number_dawg: string
- load_bigram_dawg: string
- }
-
- type LoggerMessage = {
- jobId: string
- progress: number
- status: string
- userJobId: string
- workerId: string
+ load_system_dawg: string;
+ load_freq_dawg: string;
+ load_unambig_dawg: string;
+ load_punc_dawg: string;
+ load_number_dawg: string;
+ load_bigram_dawg: string;
}
-
+
+ type LoggerMessage = {
+ jobId: string;
+ progress: number;
+ status: string;
+ userJobId: string;
+ workerId: string;
+ };
+
interface WorkerOptions {
- corePath: string
- langPath: string
- cachePath: string
- dataPath: string
- workerPath: string
- cacheMethod: string
- workerBlobURL: boolean
- gzip: boolean
- legacyLang: boolean
- legacyCore: boolean
- logger: (arg: LoggerMessage) => void,
- errorHandler: (arg: any) => void
+ corePath: string;
+ langPath: string;
+ cachePath: string;
+ dataPath: string;
+ workerPath: string;
+ cacheMethod: string;
+ workerBlobURL: boolean;
+ gzip: boolean;
+ legacyLang: boolean;
+ legacyCore: boolean;
+ logger: (arg: LoggerMessage) => void;
+ errorHandler: (arg: any) => void;
}
interface WorkerParams {
- tessedit_pageseg_mode: PSM
- tessedit_char_whitelist: string
- tessedit_char_blacklist: string
- preserve_interword_spaces: string
- user_defined_dpi: string
- [propName: string]: any
+ tessedit_pageseg_mode: PSM;
+ tessedit_char_whitelist: string;
+ tessedit_char_blacklist: string;
+ preserve_interword_spaces: string;
+ user_defined_dpi: string;
+ [propName: string]: any;
}
interface OutputFormats {
text: boolean;
@@ -88,36 +131,36 @@ declare namespace Tesseract {
debug: boolean;
}
interface RecognizeOptions {
- rectangle: Rectangle
- pdfTitle: string
- pdfTextOnly: boolean
- rotateAuto: boolean
- rotateRadians: number
+ rectangle: Rectangle;
+ pdfTitle: string;
+ pdfTextOnly: boolean;
+ rotateAuto: boolean;
+ rotateRadians: number;
}
interface ConfigResult {
- jobId: string
- data: any
+ jobId: string;
+ data: any;
}
interface RecognizeResult {
- jobId: string
- data: Page
+ jobId: string;
+ data: Page;
}
interface DetectResult {
- jobId: string
- data: DetectData
+ jobId: string;
+ data: DetectData;
}
interface DetectData {
- tesseract_script_id: number | null
- script: string | null
- script_confidence: number | null
- orientation_degrees: number | null
- orientation_confidence: number | null
+ tesseract_script_id: number | null;
+ script: string | null;
+ script_confidence: number | null;
+ orientation_degrees: number | null;
+ orientation_confidence: number | null;
}
interface Rectangle {
- left: number
- top: number
- width: number
- height: number
+ left: number;
+ top: number;
+ width: number;
+ height: number;
}
enum OEM {
TESSERACT_ONLY,
@@ -126,28 +169,36 @@ declare namespace Tesseract {
DEFAULT,
}
enum PSM {
- OSD_ONLY = '0',
- AUTO_OSD = '1',
- AUTO_ONLY = '2',
- AUTO = '3',
- SINGLE_COLUMN = '4',
- SINGLE_BLOCK_VERT_TEXT = '5',
- SINGLE_BLOCK = '6',
- SINGLE_LINE = '7',
- SINGLE_WORD = '8',
- CIRCLE_WORD = '9',
- SINGLE_CHAR = '10',
- SPARSE_TEXT = '11',
- SPARSE_TEXT_OSD = '12',
- RAW_LINE = '13'
+ OSD_ONLY = "0",
+ AUTO_OSD = "1",
+ AUTO_ONLY = "2",
+ AUTO = "3",
+ SINGLE_COLUMN = "4",
+ SINGLE_BLOCK_VERT_TEXT = "5",
+ SINGLE_BLOCK = "6",
+ SINGLE_LINE = "7",
+ SINGLE_WORD = "8",
+ CIRCLE_WORD = "9",
+ SINGLE_CHAR = "10",
+ SPARSE_TEXT = "11",
+ SPARSE_TEXT_OSD = "12",
+ RAW_LINE = "13",
}
const enum imageType {
COLOR = 0,
GREY = 1,
- BINARY = 2
+ BINARY = 2,
}
- type ImageLike = string | HTMLImageElement | HTMLCanvasElement | HTMLVideoElement
- | CanvasRenderingContext2D | File | Blob | Buffer | OffscreenCanvas;
+ type ImageLike =
+ | string
+ | HTMLImageElement
+ | HTMLCanvasElement
+ | HTMLVideoElement
+ | CanvasRenderingContext2D
+ | File
+ | Blob
+ | (typeof Buffer extends undefined ? never : Buffer)
+ | OffscreenCanvas;
interface Block {
paragraphs: Paragraph[];
text: string;
@@ -179,7 +230,7 @@ declare namespace Tesseract {
text: string;
confidence: number;
baseline: Baseline;
- rowAttributes: RowAttributes
+ rowAttributes: RowAttributes;
bbox: Bbox;
}
interface Paragraph {

View File

@@ -5,5 +5,3 @@ httpTimeout: 300000
nodeLinker: node-modules
yarnPath: .yarn/releases/yarn-4.9.1.cjs
npmRegistryServer: https://registry.npmjs.org
npmPublishRegistry: https://registry.npmjs.org

1
AGENT.md Symbolic link
View File

@@ -0,0 +1 @@
CLAUDE.md

View File

@@ -5,27 +5,22 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
## Development Commands
### Environment Setup
- **Prerequisites**: Node.js v22.x.x or higher, Yarn 4.9.1
- **Setup Yarn**: `corepack enable && corepack prepare yarn@4.9.1 --activate`
- **Prerequisites**: Node.js v20.x.x, Yarn 4.6.0
- **Setup Yarn**: `corepack enable && corepack prepare yarn@4.6.0 --activate`
- **Install Dependencies**: `yarn install`
- **Add New Dependencies**: `yarn add -D` for renderer-specific dependencies, `yarn add` for others.
### Development
- **Start Development**: `yarn dev` - Runs Electron app in development mode
- **Debug Mode**: `yarn debug` - Starts with debugging enabled, use chrome://inspect
### Testing & Quality
- **Run Tests**: `yarn test` - Runs all tests (Vitest)
- **Run E2E Tests**: `yarn test:e2e` - Playwright end-to-end tests
- **Type Check**: `yarn typecheck` - Checks TypeScript for both node and web
- **Lint**: `yarn lint` - ESLint with auto-fix
- **Format**: `yarn format` - Biome formatting
- **Format**: `yarn format` - Prettier formatting
### Build & Release
- **Build**: `yarn build` - Builds for production (includes typecheck)
- **Platform-specific builds**:
- Windows: `yarn build:win`
@@ -35,7 +30,6 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
## Architecture Overview
### Electron Multi-Process Architecture
- **Main Process** (`src/main/`): Node.js backend handling system integration, file operations, and services
- **Renderer Process** (`src/renderer/`): React-based UI running in Chromium
- **Preload Scripts** (`src/preload/`): Secure bridge between main and renderer processes
@@ -43,7 +37,6 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
### Key Architectural Components
#### Main Process Services (`src/main/services/`)
- **MCPService**: Model Context Protocol server management
- **KnowledgeService**: Document processing and knowledge base management
- **FileStorage/S3Storage/WebDav**: Multiple storage backends
@@ -52,57 +45,43 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
- **SearchService**: Full-text search capabilities
#### AI Core (`src/renderer/src/aiCore/`)
- **Middleware System**: Composable pipeline for AI request processing
- **Client Factory**: Supports multiple AI providers (OpenAI, Anthropic, Gemini, etc.)
- **Stream Processing**: Real-time response handling
#### State Management (`src/renderer/src/store/`)
- **Redux Toolkit**: Centralized state management
- **Persistent Storage**: Redux-persist for data persistence
- **Thunks**: Async actions for complex operations
#### Knowledge Management
- **Embeddings**: Vector search with multiple providers (OpenAI, Voyage, etc.)
- **OCR**: Document text extraction (system OCR, Doc2x, Mineru)
- **Preprocessing**: Document preparation pipeline
- **Loaders**: Support for various file formats (PDF, DOCX, EPUB, etc.)
### Build System
- **Electron-Vite**: Development and build tooling (v4.0.0)
- **Rolldown-Vite**: Using experimental rolldown-vite instead of standard vite
- **Electron-Vite**: Development and build tooling
- **Workspaces**: Monorepo structure with `packages/` directory
- **Multiple Entry Points**: Main app, mini window, selection toolbar
- **Styled Components**: CSS-in-JS styling with SWC optimization
### Testing Strategy
- **Vitest**: Unit and integration testing
- **Playwright**: End-to-end testing
- **Component Testing**: React Testing Library
- **Coverage**: Available via `yarn test:coverage`
### Key Patterns
- **IPC Communication**: Secure main-renderer communication via preload scripts
- **Service Layer**: Clear separation between UI and business logic
- **Plugin Architecture**: Extensible via MCP servers and middleware
- **Multi-language Support**: i18n with dynamic loading
- **Theme System**: Light/dark themes with custom CSS variables
### UI Design
The project is in the process of migrating from antd & styled-components to HeroUI. Please use HeroUI to build UI components. The use of antd and styled-components is prohibited.
HeroUI Docs: https://www.heroui.com/docs/guide/introduction
## Logging Standards
### Usage
```typescript
// Main process
import { loggerService } from '@logger'
@@ -118,7 +97,6 @@ logger.error('message', new Error('error'), CONTEXT)
```
### Log Levels (highest to lowest)
- `error` - Critical errors causing crash/unusable functionality
- `warn` - Potential issues that don't affect core functionality
- `info` - Application lifecycle and key user actions

45
LICENSE
View File

@@ -1,3 +1,48 @@
**许可协议 (Licensing)**
本项目采用**区分用户的双重许可 (User-Segmented Dual Licensing)** 模式。
**核心原则:**
* **个人用户 和 10人及以下企业/组织:** 默认适用 **GNU Affero 通用公共许可证 v3.0 (AGPLv3)**。
* **超过10人的企业/组织:** **必须** 获取 **商业许可证 (Commercial License)**。
定义“10人及以下”
指在您的组织包括公司、非营利组织、政府机构、教育机构等任何实体能够访问、使用或以任何方式直接或间接受益于本软件Cherry Studio功能的个人总数不超过10人。这包括但不限于开发者、测试人员、运营人员、最终用户、通过集成系统间接使用者等。
---
**1. 开源许可证 (Open Source License): AGPLv3 - 适用于个人及10人及以下组织**
* 如果您是个人用户或者您的组织满足上述“10人及以下”的定义您可以在 **AGPLv3** 的条款下自由使用、修改和分发 Cherry Studio。AGPLv3 的完整文本可以访问 [https://www.gnu.org/licenses/agpl-3.0.html](https://www.gnu.org/licenses/agpl-3.0.html) 获取。
* **核心义务:** AGPLv3 的一个关键要求是,如果您修改了 Cherry Studio 并通过网络提供服务,或者分发了修改后的版本,您必须以 AGPLv3 许可证向接收者提供相应的**完整源代码**。即使您符合“10人及以下”的标准如果您希望避免此源代码公开义务您也需要考虑获取商业许可证见下文
* 使用前请务必仔细阅读并理解 AGPLv3 的所有条款。
**2. 商业许可证 (Commercial License) - 适用于超过10人的组织或希望规避 AGPLv3 义务的用户**
* **强制要求:** 如果您的组织**不**满足上述“10人及以下”的定义即有11人或更多人可以访问、使用或受益于本软件您**必须**联系我们获取并签署一份商业许可证才能使用 Cherry Studio。
* **自愿选择:** 即使您的组织满足“10人及以下”的条件但如果您的使用场景**无法满足 AGPLv3 的条款要求**(特别是关于**源代码公开**的义务),或者您需要 AGPLv3 **未提供**的特定商业条款(如保证、赔偿、无 Copyleft 限制等),您也**必须**联系我们获取并签署一份商业许可证。
* **需要商业许可证的常见情况包括(但不限于):**
* 您的组织规模超过10人。
* (无论组织规模)您希望分发修改过的 Cherry Studio 版本,但**不希望**根据 AGPLv3 公开您修改部分的源代码。
* (无论组织规模)您希望基于修改过的 Cherry Studio 提供网络服务SaaS但**不希望**根据 AGPLv3 向服务使用者提供修改后的源代码。
* (无论组织规模)您的公司政策、客户合同或项目要求不允许使用 AGPLv3 许可的软件,或要求闭源分发及保密。
* 商业许可证将为您提供豁免 AGPLv3 义务(如源代码公开)的权利,并可能包含额外的商业保障条款。
* **获取商业许可:** 请通过邮箱 **bd@cherry-ai.com** 联系 Cherry Studio 开发团队洽谈商业授权事宜。
**3. 贡献 (Contributions)**
* 我们欢迎社区对 Cherry Studio 的贡献。所有向本项目提交的贡献都将被视为在 **AGPLv3** 许可证下提供。
* 通过向本项目提交贡献(例如通过 Pull Request即表示您同意您的代码以 AGPLv3 许可证授权给本项目及所有后续使用者(无论这些使用者最终遵循 AGPLv3 还是商业许可)。
* 您也理解并同意,您的贡献可能会被包含在根据商业许可证分发的 Cherry Studio 版本中。
**4. 其他条款 (Other Terms)**
* 关于商业许可证的具体条款和条件,以双方签署的正式商业许可协议为准。
* 项目维护者保留根据需要更新本许可政策(包括用户规模定义和阈值)的权利。相关更新将通过项目官方渠道(如代码仓库、官方网站)进行通知。
---
**Licensing**
This project employs a **User-Segmented Dual Licensing** model.

665
PRD.md Normal file
View File

@@ -0,0 +1,665 @@
# Product Requirements Document (PRD)
## Cherry Studio AI Agent Command Interface
### 1. Overview
**Product Name**: Cherry Studio AI Agent Command Interface
**Version**: 1.0
**Date**: July 30, 2025
**Vision**: Create a conversational AI Agent interface in Cherry Studio that enables users to execute shell commands through natural language interaction, with seamless communication between the renderer and main processes, providing an intelligent command execution experience.
### 2. Scope & Objectives
This PRD focuses on two core areas:
#### 2.1 Core Implementation Scope
- **Renderer ↔ Main Process Communication**: Robust IPC communication for command execution
- **Shell Command Execution**: Safe and efficient shell command processing in the main process
- **Real-time Output Streaming**: Live command output display integrated into chat interface
- **AI Agent Integration**: Natural language command interpretation and execution workflow
#### 2.2 UI/UX Design Scope
- **Conversational Interface Design**: Chat-like UI that fits Cherry Studio's design language
- **Command Agent Experience**: AI-powered command interpretation and execution feedback
- **Interactive Output Display**: Rich formatting of command results within chat messages
- **Responsive Design**: Consistent chat experience across different window sizes and layouts
### 3. Technical Requirements
#### 3.1 Core Implementation Requirements
##### 3.1.1 IPC Communication Architecture
**Requirement**: Establish bidirectional communication between renderer and main processes for AI Agent command execution
**Technical Specifications**:
- **Agent Command Request Flow**: Renderer → Main Process
```typescript
interface AgentCommandRequest {
id: string
messageId: string // Chat message ID for correlation
command: string
workingDirectory?: string
timeout?: number
environment?: Record<string, string>
context?: string // Additional context from chat conversation
}
```
- **Agent Output Streaming Flow**: Main Process → Renderer
```typescript
interface AgentCommandOutput {
id: string
messageId: string // Chat message ID for correlation
type: 'stdout' | 'stderr' | 'exit' | 'error' | 'progress'
data: string
exitCode?: number
timestamp: number
}
```
- **IPC Channel Names**:
- `agent-command-execute` (Renderer → Main)
- `agent-command-output` (Main → Renderer)
- `agent-command-interrupt` (Renderer → Main)
##### 3.1.2 Main Process Agent Command Service
**Requirement**: Create a new `AgentCommandService` in the main process
**Technical Specifications**:
- **Service Location**: `src/main/services/AgentCommandService.ts`
- **Core Methods**:
```typescript
class AgentCommandService {
executeCommand(request: AgentCommandRequest): Promise<void>
interruptCommand(commandId: string): Promise<void>
getRunningCommands(): string[]
setWorkingDirectory(path: string): void
formatCommandOutput(output: string, type: string): string
}
```
- **Process Management**:
- Use Node.js `child_process.spawn()` for command execution
- Support real-time stdout/stderr streaming to chat interface
- Handle process interruption via chat commands
- Maintain working directory state per agent session
- Format output for better chat display (tables, JSON, etc.)
- **Error Handling**:
- Command not found errors with helpful suggestions
- Permission denied errors with explanations
- Timeout handling with progress updates
- Process termination with cleanup notifications
##### 3.1.3 Renderer Process Integration
**Requirement**: Implement AI Agent command functionality in the renderer process
**Technical Specifications**:
- **Service Location**: `src/renderer/src/services/AgentCommandService.ts`
- **Component Integration**: Agent chat page and command execution components
- **State Management**: Chat session state, command history, output formatting
- **Message Correlation**: Link command outputs to specific chat messages
#### 3.2 Performance Requirements
- **Command Response Time**: < 100ms for command initiation
- **Output Streaming Latency**: < 50ms for real-time output display
- **Memory Management**: Efficient handling of large command outputs (>10MB)
- **Concurrent Commands**: Support up to 5 simultaneous command executions
#### 3.3 Security Requirements
- **Command Validation**: Basic validation for dangerous commands
- **Working Directory Restrictions**: Respect file system permissions
- **Environment Variable Handling**: Secure handling of environment variables
- **Process Isolation**: Commands run with application user privileges
### 4. UI/UX Design Requirements
#### 4.1 Design Principles
**Target Audience**: Senior Frontend and UI Designers
**Design Goals**: Create an intuitive, conversational AI Agent interface that enhances developer productivity through natural language command execution
##### 4.1.1 Visual Design Requirements
- **Design System Integration**: Follow Cherry Studio's existing chat design patterns
- **Theme Support**: Light/dark theme compatibility
- **Typography**: Mix of regular chat font and monospace for command outputs
- **Color Scheme**: Distinct styling for user messages, agent responses, and command outputs
- **Message Bubbles**: Clear visual distinction between conversation and command execution
##### 4.1.2 Layout Requirements
**Primary Layout Structure** (Chat Interface):
```
┌─────────────────────────────────────┐
│ Agent Header (name + status + controls) │
├─────────────────────────────────────┤
│ │
│ Chat Messages Area │
│ (user messages + agent replies │
│ + command outputs) │
│ │
├─────────────────────────────────────┤
│ Message Input (natural language) │
└─────────────────────────────────────┘
```
**Responsive Considerations**:
- Minimum width: 320px (mobile)
- Optimal width: 600-800px (desktop)
- Message bubbles adapt to content width
- Command outputs can expand full width
##### 4.1.3 Component Specifications
**Agent Header Component**:
- Agent name and avatar
- Working directory indicator
- Active command status (running/idle)
- Session controls (clear chat, export logs)
**Chat Messages Component**:
- **User Messages**: Standard chat bubbles for natural language input
- **Agent Responses**: AI responses explaining commands or asking for clarification
- **Command Execution Messages**: Special formatting for:
- Command being executed (with syntax highlighting)
- Real-time output streaming (scrollable, copyable)
- Execution status (success/error/interrupted)
- Formatted results (tables, JSON, file listings)
**Message Input Component**:
- Natural language input field
- Send button with loading state during command execution
- Suggestion chips for common requests
- Support for follow-up questions and command modifications
#### 4.2 User Experience Requirements
##### 4.2.1 Interaction Patterns
**Conversational Flow**:
- User types natural language requests ("list files in src directory")
- Agent interprets and confirms command before execution
- Real-time command output appears in chat
- User can ask follow-up questions or modify commands
**Keyboard Shortcuts**:
- `Enter`: Send message/command
- `Ctrl+Enter`: Force command execution without confirmation
- `Ctrl+K`: Interrupt running command
- `Ctrl+L`: Clear chat history
- `↑/↓`: Navigate message input history
**Mouse Interactions**:
- Click on command outputs to copy
- Click on file paths to open in Cherry Studio
- Hover over commands for quick actions (copy, re-run, modify)
##### 4.2.2 Feedback & Status Indicators
**Visual Feedback Requirements**:
- **Agent Thinking**: Typing indicator while processing user request
- **Command Execution**: Progress indicator and real-time output streaming
- **Execution Status**: Success/error/warning indicators in message bubbles
- **Working Directory**: Persistent display in agent header
- **Command History**: Visual indication of previous commands in chat
##### 4.2.3 Accessibility Requirements
- **Keyboard Navigation**: Full chat functionality accessible via keyboard
- **Screen Reader Support**: Proper ARIA labels for chat messages and command outputs
- **High Contrast**: Support for high contrast themes in all message types
- **Focus Management**: Logical tab order through chat interface
#### 4.3 Advanced UX Features (Future Considerations)
- **Command Suggestions**: AI-powered suggestions based on current context
- **Smart Output Formatting**: Automatic formatting for JSON, tables, logs, etc.
- **File Integration**: Deep integration with Cherry Studio's file management
- **Session Memory**: Agent remembers context across chat sessions
- **Multi-step Workflows**: Support for complex, multi-command operations
### 5. Implementation Approach
#### 5.1 Development Phases
**Phase 1: Core Infrastructure** (2-3 weeks)
- Implement AgentCommandService in main process
- Establish IPC communication for chat-command flow
- Basic command execution and output streaming to chat interface
**Phase 2: AI Agent Chat Interface** (3-4 weeks)
- Design and implement conversational chat components
- Create command execution message types and formatting
- Integrate natural language command interpretation
- Implement real-time output streaming in chat bubbles
**Phase 3: Enhanced Agent Features** (2-3 weeks)
- Add command confirmation and clarification flows
- Implement smart output formatting (tables, JSON, etc.)
- Add working directory management in chat context
- Integrate with Cherry Studio's existing AI infrastructure
#### 5.2 Integration Points
- **Router Integration**: Add `/agent` or `/command-agent` route to `src/renderer/src/Router.tsx`
- **Navigation**: Add agent icon to Cherry Studio's main navigation
- **AI Core Integration**: Leverage existing AI infrastructure for command interpretation
- **Settings Integration**: Agent preferences in application settings
- **Chat System**: Reuse existing chat components and patterns from Cherry Studio
### 6. Success Metrics
#### 6.1 Technical Metrics
- Command execution success rate: >99%
- Average command response time: <100ms
- Output streaming latency: <50ms
- Zero memory leaks during extended usage
#### 6.2 User Experience Metrics
- User adoption rate within first month
- Average chat session duration
- Natural language command interpretation accuracy
- Command execution success rate through conversational interface
- User feedback scores on AI Agent usability and helpfulness
### 7. Dependencies & Constraints
#### 7.1 Technical Dependencies
- Node.js `child_process` module
- Electron IPC capabilities
- Cherry Studio's existing service architecture
- React/TypeScript frontend stack
- Cherry Studio's AI Core infrastructure
- Existing chat components and design system
#### 7.2 Platform Constraints
- Cross-platform compatibility (Windows, macOS, Linux)
- Shell availability on target platforms
- File system permission handling
---
## 8. Proof of Concept (POC) Implementation
### 8.1 POC Objectives
**Primary Goal**: Validate the core concept of chat-based command execution with minimal implementation complexity.
**Key Validation Points**:
- User experience of command execution through chat interface
- Technical feasibility of IPC communication for real-time output streaming
- Performance characteristics of command output display in chat bubbles
- Cross-platform compatibility of basic shell command execution
### 8.2 POC Scope & Limitations
#### 8.2.1 Included Features
✅ **Direct Command Execution**: Users type shell commands directly (no AI interpretation)
✅ **Real-time Output Streaming**: Command output appears live in chat bubbles
✅ **Basic Chat Interface**: Simple message list with input field
✅ **Command History**: Navigate previous commands with arrow keys
✅ **Cross-platform Support**: Works on Windows, macOS, and Linux
✅ **Process Management**: Start/stop command execution
#### 8.2.2 Excluded Features (Future Work)
❌ AI natural language interpretation of commands
❌ Command confirmation or clarification flows
❌ Advanced output formatting (tables, JSON highlighting)
❌ Security validation and command filtering
❌ Session persistence between app restarts
❌ Multiple concurrent command execution
❌ Working directory management UI
❌ Integration with Cherry Studio's AI core
### 8.3 Technical Architecture
#### 8.3.1 Component Structure
```
src/renderer/src/pages/command-poc/
├── CommandPocPage.tsx # Main container component
├── components/
│ ├── PocHeader.tsx # Header with working directory
│ ├── PocMessageList.tsx # Scrollable message container
│ ├── PocMessageBubble.tsx # Individual message display
│ ├── PocCommandInput.tsx # Command input with history
│ └── PocStatusBar.tsx # Command execution status
├── hooks/
│ ├── usePocMessages.ts # Message state management
│ ├── usePocCommand.ts # Command execution logic
│ └── useCommandHistory.ts # Input history navigation
└── types.ts # POC-specific TypeScript interfaces
```
#### 8.3.2 Data Structures
```typescript
interface PocMessage {
id: string
type: 'user-command' | 'output' | 'error' | 'system'
content: string
timestamp: number
commandId?: string // Links output to originating command
isComplete: boolean // For streaming messages
}
interface PocCommandExecution {
id: string
command: string
startTime: number
endTime?: number
exitCode?: number
isRunning: boolean
}
```
#### 8.3.3 IPC Communication
```typescript
// Renderer → Main Process
interface PocExecuteCommandRequest {
id: string
command: string
workingDirectory: string
}
// Main Process → Renderer
interface PocCommandOutput {
commandId: string
type: 'stdout' | 'stderr' | 'exit' | 'error'
data: string
exitCode?: number
}
// IPC Channels
const IPC_CHANNELS = {
EXECUTE_COMMAND: 'poc-execute-command',
COMMAND_OUTPUT: 'poc-command-output',
INTERRUPT_COMMAND: 'poc-interrupt-command'
}
```
### 8.4 Implementation Details
#### 8.4.1 Main Process Implementation
**File**: `src/main/poc/commandExecutor.ts`
```typescript
class PocCommandExecutor {
private activeProcesses = new Map<string, ChildProcess>()
executeCommand(request: PocExecuteCommandRequest) {
const { spawn } = require('child_process')
const shell = process.platform === 'win32' ? 'cmd' : 'bash'
const args = process.platform === 'win32' ? ['/c'] : ['-c']
const child = spawn(shell, [...args, request.command], {
cwd: request.workingDirectory
})
this.activeProcesses.set(request.id, child)
// Stream output handling
child.stdout.on('data', (data) => {
this.sendOutput(request.id, 'stdout', data.toString())
})
child.stderr.on('data', (data) => {
this.sendOutput(request.id, 'stderr', data.toString())
})
child.on('close', (code) => {
this.sendOutput(request.id, 'exit', '', code)
this.activeProcesses.delete(request.id)
})
}
}
```
#### 8.4.2 Renderer Process Implementation
**State Management Strategy**:
```typescript
const usePocMessages = () => {
const [messages, setMessages] = useState<PocMessage[]>([])
const [activeCommand, setActiveCommand] = useState<string | null>(null)
const addUserCommand = (command: string) => {
const commandMessage: PocMessage = {
id: uuid(),
type: 'user-command',
content: command,
timestamp: Date.now(),
isComplete: true
}
const outputMessage: PocMessage = {
id: uuid(),
type: 'output',
content: '',
timestamp: Date.now(),
commandId: commandMessage.id,
isComplete: false
}
setMessages(prev => [...prev, commandMessage, outputMessage])
return outputMessage.id
}
const appendOutput = (messageId: string, data: string) => {
setMessages(prev => prev.map(msg =>
msg.id === messageId
? { ...msg, content: msg.content + data }
: msg
))
}
}
```
**Output Streaming with Buffering**:
```typescript
const useOutputBuffer = () => {
const bufferRef = useRef<string>('')
const timeoutRef = useRef<NodeJS.Timeout>()
const bufferOutput = (data: string, messageId: string) => {
bufferRef.current += data
clearTimeout(timeoutRef.current)
timeoutRef.current = setTimeout(() => {
appendOutput(messageId, bufferRef.current)
bufferRef.current = ''
}, 100) // 100ms debounce
}
}
```
#### 8.4.3 UI Components
**Message Bubble Component**:
```typescript
const PocMessageBubble: React.FC<{ message: PocMessage }> = ({ message }) => {
const isUserCommand = message.type === 'user-command'
return (
<MessageContainer isUser={isUserCommand}>
{isUserCommand ? (
<CommandBubble>
<CommandPrefix>$</CommandPrefix>
<CommandText>{message.content}</CommandText>
</CommandBubble>
) : (
<OutputBubble>
<pre>{message.content}</pre>
{!message.isComplete && <LoadingDots />}
</OutputBubble>
)}
</MessageContainer>
)
}
```
**Command Input with History**:
```typescript
const PocCommandInput: React.FC = ({ onSendCommand }) => {
const [input, setInput] = useState('')
const { history, addToHistory, navigateHistory } = useCommandHistory()
const handleKeyDown = (e: React.KeyboardEvent) => {
switch (e.key) {
case 'Enter':
if (input.trim()) {
onSendCommand(input.trim())
addToHistory(input.trim())
setInput('')
}
break
case 'ArrowUp':
e.preventDefault()
setInput(navigateHistory('up'))
break
case 'ArrowDown':
e.preventDefault()
setInput(navigateHistory('down'))
break
}
}
}
```
### 8.5 Cross-Platform Considerations
#### 8.5.1 Shell Detection
```typescript
const getShellConfig = () => {
switch (process.platform) {
case 'win32':
return { shell: 'cmd', args: ['/c'] }
case 'darwin':
case 'linux':
return { shell: 'bash', args: ['-c'] }
default:
return { shell: 'sh', args: ['-c'] }
}
}
```
#### 8.5.2 Path Handling
```typescript
const normalizeWorkingDirectory = (path: string) => {
return process.platform === 'win32'
? path.replace(/\//g, '\\')
: path.replace(/\\/g, '/')
}
```
### 8.6 Performance Optimizations
#### 8.6.1 Virtual Scrolling
```typescript
const PocMessageList: React.FC = ({ messages }) => {
const [visibleRange, setVisibleRange] = useState({ start: 0, end: 50 })
// Only render visible messages for large message lists
const visibleMessages = messages.slice(
visibleRange.start,
visibleRange.end
)
return (
<VirtualScrollContainer onScroll={handleScroll}>
{visibleMessages.map(message => (
<PocMessageBubble key={message.id} message={message} />
))}
</VirtualScrollContainer>
)
}
```
#### 8.6.2 Output Truncation
```typescript
const MAX_OUTPUT_LENGTH = 1024 * 1024 // 1MB per message
const MAX_TOTAL_MESSAGES = 1000
const truncateIfNeeded = (content: string) => {
if (content.length > MAX_OUTPUT_LENGTH) {
return content.slice(0, MAX_OUTPUT_LENGTH) + '\n\n[Output truncated...]'
}
return content
}
```
### 8.7 Testing Strategy
#### 8.7.1 Manual Test Cases
1. **Basic Commands**:
- `ls -la` / `dir` (directory listing)
- `pwd` / `cd` (working directory)
- `echo "Hello World"` (simple output)
2. **Streaming Output**:
- `ping google.com -c 5` (timed output)
- `find . -name "*.ts"` (large output)
- `npm install` (mixed stdout/stderr)
3. **Error Scenarios**:
- `nonexistentcommand` (command not found)
- `cat /root/protected` (permission denied)
- Long-running command interruption
4. **Cross-Platform**:
- Test on Windows, macOS, and Linux
- Verify shell detection works correctly
- Check path handling differences
#### 8.7.2 Performance Tests
- **Large Output**: Commands generating >100MB output
- **Rapid Output**: Commands with high-frequency output
- **Memory Usage**: Monitor memory consumption during long sessions
- **UI Responsiveness**: Ensure UI remains responsive during command execution
### 8.8 Success Criteria
#### 8.8.1 Functional Requirements
✅ Users can execute shell commands through chat interface
✅ Command output streams in real-time to chat bubbles
✅ Command history navigation works with arrow keys
✅ Cross-platform compatibility (Windows/macOS/Linux)
✅ Process interruption works reliably
#### 8.8.2 Performance Requirements
✅ Command execution starts within 100ms of user sending
✅ Output streaming latency < 200ms
✅ UI remains responsive with outputs up to 10MB
✅ Memory usage remains stable during extended use
#### 8.8.3 User Experience Requirements
✅ Chat interface feels natural and intuitive
✅ Clear visual distinction between commands and output
✅ Loading indicators provide appropriate feedback
✅ Auto-scroll behavior works as expected
### 8.9 Implementation Timeline
**Phase 1: Core Infrastructure** (Day 1)
- Set up POC page structure and routing
- Implement basic IPC communication
- Create simple command execution in main process
**Phase 2: Basic UI** (Day 2)
- Build message display components
- Implement command input with history
- Add basic styling and layout
**Phase 3: Streaming & Polish** (Day 3)
- Implement real-time output streaming
- Add loading states and status indicators
- Test cross-platform compatibility
**Phase 4: Testing & Refinement** (Day 4)
- Comprehensive manual testing
- Performance optimization
- Bug fixes and UX improvements
**Total Estimated Time: 4 days**
### 8.10 Migration Path to Production
The POC provides a foundation for the full production implementation:
1. **Component Reusability**: POC components can be enhanced rather than rewritten
2. **Architecture Validation**: IPC patterns proven in POC extend to production
3. **User Feedback**: POC enables early user testing and feedback collection
4. **Performance Baseline**: POC establishes performance expectations
5. **Cross-platform Foundation**: Platform compatibility issues resolved early
---
This PRD provides a focused scope for implementing a robust AI Agent command interface that enhances Cherry Studio's development capabilities through natural language interaction, while maintaining high standards for both technical implementation and user experience design.

View File

@@ -57,7 +57,7 @@
<div align="center">
<a href="https://hellogithub.com/repository/1605492e1e2a4df3be07abfa4578dd37" target="_blank" style="text-decoration: none"><img src="https://api.hellogithub.com/v1/widgets/recommend.svg?rid=1605492e1e2a4df3be07abfa4578dd37" alt="FeaturedHelloGitHub" width="220" height="55" /></a>
<a href="https://trendshift.io/repositories/14318" target="_blank" style="text-decoration: none"><img src="https://trendshift.io/api/badge/repositories/14318" alt="CherryHQ%2Fcherry-studio | Trendshift" width="220" height="55" /></a>
<a href="https://trendshift.io/repositories/11772" target="_blank" style="text-decoration: none"><img src="https://trendshift.io/api/badge/repositories/11772" alt="kangfenmao%2Fcherry-studio | Trendshift" width="220" height="55" /></a>
<a href="https://www.producthunt.com/posts/cherry-studio?embed=true&utm_source=badge-featured&utm_medium=badge&utm_souce=badge-cherry&#0045;studio" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=496640&theme=light" alt="Cherry&#0032;Studio - AI&#0032;Chatbots&#0044;&#0032;AI&#0032;Desktop&#0032;Client | Product Hunt" width="220" height="55" /></a>
</div>
@@ -82,7 +82,7 @@ Cherry Studio is a desktop client that supports multiple LLM providers, availabl
1. **Diverse LLM Provider Support**:
- ☁️ Major LLM Cloud Services: OpenAI, Gemini, Anthropic, and more
- 🔗 AI Web Service Integration: Claude, Perplexity, Poe, and others
- 🔗 AI Web Service Integration: Claude, Peplexity, Poe, and others
- 💻 Local Model Support with Ollama, LM Studio
2. **AI Assistants & Conversations**:

View File

@@ -1,97 +0,0 @@
{
"$schema": "https://biomejs.dev/schemas/2.2.4/schema.json",
"assist": {
// to sort json
"actions": {
"source": {
"organizeImports": "on",
"useSortedKeys": {
"level": "on",
"options": {
"sortOrder": "lexicographic"
}
}
}
},
"enabled": true,
"includes": ["**/*.json", "!*.json", "!**/package.json"]
},
"css": {
"formatter": {
"quoteStyle": "single"
}
},
"files": { "ignoreUnknown": false },
"formatter": {
"attributePosition": "auto",
"bracketSameLine": false,
"bracketSpacing": true,
"enabled": true,
"expand": "auto",
"formatWithErrors": true,
"includes": [
"**",
"!out/**",
"!**/dist/**",
"!build/**",
"!.yarn/**",
"!.github/**",
"!.husky/**",
"!.vscode/**",
"!*.yaml",
"!*.yml",
"!*.mjs",
"!*.cjs",
"!*.md",
"!*.json",
"!src/main/integration/**",
"!**/tailwind.css",
"!**/package.json"
],
"indentStyle": "space",
"indentWidth": 2,
"lineEnding": "lf",
"lineWidth": 120,
"useEditorconfig": true
},
"html": { "formatter": { "selfCloseVoidElements": "always" } },
"javascript": {
"formatter": {
"arrowParentheses": "always",
"attributePosition": "auto",
// To minimize changes in this PR as much as possible, it's set to true. However, setting it to false would make it more convenient to add attributes at the end.
"bracketSameLine": true,
"bracketSpacing": true,
"jsxQuoteStyle": "double",
"quoteProperties": "asNeeded",
"quoteStyle": "single",
"semicolons": "asNeeded",
"trailingCommas": "none"
}
},
"json": {
"parser": {
"allowComments": true
}
},
"linter": {
"enabled": true,
"includes": ["!**/tailwind.css", "src/renderer/**/*.{tsx,ts}"],
// only enable sorted tailwind css rule. used as formatter instead of linter
"rules": {
"nursery": {
// to sort tailwind css classes
"useSortedClasses": {
"fix": "safe",
"level": "warn",
"options": {
"functions": ["cn"]
}
}
},
"recommended": false,
"suspicious": "off"
}
},
"vcs": { "clientKind": "git", "enabled": false, "useIgnoreFile": false }
}

View File

@@ -8,7 +8,5 @@
<true/>
<key>com.apple.security.cs.allow-dyld-environment-variables</key>
<true/>
<key>com.apple.security.cs.disable-library-validation</key>
<true/>
</dict>
</plist>

View File

@@ -1,21 +0,0 @@
{
"$schema": "https://ui.shadcn.com/schema.json",
"aliases": {
"components": "@renderer/ui/third-party",
"hooks": "@renderer/hooks",
"lib": "@renderer/lib",
"ui": "@renderer/ui",
"utils": "@renderer/utils"
},
"iconLibrary": "lucide",
"rsc": false,
"style": "new-york",
"tailwind": {
"baseColor": "zinc",
"config": "",
"css": "src/renderer/src/assets/styles/tailwind.css",
"cssVariables": true,
"prefix": ""
},
"tsx": true
}

View File

@@ -13,7 +13,7 @@
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=fr">Français</a></p>
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=de">Deutsch</a></p>
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=es">Español</a></p>
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=it">Italiano</a></p>
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=it">Itapano</a></p>
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=ru">Русский</a></p>
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=pt">Português</a></p>
<p><a href="https://openaitx.github.io/view.html?user=CherryHQ&project=cherry-studio&lang=nl">Nederlands</a></p>
@@ -89,7 +89,7 @@ https://docs.cherry-ai.com
1. **多样化 LLM 服务支持**
- ☁️ 支持主流 LLM 云服务OpenAI、Gemini、Anthropic、硅基流动等
- 🔗 集成流行 AI Web 服务Claude、Perplexity、Poe、腾讯元宝、知乎直答等
- 🔗 集成流行 AI Web 服务Claude、Peplexity、Poe、腾讯元宝、知乎直答等
- 💻 支持 Ollama、LM Studio 本地模型部署
2. **智能助手与对话**

View File

@@ -2,9 +2,7 @@
## IDE Setup
- Editor: [Cursor](https://www.cursor.com/), etc. Any VS Code compatible editor.
- Linter: [ESLint](https://marketplace.visualstudio.com/items?itemName=dbaeumer.vscode-eslint)
- Formatter: [Biome](https://marketplace.visualstudio.com/items?itemName=biomejs.biome)
[Cursor](https://www.cursor.com/) + [ESLint](https://marketplace.visualstudio.com/items?itemName=dbaeumer.vscode-eslint) + [Prettier](https://marketplace.visualstudio.com/items?itemName=esbenp.prettier-vscode)
## Project Setup

Binary file not shown.

Before

Width:  |  Height:  |  Size: 40 KiB

After

Width:  |  Height:  |  Size: 38 KiB

View File

@@ -1,180 +0,0 @@
# CodeBlockView Component Structure
## Overview
CodeBlockView is the core component in Cherry Studio for displaying and manipulating code blocks. It supports multiple view modes and visual previews for special languages, providing rich interactive tools.
## Component Structure
```mermaid
graph TD
A[CodeBlockView] --> B[CodeToolbar]
A --> C[SourceView]
A --> D[SpecialView]
A --> E[StatusBar]
B --> F[CodeToolButton]
C --> G[CodeEditor / CodeViewer]
D --> H[MermaidPreview]
D --> I[PlantUmlPreview]
D --> J[SvgPreview]
D --> K[GraphvizPreview]
F --> L[useCopyTool]
F --> M[useDownloadTool]
F --> N[useViewSourceTool]
F --> O[useSplitViewTool]
F --> P[useRunTool]
F --> Q[useExpandTool]
F --> R[useWrapTool]
F --> S[useSaveTool]
```
## Core Concepts
### View Types
- **preview**: Preview view, where non-source code is displayed as special views
- **edit**: Edit view
### View Modes
- **source**: Source code view mode
- **special**: Special view mode (Mermaid, PlantUML, SVG)
- **split**: Split view mode (source code and special view displayed side by side)
### Special View Languages
- mermaid
- plantuml
- svg
- dot
- graphviz
## Component Details
### CodeBlockView Main Component
Main responsibilities:
1. Managing view mode state
2. Coordinating the display of source code view and special view
3. Managing toolbar tools
4. Handling code execution state
### Subcomponents
#### CodeToolbar
- Toolbar displayed at the top-right corner of the code block
- Contains core and quick tools
- Dynamically displays relevant tools based on context
#### CodeEditor/CodeViewer Source View
- Editable code editor or read-only code viewer
- Uses either component based on settings
- Supports syntax highlighting for multiple programming languages
#### Special View Components
- **MermaidPreview**: Mermaid diagram preview
- **PlantUmlPreview**: PlantUML diagram preview
- **SvgPreview**: SVG image preview
- **GraphvizPreview**: Graphviz diagram preview
All special view components share a common architecture for consistent user experience and functionality. For detailed information about these components and their implementation, see [Image Preview Components Documentation](./ImagePreview-en.md).
#### StatusBar
- Displays Python code execution results
- Can show both text and image results
## Tool System
CodeBlockView uses a hook-based tool system:
```mermaid
graph TD
A[CodeBlockView] --> B[useCopyTool]
A --> C[useDownloadTool]
A --> D[useViewSourceTool]
A --> E[useSplitViewTool]
A --> F[useRunTool]
A --> G[useExpandTool]
A --> H[useWrapTool]
A --> I[useSaveTool]
B --> J[ToolManager]
C --> J
D --> J
E --> J
F --> J
G --> J
H --> J
I --> J
J --> K[CodeToolbar]
```
Each tool hook is responsible for registering specific function tool buttons to the tool manager, which then passes these tools to the CodeToolbar component for rendering.
### Tool Types
- **core**: Core tools, always displayed in the toolbar
- **quick**: Quick tools, displayed in a dropdown menu when there are more than one
### Tool List
1. **Copy**: Copy code or image
2. **Download**: Download code or image
3. **View Source**: Switch between special view and source code view
4. **Split View**: Toggle split view mode
5. **Run**: Run Python code
6. **Expand/Collapse**: Control code block expansion/collapse
7. **Wrap**: Control automatic line wrapping
8. **Save**: Save edited code
## State Management
CodeBlockView manages the following states through React hooks:
1. **viewMode**: Current view mode ('source' | 'special' | 'split')
2. **isRunning**: Python code execution status
3. **executionResult**: Python code execution result
4. **tools**: Toolbar tool list
5. **expandOverride/unwrapOverride**: User override settings for expand/wrap
6. **sourceScrollHeight**: Source code view scroll height
## Interaction Flow
```mermaid
sequenceDiagram
participant U as User
participant CB as CodeBlockView
participant CT as CodeToolbar
participant SV as SpecialView
participant SE as SourceEditor
U->>CB: View code block
CB->>CB: Initialize state
CB->>CT: Register tools
CB->>SV: Render special view (if applicable)
CB->>SE: Render source view
U->>CT: Click tool button
CT->>CB: Trigger tool callback
CB->>CB: Update state
CB->>CT: Re-register tools (if needed)
```
## Special Handling
### HTML Code Blocks
HTML code blocks are specially handled using the HtmlArtifactsCard component.
### Python Code Execution
Supports executing Python code and displaying results using Pyodide to run Python code in the browser.

View File

@@ -1,180 +0,0 @@
# CodeBlockView 组件结构说明
## 概述
CodeBlockView 是 Cherry Studio 中用于显示和操作代码块的核心组件。它支持多种视图模式和特殊语言的可视化预览,提供丰富的交互工具。
## 组件结构
```mermaid
graph TD
A[CodeBlockView] --> B[CodeToolbar]
A --> C[SourceView]
A --> D[SpecialView]
A --> E[StatusBar]
B --> F[CodeToolButton]
C --> G[CodeEditor / CodeViewer]
D --> H[MermaidPreview]
D --> I[PlantUmlPreview]
D --> J[SvgPreview]
D --> K[GraphvizPreview]
F --> L[useCopyTool]
F --> M[useDownloadTool]
F --> N[useViewSourceTool]
F --> O[useSplitViewTool]
F --> P[useRunTool]
F --> Q[useExpandTool]
F --> R[useWrapTool]
F --> S[useSaveTool]
```
## 核心概念
### 视图类型
- **preview**: 预览视图,非源代码的是特殊视图
- **edit**: 编辑视图
### 视图模式
- **source**: 源代码视图模式
- **special**: 特殊视图模式Mermaid、PlantUML、SVG
- **split**: 分屏模式(源代码和特殊视图并排显示)
### 特殊视图语言
- mermaid
- plantuml
- svg
- dot
- graphviz
## 组件详细说明
### CodeBlockView 主组件
主要负责:
1. 管理视图模式状态
2. 协调源代码视图和特殊视图的显示
3. 管理工具栏工具
4. 处理代码执行状态
### 子组件
#### CodeToolbar 工具栏
- 显示在代码块右上角的工具栏
- 包含核心(core)和快捷(quick)两类工具
- 根据上下文动态显示相关工具
#### CodeEditor/CodeViewer 源代码视图
- 可编辑的代码编辑器或只读的代码查看器
- 根据设置决定使用哪个组件
- 支持多种编程语言高亮
#### 特殊视图组件
- **MermaidPreview**: Mermaid 图表预览
- **PlantUmlPreview**: PlantUML 图表预览
- **SvgPreview**: SVG 图像预览
- **GraphvizPreview**: Graphviz 图表预览
所有特殊视图组件共享通用架构,以确保一致的用户体验和功能。有关这些组件及其实现的详细信息,请参阅 [图像预览组件文档](./ImagePreview-zh.md)。
#### StatusBar 状态栏
- 显示 Python 代码执行结果
- 可显示文本和图像结果
## 工具系统
CodeBlockView 使用基于 hooks 的工具系统:
```mermaid
graph TD
A[CodeBlockView] --> B[useCopyTool]
A --> C[useDownloadTool]
A --> D[useViewSourceTool]
A --> E[useSplitViewTool]
A --> F[useRunTool]
A --> G[useExpandTool]
A --> H[useWrapTool]
A --> I[useSaveTool]
B --> J[ToolManager]
C --> J
D --> J
E --> J
F --> J
G --> J
H --> J
I --> J
J --> K[CodeToolbar]
```
每个工具 hook 负责注册特定功能的工具按钮到工具管理器,工具管理器再将这些工具传递给 CodeToolbar 组件进行渲染。
### 工具类型
- **core**: 核心工具,始终显示在工具栏
- **quick**: 快捷工具当数量大于1时通过下拉菜单显示
### 工具列表
1. **复制(copy)**: 复制代码或图像
2. **下载(download)**: 下载代码或图像
3. **查看源码(view-source)**: 在特殊视图和源码视图间切换
4. **分屏(split-view)**: 切换分屏模式
5. **运行(run)**: 运行 Python 代码
6. **展开/折叠(expand)**: 控制代码块的展开/折叠
7. **换行(wrap)**: 控制代码的自动换行
8. **保存(save)**: 保存编辑的代码
## 状态管理
CodeBlockView 通过 React hooks 管理以下状态:
1. **viewMode**: 当前视图模式 ('source' | 'special' | 'split')
2. **isRunning**: Python 代码执行状态
3. **executionResult**: Python 代码执行结果
4. **tools**: 工具栏工具列表
5. **expandOverride/unwrapOverride**: 用户展开/换行的覆盖设置
6. **sourceScrollHeight**: 源代码视图滚动高度
## 交互流程
```mermaid
sequenceDiagram
participant U as User
participant CB as CodeBlockView
participant CT as CodeToolbar
participant SV as SpecialView
participant SE as SourceEditor
U->>CB: 查看代码块
CB->>CB: 初始化状态
CB->>CT: 注册工具
CB->>SV: 渲染特殊视图(如果适用)
CB->>SE: 渲染源码视图
U->>CT: 点击工具按钮
CT->>CB: 触发工具回调
CB->>CB: 更新状态
CB->>CT: 重新注册工具(如果需要)
```
## 特殊处理
### HTML 代码块
HTML 代码块会被特殊处理,使用 HtmlArtifactsCard 组件显示。
### Python 代码执行
支持执行 Python 代码并显示结果,使用 Pyodide 在浏览器中运行 Python 代码。

View File

@@ -1,195 +0,0 @@
# Image Preview Components
## Overview
Image Preview Components are a set of specialized components in Cherry Studio for rendering and displaying various diagram and image formats. They provide a consistent user experience across different preview types with shared functionality for loading states, error handling, and interactive controls.
## Supported Formats
- **Mermaid**: Interactive diagrams and flowcharts
- **PlantUML**: UML diagrams and system architecture
- **SVG**: Scalable vector graphics
- **Graphviz/DOT**: Graph visualization and network diagrams
## Architecture
```mermaid
graph TD
A[MermaidPreview] --> D[ImagePreviewLayout]
B[PlantUmlPreview] --> D
C[SvgPreview] --> D
E[GraphvizPreview] --> D
D --> F[ImageToolbar]
D --> G[useDebouncedRender]
F --> H[Pan Controls]
F --> I[Zoom Controls]
F --> J[Reset Function]
F --> K[Dialog Control]
G --> L[Debounced Rendering]
G --> M[Error Handling]
G --> N[Loading State]
G --> O[Dependency Management]
```
## Core Components
### ImagePreviewLayout
A common layout wrapper that provides the foundation for all image preview components.
**Features:**
- **Loading State Management**: Shows loading spinner during rendering
- **Error Display**: Displays error messages when rendering fails
- **Toolbar Integration**: Conditionally renders ImageToolbar when enabled
- **Container Management**: Wraps preview content with consistent styling
- **Responsive Design**: Adapts to different container sizes
**Props:**
- `children`: The preview content to be displayed
- `loading`: Boolean indicating if content is being rendered
- `error`: Error message to display if rendering fails
- `enableToolbar`: Whether to show the interactive toolbar
- `imageRef`: Reference to the container element for image manipulation
### ImageToolbar
Interactive toolbar component providing image manipulation controls.
**Features:**
- **Pan Controls**: 4-directional pan buttons (up, down, left, right)
- **Zoom Controls**: Zoom in/out functionality with configurable increments
- **Reset Function**: Restore original pan and zoom state
- **Dialog Control**: Open preview in expanded dialog view
- **Accessible Design**: Full keyboard navigation and screen reader support
**Layout:**
- 3x3 grid layout positioned at bottom-right of preview
- Responsive button sizing
- Tooltip support for all controls
### useDebouncedRender Hook
A specialized React hook for managing preview rendering with performance optimizations.
**Features:**
- **Debounced Rendering**: Prevents excessive re-renders during rapid content changes (default 300ms delay)
- **Automatic Dependency Management**: Handles dependencies for render and condition functions
- **Error Handling**: Catches and manages rendering errors with detailed error messages
- **Loading State**: Tracks rendering progress with automatic state updates
- **Conditional Rendering**: Supports pre-render condition checks
- **Manual Controls**: Provides trigger, cancel, and state management functions
**API:**
```typescript
const { containerRef, error, isLoading, triggerRender, cancelRender, clearError, setLoading } = useDebouncedRender(
value,
renderFunction,
options
)
```
**Options:**
- `debounceDelay`: Customize debounce timing
- `shouldRender`: Function for conditional rendering logic
## Component Implementations
### MermaidPreview
Renders Mermaid diagrams with special handling for visibility detection.
**Special Features:**
- Syntax validation before rendering
- Visibility detection to handle collapsed containers
- SVG coordinate fixing for edge cases
- Integration with mermaid.js library
### PlantUmlPreview
Renders PlantUML diagrams using the online PlantUML server.
**Special Features:**
- Network error handling and retry logic
- Diagram encoding using deflate compression
- Support for light/dark themes
- Server status monitoring
### SvgPreview
Renders SVG content using Shadow DOM for isolation.
**Special Features:**
- Shadow DOM rendering for style isolation
- Direct SVG content injection
- Minimal processing overhead
- Cross-browser compatibility
### GraphvizPreview
Renders Graphviz/DOT diagrams using the viz.js library.
**Special Features:**
- Client-side rendering with viz.js
- Lazy loading of viz.js library
- SVG element generation
- Memory-efficient processing
## Shared Functionality
### Error Handling
All preview components provide consistent error handling:
- Network errors (connection failures)
- Syntax errors (invalid diagram code)
- Server errors (external service failures)
- Rendering errors (library failures)
### Loading States
Standardized loading indicators across all components:
- Spinner animation during processing
- Progress feedback for long operations
- Smooth transitions between states
### Interactive Controls
Common interaction patterns:
- Pan and zoom functionality
- Reset to original view
- Full-screen dialog mode
- Keyboard accessibility
### Performance Optimizations
- Debounced rendering to prevent excessive updates
- Lazy loading of heavy libraries
- Memory management for large diagrams
- Efficient re-rendering strategies
## Integration with CodeBlockView
Image Preview Components integrate seamlessly with CodeBlockView:
- Automatic format detection based on language tags
- Consistent toolbar integration
- Shared state management
- Responsive layout adaptation
For more information about the overall CodeBlockView architecture, see [CodeBlockView Documentation](./CodeBlockView-en.md).

View File

@@ -1,195 +0,0 @@
# 图像预览组件
## 概述
图像预览组件是 Cherry Studio 中用于渲染和显示各种图表和图像格式的专用组件集合。它们为不同预览类型提供一致的用户体验,具有共享的加载状态、错误处理和交互控制功能。
## 支持格式
- **Mermaid**: 交互式图表和流程图
- **PlantUML**: UML 图表和系统架构
- **SVG**: 可缩放矢量图形
- **Graphviz/DOT**: 图形可视化和网络图表
## 架构
```mermaid
graph TD
A[MermaidPreview] --> D[ImagePreviewLayout]
B[PlantUmlPreview] --> D
C[SvgPreview] --> D
E[GraphvizPreview] --> D
D --> F[ImageToolbar]
D --> G[useDebouncedRender]
F --> H[平移控制]
F --> I[缩放控制]
F --> J[重置功能]
F --> K[对话框控制]
G --> L[防抖渲染]
G --> M[错误处理]
G --> N[加载状态]
G --> O[依赖管理]
```
## 核心组件
### ImagePreviewLayout 图像预览布局
为所有图像预览组件提供基础的通用布局包装器。
**功能特性:**
- **加载状态管理**: 在渲染期间显示加载动画
- **错误显示**: 渲染失败时显示错误信息
- **工具栏集成**: 启用时有条件地渲染 ImageToolbar
- **容器管理**: 使用一致的样式包装预览内容
- **响应式设计**: 适应不同的容器尺寸
**属性:**
- `children`: 要显示的预览内容
- `loading`: 指示内容是否正在渲染的布尔值
- `error`: 渲染失败时显示的错误信息
- `enableToolbar`: 是否显示交互式工具栏
- `imageRef`: 用于图像操作的容器元素引用
### ImageToolbar 图像工具栏
提供图像操作控制的交互式工具栏组件。
**功能特性:**
- **平移控制**: 4方向平移按钮上、下、左、右
- **缩放控制**: 放大/缩小功能,支持可配置的增量
- **重置功能**: 恢复原始平移和缩放状态
- **对话框控制**: 在展开对话框中打开预览
- **无障碍设计**: 完整的键盘导航和屏幕阅读器支持
**布局:**
- 3x3 网格布局,位于预览右下角
- 响应式按钮尺寸
- 所有控件的工具提示支持
### useDebouncedRender Hook 防抖渲染钩子
用于管理预览渲染的专用 React Hook具有性能优化功能。
**功能特性:**
- **防抖渲染**: 防止内容快速变化时的过度重新渲染(默认 300ms 延迟)
- **自动依赖管理**: 处理渲染和条件函数的依赖项
- **错误处理**: 捕获和管理渲染错误,提供详细的错误信息
- **加载状态**: 跟踪渲染进度并自动更新状态
- **条件渲染**: 支持预渲染条件检查
- **手动控制**: 提供触发、取消和状态管理功能
**API:**
```typescript
const { containerRef, error, isLoading, triggerRender, cancelRender, clearError, setLoading } = useDebouncedRender(
value,
renderFunction,
options
)
```
**选项:**
- `debounceDelay`: 自定义防抖时间
- `shouldRender`: 条件渲染逻辑函数
## 组件实现
### MermaidPreview Mermaid 预览
渲染 Mermaid 图表,具有可见性检测的特殊处理。
**特殊功能:**
- 渲染前语法验证
- 可见性检测以处理折叠的容器
- 边缘情况的 SVG 坐标修复
- 与 mermaid.js 库集成
### PlantUmlPreview PlantUML 预览
使用在线 PlantUML 服务器渲染 PlantUML 图表。
**特殊功能:**
- 网络错误处理和重试逻辑
- 使用 deflate 压缩的图表编码
- 支持明/暗主题
- 服务器状态监控
### SvgPreview SVG 预览
使用 Shadow DOM 隔离渲染 SVG 内容。
**特殊功能:**
- Shadow DOM 渲染实现样式隔离
- 直接 SVG 内容注入
- 最小化处理开销
- 跨浏览器兼容性
### GraphvizPreview Graphviz 预览
使用 viz.js 库渲染 Graphviz/DOT 图表。
**特殊功能:**
- 使用 viz.js 进行客户端渲染
- viz.js 库的懒加载
- SVG 元素生成
- 内存高效处理
## 共享功能
### 错误处理
所有预览组件提供一致的错误处理:
- 网络错误(连接失败)
- 语法错误(无效的图表代码)
- 服务器错误(外部服务失败)
- 渲染错误(库失败)
### 加载状态
所有组件的标准化加载指示器:
- 处理期间的动画
- 长时间操作的进度反馈
- 状态间的平滑过渡
### 交互控制
通用交互模式:
- 平移和缩放功能
- 重置到原始视图
- 全屏对话框模式
- 键盘无障碍访问
### 性能优化
- 防抖渲染以防止过度更新
- 重型库的懒加载
- 大型图表的内存管理
- 高效的重新渲染策略
## 与 CodeBlockView 的集成
图像预览组件与 CodeBlockView 无缝集成:
- 基于语言标签的自动格式检测
- 一致的工具栏集成
- 共享状态管理
- 响应式布局适应
有关整体 CodeBlockView 架构的更多信息,请参阅 [CodeBlockView 文档](./CodeBlockView-zh.md)。

View File

@@ -1,16 +0,0 @@
# `translate_languages` 表技术文档
## 📄 概述
`translate_languages` 记录用户自定义的的语言类型(`Language`)。
### 字段说明
| 字段名 | 类型 | 是否主键 | 索引 | 说明 |
| ---------- | ------ | -------- | ---- | ------------------------------------------------------------------------ |
| `id` | string | ✅ 是 | ✅ | 唯一标识符,主键 |
| `langCode` | string | ❌ 否 | ✅ | 语言代码(如:`zh-cn`, `en-us`, `ja-jp` 等,均为小写),支持普通索引查询 |
| `value` | string | ❌ 否 | ❌ | 语言的名称,用户输入 |
| `emoji` | string | ❌ 否 | ❌ | 语言的emoji用户输入 |
> `langCode` 虽非主键,但在业务层应当避免重复插入相同语言代码。

View File

@@ -17,52 +17,50 @@ protocols:
schemes:
- cherrystudio
files:
- "**/*"
- "!**/{.vscode,.yarn,.yarn-lock,.github,.cursorrules,.prettierrc}"
- "!electron.vite.config.{js,ts,mjs,cjs}}"
- "!**/{.eslintignore,.eslintrc.js,.eslintrc.json,.eslintcache,root.eslint.config.js,eslint.config.js,.eslintrc.cjs,.prettierignore,.prettierrc.yaml,eslint.config.mjs,dev-app-update.yml,CHANGELOG.md,README.md,biome.jsonc}"
- "!**/{.env,.env.*,.npmrc,pnpm-lock.yaml}"
- "!**/{tsconfig.json,tsconfig.tsbuildinfo,tsconfig.node.json,tsconfig.web.json}"
- "!**/{.editorconfig,.jekyll-metadata}"
- "!src"
- "!scripts"
- "!local"
- "!docs"
- "!packages"
- "!.swc"
- "!.bin"
- "!._*"
- "!*.log"
- "!stats.html"
- "!*.md"
- "!**/*.{iml,o,hprof,orig,pyc,pyo,rbc,swp,csproj,sln,xproj}"
- "!**/*.{map,ts,tsx,jsx,less,scss,sass,css.d.ts,d.cts,d.mts,md,markdown,yaml,yml}"
- "!**/{test,tests,__tests__,powered-test,coverage}/**"
- "!**/{example,examples}/**"
- "!**/*.{spec,test}.{js,jsx,ts,tsx}"
- "!**/*.min.*.map"
- "!**/*.d.ts"
- "!**/dist/es6/**"
- "!**/dist/demo/**"
- "!**/amd/**"
- "!**/{.DS_Store,Thumbs.db,thumbs.db,__pycache__}"
- "!**/{LICENSE,license,LICENSE.*,*.LICENSE.txt,NOTICE.txt,README.md,readme.md,CHANGELOG.md}"
- "!node_modules/rollup-plugin-visualizer"
- "!node_modules/js-tiktoken"
- "!node_modules/@tavily/core/node_modules/js-tiktoken"
- "!node_modules/pdf-parse/lib/pdf.js/{v1.9.426,v1.10.88,v2.0.550}"
- "!node_modules/mammoth/{mammoth.browser.js,mammoth.browser.min.js}"
- "!node_modules/selection-hook/prebuilds/**/*" # we rebuild .node, don't use prebuilds
- "!node_modules/selection-hook/node_modules" # we don't need what in the node_modules dir
- "!node_modules/selection-hook/src" # we don't need source files
- "!node_modules/tesseract.js-core/{tesseract-core.js,tesseract-core.wasm,tesseract-core.wasm.js}" # we don't need source files
- "!node_modules/tesseract.js-core/{tesseract-core-lstm.js,tesseract-core-lstm.wasm,tesseract-core-lstm.wasm.js}" # we don't need source files
- "!node_modules/tesseract.js-core/{tesseract-core-simd-lstm.js,tesseract-core-simd-lstm.wasm,tesseract-core-simd-lstm.wasm.js}" # we don't need source files
- "!**/*.{h,iobj,ipdb,tlog,recipe,vcxproj,vcxproj.filters,Makefile,*.Makefile}" # filter .node build files
- '**/*'
- '!**/{.vscode,.yarn,.yarn-lock,.github,.cursorrules,.prettierrc}'
- '!electron.vite.config.{js,ts,mjs,cjs}}'
- '!**/{.eslintignore,.eslintrc.js,.eslintrc.json,.eslintcache,root.eslint.config.js,eslint.config.js,.eslintrc.cjs,.prettierignore,.prettierrc.yaml,eslint.config.mjs,dev-app-update.yml,CHANGELOG.md,README.md}'
- '!**/{.env,.env.*,.npmrc,pnpm-lock.yaml}'
- '!**/{tsconfig.json,tsconfig.tsbuildinfo,tsconfig.node.json,tsconfig.web.json}'
- '!**/{.editorconfig,.jekyll-metadata}'
- '!src'
- '!scripts'
- '!local'
- '!docs'
- '!packages'
- '!.swc'
- '!.bin'
- '!._*'
- '!*.log'
- '!stats.html'
- '!*.md'
- '!**/*.{iml,o,hprof,orig,pyc,pyo,rbc,swp,csproj,sln,xproj}'
- '!**/*.{map,ts,tsx,jsx,less,scss,sass,css.d.ts,d.cts,d.mts,md,markdown,yaml,yml}'
- '!**/{test,tests,__tests__,powered-test,coverage}/**'
- '!**/{example,examples}/**'
- '!**/*.{spec,test}.{js,jsx,ts,tsx}'
- '!**/*.min.*.map'
- '!**/*.d.ts'
- '!**/dist/es6/**'
- '!**/dist/demo/**'
- '!**/amd/**'
- '!**/{.DS_Store,Thumbs.db,thumbs.db,__pycache__}'
- '!**/{LICENSE,license,LICENSE.*,*.LICENSE.txt,NOTICE.txt,README.md,readme.md,CHANGELOG.md}'
- '!node_modules/rollup-plugin-visualizer'
- '!node_modules/js-tiktoken'
- '!node_modules/@tavily/core/node_modules/js-tiktoken'
- '!node_modules/pdf-parse/lib/pdf.js/{v1.9.426,v1.10.88,v2.0.550}'
- '!node_modules/mammoth/{mammoth.browser.js,mammoth.browser.min.js}'
- '!node_modules/selection-hook/prebuilds/**/*' # we rebuild .node, don't use prebuilds
- '!node_modules/pdfjs-dist/web/**/*'
- '!node_modules/pdfjs-dist/legacy/**/*'
- '!node_modules/selection-hook/node_modules' # we don't need what in the node_modules dir
- '!node_modules/selection-hook/src' # we don't need source files
- '!**/*.{h,iobj,ipdb,tlog,recipe,vcxproj,vcxproj.filters,Makefile,*.Makefile}' # filter .node build files
asarUnpack:
- resources/**
- "**/*.{metal,exp,lib}"
- "node_modules/@img/sharp-libvips-*/**"
- '**/*.{metal,exp,lib}'
win:
executableName: Cherry Studio
artifactName: ${productName}-${version}-${arch}-setup.${ext}
@@ -88,7 +86,7 @@ mac:
entitlementsInherit: build/entitlements.mac.plist
notarize: false
artifactName: ${productName}-${version}-${arch}.${ext}
minimumSystemVersion: "20.1.0" # 最低支持 macOS 11.0
minimumSystemVersion: '20.1.0' # 最低支持 macOS 11.0
extendInfo:
- NSCameraUsageDescription: Application requests access to the device's camera.
- NSMicrophoneUsageDescription: Application requests access to the device's microphone.
@@ -102,7 +100,6 @@ linux:
target:
- target: AppImage
- target: deb
- target: rpm
maintainer: electronjs.org
category: Utility
desktop:
@@ -110,54 +107,27 @@ linux:
StartupWMClass: CherryStudio
mimeTypes:
- x-scheme-handler/cherrystudio
rpm:
# Workaround for electron build issue on rpm package:
# https://github.com/electron/forge/issues/3594
fpm: ["--rpm-rpmbuild-define=_build_id_links none"]
publish:
provider: generic
url: https://releases.cherry-ai.com
electronDownload:
mirror: https://npmmirror.com/mirrors/electron/
beforePack: scripts/before-pack.js
afterPack: scripts/after-pack.js
afterSign: scripts/notarize.js
artifactBuildCompleted: scripts/artifact-build-completed.js
releaseInfo:
releaseNotes: |
<!--LANG:en-->
What's New in v1.6.5
Features:
- Add Claude Haiku 4.5 model support
- Add Mistral provider configuration
- Add Intel OpenVINO (NPU) OCR provider
- Add notes full-text search with highlighting
- Add built-in DiDi MCP server (China only)
- Support NewAPI as generic provider
Bug Fixes:
- Fix webview search (Cmd/Ctrl+F) functionality
- Fix API key rotation for each request
- Fix translate auto copy functionality
- Fix message layout and overflow display
<!--LANG:zh-CN-->
v1.6.5 版本更新
新增功能:
- 新增 Claude Haiku 4.5 模型支持
- 新增 Mistral 提供商配置
- 新增 Intel OpenVINO (NPU) OCR 提取功能
- 新增笔记全文搜索和高亮显示
- 新增内置滴滴 MCP 服务器(仅限中国)
- 支持 NewAPI 作为通用提供商
问题修复:
- 修复 webview 搜索(Cmd/Ctrl+F)功能
- 修复 API 密钥轮换机制
- 修复翻译自动复制功能
- 修复消息布局和溢出显示
<!--LANG:END-->
新增服务商AWS Bedrock
富文本编辑器支持:提升提示词编辑体验,支持更丰富的格式调整
拖拽输入优化:支持从其他软件直接拖拽文本至输入框,简化内容输入流程
参数调节增强:新增 Top-P 和 Temperature 开关设置,提供更灵活的模型调控选项
翻译任务后台执行:翻译任务支持后台运行,提升多任务处理效率
新模型支持:新增 Qwen-MT、Qwen3235BA22Bthinking 和 sonar-deep-research 模型,扩展推理能力
推理稳定性提升:修复部分模型思考内容无法输出的问题,确保推理结果完整
Mistral 模型修复:解决 Mistral 模型无法使用的问题,恢复其推理功能
备份目录优化:支持相对路径输入,提升备份配置灵活性
数据导出调整:新增引用内容导出开关,提供更精细的导出控制
文本流完整性:修复文本流末尾文字丢失问题,确保输出内容完整
内存泄漏修复:优化代码逻辑,解决内存泄漏问题,提升运行稳定性
嵌入模型简化:降低嵌入模型配置复杂度,提高易用性
MCP Tool 长时间运行:增强 MCP 工具的稳定性,支持长时间任务执行

View File

@@ -4,10 +4,6 @@ import { defineConfig, externalizeDepsPlugin } from 'electron-vite'
import { resolve } from 'path'
import { visualizer } from 'rollup-plugin-visualizer'
// assert not supported by biome
// import pkg from './package.json' assert { type: 'json' }
import pkg from './package.json'
const visualizerPlugin = (type: 'renderer' | 'main') => {
return process.env[`VISUALIZER_${type.toUpperCase()}`] ? [visualizer({ open: true })] : []
}
@@ -30,15 +26,13 @@ export default defineConfig({
},
build: {
rollupOptions: {
external: ['bufferutil', 'utf-8-validate', 'electron', ...Object.keys(pkg.dependencies)],
output: {
manualChunks: undefined, // 彻底禁用代码分割 - 返回 null 强制单文件打包
inlineDynamicImports: true // 内联所有动态导入,这是关键配置
},
onwarn(warning, warn) {
if (warning.code === 'COMMONJS_VARIABLE_IN_ESM') return
warn(warning)
}
external: ['@libsql/client', 'bufferutil', 'utf-8-validate', '@cherrystudio/mac-system-ocr'],
output: isProd
? {
manualChunks: undefined, // 彻底禁用代码分割 - 返回 null 强制单文件打包
inlineDynamicImports: true // 内联所有动态导入,这是关键配置
}
: undefined
},
sourcemap: isDev
},
@@ -66,7 +60,6 @@ export default defineConfig({
},
renderer: {
plugins: [
(async () => (await import('@tailwindcss/vite')).default())(),
react({
tsDecorators: true,
plugins: [
@@ -90,11 +83,7 @@ export default defineConfig({
'@shared': resolve('packages/shared'),
'@logger': resolve('src/renderer/src/services/LoggerService'),
'@mcp-trace/trace-core': resolve('packages/mcp-trace/trace-core'),
'@mcp-trace/trace-web': resolve('packages/mcp-trace/trace-web'),
'@cherrystudio/ai-core/provider': resolve('packages/aiCore/src/core/providers'),
'@cherrystudio/ai-core/built-in/plugins': resolve('packages/aiCore/src/core/plugins/built-in'),
'@cherrystudio/ai-core': resolve('packages/aiCore/src'),
'@cherrystudio/extension-table-plus': resolve('packages/extension-table-plus/src')
'@mcp-trace/trace-web': resolve('packages/mcp-trace/trace-web')
}
},
optimizeDeps: {
@@ -115,10 +104,6 @@ export default defineConfig({
selectionToolbar: resolve(__dirname, 'src/renderer/selectionToolbar.html'),
selectionAction: resolve(__dirname, 'src/renderer/selectionAction.html'),
traceWindow: resolve(__dirname, 'src/renderer/traceWindow.html')
},
onwarn(warning, warn) {
if (warning.code === 'COMMONJS_VARIABLE_IN_ESM') return
warn(warning)
}
}
},

View File

@@ -1,8 +1,8 @@
import electronConfigPrettier from '@electron-toolkit/eslint-config-prettier'
import tseslint from '@electron-toolkit/eslint-config-ts'
import eslint from '@eslint/js'
import eslintReact from '@eslint-react/eslint-plugin'
import { defineConfig } from 'eslint/config'
import oxlint from 'eslint-plugin-oxlint'
import reactHooks from 'eslint-plugin-react-hooks'
import simpleImportSort from 'eslint-plugin-simple-import-sort'
import unusedImports from 'eslint-plugin-unused-imports'
@@ -10,6 +10,7 @@ import unusedImports from 'eslint-plugin-unused-imports'
export default defineConfig([
eslint.configs.recommended,
tseslint.configs.recommended,
electronConfigPrettier,
eslintReact.configs['recommended-typescript'],
reactHooks.configs['recommended-latest'],
{
@@ -25,6 +26,7 @@ export default defineConfig([
'simple-import-sort/exports': 'error',
'unused-imports/no-unused-imports': 'error',
'@eslint-react/no-prop-types': 'error',
'prettier/prettier': ['error']
}
},
// Configuration for ensuring compatibility with the original ESLint(8.x) rules
@@ -48,31 +50,10 @@ export default defineConfig([
'@eslint-react/no-children-to-array': 'off'
}
},
{
ignores: [
'node_modules/**',
'build/**',
'dist/**',
'out/**',
'local/**',
'.yarn/**',
'.gitignore',
'scripts/cloudflare-worker.js',
'src/main/integration/nutstore/sso/lib/**',
'src/main/integration/cherryai/index.js',
'src/main/integration/nutstore/sso/lib/**',
'src/renderer/src/ui/**',
'packages/**/dist'
]
},
// turn off oxlint supported rules.
...oxlint.configs['flat/eslint'],
...oxlint.configs['flat/typescript'],
...oxlint.configs['flat/unicorn'],
{
// LoggerService Custom Rules - only apply to src directory
files: ['src/**/*.{ts,tsx,js,jsx}'],
ignores: ['src/**/__tests__/**', 'src/**/__mocks__/**', 'src/**/*.test.*', 'src/preload/**'],
ignores: ['src/**/__tests__/**', 'src/**/__mocks__/**', 'src/**/*.test.*'],
rules: {
'no-restricted-syntax': [
process.env.PRCI ? 'error' : 'warn',
@@ -131,4 +112,17 @@ export default defineConfig([
'i18n/no-template-in-t': 'warn'
}
},
{
ignores: [
'node_modules/**',
'build/**',
'dist/**',
'out/**',
'local/**',
'.yarn/**',
'.gitignore',
'scripts/cloudflare-worker.js',
'src/main/integration/nutstore/sso/lib/**'
]
}
])

View File

@@ -1,6 +1,6 @@
{
"name": "CherryStudio",
"version": "1.6.5",
"version": "1.5.4-rc.1",
"private": true,
"description": "A powerful AI assistant for producer.",
"main": "./out/main/index.js",
@@ -19,8 +19,7 @@
"packages/database",
"packages/mcp-trace/trace-core",
"packages/mcp-trace/trace-node",
"packages/mcp-trace/trace-web",
"packages/extension-table-plus"
"packages/mcp-trace/trace-web"
]
}
},
@@ -40,6 +39,7 @@
"build:linux": "dotenv npm run build && electron-builder --linux --x64 --arm64",
"build:linux:arm64": "dotenv npm run build && electron-builder --linux --arm64",
"build:linux:x64": "dotenv npm run build && electron-builder --linux --x64",
"build:npm": "node scripts/build-npm.js",
"release": "node scripts/version.js",
"publish": "yarn build:check && yarn release patch push",
"pulish:artifacts": "cd packages/artifacts && npm publish && cd -",
@@ -47,9 +47,9 @@
"generate:icons": "electron-icon-builder --input=./build/logo.png --output=build",
"analyze:renderer": "VISUALIZER_RENDERER=true yarn build",
"analyze:main": "VISUALIZER_MAIN=true yarn build",
"typecheck": "concurrently -n \"node,web\" -c \"cyan,magenta\" \"npm run typecheck:node\" \"npm run typecheck:web\"",
"typecheck:node": "tsgo --noEmit -p tsconfig.node.json --composite false",
"typecheck:web": "tsgo --noEmit -p tsconfig.web.json --composite false",
"typecheck": "npm run typecheck:node && npm run typecheck:web",
"typecheck:node": "tsc --noEmit -p tsconfig.node.json --composite false",
"typecheck:web": "tsc --noEmit -p tsconfig.web.json --composite false",
"check:i18n": "tsx scripts/check-i18n.ts",
"sync:i18n": "tsx scripts/sync-i18n.ts",
"update:i18n": "dotenv -e .env -- tsx scripts/update-i18n.ts",
@@ -63,52 +63,38 @@
"test:ui": "vitest --ui",
"test:watch": "vitest",
"test:e2e": "yarn playwright test",
"test:lint": "oxlint --deny-warnings && eslint . --ext .js,.jsx,.cjs,.mjs,.ts,.tsx,.cts,.mts --cache",
"test:lint": "eslint . --ext .js,.jsx,.cjs,.mjs,.ts,.tsx,.cts,.mts",
"test:scripts": "vitest scripts",
"lint": "oxlint --fix && eslint . --ext .js,.jsx,.cjs,.mjs,.ts,.tsx,.cts,.mts --fix --cache && yarn typecheck && yarn check:i18n",
"format": "biome format --write && biome lint --write",
"format:check": "biome format && biome lint",
"prepare": "git config blame.ignoreRevsFile .git-blame-ignore-revs && husky",
"claude": "dotenv -e .env -- claude",
"release:aicore:alpha": "yarn workspace @cherrystudio/ai-core version prerelease --immediate && yarn workspace @cherrystudio/ai-core npm publish --tag alpha --access public",
"release:aicore:beta": "yarn workspace @cherrystudio/ai-core version prerelease --immediate && yarn workspace @cherrystudio/ai-core npm publish --tag beta --access public",
"release:aicore": "yarn workspace @cherrystudio/ai-core version patch --immediate && yarn workspace @cherrystudio/ai-core npm publish --access public"
"format": "prettier --write .",
"lint": "eslint . --ext .js,.jsx,.cjs,.mjs,.ts,.tsx,.cts,.mts --fix && yarn typecheck && yarn check:i18n",
"prepare": "git config blame.ignoreRevsFile .git-blame-ignore-revs && husky"
},
"dependencies": {
"@cherrystudio/pdf-to-img-napi": "^0.0.1",
"@libsql/client": "0.14.0",
"@libsql/win32-x64-msvc": "^0.4.7",
"@napi-rs/system-ocr": "patch:@napi-rs/system-ocr@npm%3A1.0.2#~/.yarn/patches/@napi-rs-system-ocr-npm-1.0.2-59e7a78e8b.patch",
"@strongtz/win32-arm64-msvc": "^0.4.7",
"express": "^5.1.0",
"font-list": "^2.0.0",
"graceful-fs": "^4.2.11",
"jsdom": "26.1.0",
"node-stream-zip": "^1.15.0",
"officeparser": "^4.2.0",
"os-proxy-config": "^1.1.2",
"selection-hook": "^1.0.12",
"sharp": "^0.34.3",
"pdfjs-dist": "4.10.38",
"selection-hook": "^1.0.8",
"swagger-jsdoc": "^6.2.8",
"swagger-ui-express": "^5.0.1",
"tesseract.js": "patch:tesseract.js@npm%3A6.0.1#~/.yarn/patches/tesseract.js-npm-6.0.1-2562a7e46d.patch",
"turndown": "7.2.0"
},
"devDependencies": {
"@agentic/exa": "^7.3.3",
"@agentic/searxng": "^7.3.3",
"@agentic/tavily": "^7.3.3",
"@ai-sdk/amazon-bedrock": "^3.0.29",
"@ai-sdk/google-vertex": "^3.0.33",
"@ai-sdk/mistral": "^2.0.17",
"@ai-sdk/perplexity": "^2.0.11",
"@ant-design/v5-patch-for-react-19": "^1.0.3",
"@anthropic-ai/sdk": "^0.41.0",
"@anthropic-ai/vertex-sdk": "patch:@anthropic-ai/vertex-sdk@npm%3A0.11.4#~/.yarn/patches/@anthropic-ai-vertex-sdk-npm-0.11.4-c19cb41edb.patch",
"@aws-sdk/client-bedrock": "^3.840.0",
"@aws-sdk/client-bedrock-runtime": "^3.840.0",
"@aws-sdk/client-s3": "^3.840.0",
"@biomejs/biome": "2.2.4",
"@cherrystudio/ai-core": "workspace:^1.0.0-alpha.18",
"@cherrystudio/embedjs": "^0.1.31",
"@cherrystudio/embedjs-libsql": "^0.1.31",
"@cherrystudio/embedjs-loader-csv": "^0.1.31",
@@ -121,11 +107,8 @@
"@cherrystudio/embedjs-loader-xml": "^0.1.31",
"@cherrystudio/embedjs-ollama": "^0.1.31",
"@cherrystudio/embedjs-openai": "^0.1.31",
"@cherrystudio/extension-table-plus": "workspace:^",
"@dnd-kit/core": "^6.3.1",
"@dnd-kit/modifiers": "^9.0.0",
"@dnd-kit/sortable": "^10.0.0",
"@dnd-kit/utilities": "^3.2.2",
"@codemirror/view": "^6.0.0",
"@electron-toolkit/eslint-config-prettier": "^3.0.0",
"@electron-toolkit/eslint-config-ts": "^3.0.0",
"@electron-toolkit/preload": "^3.0.0",
"@electron-toolkit/tsconfig": "^1.0.1",
@@ -135,15 +118,14 @@
"@eslint-react/eslint-plugin": "^1.36.1",
"@eslint/js": "^9.22.0",
"@google/genai": "patch:@google/genai@npm%3A1.0.1#~/.yarn/patches/@google-genai-npm-1.0.1-e26f0f9af7.patch",
"@hello-pangea/dnd": "^18.0.1",
"@heroui/react": "^2.8.3",
"@hello-pangea/dnd": "^16.6.0",
"@kangfenmao/keyv-storage": "^0.1.0",
"@langchain/community": "^0.3.50",
"@langchain/community": "^0.3.36",
"@langchain/ollama": "^0.2.1",
"@mistralai/mistralai": "^1.7.5",
"@modelcontextprotocol/sdk": "^1.17.5",
"@modelcontextprotocol/sdk": "^1.17.0",
"@mozilla/readability": "^0.6.0",
"@notionhq/client": "^2.2.15",
"@openrouter/ai-sdk-provider": "^1.1.2",
"@opentelemetry/api": "^1.9.0",
"@opentelemetry/core": "2.0.0",
"@opentelemetry/exporter-trace-otlp-http": "^0.200.0",
@@ -152,32 +134,14 @@
"@opentelemetry/sdk-trace-web": "^2.0.0",
"@playwright/test": "^1.52.0",
"@reduxjs/toolkit": "^2.2.5",
"@shikijs/markdown-it": "^3.12.0",
"@swc/plugin-styled-components": "^8.0.4",
"@tailwindcss/vite": "^4.1.13",
"@tanstack/react-query": "^5.85.5",
"@shikijs/markdown-it": "^3.7.0",
"@swc/plugin-styled-components": "^7.1.5",
"@tanstack/react-query": "^5.27.0",
"@tanstack/react-virtual": "^3.13.12",
"@testing-library/dom": "^10.4.0",
"@testing-library/jest-dom": "^6.6.3",
"@testing-library/react": "^16.3.0",
"@testing-library/user-event": "^14.6.1",
"@tiptap/extension-collaboration": "^3.2.0",
"@tiptap/extension-drag-handle": "patch:@tiptap/extension-drag-handle@npm%3A3.2.0#~/.yarn/patches/@tiptap-extension-drag-handle-npm-3.2.0-5a9ebff7c9.patch",
"@tiptap/extension-drag-handle-react": "^3.2.0",
"@tiptap/extension-image": "^3.2.0",
"@tiptap/extension-list": "^3.2.0",
"@tiptap/extension-mathematics": "^3.2.0",
"@tiptap/extension-mention": "^3.2.0",
"@tiptap/extension-node-range": "^3.2.0",
"@tiptap/extension-table-of-contents": "^3.2.0",
"@tiptap/extension-typography": "^3.2.0",
"@tiptap/extension-underline": "^3.2.0",
"@tiptap/pm": "^3.2.0",
"@tiptap/react": "^3.2.0",
"@tiptap/starter-kit": "^3.2.0",
"@tiptap/suggestion": "^3.2.0",
"@tiptap/y-tiptap": "^3.0.0",
"@truto/turndown-plugin-gfm": "^1.0.2",
"@tryfabric/martian": "^1.2.4",
"@types/cli-progress": "^3",
"@types/content-type": "^1.1.9",
@@ -185,28 +149,22 @@
"@types/diff": "^7",
"@types/express": "^5",
"@types/fs-extra": "^11",
"@types/he": "^1",
"@types/html-to-text": "^9",
"@types/lodash": "^4.17.5",
"@types/markdown-it": "^14",
"@types/md5": "^2.3.5",
"@types/mime-types": "^3",
"@types/node": "^22.17.1",
"@types/node": "^18.19.9",
"@types/pako": "^1.0.2",
"@types/react": "^19.0.12",
"@types/react-dom": "^19.0.4",
"@types/react-infinite-scroll-component": "^5.0.0",
"@types/react-transition-group": "^4.4.12",
"@types/react-window": "^1",
"@types/swagger-jsdoc": "^6",
"@types/swagger-ui-express": "^4.1.8",
"@types/tinycolor2": "^1",
"@types/turndown": "^5.0.5",
"@types/word-extractor": "^1",
"@typescript/native-preview": "latest",
"@uiw/codemirror-extensions-langs": "^4.25.1",
"@uiw/codemirror-themes-all": "^4.25.1",
"@uiw/react-codemirror": "^4.25.1",
"@uiw/codemirror-extensions-langs": "^4.23.14",
"@uiw/codemirror-themes-all": "^4.23.14",
"@uiw/react-codemirror": "^4.23.14",
"@vitejs/plugin-react-swc": "^3.9.0",
"@vitest/browser": "^3.2.4",
"@vitest/coverage-v8": "^3.2.4",
@@ -215,30 +173,23 @@
"@viz-js/lang-dot": "^1.0.5",
"@viz-js/viz": "^3.14.0",
"@xyflow/react": "^12.4.4",
"ai": "^5.0.59",
"antd": "patch:antd@npm%3A5.27.0#~/.yarn/patches/antd-npm-5.27.0-aa91c36546.patch",
"antd": "patch:antd@npm%3A5.24.7#~/.yarn/patches/antd-npm-5.24.7-356a553ae5.patch",
"archiver": "^7.0.1",
"async-mutex": "^0.5.0",
"axios": "^1.7.3",
"browser-image-compression": "^2.0.2",
"chardet": "^2.1.0",
"check-disk-space": "3.4.0",
"cheerio": "^1.1.2",
"chokidar": "^4.0.3",
"cli-progress": "^3.12.0",
"clsx": "^2.1.1",
"code-inspector-plugin": "^0.20.14",
"color": "^5.0.0",
"concurrently": "^9.2.1",
"country-flag-emoji-polyfill": "0.1.8",
"dayjs": "^1.11.11",
"dexie": "^4.0.8",
"dexie-react-hooks": "^1.1.7",
"diff": "^8.0.2",
"diff": "^7.0.0",
"docx": "^9.0.2",
"dompurify": "^3.2.6",
"dotenv-cli": "^7.4.2",
"electron": "37.6.0",
"electron": "37.2.3",
"electron-builder": "26.0.15",
"electron-devtools-installer": "^3.2.0",
"electron-store": "^8.2.0",
@@ -249,91 +200,73 @@
"emoji-picker-element": "^1.22.1",
"epub": "patch:epub@npm%3A1.3.0#~/.yarn/patches/epub-npm-1.3.0-8325494ffe.patch",
"eslint": "^9.22.0",
"eslint-plugin-oxlint": "^1.15.0",
"eslint-plugin-react-hooks": "^5.2.0",
"eslint-plugin-simple-import-sort": "^12.1.1",
"eslint-plugin-unused-imports": "^4.1.4",
"fast-diff": "^1.3.0",
"fast-xml-parser": "^5.2.0",
"fetch-socks": "1.3.2",
"framer-motion": "^12.23.12",
"franc-min": "^6.2.0",
"fs-extra": "^11.2.0",
"google-auth-library": "^9.15.1",
"he": "^1.2.0",
"html-tags": "^5.1.0",
"html-to-image": "^1.11.13",
"html-to-text": "^9.0.5",
"htmlparser2": "^10.0.0",
"husky": "^9.1.7",
"i18next": "^23.11.5",
"iconv-lite": "^0.6.3",
"isbinaryfile": "5.0.4",
"jaison": "^2.0.2",
"jest-styled-components": "^7.2.0",
"linguist-languages": "^8.1.0",
"linguist-languages": "^8.0.0",
"lint-staged": "^15.5.0",
"lodash": "^4.17.21",
"lru-cache": "^11.1.0",
"lucide-react": "^0.525.0",
"macos-release": "^3.4.0",
"markdown-it": "^14.1.0",
"mermaid": "^11.10.1",
"mermaid": "^11.7.0",
"mime": "^4.0.4",
"mime-types": "^3.0.1",
"motion": "^12.10.5",
"notion-helper": "^1.3.22",
"npx-scope-finder": "^1.2.0",
"openai": "patch:openai@npm%3A5.12.2#~/.yarn/patches/openai-npm-5.12.2-30b075401c.patch",
"oxlint": "^1.15.0",
"oxlint-tsgolint": "^0.2.0",
"openai": "patch:openai@npm%3A5.1.0#~/.yarn/patches/openai-npm-5.1.0-0e7b3ccb07.patch",
"p-queue": "^8.1.0",
"pdf-lib": "^1.17.1",
"pdf-parse": "^1.1.1",
"playwright": "^1.52.0",
"prettier": "^3.5.3",
"prettier-plugin-sort-json": "^4.1.1",
"proxy-agent": "^6.5.0",
"rc-virtual-list": "^3.18.6",
"react": "^19.0.0",
"react-dom": "^19.0.0",
"react-error-boundary": "^6.0.0",
"react-hotkeys-hook": "^4.6.1",
"react-i18next": "^14.1.2",
"react-infinite-scroll-component": "^6.1.0",
"react-json-view": "^1.21.3",
"react-markdown": "^10.1.0",
"react-player": "^3.3.1",
"react-redux": "^9.1.2",
"react-router": "6",
"react-router-dom": "6",
"react-spinners": "^0.14.1",
"react-transition-group": "^4.4.5",
"react-window": "^1.8.11",
"redux": "^5.0.1",
"redux-persist": "^6.0.0",
"reflect-metadata": "0.2.2",
"rehype-katex": "^7.0.1",
"rehype-mathjax": "^7.1.0",
"rehype-parse": "^9.0.1",
"rehype-raw": "^7.0.0",
"rehype-stringify": "^10.0.1",
"remark-cjk-friendly": "^1.2.0",
"remark-gfm": "^4.0.1",
"remark-github-blockquote-alert": "^2.0.0",
"remark-math": "^6.0.0",
"remove-markdown": "^0.6.2",
"rollup-plugin-visualizer": "^5.12.0",
"shiki": "^3.12.0",
"sass": "^1.88.0",
"shiki": "^3.7.0",
"strict-url-sanitise": "^0.0.1",
"string-width": "^7.2.0",
"striptags": "^3.2.0",
"styled-components": "^6.1.11",
"swr": "^2.3.6",
"tailwindcss": "^4.1.13",
"tar": "^7.4.3",
"tiny-pinyin": "^1.3.2",
"tokenx": "^1.1.0",
"tsx": "^4.20.3",
"turndown-plugin-gfm": "^1.0.2",
"tw-animate-css": "^1.3.8",
"typescript": "~5.8.2",
"typescript": "^5.6.2",
"undici": "6.21.2",
"unified": "^11.0.5",
"uuid": "^10.0.0",
@@ -343,43 +276,37 @@
"winston": "^3.17.0",
"winston-daily-rotate-file": "^5.0.0",
"word-extractor": "^1.0.4",
"y-protocols": "^1.0.6",
"yaml": "^2.8.1",
"yjs": "^13.6.27",
"youtubei.js": "^15.0.1",
"zipread": "^1.3.3",
"zod": "^4.1.5"
"zod": "^3.25.74"
},
"optionalDependencies": {
"@cherrystudio/mac-system-ocr": "^0.2.2"
},
"resolutions": {
"@codemirror/language": "6.11.3",
"@codemirror/lint": "6.8.5",
"@codemirror/view": "6.38.1",
"@langchain/core@npm:^0.3.26": "patch:@langchain/core@npm%3A0.3.44#~/.yarn/patches/@langchain-core-npm-0.3.44-41d5c3cb0a.patch",
"pdf-parse@npm:1.1.1": "patch:pdf-parse@npm%3A1.1.1#~/.yarn/patches/pdf-parse-npm-1.1.1-04a6109b2a.patch",
"@langchain/openai@npm:^0.3.16": "patch:@langchain/openai@npm%3A0.3.16#~/.yarn/patches/@langchain-openai-npm-0.3.16-e525b59526.patch",
"@langchain/openai@npm:>=0.1.0 <0.4.0": "patch:@langchain/openai@npm%3A0.3.16#~/.yarn/patches/@langchain-openai-npm-0.3.16-e525b59526.patch",
"app-builder-lib@npm:26.0.13": "patch:app-builder-lib@npm%3A26.0.13#~/.yarn/patches/app-builder-lib-npm-26.0.13-a064c9e1d0.patch",
"app-builder-lib@npm:26.0.15": "patch:app-builder-lib@npm%3A26.0.15#~/.yarn/patches/app-builder-lib-npm-26.0.15-360e5b0476.patch",
"atomically@npm:^1.7.0": "patch:atomically@npm%3A1.7.0#~/.yarn/patches/atomically-npm-1.7.0-e742e5293b.patch",
"file-stream-rotator@npm:^0.6.1": "patch:file-stream-rotator@npm%3A0.6.1#~/.yarn/patches/file-stream-rotator-npm-0.6.1-eab45fb13d.patch",
"libsql@npm:^0.4.4": "patch:libsql@npm%3A0.4.7#~/.yarn/patches/libsql-npm-0.4.7-444e260fb1.patch",
"node-abi": "4.12.0",
"openai@npm:^4.77.0": "patch:openai@npm%3A5.12.2#~/.yarn/patches/openai-npm-5.12.2-30b075401c.patch",
"openai@npm:^4.87.3": "patch:openai@npm%3A5.12.2#~/.yarn/patches/openai-npm-5.12.2-30b075401c.patch",
"pdf-parse@npm:1.1.1": "patch:pdf-parse@npm%3A1.1.1#~/.yarn/patches/pdf-parse-npm-1.1.1-04a6109b2a.patch",
"openai@npm:^4.77.0": "patch:openai@npm%3A5.1.0#~/.yarn/patches/openai-npm-5.1.0-0e7b3ccb07.patch",
"pkce-challenge@npm:^4.1.0": "patch:pkce-challenge@npm%3A4.1.0#~/.yarn/patches/pkce-challenge-npm-4.1.0-fbc51695a3.patch",
"app-builder-lib@npm:26.0.13": "patch:app-builder-lib@npm%3A26.0.13#~/.yarn/patches/app-builder-lib-npm-26.0.13-a064c9e1d0.patch",
"openai@npm:^4.87.3": "patch:openai@npm%3A5.1.0#~/.yarn/patches/openai-npm-5.1.0-0e7b3ccb07.patch",
"app-builder-lib@npm:26.0.15": "patch:app-builder-lib@npm%3A26.0.15#~/.yarn/patches/app-builder-lib-npm-26.0.15-360e5b0476.patch",
"@langchain/core@npm:^0.3.26": "patch:@langchain/core@npm%3A0.3.44#~/.yarn/patches/@langchain-core-npm-0.3.44-41d5c3cb0a.patch",
"node-abi": "4.12.0",
"undici": "6.21.2",
"vite": "npm:rolldown-vite@latest",
"tesseract.js@npm:*": "patch:tesseract.js@npm%3A6.0.1#~/.yarn/patches/tesseract.js-npm-6.0.1-2562a7e46d.patch",
"@ai-sdk/google@npm:2.0.17": "patch:@ai-sdk/google@npm%3A2.0.17#~/.yarn/patches/@ai-sdk-google-npm-2.0.17-fd88491de4.patch"
"atomically@npm:^1.7.0": "patch:atomically@npm%3A1.7.0#~/.yarn/patches/atomically-npm-1.7.0-e742e5293b.patch",
"file-stream-rotator@npm:^0.6.1": "patch:file-stream-rotator@npm%3A0.6.1#~/.yarn/patches/file-stream-rotator-npm-0.6.1-eab45fb13d.patch"
},
"packageManager": "yarn@4.9.1",
"lint-staged": {
"*.{js,jsx,ts,tsx,cjs,mjs,cts,mts}": [
"biome format --write --no-errors-on-unmatched",
"prettier --write",
"eslint --fix"
],
"*.{json,yml,yaml,css,html}": [
"biome format --write --no-errors-on-unmatched"
"*.{json,md,yml,yaml,css,scss,html}": [
"prettier --write"
]
}
}

View File

@@ -1,514 +0,0 @@
# AI Core 基于 Vercel AI SDK 的技术架构
## 1. 架构设计理念
### 1.1 设计目标
- **简化分层**`models`(模型层)→ `runtime`(运行时层),清晰的职责分离
- **统一接口**:使用 Vercel AI SDK 统一不同 AI Provider 的接口差异
- **动态导入**:通过动态导入实现按需加载,减少打包体积
- **最小包装**:直接使用 AI SDK 的类型和接口,避免重复定义
- **插件系统**:基于钩子的通用插件架构,支持请求全生命周期扩展
- **类型安全**:利用 TypeScript 和 AI SDK 的类型系统确保类型安全
- **轻量级**:专注核心功能,保持包的轻量和高效
- **包级独立**:作为独立包管理,便于复用和维护
- **Agent就绪**:为将来集成 OpenAI Agents SDK 预留扩展空间
### 1.2 核心优势
- **标准化**AI SDK 提供统一的模型接口,减少适配工作
- **简化设计**函数式API避免过度抽象
- **更好的开发体验**:完整的 TypeScript 支持和丰富的生态系统
- **性能优化**AI SDK 内置优化和最佳实践
- **模块化设计**:独立包结构,支持跨项目复用
- **可扩展插件**:通用的流转换和参数处理插件系统
- **面向未来**:为 OpenAI Agents SDK 集成做好准备
## 2. 整体架构图
```mermaid
graph TD
subgraph "用户应用 (如 Cherry Studio)"
UI["用户界面"]
Components["应用组件"]
end
subgraph "packages/aiCore (AI Core 包)"
subgraph "Runtime Layer (运行时层)"
RuntimeExecutor["RuntimeExecutor (运行时执行器)"]
PluginEngine["PluginEngine (插件引擎)"]
RuntimeAPI["Runtime API (便捷函数)"]
end
subgraph "Models Layer (模型层)"
ModelFactory["createModel() (模型工厂)"]
ProviderCreator["ProviderCreator (提供商创建器)"]
end
subgraph "Core Systems (核心系统)"
subgraph "Plugins (插件)"
PluginManager["PluginManager (插件管理)"]
BuiltInPlugins["Built-in Plugins (内置插件)"]
StreamTransforms["Stream Transforms (流转换)"]
end
subgraph "Middleware (中间件)"
MiddlewareWrapper["wrapModelWithMiddlewares() (中间件包装)"]
end
subgraph "Providers (提供商)"
Registry["Provider Registry (注册表)"]
Factory["Provider Factory (工厂)"]
end
end
end
subgraph "Vercel AI SDK"
AICore["ai (核心库)"]
OpenAI["@ai-sdk/openai"]
Anthropic["@ai-sdk/anthropic"]
Google["@ai-sdk/google"]
XAI["@ai-sdk/xai"]
Others["其他 19+ Providers"]
end
subgraph "Future: OpenAI Agents SDK"
AgentSDK["@openai/agents (未来集成)"]
AgentExtensions["Agent Extensions (预留)"]
end
UI --> RuntimeAPI
Components --> RuntimeExecutor
RuntimeAPI --> RuntimeExecutor
RuntimeExecutor --> PluginEngine
RuntimeExecutor --> ModelFactory
PluginEngine --> PluginManager
ModelFactory --> ProviderCreator
ModelFactory --> MiddlewareWrapper
ProviderCreator --> Registry
Registry --> Factory
Factory --> OpenAI
Factory --> Anthropic
Factory --> Google
Factory --> XAI
Factory --> Others
RuntimeExecutor --> AICore
AICore --> streamText
AICore --> generateText
AICore --> streamObject
AICore --> generateObject
PluginManager --> StreamTransforms
PluginManager --> BuiltInPlugins
%% 未来集成路径
RuntimeExecutor -.-> AgentSDK
AgentSDK -.-> AgentExtensions
```
## 3. 包结构设计
### 3.1 新架构文件结构
```
packages/aiCore/
├── src/
│ ├── core/ # 核心层 - 内部实现
│ │ ├── models/ # 模型层 - 模型创建和配置
│ │ │ ├── factory.ts # 模型工厂函数 ✅
│ │ │ ├── ModelCreator.ts # 模型创建器 ✅
│ │ │ ├── ConfigManager.ts # 配置管理器 ✅
│ │ │ ├── types.ts # 模型类型定义 ✅
│ │ │ └── index.ts # 模型层导出 ✅
│ │ ├── runtime/ # 运行时层 - 执行和用户API
│ │ │ ├── executor.ts # 运行时执行器 ✅
│ │ │ ├── pluginEngine.ts # 插件引擎 ✅
│ │ │ ├── types.ts # 运行时类型定义 ✅
│ │ │ └── index.ts # 运行时导出 ✅
│ │ ├── middleware/ # 中间件系统
│ │ │ ├── wrapper.ts # 模型包装器 ✅
│ │ │ ├── manager.ts # 中间件管理器 ✅
│ │ │ ├── types.ts # 中间件类型 ✅
│ │ │ └── index.ts # 中间件导出 ✅
│ │ ├── plugins/ # 插件系统
│ │ │ ├── types.ts # 插件类型定义 ✅
│ │ │ ├── manager.ts # 插件管理器 ✅
│ │ │ ├── built-in/ # 内置插件 ✅
│ │ │ │ ├── logging.ts # 日志插件 ✅
│ │ │ │ ├── webSearchPlugin/ # 网络搜索插件 ✅
│ │ │ │ ├── toolUsePlugin/ # 工具使用插件 ✅
│ │ │ │ └── index.ts # 内置插件导出 ✅
│ │ │ ├── README.md # 插件文档 ✅
│ │ │ └── index.ts # 插件导出 ✅
│ │ ├── providers/ # 提供商管理
│ │ │ ├── registry.ts # 提供商注册表 ✅
│ │ │ ├── factory.ts # 提供商工厂 ✅
│ │ │ ├── creator.ts # 提供商创建器 ✅
│ │ │ ├── types.ts # 提供商类型 ✅
│ │ │ ├── utils.ts # 工具函数 ✅
│ │ │ └── index.ts # 提供商导出 ✅
│ │ ├── options/ # 配置选项
│ │ │ ├── factory.ts # 选项工厂 ✅
│ │ │ ├── types.ts # 选项类型 ✅
│ │ │ ├── xai.ts # xAI 选项 ✅
│ │ │ ├── openrouter.ts # OpenRouter 选项 ✅
│ │ │ ├── examples.ts # 示例配置 ✅
│ │ │ └── index.ts # 选项导出 ✅
│ │ └── index.ts # 核心层导出 ✅
│ ├── types.ts # 全局类型定义 ✅
│ └── index.ts # 包主入口文件 ✅
├── package.json # 包配置文件 ✅
├── tsconfig.json # TypeScript 配置 ✅
├── README.md # 包说明文档 ✅
└── AI_SDK_ARCHITECTURE.md # 本文档 ✅
```
## 4. 架构分层详解
### 4.1 Models Layer (模型层)
**职责**:统一的模型创建和配置管理
**核心文件**
- `factory.ts`: 模型工厂函数 (`createModel`, `createModels`)
- `ProviderCreator.ts`: 底层提供商创建和模型实例化
- `types.ts`: 模型配置类型定义
**设计特点**
- 函数式设计,避免不必要的类抽象
- 统一的模型配置接口
- 自动处理中间件应用
- 支持批量模型创建
**核心API**
```typescript
// 模型配置接口
export interface ModelConfig {
providerId: ProviderId
modelId: string
options: ProviderSettingsMap[ProviderId]
middlewares?: LanguageModelV1Middleware[]
}
// 核心模型创建函数
export async function createModel(config: ModelConfig): Promise<LanguageModel>
export async function createModels(configs: ModelConfig[]): Promise<LanguageModel[]>
```
### 4.2 Runtime Layer (运行时层)
**职责**运行时执行器和用户面向的API接口
**核心组件**
- `executor.ts`: 运行时执行器类
- `plugin-engine.ts`: 插件引擎原PluginEnabledAiClient
- `index.ts`: 便捷函数和工厂方法
**设计特点**
- 提供三种使用方式:类实例、静态工厂、函数式调用
- 自动集成模型创建和插件处理
- 完整的类型安全支持
- 为 OpenAI Agents SDK 预留扩展接口
**核心API**
```typescript
// 运行时执行器
export class RuntimeExecutor<T extends ProviderId = ProviderId> {
static create<T extends ProviderId>(
providerId: T,
options: ProviderSettingsMap[T],
plugins?: AiPlugin[]
): RuntimeExecutor<T>
async streamText(modelId: string, params: StreamTextParams): Promise<StreamTextResult>
async generateText(modelId: string, params: GenerateTextParams): Promise<GenerateTextResult>
async streamObject(modelId: string, params: StreamObjectParams): Promise<StreamObjectResult>
async generateObject(modelId: string, params: GenerateObjectParams): Promise<GenerateObjectResult>
}
// 便捷函数式API
export async function streamText<T extends ProviderId>(
providerId: T,
options: ProviderSettingsMap[T],
modelId: string,
params: StreamTextParams,
plugins?: AiPlugin[]
): Promise<StreamTextResult>
```
### 4.3 Plugin System (插件系统)
**职责**:可扩展的插件架构
**核心组件**
- `PluginManager`: 插件生命周期管理
- `built-in/`: 内置插件集合
- 流转换收集和应用
**设计特点**
- 借鉴 Rollup 的钩子分类设计
- 支持流转换 (`experimental_transform`)
- 内置常用插件(日志、计数等)
- 完整的生命周期钩子
**插件接口**
```typescript
export interface AiPlugin {
name: string
enforce?: 'pre' | 'post'
// 【First】首个钩子 - 只执行第一个返回值的插件
resolveModel?: (modelId: string, context: AiRequestContext) => string | null | Promise<string | null>
loadTemplate?: (templateName: string, context: AiRequestContext) => any | null | Promise<any | null>
// 【Sequential】串行钩子 - 链式执行,支持数据转换
transformParams?: (params: any, context: AiRequestContext) => any | Promise<any>
transformResult?: (result: any, context: AiRequestContext) => any | Promise<any>
// 【Parallel】并行钩子 - 不依赖顺序,用于副作用
onRequestStart?: (context: AiRequestContext) => void | Promise<void>
onRequestEnd?: (context: AiRequestContext, result: any) => void | Promise<void>
onError?: (error: Error, context: AiRequestContext) => void | Promise<void>
// 【Stream】流处理
transformStream?: () => TransformStream
}
```
### 4.4 Middleware System (中间件系统)
**职责**AI SDK原生中间件支持
**核心组件**
- `ModelWrapper.ts`: 模型包装函数
**设计哲学**
- 直接使用AI SDK的 `wrapLanguageModel`
- 与插件系统分离,职责明确
- 函数式设计,简化使用
```typescript
export function wrapModelWithMiddlewares(model: LanguageModel, middlewares: LanguageModelV1Middleware[]): LanguageModel
```
### 4.5 Provider System (提供商系统)
**职责**AI Provider注册表和动态导入
**核心组件**
- `registry.ts`: 19+ Provider配置和类型
- `factory.ts`: Provider配置工厂
**支持的Providers**
- OpenAI, Anthropic, Google, XAI
- Azure OpenAI, Amazon Bedrock, Google Vertex
- Groq, Together.ai, Fireworks, DeepSeek
- 等19+ AI SDK官方支持的providers
## 5. 使用方式
### 5.1 函数式调用 (推荐 - 简单场景)
```typescript
import { streamText, generateText } from '@cherrystudio/ai-core/runtime'
// 直接函数调用
const stream = await streamText(
'anthropic',
{ apiKey: 'your-api-key' },
'claude-3',
{ messages: [{ role: 'user', content: 'Hello!' }] },
[loggingPlugin]
)
```
### 5.2 执行器实例 (推荐 - 复杂场景)
```typescript
import { createExecutor } from '@cherrystudio/ai-core/runtime'
// 创建可复用的执行器
const executor = createExecutor('openai', { apiKey: 'your-api-key' }, [plugin1, plugin2])
// 多次使用
const stream = await executor.streamText('gpt-4', {
messages: [{ role: 'user', content: 'Hello!' }]
})
const result = await executor.generateText('gpt-4', {
messages: [{ role: 'user', content: 'How are you?' }]
})
```
### 5.3 静态工厂方法
```typescript
import { RuntimeExecutor } from '@cherrystudio/ai-core/runtime'
// 静态创建
const executor = RuntimeExecutor.create('anthropic', { apiKey: 'your-api-key' })
await executor.streamText('claude-3', { messages: [...] })
```
### 5.4 直接模型创建 (高级用法)
```typescript
import { createModel } from '@cherrystudio/ai-core/models'
import { streamText } from 'ai'
// 直接创建模型使用
const model = await createModel({
providerId: 'openai',
modelId: 'gpt-4',
options: { apiKey: 'your-api-key' },
middlewares: [middleware1, middleware2]
})
// 直接使用 AI SDK
const result = await streamText({ model, messages: [...] })
```
## 6. 为 OpenAI Agents SDK 预留的设计
### 6.1 架构兼容性
当前架构完全兼容 OpenAI Agents SDK 的集成需求:
```typescript
// 当前的模型创建
const model = await createModel({
providerId: 'anthropic',
modelId: 'claude-3',
options: { apiKey: 'xxx' }
})
// 将来可以直接用于 OpenAI Agents SDK
import { Agent, run } from '@openai/agents'
const agent = new Agent({
model, // ✅ 直接兼容 LanguageModel 接口
name: 'Assistant',
instructions: '...',
tools: [tool1, tool2]
})
const result = await run(agent, 'user input')
```
### 6.2 预留的扩展点
1. **runtime/agents/** 目录预留
2. **AgentExecutor** 类预留
3. **Agent工具转换插件** 预留
4. **多Agent编排** 预留
### 6.3 未来架构扩展
```
packages/aiCore/src/core/
├── runtime/
│ ├── agents/ # 🚀 未来添加
│ │ ├── AgentExecutor.ts
│ │ ├── WorkflowManager.ts
│ │ └── ConversationManager.ts
│ ├── executor.ts
│ └── index.ts
```
## 7. 架构优势
### 7.1 简化设计
- **移除过度抽象**删除了orchestration层和creation层的复杂包装
- **函数式优先**models层使用函数而非类
- **直接明了**runtime层直接提供用户API
### 7.2 职责清晰
- **Models**: 专注模型创建和配置
- **Runtime**: 专注执行和用户API
- **Plugins**: 专注扩展功能
- **Providers**: 专注AI Provider管理
### 7.3 类型安全
- 完整的 TypeScript 支持
- AI SDK 类型的直接复用
- 避免类型重复定义
### 7.4 灵活使用
- 三种使用模式满足不同需求
- 从简单函数调用到复杂执行器
- 支持直接AI SDK使用
### 7.5 面向未来
- 为 OpenAI Agents SDK 集成做好准备
- 清晰的扩展点和架构边界
- 模块化设计便于功能添加
## 8. 技术决策记录
### 8.1 为什么选择简化的两层架构?
- **职责分离**models专注创建runtime专注执行
- **模块化**:每层都有清晰的边界和职责
- **扩展性**为Agent功能预留了清晰的扩展空间
### 8.2 为什么选择函数式设计?
- **简洁性**:避免不必要的类设计
- **性能**:减少对象创建开销
- **易用性**:函数调用更直观
### 8.3 为什么分离插件和中间件?
- **职责明确**: 插件处理应用特定需求
- **原生支持**: 中间件使用AI SDK原生功能
- **灵活性**: 两套系统可以独立演进
## 9. 总结
AI Core架构实现了
### 9.1 核心特点
-**简化架构**: 2层核心架构职责清晰
-**函数式设计**: models层完全函数化
-**类型安全**: 统一的类型定义和AI SDK类型复用
-**插件扩展**: 强大的插件系统
-**多种使用方式**: 满足不同复杂度需求
-**Agent就绪**: 为OpenAI Agents SDK集成做好准备
### 9.2 核心价值
- **统一接口**: 一套API支持19+ AI providers
- **灵活使用**: 函数式、实例式、静态工厂式
- **强类型**: 完整的TypeScript支持
- **可扩展**: 插件和中间件双重扩展能力
- **高性能**: 最小化包装直接使用AI SDK
- **面向未来**: Agent SDK集成架构就绪
### 9.3 未来发展
这个架构提供了:
- **优秀的开发体验**: 简洁的API和清晰的使用模式
- **强大的扩展能力**: 为Agent功能预留了完整的架构空间
- **良好的维护性**: 职责分离明确,代码易于维护
- **广泛的适用性**: 既适合简单调用也适合复杂应用

View File

@@ -1,433 +0,0 @@
# @cherrystudio/ai-core
Cherry Studio AI Core 是一个基于 Vercel AI SDK 的统一 AI Provider 接口包,为 AI 应用提供强大的抽象层和插件化架构。
## ✨ 核心亮点
### 🏗️ 优雅的架构设计
- **简化分层**`models`(模型层)→ `runtime`(运行时层),清晰的职责分离
- **函数式优先**:避免过度抽象,提供简洁直观的 API
- **类型安全**:完整的 TypeScript 支持,直接复用 AI SDK 类型系统
- **最小包装**:直接使用 AI SDK 的接口,避免重复定义和性能损耗
### 🔌 强大的插件系统
- **生命周期钩子**:支持请求全生命周期的扩展点
- **流转换支持**:基于 AI SDK 的 `experimental_transform` 实现流处理
- **插件分类**First、Sequential、Parallel 三种钩子类型,满足不同场景
- **内置插件**webSearch、logging、toolUse 等开箱即用的功能
### 🌐 统一多 Provider 接口
- **扩展注册**:支持自定义 Provider 注册,无限扩展能力
- **配置统一**:统一的配置接口,简化多 Provider 管理
### 🚀 多种使用方式
- **函数式调用**:适合简单场景的直接函数调用
- **执行器实例**:适合复杂场景的可复用执行器
- **静态工厂**:便捷的静态创建方法
- **原生兼容**:完全兼容 AI SDK 原生 Provider Registry
### 🔮 面向未来
- **Agent 就绪**:为 OpenAI Agents SDK 集成预留架构空间
- **模块化设计**:独立包结构,支持跨项目复用
- **渐进式迁移**:可以逐步从现有 AI SDK 代码迁移
## 特性
- 🚀 统一的 AI Provider 接口
- 🔄 动态导入支持
- 🛠️ TypeScript 支持
- 📦 强大的插件系统
- 🌍 内置webSearch(Openai,Google,Anthropic,xAI)
- 🎯 多种使用模式(函数式/实例式/静态工厂)
- 🔌 可扩展的 Provider 注册系统
- 🧩 完整的中间件支持
- 📊 插件统计和调试功能
## 支持的 Providers
基于 [AI SDK 官方支持的 providers](https://ai-sdk.dev/providers/ai-sdk-providers)
**核心 Providers内置支持:**
- OpenAI
- Anthropic
- Google Generative AI
- OpenAI-Compatible
- xAI (Grok)
- Azure OpenAI
- DeepSeek
**扩展 Providers通过注册API支持:**
- Google Vertex AI
- ...
- 自定义 Provider
## 安装
```bash
npm install @cherrystudio/ai-core ai
```
### React Native
如果你在 React Native 项目中使用此包,需要在 `metro.config.js` 中添加以下配置:
```javascript
// metro.config.js
const { getDefaultConfig } = require('expo/metro-config')
const config = getDefaultConfig(__dirname)
// 添加对 @cherrystudio/ai-core 的支持
config.resolver.resolverMainFields = ['react-native', 'browser', 'main']
config.resolver.platforms = ['ios', 'android', 'native', 'web']
module.exports = config
```
还需要安装你要使用的 AI SDK provider:
```bash
npm install @ai-sdk/openai @ai-sdk/anthropic @ai-sdk/google
```
## 使用示例
### 基础用法
```typescript
import { AiCore } from '@cherrystudio/ai-core'
// 创建 OpenAI executor
const executor = AiCore.create('openai', {
apiKey: 'your-api-key'
})
// 流式生成
const result = await executor.streamText('gpt-4', {
messages: [{ role: 'user', content: 'Hello!' }]
})
// 非流式生成
const response = await executor.generateText('gpt-4', {
messages: [{ role: 'user', content: 'Hello!' }]
})
```
### 便捷函数
```typescript
import { createOpenAIExecutor } from '@cherrystudio/ai-core'
// 快速创建 OpenAI executor
const executor = createOpenAIExecutor({
apiKey: 'your-api-key'
})
// 使用 executor
const result = await executor.streamText('gpt-4', {
messages: [{ role: 'user', content: 'Hello!' }]
})
```
### 多 Provider 支持
```typescript
import { AiCore } from '@cherrystudio/ai-core'
// 支持多种 AI providers
const openaiExecutor = AiCore.create('openai', { apiKey: 'openai-key' })
const anthropicExecutor = AiCore.create('anthropic', { apiKey: 'anthropic-key' })
const googleExecutor = AiCore.create('google', { apiKey: 'google-key' })
const xaiExecutor = AiCore.create('xai', { apiKey: 'xai-key' })
```
### 扩展 Provider 注册
对于非内置的 providers可以通过注册 API 扩展支持:
```typescript
import { registerProvider, AiCore } from '@cherrystudio/ai-core'
// 方式一:导入并注册第三方 provider
import { createGroq } from '@ai-sdk/groq'
registerProvider({
id: 'groq',
name: 'Groq',
creator: createGroq,
supportsImageGeneration: false
})
// 现在可以使用 Groq
const groqExecutor = AiCore.create('groq', { apiKey: 'groq-key' })
// 方式二:动态导入方式注册
registerProvider({
id: 'mistral',
name: 'Mistral AI',
import: () => import('@ai-sdk/mistral'),
creatorFunctionName: 'createMistral'
})
const mistralExecutor = AiCore.create('mistral', { apiKey: 'mistral-key' })
```
## 🔌 插件系统
AI Core 提供了强大的插件系统,支持请求全生命周期的扩展。
### 内置插件
#### webSearchPlugin - 网络搜索插件
为不同 AI Provider 提供统一的网络搜索能力:
```typescript
import { webSearchPlugin } from '@cherrystudio/ai-core/built-in/plugins'
const executor = AiCore.create('openai', { apiKey: 'your-key' }, [
webSearchPlugin({
openai: {
/* OpenAI 搜索配置 */
},
anthropic: { maxUses: 5 },
google: {
/* Google 搜索配置 */
},
xai: {
mode: 'on',
returnCitations: true,
maxSearchResults: 5,
sources: [{ type: 'web' }, { type: 'x' }, { type: 'news' }]
}
})
])
```
#### loggingPlugin - 日志插件
提供详细的请求日志记录:
```typescript
import { createLoggingPlugin } from '@cherrystudio/ai-core/built-in/plugins'
const executor = AiCore.create('openai', { apiKey: 'your-key' }, [
createLoggingPlugin({
logLevel: 'info',
includeParams: true,
includeResult: false
})
])
```
#### promptToolUsePlugin - 提示工具使用插件
为不支持原生 Function Call 的模型提供 prompt 方式的工具调用:
```typescript
import { createPromptToolUsePlugin } from '@cherrystudio/ai-core/built-in/plugins'
// 对于不支持 function call 的模型
const executor = AiCore.create(
'providerId',
{
apiKey: 'your-key',
baseURL: 'https://your-model-endpoint'
},
[
createPromptToolUsePlugin({
enabled: true,
// 可选:自定义系统提示符构建
buildSystemPrompt: (userPrompt, tools) => {
return `${userPrompt}\n\nAvailable tools: ${Object.keys(tools).join(', ')}`
}
})
]
)
```
### 自定义插件
创建自定义插件非常简单:
```typescript
import { definePlugin } from '@cherrystudio/ai-core'
const customPlugin = definePlugin({
name: 'custom-plugin',
enforce: 'pre', // 'pre' | 'post' | undefined
// 在请求开始时记录日志
onRequestStart: async (context) => {
console.log(`Starting request for model: ${context.modelId}`)
},
// 转换请求参数
transformParams: async (params, context) => {
// 添加自定义系统消息
if (params.messages) {
params.messages.unshift({
role: 'system',
content: 'You are a helpful assistant.'
})
}
return params
},
// 处理响应结果
transformResult: async (result, context) => {
// 添加元数据
if (result.text) {
result.metadata = {
processedAt: new Date().toISOString(),
modelId: context.modelId
}
}
return result
}
})
// 使用自定义插件
const executor = AiCore.create('openai', { apiKey: 'your-key' }, [customPlugin])
```
### 使用 AI SDK 原生 Provider 注册表
> https://ai-sdk.dev/docs/reference/ai-sdk-core/provider-registry
除了使用内建的 provider 管理,你还可以使用 AI SDK 原生的 `createProviderRegistry` 来构建自己的 provider 注册表。
#### 基本用法示例
```typescript
import { createClient } from '@cherrystudio/ai-core'
import { createProviderRegistry } from 'ai'
import { createOpenAI } from '@ai-sdk/openai'
import { anthropic } from '@ai-sdk/anthropic'
// 1. 创建 AI SDK 原生注册表
export const registry = createProviderRegistry({
// register provider with prefix and default setup:
anthropic,
// register provider with prefix and custom setup:
openai: createOpenAI({
apiKey: process.env.OPENAI_API_KEY
})
})
// 2. 创建client,'openai'可以传空或者传providerId(内建的provider)
const client = PluginEnabledAiClient.create('openai', {
apiKey: process.env.OPENAI_API_KEY
})
// 3. 方式1使用内建逻辑传统方式
const result1 = await client.streamText('gpt-4', {
messages: [{ role: 'user', content: 'Hello with built-in logic!' }]
})
// 4. 方式2使用自定义注册表灵活方式
const result2 = await client.streamText({
model: registry.languageModel('openai:gpt-4'),
messages: [{ role: 'user', content: 'Hello with custom registry!' }]
})
// 5. 支持的重载方法
await client.generateObject({
model: registry.languageModel('openai:gpt-4'),
schema: z.object({ name: z.string() }),
messages: [{ role: 'user', content: 'Generate a user' }]
})
await client.streamObject({
model: registry.languageModel('anthropic:claude-3-opus-20240229'),
schema: z.object({ items: z.array(z.string()) }),
messages: [{ role: 'user', content: 'Generate a list' }]
})
```
#### 与插件系统配合使用
更强大的是,你还可以将自定义注册表与 Cherry Studio 的插件系统结合使用:
```typescript
import { PluginEnabledAiClient } from '@cherrystudio/ai-core'
import { createProviderRegistry } from 'ai'
import { createOpenAI } from '@ai-sdk/openai'
import { anthropic } from '@ai-sdk/anthropic'
// 1. 创建带插件的客户端
const client = PluginEnabledAiClient.create(
'openai',
{
apiKey: process.env.OPENAI_API_KEY
},
[LoggingPlugin, RetryPlugin]
)
// 2. 创建自定义注册表
const registry = createProviderRegistry({
openai: createOpenAI({ apiKey: process.env.OPENAI_API_KEY }),
anthropic: anthropic({ apiKey: process.env.ANTHROPIC_API_KEY })
})
// 3. 方式1使用内建逻辑 + 完整插件系统
await client.streamText('gpt-4', {
messages: [{ role: 'user', content: 'Hello with plugins!' }]
})
// 4. 方式2使用自定义注册表 + 有限插件支持
await client.streamText({
model: registry.languageModel('anthropic:claude-3-opus-20240229'),
messages: [{ role: 'user', content: 'Hello from Claude!' }]
})
// 5. 支持的方法
await client.generateObject({
model: registry.languageModel('openai:gpt-4'),
schema: z.object({ name: z.string() }),
messages: [{ role: 'user', content: 'Generate a user' }]
})
await client.streamObject({
model: registry.languageModel('openai:gpt-4'),
schema: z.object({ items: z.array(z.string()) }),
messages: [{ role: 'user', content: 'Generate a list' }]
})
```
#### 混合使用的优势
- **灵活性**:可以根据需要选择使用内建逻辑或自定义注册表
- **兼容性**:完全兼容 AI SDK 的 `createProviderRegistry` API
- **渐进式**:可以逐步迁移现有代码,无需一次性重构
- **插件支持**:自定义注册表仍可享受插件系统的部分功能
- **最佳实践**:结合两种方式的优点,既有动态加载的性能优势,又有统一注册表的便利性
## 📚 相关资源
- [Vercel AI SDK 文档](https://ai-sdk.dev/)
- [Cherry Studio 项目](https://github.com/CherryHQ/cherry-studio)
- [AI SDK Providers](https://ai-sdk.dev/providers/ai-sdk-providers)
## 未来版本
- 🔮 多 Agent 编排
- 🔮 可视化插件配置
- 🔮 实时监控和分析
- 🔮 云端插件同步
## 📄 License
MIT License - 详见 [LICENSE](https://github.com/CherryHQ/cherry-studio/blob/main/LICENSE) 文件
---
**Cherry Studio AI Core** - 让 AI 开发更简单、更强大、更灵活 🚀

View File

@@ -1,84 +0,0 @@
{
"name": "@cherrystudio/ai-core",
"version": "1.0.1",
"description": "Cherry Studio AI Core - Unified AI Provider Interface Based on Vercel AI SDK",
"main": "dist/index.js",
"module": "dist/index.mjs",
"types": "dist/index.d.ts",
"react-native": "dist/index.js",
"scripts": {
"build": "tsdown",
"dev": "tsc -w",
"clean": "rm -rf dist",
"test": "vitest run",
"test:watch": "vitest"
},
"keywords": [
"ai",
"sdk",
"openai",
"anthropic",
"google",
"cherry-studio",
"vercel-ai-sdk"
],
"author": "Cherry Studio",
"license": "MIT",
"repository": {
"type": "git",
"url": "git+https://github.com/CherryHQ/cherry-studio.git"
},
"bugs": {
"url": "https://github.com/CherryHQ/cherry-studio/issues"
},
"homepage": "https://github.com/CherryHQ/cherry-studio#readme",
"peerDependencies": {
"ai": "^5.0.26"
},
"dependencies": {
"@ai-sdk/anthropic": "^2.0.22",
"@ai-sdk/azure": "^2.0.42",
"@ai-sdk/deepseek": "^1.0.20",
"@ai-sdk/openai": "^2.0.42",
"@ai-sdk/openai-compatible": "^1.0.19",
"@ai-sdk/provider": "^2.0.0",
"@ai-sdk/provider-utils": "^3.0.10",
"@ai-sdk/xai": "^2.0.23",
"zod": "^4.1.5"
},
"devDependencies": {
"tsdown": "^0.12.9",
"typescript": "^5.0.0",
"vitest": "^3.2.4"
},
"sideEffects": false,
"engines": {
"node": ">=18.0.0"
},
"files": [
"dist"
],
"exports": {
".": {
"types": "./dist/index.d.ts",
"react-native": "./dist/index.js",
"import": "./dist/index.mjs",
"require": "./dist/index.js",
"default": "./dist/index.js"
},
"./built-in/plugins": {
"types": "./dist/built-in/plugins/index.d.ts",
"react-native": "./dist/built-in/plugins/index.js",
"import": "./dist/built-in/plugins/index.mjs",
"require": "./dist/built-in/plugins/index.js",
"default": "./dist/built-in/plugins/index.js"
},
"./provider": {
"types": "./dist/provider/index.d.ts",
"react-native": "./dist/provider/index.js",
"import": "./dist/provider/index.mjs",
"require": "./dist/provider/index.js",
"default": "./dist/provider/index.js"
}
}
}

View File

@@ -1,2 +0,0 @@
// 模拟 Vite SSR helper避免 Node 环境找不到时报错
;(globalThis as any).__vite_ssr_exportName__ = (name: string, value: any) => value

View File

@@ -1,3 +0,0 @@
# @cherryStudio-aiCore
Core

View File

@@ -1,17 +0,0 @@
/**
* Core 模块导出
* 内部核心功能,供其他模块使用,不直接面向最终调用者
*/
// 中间件系统
export type { NamedMiddleware } from './middleware'
export { createMiddlewares, wrapModelWithMiddlewares } from './middleware'
// 创建管理
export { globalModelResolver, ModelResolver } from './models'
export type { ModelConfig as ModelConfigType } from './models/types'
// 执行管理
export type { ToolUseRequestContext } from './plugins/built-in/toolUsePlugin/type'
export { createExecutor, createOpenAICompatibleExecutor } from './runtime'
export type { RuntimeConfig } from './runtime/types'

View File

@@ -1,8 +0,0 @@
/**
* Middleware 模块导出
* 提供通用的中间件管理能力
*/
export { createMiddlewares } from './manager'
export type { NamedMiddleware } from './types'
export { wrapModelWithMiddlewares } from './wrapper'

View File

@@ -1,16 +0,0 @@
/**
* 中间件管理器
* 专注于 AI SDK 中间件的管理,与插件系统分离
*/
import { LanguageModelV2Middleware } from '@ai-sdk/provider'
/**
* 创建中间件列表
* 合并用户提供的中间件
*/
export function createMiddlewares(userMiddlewares: LanguageModelV2Middleware[] = []): LanguageModelV2Middleware[] {
// 未来可以在这里添加默认的中间件
const defaultMiddlewares: LanguageModelV2Middleware[] = []
return [...defaultMiddlewares, ...userMiddlewares]
}

View File

@@ -1,12 +0,0 @@
/**
* 中间件系统类型定义
*/
import { LanguageModelV2Middleware } from '@ai-sdk/provider'
/**
* 具名中间件接口
*/
export interface NamedMiddleware {
name: string
middleware: LanguageModelV2Middleware
}

View File

@@ -1,23 +0,0 @@
/**
* 模型包装工具函数
* 用于将中间件应用到LanguageModel上
*/
import { LanguageModelV2, LanguageModelV2Middleware } from '@ai-sdk/provider'
import { wrapLanguageModel } from 'ai'
/**
* 使用中间件包装模型
*/
export function wrapModelWithMiddlewares(
model: LanguageModelV2,
middlewares: LanguageModelV2Middleware[]
): LanguageModelV2 {
if (middlewares.length === 0) {
return model
}
return wrapLanguageModel({
model,
middleware: middlewares
})
}

View File

@@ -1,124 +0,0 @@
/**
* 模型解析器 - models模块的核心
* 负责将modelId解析为AI SDK的LanguageModel实例
* 支持传统格式和命名空间格式
* 集成了来自 ModelCreator 的特殊处理逻辑
*/
import { EmbeddingModelV2, ImageModelV2, LanguageModelV2, LanguageModelV2Middleware } from '@ai-sdk/provider'
import { wrapModelWithMiddlewares } from '../middleware/wrapper'
import { DEFAULT_SEPARATOR, globalRegistryManagement } from '../providers/RegistryManagement'
export class ModelResolver {
/**
* 核心方法解析任意格式的modelId为语言模型
*
* @param modelId 模型ID支持 'gpt-4' 和 'anthropic>claude-3' 两种格式
* @param fallbackProviderId 当modelId为传统格式时使用的providerId
* @param providerOptions provider配置选项用于OpenAI模式选择等
* @param middlewares 中间件数组,会应用到最终模型上
*/
async resolveLanguageModel(
modelId: string,
fallbackProviderId: string,
providerOptions?: any,
middlewares?: LanguageModelV2Middleware[]
): Promise<LanguageModelV2> {
let finalProviderId = fallbackProviderId
let model: LanguageModelV2
// 🎯 处理 OpenAI 模式选择逻辑 (从 ModelCreator 迁移)
if ((fallbackProviderId === 'openai' || fallbackProviderId === 'azure') && providerOptions?.mode === 'chat') {
finalProviderId = `${fallbackProviderId}-chat`
}
// 检查是否是命名空间格式
if (modelId.includes(DEFAULT_SEPARATOR)) {
model = this.resolveNamespacedModel(modelId)
} else {
// 传统格式:使用处理后的 providerId + modelId
model = this.resolveTraditionalModel(finalProviderId, modelId)
}
// 🎯 应用中间件(如果有)
if (middlewares && middlewares.length > 0) {
model = wrapModelWithMiddlewares(model, middlewares)
}
return model
}
/**
* 解析文本嵌入模型
*/
async resolveTextEmbeddingModel(modelId: string, fallbackProviderId: string): Promise<EmbeddingModelV2<string>> {
if (modelId.includes(DEFAULT_SEPARATOR)) {
return this.resolveNamespacedEmbeddingModel(modelId)
}
return this.resolveTraditionalEmbeddingModel(fallbackProviderId, modelId)
}
/**
* 解析图像模型
*/
async resolveImageModel(modelId: string, fallbackProviderId: string): Promise<ImageModelV2> {
if (modelId.includes(DEFAULT_SEPARATOR)) {
return this.resolveNamespacedImageModel(modelId)
}
return this.resolveTraditionalImageModel(fallbackProviderId, modelId)
}
/**
* 解析命名空间格式的语言模型
* aihubmix:anthropic:claude-3 -> globalRegistryManagement.languageModel('aihubmix:anthropic:claude-3')
*/
private resolveNamespacedModel(modelId: string): LanguageModelV2 {
return globalRegistryManagement.languageModel(modelId as any)
}
/**
* 解析传统格式的语言模型
* providerId: 'openai', modelId: 'gpt-4' -> globalRegistryManagement.languageModel('openai:gpt-4')
*/
private resolveTraditionalModel(providerId: string, modelId: string): LanguageModelV2 {
const fullModelId = `${providerId}${DEFAULT_SEPARATOR}${modelId}`
return globalRegistryManagement.languageModel(fullModelId as any)
}
/**
* 解析命名空间格式的嵌入模型
*/
private resolveNamespacedEmbeddingModel(modelId: string): EmbeddingModelV2<string> {
return globalRegistryManagement.textEmbeddingModel(modelId as any)
}
/**
* 解析传统格式的嵌入模型
*/
private resolveTraditionalEmbeddingModel(providerId: string, modelId: string): EmbeddingModelV2<string> {
const fullModelId = `${providerId}${DEFAULT_SEPARATOR}${modelId}`
return globalRegistryManagement.textEmbeddingModel(fullModelId as any)
}
/**
* 解析命名空间格式的图像模型
*/
private resolveNamespacedImageModel(modelId: string): ImageModelV2 {
return globalRegistryManagement.imageModel(modelId as any)
}
/**
* 解析传统格式的图像模型
*/
private resolveTraditionalImageModel(providerId: string, modelId: string): ImageModelV2 {
const fullModelId = `${providerId}${DEFAULT_SEPARATOR}${modelId}`
return globalRegistryManagement.imageModel(fullModelId as any)
}
}
/**
* 全局模型解析器实例
*/
export const globalModelResolver = new ModelResolver()

View File

@@ -1,9 +0,0 @@
/**
* Models 模块统一导出 - 简化版
*/
// 核心模型解析器
export { globalModelResolver, ModelResolver } from './ModelResolver'
// 保留的类型定义(可能被其他地方使用)
export type { ModelConfig as ModelConfigType } from './types'

View File

@@ -1,15 +0,0 @@
/**
* Creation 模块类型定义
*/
import { LanguageModelV2Middleware } from '@ai-sdk/provider'
import type { ProviderId, ProviderSettingsMap } from '../providers/types'
export interface ModelConfig<T extends ProviderId = ProviderId> {
providerId: T
modelId: string
providerSettings: ProviderSettingsMap[T] & { mode?: 'chat' | 'responses' }
middlewares?: LanguageModelV2Middleware[]
// 额外模型参数
extraModelConfig?: Record<string, any>
}

View File

@@ -1,87 +0,0 @@
import { streamText } from 'ai'
import {
createAnthropicOptions,
createGenericProviderOptions,
createGoogleOptions,
createOpenAIOptions,
mergeProviderOptions
} from './factory'
// 示例1: 使用已知供应商的严格类型约束
export function exampleOpenAIWithOptions() {
const openaiOptions = createOpenAIOptions({
reasoningEffort: 'medium'
})
// 这里会有类型检查确保选项符合OpenAI的设置
return streamText({
model: {} as any, // 实际使用时替换为真实模型
prompt: 'Hello',
providerOptions: openaiOptions
})
}
// 示例2: 使用Anthropic供应商选项
export function exampleAnthropicWithOptions() {
const anthropicOptions = createAnthropicOptions({
thinking: {
type: 'enabled',
budgetTokens: 1000
}
})
return streamText({
model: {} as any,
prompt: 'Hello',
providerOptions: anthropicOptions
})
}
// 示例3: 使用Google供应商选项
export function exampleGoogleWithOptions() {
const googleOptions = createGoogleOptions({
thinkingConfig: {
includeThoughts: true,
thinkingBudget: 1000
}
})
return streamText({
model: {} as any,
prompt: 'Hello',
providerOptions: googleOptions
})
}
// 示例4: 使用未知供应商(通用类型)
export function exampleUnknownProviderWithOptions() {
const customProviderOptions = createGenericProviderOptions('custom-provider', {
temperature: 0.7,
customSetting: 'value',
anotherOption: true
})
return streamText({
model: {} as any,
prompt: 'Hello',
providerOptions: customProviderOptions
})
}
// 示例5: 合并多个供应商选项
export function exampleMergedOptions() {
const openaiOptions = createOpenAIOptions({})
const customOptions = createGenericProviderOptions('custom', {
customParam: 'value'
})
const mergedOptions = mergeProviderOptions(openaiOptions, customOptions)
return streamText({
model: {} as any,
prompt: 'Hello',
providerOptions: mergedOptions
})
}

View File

@@ -1,71 +0,0 @@
import { ExtractProviderOptions, ProviderOptionsMap, TypedProviderOptions } from './types'
/**
* 创建特定供应商的选项
* @param provider 供应商名称
* @param options 供应商特定的选项
* @returns 格式化的provider options
*/
export function createProviderOptions<T extends keyof ProviderOptionsMap>(
provider: T,
options: ExtractProviderOptions<T>
): Record<T, ExtractProviderOptions<T>> {
return { [provider]: options } as Record<T, ExtractProviderOptions<T>>
}
/**
* 创建任意供应商的选项(包括未知供应商)
* @param provider 供应商名称
* @param options 供应商选项
* @returns 格式化的provider options
*/
export function createGenericProviderOptions<T extends string>(
provider: T,
options: Record<string, any>
): Record<T, Record<string, any>> {
return { [provider]: options } as Record<T, Record<string, any>>
}
/**
* 合并多个供应商的options
* @param optionsMap 包含多个供应商选项的对象
* @returns 合并后的TypedProviderOptions
*/
export function mergeProviderOptions(...optionsMap: Partial<TypedProviderOptions>[]): TypedProviderOptions {
return Object.assign({}, ...optionsMap)
}
/**
* 创建OpenAI供应商选项的便捷函数
*/
export function createOpenAIOptions(options: ExtractProviderOptions<'openai'>) {
return createProviderOptions('openai', options)
}
/**
* 创建Anthropic供应商选项的便捷函数
*/
export function createAnthropicOptions(options: ExtractProviderOptions<'anthropic'>) {
return createProviderOptions('anthropic', options)
}
/**
* 创建Google供应商选项的便捷函数
*/
export function createGoogleOptions(options: ExtractProviderOptions<'google'>) {
return createProviderOptions('google', options)
}
/**
* 创建OpenRouter供应商选项的便捷函数
*/
export function createOpenRouterOptions(options: ExtractProviderOptions<'openrouter'> | Record<string, any>) {
return createProviderOptions('openrouter', options)
}
/**
* 创建XAI供应商选项的便捷函数
*/
export function createXaiOptions(options: ExtractProviderOptions<'xai'>) {
return createProviderOptions('xai', options)
}

View File

@@ -1,2 +0,0 @@
export * from './factory'
export * from './types'

View File

@@ -1,32 +0,0 @@
import { type AnthropicProviderOptions } from '@ai-sdk/anthropic'
import { type GoogleGenerativeAIProviderOptions } from '@ai-sdk/google'
import { type OpenAIResponsesProviderOptions } from '@ai-sdk/openai'
import { type SharedV2ProviderMetadata } from '@ai-sdk/provider'
import { type XaiProviderOptions } from '@ai-sdk/xai'
import { type OpenRouterProviderOptions } from '@openrouter/ai-sdk-provider'
export type ProviderOptions<T extends keyof SharedV2ProviderMetadata> = SharedV2ProviderMetadata[T]
/**
* 供应商选项类型如果map中没有说明没有约束
*/
export type ProviderOptionsMap = {
openai: OpenAIResponsesProviderOptions
anthropic: AnthropicProviderOptions
google: GoogleGenerativeAIProviderOptions
openrouter: OpenRouterProviderOptions
xai: XaiProviderOptions
}
// 工具类型用于从ProviderOptionsMap中提取特定供应商的选项类型
export type ExtractProviderOptions<T extends keyof ProviderOptionsMap> = ProviderOptionsMap[T]
/**
* 类型安全的ProviderOptions
* 对于已知供应商使用严格类型对于未知供应商允许任意Record<string, JSONValue>
*/
export type TypedProviderOptions = {
[K in keyof ProviderOptionsMap]?: ProviderOptionsMap[K]
} & {
[K in string]?: Record<string, any>
} & SharedV2ProviderMetadata

View File

@@ -1,257 +0,0 @@
# AI Core 插件系统
支持四种钩子类型:**First**、**Sequential**、**Parallel** 和 **Stream**
## 🎯 设计理念
- **语义清晰**:不同钩子有不同的执行语义
- **类型安全**TypeScript 完整支持
- **性能优化**First 短路、Parallel 并发、Sequential 链式
- **易于扩展**`enforce` 排序 + 功能分类
## 📋 钩子类型
### 🥇 First 钩子 - 首个有效结果
```typescript
// 只执行第一个返回值的插件,用于解析和查找
resolveModel?: (modelId: string, context: AiRequestContext) => string | null
loadTemplate?: (templateName: string, context: AiRequestContext) => any | null
```
### 🔄 Sequential 钩子 - 链式数据转换
```typescript
// 按顺序链式执行,每个插件可以修改数据
transformParams?: (params: any, context: AiRequestContext) => any
transformResult?: (result: any, context: AiRequestContext) => any
```
### ⚡ Parallel 钩子 - 并行副作用
```typescript
// 并发执行,用于日志、监控等副作用
onRequestStart?: (context: AiRequestContext) => void
onRequestEnd?: (context: AiRequestContext, result: any) => void
onError?: (error: Error, context: AiRequestContext) => void
```
### 🌊 Stream 钩子 - 流处理
```typescript
// 直接使用 AI SDK 的 TransformStream
transformStream?: () => (options) => TransformStream<TextStreamPart, TextStreamPart>
```
## 🚀 快速开始
### 基础用法
```typescript
import { PluginManager, createContext, definePlugin } from '@cherrystudio/ai-core/middleware'
// 创建插件管理器
const pluginManager = new PluginManager()
// 添加插件
pluginManager.use({
name: 'my-plugin',
async transformParams(params, context) {
return { ...params, temperature: 0.7 }
}
})
// 使用插件
const context = createContext('openai', 'gpt-4', { messages: [] })
const transformedParams = await pluginManager.executeSequential(
'transformParams',
{ messages: [{ role: 'user', content: 'Hello' }] },
context
)
```
### 完整示例
```typescript
import {
PluginManager,
ModelAliasPlugin,
LoggingPlugin,
ParamsValidationPlugin,
createContext
} from '@cherrystudio/ai-core/middleware'
// 创建插件管理器
const manager = new PluginManager([
ModelAliasPlugin, // 模型别名解析
ParamsValidationPlugin, // 参数验证
LoggingPlugin // 日志记录
])
// AI 请求流程
async function aiRequest(providerId: string, modelId: string, params: any) {
const context = createContext(providerId, modelId, params)
try {
// 1. 【并行】触发请求开始事件
await manager.executeParallel('onRequestStart', context)
// 2. 【首个】解析模型别名
const resolvedModel = await manager.executeFirst('resolveModel', modelId, context)
context.modelId = resolvedModel || modelId
// 3. 【串行】转换请求参数
const transformedParams = await manager.executeSequential('transformParams', params, context)
// 4. 【流处理】收集流转换器AI SDK 原生支持数组)
const streamTransforms = manager.collectStreamTransforms()
// 5. 调用 AI SDK这里省略具体实现
const result = await callAiSdk(transformedParams, streamTransforms)
// 6. 【串行】转换响应结果
const transformedResult = await manager.executeSequential('transformResult', result, context)
// 7. 【并行】触发请求完成事件
await manager.executeParallel('onRequestEnd', context, transformedResult)
return transformedResult
} catch (error) {
// 8. 【并行】触发错误事件
await manager.executeParallel('onError', context, undefined, error)
throw error
}
}
```
## 🔧 自定义插件
### 模型别名插件
```typescript
const ModelAliasPlugin = definePlugin({
name: 'model-alias',
enforce: 'pre', // 最先执行
async resolveModel(modelId) {
const aliases = {
gpt4: 'gpt-4-turbo-preview',
claude: 'claude-3-sonnet-20240229'
}
return aliases[modelId] || null
}
})
```
### 参数验证插件
```typescript
const ValidationPlugin = definePlugin({
name: 'validation',
async transformParams(params) {
if (!params.messages) {
throw new Error('messages is required')
}
return {
...params,
temperature: params.temperature ?? 0.7,
max_tokens: params.max_tokens ?? 4096
}
}
})
```
### 监控插件
```typescript
const MonitoringPlugin = definePlugin({
name: 'monitoring',
enforce: 'post', // 最后执行
async onRequestEnd(context, result) {
const duration = Date.now() - context.startTime
console.log(`请求耗时: ${duration}ms`)
}
})
```
### 内容过滤插件
```typescript
const FilterPlugin = definePlugin({
name: 'content-filter',
transformStream() {
return () =>
new TransformStream({
transform(chunk, controller) {
if (chunk.type === 'text-delta') {
const filtered = chunk.textDelta.replace(/敏感词/g, '***')
controller.enqueue({ ...chunk, textDelta: filtered })
} else {
controller.enqueue(chunk)
}
}
})
}
})
```
## 📊 执行顺序
### 插件排序
```
enforce: 'pre' → normal → enforce: 'post'
```
### 钩子执行流程
```mermaid
graph TD
A[请求开始] --> B[onRequestStart 并行执行]
B --> C[resolveModel 首个有效]
C --> D[loadTemplate 首个有效]
D --> E[transformParams 串行执行]
E --> F[collectStreamTransforms]
F --> G[AI SDK 调用]
G --> H[transformResult 串行执行]
H --> I[onRequestEnd 并行执行]
G --> J[异常处理]
J --> K[onError 并行执行]
```
## 💡 最佳实践
1. **功能单一**:每个插件专注一个功能
2. **幂等性**:插件应该是幂等的,重复执行不会产生副作用
3. **错误处理**:插件内部处理异常,不要让异常向上传播
4. **性能优化**使用合适的钩子类型First vs Sequential vs Parallel
5. **命名规范**:使用语义化的插件名称
## 🔍 调试工具
```typescript
// 查看插件统计信息
const stats = manager.getStats()
console.log('插件统计:', stats)
// 查看所有插件
const plugins = manager.getPlugins()
console.log(
'已注册插件:',
plugins.map((p) => p.name)
)
```
## ⚡ 性能优势
- **First 钩子**:一旦找到结果立即停止,避免无效计算
- **Parallel 钩子**:真正并发执行,不阻塞主流程
- **Sequential 钩子**:保证数据转换的顺序性
- **Stream 钩子**:直接集成 AI SDK零开销
这个设计兼顾了简洁性和强大功能,为 AI Core 提供了灵活而高效的扩展机制。

View File

@@ -1,38 +0,0 @@
import { google } from '@ai-sdk/google'
import { definePlugin } from '../../'
import type { AiRequestContext } from '../../types'
const toolNameMap = {
googleSearch: 'google_search',
urlContext: 'url_context',
codeExecution: 'code_execution'
} as const
type ToolConfigKey = keyof typeof toolNameMap
type ToolConfig = { googleSearch?: boolean; urlContext?: boolean; codeExecution?: boolean }
export const googleToolsPlugin = (config?: ToolConfig) =>
definePlugin({
name: 'googleToolsPlugin',
transformParams: <T>(params: T, context: AiRequestContext): T => {
const { providerId } = context
if (providerId === 'google' && config) {
if (typeof params === 'object' && params !== null) {
const typedParams = params as T & { tools?: Record<string, unknown> }
if (!typedParams.tools) {
typedParams.tools = {}
}
// 使用类型安全的方式遍历配置
;(Object.keys(config) as ToolConfigKey[]).forEach((key) => {
if (config[key] && key in toolNameMap && key in google.tools) {
const toolName = toolNameMap[key]
typedParams.tools![toolName] = google.tools[key]({})
}
})
}
}
return params
}
})

View File

@@ -1,15 +0,0 @@
/**
* 内置插件命名空间
* 所有内置插件都以 'built-in:' 为前缀
*/
export const BUILT_IN_PLUGIN_PREFIX = 'built-in:'
export { googleToolsPlugin } from './googleToolsPlugin'
export { createLoggingPlugin } from './logging'
export { createPromptToolUsePlugin } from './toolUsePlugin/promptToolUsePlugin'
export type {
PromptToolUseConfig,
ToolUseRequestContext,
ToolUseResult
} from './toolUsePlugin/type'
export { webSearchPlugin, type WebSearchPluginConfig } from './webSearchPlugin'

View File

@@ -1,86 +0,0 @@
/**
* 内置插件:日志记录
* 记录AI调用的关键信息支持性能监控和调试
*/
import { definePlugin } from '../index'
import type { AiRequestContext } from '../types'
export interface LoggingConfig {
// 日志级别
level?: 'debug' | 'info' | 'warn' | 'error'
// 是否记录参数
logParams?: boolean
// 是否记录结果
logResult?: boolean
// 是否记录性能数据
logPerformance?: boolean
// 自定义日志函数
logger?: (level: string, message: string, data?: any) => void
}
/**
* 创建日志插件
*/
export function createLoggingPlugin(config: LoggingConfig = {}) {
const { level = 'info', logParams = true, logResult = false, logPerformance = true, logger = console.log } = config
const startTimes = new Map<string, number>()
return definePlugin({
name: 'built-in:logging',
onRequestStart: (context: AiRequestContext) => {
const requestId = context.requestId
startTimes.set(requestId, Date.now())
logger(level, `🚀 AI Request Started`, {
requestId,
providerId: context.providerId,
modelId: context.modelId,
originalParams: logParams ? context.originalParams : '[hidden]'
})
},
onRequestEnd: (context: AiRequestContext, result: any) => {
const requestId = context.requestId
const startTime = startTimes.get(requestId)
const duration = startTime ? Date.now() - startTime : undefined
startTimes.delete(requestId)
const logData: any = {
requestId,
providerId: context.providerId,
modelId: context.modelId
}
if (logPerformance && duration) {
logData.duration = `${duration}ms`
}
if (logResult) {
logData.result = result
}
logger(level, `✅ AI Request Completed`, logData)
},
onError: (error: Error, context: AiRequestContext) => {
const requestId = context.requestId
const startTime = startTimes.get(requestId)
const duration = startTime ? Date.now() - startTime : undefined
startTimes.delete(requestId)
logger('error', `❌ AI Request Failed`, {
requestId,
providerId: context.providerId,
modelId: context.modelId,
duration: duration ? `${duration}ms` : undefined,
error: {
name: error.name,
message: error.message,
stack: error.stack
}
})
}
})
}

View File

@@ -1,174 +0,0 @@
/**
* 流事件管理器
*
* 负责处理 AI SDK 流事件的发送和管理
* 从 promptToolUsePlugin.ts 中提取出来以降低复杂度
*/
import type { ModelMessage } from 'ai'
import type { AiRequestContext } from '../../types'
import type { StreamController } from './ToolExecutor'
/**
* 流事件管理器类
*/
export class StreamEventManager {
/**
* 发送工具调用步骤开始事件
*/
sendStepStartEvent(controller: StreamController): void {
controller.enqueue({
type: 'start-step',
request: {},
warnings: []
})
}
/**
* 发送步骤完成事件
*/
sendStepFinishEvent(
controller: StreamController,
chunk: any,
context: AiRequestContext,
finishReason: string = 'stop'
): void {
// 累加当前步骤的 usage
if (chunk.usage && context.accumulatedUsage) {
this.accumulateUsage(context.accumulatedUsage, chunk.usage)
}
controller.enqueue({
type: 'finish-step',
finishReason,
response: chunk.response,
usage: chunk.usage,
providerMetadata: chunk.providerMetadata
})
}
/**
* 处理递归调用并将结果流接入当前流
*/
async handleRecursiveCall(
controller: StreamController,
recursiveParams: any,
context: AiRequestContext
): Promise<void> {
// try {
// 重置工具执行状态,准备处理新的步骤
context.hasExecutedToolsInCurrentStep = false
const recursiveResult = await context.recursiveCall(recursiveParams)
if (recursiveResult && recursiveResult.fullStream) {
await this.pipeRecursiveStream(controller, recursiveResult.fullStream, context)
} else {
console.warn('[MCP Prompt] No fullstream found in recursive result:', recursiveResult)
}
// } catch (error) {
// this.handleRecursiveCallError(controller, error, stepId)
// }
}
/**
* 将递归流的数据传递到当前流
*/
private async pipeRecursiveStream(
controller: StreamController,
recursiveStream: ReadableStream,
context?: AiRequestContext
): Promise<void> {
const reader = recursiveStream.getReader()
try {
while (true) {
const { done, value } = await reader.read()
if (done) {
break
}
if (value.type === 'finish') {
// 迭代的流不发finish但需要累加其 usage
if (value.usage && context?.accumulatedUsage) {
this.accumulateUsage(context.accumulatedUsage, value.usage)
}
break
}
// 对于 finish-step 类型,累加其 usage
if (value.type === 'finish-step' && value.usage && context?.accumulatedUsage) {
this.accumulateUsage(context.accumulatedUsage, value.usage)
}
// 将递归流的数据传递到当前流
controller.enqueue(value)
}
} finally {
reader.releaseLock()
}
}
/**
* 处理递归调用错误
*/
// private handleRecursiveCallError(controller: StreamController, error: unknown): void {
// console.error('[MCP Prompt] Recursive call failed:', error)
// // 使用 AI SDK 标准错误格式,但不中断流
// controller.enqueue({
// type: 'error',
// error: {
// message: error instanceof Error ? error.message : String(error),
// name: error instanceof Error ? error.name : 'RecursiveCallError'
// }
// })
// // // 继续发送文本增量,保持流的连续性
// // controller.enqueue({
// // type: 'text-delta',
// // id: stepId,
// // text: '\n\n[工具执行后递归调用失败,继续对话...]'
// // })
// }
/**
* 构建递归调用的参数
*/
buildRecursiveParams(context: AiRequestContext, textBuffer: string, toolResultsText: string, tools: any): any {
// 构建新的对话消息
const newMessages: ModelMessage[] = [
...(context.originalParams.messages || []),
{
role: 'assistant',
content: textBuffer
},
{
role: 'user',
content: toolResultsText
}
]
// 递归调用,继续对话,重新传递 tools
const recursiveParams = {
...context.originalParams,
messages: newMessages,
tools: tools
}
// 更新上下文中的消息
context.originalParams.messages = newMessages
return recursiveParams
}
/**
* 累加 usage 数据
*/
private accumulateUsage(target: any, source: any): void {
if (!target || !source) return
// 累加各种 token 类型
target.inputTokens = (target.inputTokens || 0) + (source.inputTokens || 0)
target.outputTokens = (target.outputTokens || 0) + (source.outputTokens || 0)
target.totalTokens = (target.totalTokens || 0) + (source.totalTokens || 0)
target.reasoningTokens = (target.reasoningTokens || 0) + (source.reasoningTokens || 0)
target.cachedInputTokens = (target.cachedInputTokens || 0) + (source.cachedInputTokens || 0)
}
}

View File

@@ -1,151 +0,0 @@
/**
* 工具执行器
*
* 负责工具的执行、结果格式化和相关事件发送
* 从 promptToolUsePlugin.ts 中提取出来以降低复杂度
*/
import type { ToolSet, TypedToolError } from 'ai'
import type { ToolUseResult } from './type'
/**
* 工具执行结果
*/
export interface ExecutedResult {
toolCallId: string
toolName: string
result: any
isError?: boolean
}
/**
* 流控制器类型(从 AI SDK 提取)
*/
export interface StreamController {
enqueue(chunk: any): void
}
/**
* 工具执行器类
*/
export class ToolExecutor {
/**
* 执行多个工具调用
*/
async executeTools(
toolUses: ToolUseResult[],
tools: ToolSet,
controller: StreamController
): Promise<ExecutedResult[]> {
const executedResults: ExecutedResult[] = []
for (const toolUse of toolUses) {
try {
const tool = tools[toolUse.toolName]
if (!tool || typeof tool.execute !== 'function') {
throw new Error(`Tool "${toolUse.toolName}" has no execute method`)
}
// 发送 tool-call 事件
controller.enqueue({
type: 'tool-call',
toolCallId: toolUse.id,
toolName: toolUse.toolName,
input: toolUse.arguments
})
const result = await tool.execute(toolUse.arguments, {
toolCallId: toolUse.id,
messages: [],
abortSignal: new AbortController().signal
})
// 发送 tool-result 事件
controller.enqueue({
type: 'tool-result',
toolCallId: toolUse.id,
toolName: toolUse.toolName,
input: toolUse.arguments,
output: result
})
executedResults.push({
toolCallId: toolUse.id,
toolName: toolUse.toolName,
result,
isError: false
})
} catch (error) {
console.error(`[MCP Prompt Stream] Tool execution failed: ${toolUse.toolName}`, error)
// 处理错误情况
const errorResult = this.handleToolError(toolUse, error, controller)
executedResults.push(errorResult)
}
}
return executedResults
}
/**
* 格式化工具结果为 Cherry Studio 标准格式
*/
formatToolResults(executedResults: ExecutedResult[]): string {
return executedResults
.map((tr) => {
if (!tr.isError) {
return `<tool_use_result>\n <name>${tr.toolName}</name>\n <result>${JSON.stringify(tr.result)}</result>\n</tool_use_result>`
} else {
const error = tr.result || 'Unknown error'
return `<tool_use_result>\n <name>${tr.toolName}</name>\n <error>${error}</error>\n</tool_use_result>`
}
})
.join('\n\n')
}
/**
* 发送工具调用开始相关事件
*/
// private sendToolStartEvents(controller: StreamController, toolUse: ToolUseResult): void {
// // 发送 tool-input-start 事件
// controller.enqueue({
// type: 'tool-input-start',
// id: toolUse.id,
// toolName: toolUse.toolName
// })
// }
/**
* 处理工具执行错误
*/
private handleToolError<T extends ToolSet>(
toolUse: ToolUseResult,
error: unknown,
controller: StreamController
): ExecutedResult {
// 使用 AI SDK 标准错误格式
const toolError: TypedToolError<T> = {
type: 'tool-error',
toolCallId: toolUse.id,
toolName: toolUse.toolName,
input: toolUse.arguments,
error
}
controller.enqueue(toolError)
// 发送标准错误事件
// controller.enqueue({
// type: 'tool-error',
// toolCallId: toolUse.id,
// error: error instanceof Error ? error.message : String(error),
// input: toolUse.arguments
// })
return {
toolCallId: toolUse.id,
toolName: toolUse.toolName,
result: error,
isError: true
}
}
}

View File

@@ -1,445 +0,0 @@
/**
* 内置插件MCP Prompt 模式
* 为不支持原生 Function Call 的模型提供 prompt 方式的工具调用
* 内置默认逻辑,支持自定义覆盖
*/
import type { TextStreamPart, ToolSet } from 'ai'
import { definePlugin } from '../../index'
import type { AiRequestContext } from '../../types'
import { StreamEventManager } from './StreamEventManager'
import { type TagConfig, TagExtractor } from './tagExtraction'
import { ToolExecutor } from './ToolExecutor'
import { PromptToolUseConfig, ToolUseResult } from './type'
/**
* 工具使用标签配置
*/
const TOOL_USE_TAG_CONFIG: TagConfig = {
openingTag: '<tool_use>',
closingTag: '</tool_use>',
separator: '\n'
}
/**
* 默认系统提示符模板(提取自 Cherry Studio
*/
const DEFAULT_SYSTEM_PROMPT = `In this environment you have access to a set of tools you can use to answer the user's question. \\
You can use one tool per message, and will receive the result of that tool use in the user's response. You use tools step-by-step to accomplish a given task, with each tool use informed by the result of the previous tool use.
## Tool Use Formatting
Tool use is formatted using XML-style tags. The tool name is enclosed in opening and closing tags, and each parameter is similarly enclosed within its own set of tags. Here's the structure:
<tool_use>
<name>{tool_name}</name>
<arguments>{json_arguments}</arguments>
</tool_use>
The tool name should be the exact name of the tool you are using, and the arguments should be a JSON object containing the parameters required by that tool. For example:
<tool_use>
<name>python_interpreter</name>
<arguments>{"code": "5 + 3 + 1294.678"}</arguments>
</tool_use>
The user will respond with the result of the tool use, which should be formatted as follows:
<tool_use_result>
<name>{tool_name}</name>
<result>{result}</result>
</tool_use_result>
The result should be a string, which can represent a file or any other output type. You can use this result as input for the next action.
For example, if the result of the tool use is an image file, you can use it in the next action like this:
<tool_use>
<name>image_transformer</name>
<arguments>{"image": "image_1.jpg"}</arguments>
</tool_use>
Always adhere to this format for the tool use to ensure proper parsing and execution.
## Tool Use Examples
{{ TOOL_USE_EXAMPLES }}
## Tool Use Available Tools
Above example were using notional tools that might not exist for you. You only have access to these tools:
{{ AVAILABLE_TOOLS }}
## Tool Use Rules
Here are the rules you should always follow to solve your task:
1. Always use the right arguments for the tools. Never use variable names as the action arguments, use the value instead.
2. Call a tool only when needed: do not call the search agent if you do not need information, try to solve the task yourself.
3. If no tool call is needed, just answer the question directly.
4. Never re-do a tool call that you previously did with the exact same parameters.
5. For tool use, MAKE SURE use XML tag format as shown in the examples above. Do not use any other format.
# User Instructions
{{ USER_SYSTEM_PROMPT }}
Now Begin! If you solve the task correctly, you will receive a reward of $1,000,000.`
/**
* 默认工具使用示例(提取自 Cherry Studio
*/
const DEFAULT_TOOL_USE_EXAMPLES = `
Here are a few examples using notional tools:
---
User: Generate an image of the oldest person in this document.
A: I can use the document_qa tool to find out who the oldest person is in the document.
<tool_use>
<name>document_qa</name>
<arguments>{"document": "document.pdf", "question": "Who is the oldest person mentioned?"}</arguments>
</tool_use>
User: <tool_use_result>
<name>document_qa</name>
<result>John Doe, a 55 year old lumberjack living in Newfoundland.</result>
</tool_use_result>
A: I can use the image_generator tool to create a portrait of John Doe.
<tool_use>
<name>image_generator</name>
<arguments>{"prompt": "A portrait of John Doe, a 55-year-old man living in Canada."}</arguments>
</tool_use>
User: <tool_use_result>
<name>image_generator</name>
<result>image.png</result>
</tool_use_result>
A: the image is generated as image.png
---
User: "What is the result of the following operation: 5 + 3 + 1294.678?"
A: I can use the python_interpreter tool to calculate the result of the operation.
<tool_use>
<name>python_interpreter</name>
<arguments>{"code": "5 + 3 + 1294.678"}</arguments>
</tool_use>
User: <tool_use_result>
<name>python_interpreter</name>
<result>1302.678</result>
</tool_use_result>
A: The result of the operation is 1302.678.
---
User: "Which city has the highest population , Guangzhou or Shanghai?"
A: I can use the search tool to find the population of Guangzhou.
<tool_use>
<name>search</name>
<arguments>{"query": "Population Guangzhou"}</arguments>
</tool_use>
User: <tool_use_result>
<name>search</name>
<result>Guangzhou has a population of 15 million inhabitants as of 2021.</result>
</tool_use_result>
A: I can use the search tool to find the population of Shanghai.
<tool_use>
<name>search</name>
<arguments>{"query": "Population Shanghai"}</arguments>
</tool_use>
User: <tool_use_result>
<name>search</name>
<result>26 million (2019)</result>
</tool_use_result>
Assistant: The population of Shanghai is 26 million, while Guangzhou has a population of 15 million. Therefore, Shanghai has the highest population.`
/**
* 构建可用工具部分(提取自 Cherry Studio
*/
function buildAvailableTools(tools: ToolSet): string | null {
const availableTools = Object.keys(tools)
if (availableTools.length === 0) return null
const result = availableTools
.map((toolName: string) => {
const tool = tools[toolName]
return `
<tool>
<name>${toolName}</name>
<description>${tool.description || ''}</description>
<arguments>
${tool.inputSchema ? JSON.stringify(tool.inputSchema) : ''}
</arguments>
</tool>
`
})
.join('\n')
return `<tools>
${result}
</tools>`
}
/**
* 默认的系统提示符构建函数(提取自 Cherry Studio
*/
function defaultBuildSystemPrompt(userSystemPrompt: string, tools: ToolSet): string {
const availableTools = buildAvailableTools(tools)
if (availableTools === null) return userSystemPrompt
const fullPrompt = DEFAULT_SYSTEM_PROMPT.replace('{{ TOOL_USE_EXAMPLES }}', DEFAULT_TOOL_USE_EXAMPLES)
.replace('{{ AVAILABLE_TOOLS }}', availableTools)
.replace('{{ USER_SYSTEM_PROMPT }}', userSystemPrompt || '')
return fullPrompt
}
/**
* 默认工具解析函数(提取自 Cherry Studio
* 解析 XML 格式的工具调用
*/
function defaultParseToolUse(content: string, tools: ToolSet): { results: ToolUseResult[]; content: string } {
if (!content || !tools || Object.keys(tools).length === 0) {
return { results: [], content: content }
}
// 支持两种格式:
// 1. 完整的 <tool_use></tool_use> 标签包围的内容
// 2. 只有内部内容(从 TagExtractor 提取出来的)
let contentToProcess = content
// 如果内容不包含 <tool_use> 标签,说明是从 TagExtractor 提取的内部内容,需要包装
if (!content.includes('<tool_use>')) {
contentToProcess = `<tool_use>\n${content}\n</tool_use>`
}
const toolUsePattern =
/<tool_use>([\s\S]*?)<name>([\s\S]*?)<\/name>([\s\S]*?)<arguments>([\s\S]*?)<\/arguments>([\s\S]*?)<\/tool_use>/g
const results: ToolUseResult[] = []
let match
let idx = 0
// Find all tool use blocks
while ((match = toolUsePattern.exec(contentToProcess)) !== null) {
const fullMatch = match[0]
const toolName = match[2].trim()
const toolArgs = match[4].trim()
// Try to parse the arguments as JSON
let parsedArgs
try {
parsedArgs = JSON.parse(toolArgs)
} catch (error) {
// If parsing fails, use the string as is
parsedArgs = toolArgs
}
// Find the corresponding tool
const tool = tools[toolName]
if (!tool) {
console.warn(`Tool "${toolName}" not found in available tools`)
continue
}
// Add to results array
results.push({
id: `${toolName}-${idx++}`, // Unique ID for each tool use
toolName: toolName,
arguments: parsedArgs,
status: 'pending'
})
contentToProcess = contentToProcess.replace(fullMatch, '')
}
return { results, content: contentToProcess }
}
export const createPromptToolUsePlugin = (config: PromptToolUseConfig = {}) => {
const { enabled = true, buildSystemPrompt = defaultBuildSystemPrompt, parseToolUse = defaultParseToolUse } = config
return definePlugin({
name: 'built-in:prompt-tool-use',
transformParams: (params: any, context: AiRequestContext) => {
if (!enabled || !params.tools || typeof params.tools !== 'object') {
return params
}
// 分离 provider-defined 和其他类型的工具
const providerDefinedTools: ToolSet = {}
const promptTools: ToolSet = {}
for (const [toolName, tool] of Object.entries(params.tools as ToolSet)) {
if (tool.type === 'provider-defined') {
// provider-defined 类型的工具保留在 tools 参数中
providerDefinedTools[toolName] = tool
} else {
// 其他工具转换为 prompt 模式
promptTools[toolName] = tool
}
}
// 只有当有非 provider-defined 工具时才保存到 context
if (Object.keys(promptTools).length > 0) {
context.mcpTools = promptTools
}
// 构建系统提示符(只包含非 provider-defined 工具)
const userSystemPrompt = typeof params.system === 'string' ? params.system : ''
const systemPrompt = buildSystemPrompt(userSystemPrompt, promptTools)
let systemMessage: string | null = systemPrompt
if (config.createSystemMessage) {
// 🎯 如果用户提供了自定义处理函数,使用它
systemMessage = config.createSystemMessage(systemPrompt, params, context)
}
// 保留 provider-defined tools移除其他 tools
const transformedParams = {
...params,
...(systemMessage ? { system: systemMessage } : {}),
tools: Object.keys(providerDefinedTools).length > 0 ? providerDefinedTools : undefined
}
context.originalParams = transformedParams
return transformedParams
},
transformStream: (_: any, context: AiRequestContext) => () => {
let textBuffer = ''
// let stepId = ''
// 如果没有需要 prompt 模式处理的工具,直接返回原始流
if (!context.mcpTools) {
return new TransformStream()
}
// 从 context 中获取或初始化 usage 累加器
if (!context.accumulatedUsage) {
context.accumulatedUsage = {
inputTokens: 0,
outputTokens: 0,
totalTokens: 0,
reasoningTokens: 0,
cachedInputTokens: 0
}
}
// 创建工具执行器、流事件管理器和标签提取器
const toolExecutor = new ToolExecutor()
const streamEventManager = new StreamEventManager()
const tagExtractor = new TagExtractor(TOOL_USE_TAG_CONFIG)
// 在context中初始化工具执行状态避免递归调用时状态丢失
if (!context.hasExecutedToolsInCurrentStep) {
context.hasExecutedToolsInCurrentStep = false
}
// 用于hold text-start事件直到确认有非工具标签内容
let pendingTextStart: TextStreamPart<TOOLS> | null = null
let hasStartedText = false
type TOOLS = NonNullable<typeof context.mcpTools>
return new TransformStream<TextStreamPart<TOOLS>, TextStreamPart<TOOLS>>({
async transform(
chunk: TextStreamPart<TOOLS>,
controller: TransformStreamDefaultController<TextStreamPart<TOOLS>>
) {
// Hold住text-start事件直到确认有非工具标签内容
if ((chunk as any).type === 'text-start') {
pendingTextStart = chunk
return
}
// text-delta阶段收集文本内容并过滤工具标签
if (chunk.type === 'text-delta') {
textBuffer += chunk.text || ''
// stepId = chunk.id || ''
// 使用TagExtractor过滤工具标签只传递非标签内容到UI层
const extractionResults = tagExtractor.processText(chunk.text || '')
for (const result of extractionResults) {
// 只传递非标签内容到UI层
if (!result.isTagContent && result.content) {
// 如果还没有发送text-start且有pending的text-start先发送它
if (!hasStartedText && pendingTextStart) {
controller.enqueue(pendingTextStart)
hasStartedText = true
pendingTextStart = null
}
const filteredChunk = {
...chunk,
text: result.content
}
controller.enqueue(filteredChunk)
}
}
return
}
if (chunk.type === 'text-end') {
// 只有当已经发送了text-start时才发送text-end
if (hasStartedText) {
controller.enqueue(chunk)
}
return
}
if (chunk.type === 'finish-step') {
// 统一在finish-step阶段检查并执行工具调用
const tools = context.mcpTools
if (tools && Object.keys(tools).length > 0 && !context.hasExecutedToolsInCurrentStep) {
// 解析完整的textBuffer来检测工具调用
const { results: parsedTools } = parseToolUse(textBuffer, tools)
const validToolUses = parsedTools.filter((t) => t.status === 'pending')
if (validToolUses.length > 0) {
context.hasExecutedToolsInCurrentStep = true
// 执行工具调用(不需要手动发送 start-step外部流已经处理
const executedResults = await toolExecutor.executeTools(validToolUses, tools, controller)
// 发送步骤完成事件,使用 tool-calls 作为 finishReason
streamEventManager.sendStepFinishEvent(controller, chunk, context, 'tool-calls')
// 处理递归调用
const toolResultsText = toolExecutor.formatToolResults(executedResults)
const recursiveParams = streamEventManager.buildRecursiveParams(
context,
textBuffer,
toolResultsText,
tools
)
await streamEventManager.handleRecursiveCall(controller, recursiveParams, context)
return
}
}
// 如果没有执行工具调用直接传递原始finish-step事件
controller.enqueue(chunk)
// 清理状态
textBuffer = ''
return
}
// 处理 finish 类型,使用累加后的 totalUsage
if (chunk.type === 'finish') {
controller.enqueue({
...chunk,
totalUsage: context.accumulatedUsage
})
return
}
// 对于其他类型的事件直接传递不包括text-start已在上面处理
if ((chunk as any).type !== 'text-start') {
controller.enqueue(chunk)
}
},
flush() {
// 清理pending状态
pendingTextStart = null
hasStartedText = false
}
})
}
})
}

View File

@@ -1,196 +0,0 @@
// Copied from https://github.com/vercel/ai/blob/main/packages/ai/core/util/get-potential-start-index.ts
/**
* Returns the index of the start of the searchedText in the text, or null if it
* is not found.
*/
export function getPotentialStartIndex(text: string, searchedText: string): number | null {
// Return null immediately if searchedText is empty.
if (searchedText.length === 0) {
return null
}
// Check if the searchedText exists as a direct substring of text.
const directIndex = text.indexOf(searchedText)
if (directIndex !== -1) {
return directIndex
}
// Otherwise, look for the largest suffix of "text" that matches
// a prefix of "searchedText". We go from the end of text inward.
for (let i = text.length - 1; i >= 0; i--) {
const suffix = text.substring(i)
if (searchedText.startsWith(suffix)) {
return i
}
}
return null
}
export interface TagConfig {
openingTag: string
closingTag: string
separator?: string
}
export interface TagExtractionState {
textBuffer: string
isInsideTag: boolean
isFirstTag: boolean
isFirstText: boolean
afterSwitch: boolean
accumulatedTagContent: string
hasTagContent: boolean
}
export interface TagExtractionResult {
content: string
isTagContent: boolean
complete: boolean
tagContentExtracted?: string
}
/**
* 通用标签提取处理器
* 可以处理各种形式的标签对,如 <think>...</think>, <tool_use>...</tool_use> 等
*/
export class TagExtractor {
private config: TagConfig
private state: TagExtractionState
constructor(config: TagConfig) {
this.config = config
this.state = {
textBuffer: '',
isInsideTag: false,
isFirstTag: true,
isFirstText: true,
afterSwitch: false,
accumulatedTagContent: '',
hasTagContent: false
}
}
/**
* 处理文本块,返回处理结果
*/
processText(newText: string): TagExtractionResult[] {
this.state.textBuffer += newText
const results: TagExtractionResult[] = []
// 处理标签提取逻辑
while (true) {
const nextTag = this.state.isInsideTag ? this.config.closingTag : this.config.openingTag
const startIndex = getPotentialStartIndex(this.state.textBuffer, nextTag)
if (startIndex == null) {
const content = this.state.textBuffer
if (content.length > 0) {
results.push({
content: this.addPrefix(content),
isTagContent: this.state.isInsideTag,
complete: false
})
if (this.state.isInsideTag) {
this.state.accumulatedTagContent += this.addPrefix(content)
this.state.hasTagContent = true
}
}
this.state.textBuffer = ''
break
}
// 处理标签前的内容
const contentBeforeTag = this.state.textBuffer.slice(0, startIndex)
if (contentBeforeTag.length > 0) {
results.push({
content: this.addPrefix(contentBeforeTag),
isTagContent: this.state.isInsideTag,
complete: false
})
if (this.state.isInsideTag) {
this.state.accumulatedTagContent += this.addPrefix(contentBeforeTag)
this.state.hasTagContent = true
}
}
const foundFullMatch = startIndex + nextTag.length <= this.state.textBuffer.length
if (foundFullMatch) {
// 如果找到完整的标签
this.state.textBuffer = this.state.textBuffer.slice(startIndex + nextTag.length)
// 如果刚刚结束一个标签内容,生成完整的标签内容结果
if (this.state.isInsideTag && this.state.hasTagContent) {
results.push({
content: '',
isTagContent: false,
complete: true,
tagContentExtracted: this.state.accumulatedTagContent
})
this.state.accumulatedTagContent = ''
this.state.hasTagContent = false
}
this.state.isInsideTag = !this.state.isInsideTag
this.state.afterSwitch = true
if (this.state.isInsideTag) {
this.state.isFirstTag = false
} else {
this.state.isFirstText = false
}
} else {
this.state.textBuffer = this.state.textBuffer.slice(startIndex)
break
}
}
return results
}
/**
* 完成处理,返回任何剩余的标签内容
*/
finalize(): TagExtractionResult | null {
if (this.state.hasTagContent && this.state.accumulatedTagContent) {
const result = {
content: '',
isTagContent: false,
complete: true,
tagContentExtracted: this.state.accumulatedTagContent
}
this.state.accumulatedTagContent = ''
this.state.hasTagContent = false
return result
}
return null
}
private addPrefix(text: string): string {
const needsPrefix =
this.state.afterSwitch && (this.state.isInsideTag ? !this.state.isFirstTag : !this.state.isFirstText)
const prefix = needsPrefix && this.config.separator ? this.config.separator : ''
this.state.afterSwitch = false
return prefix + text
}
/**
* 重置状态
*/
reset(): void {
this.state = {
textBuffer: '',
isInsideTag: false,
isFirstTag: true,
isFirstText: true,
afterSwitch: false,
accumulatedTagContent: '',
hasTagContent: false
}
}
}

View File

@@ -1,33 +0,0 @@
import { ToolSet } from 'ai'
import { AiRequestContext } from '../..'
/**
* 解析结果类型
* 表示从AI响应中解析出的工具使用意图
*/
export interface ToolUseResult {
id: string
toolName: string
arguments: any
status: 'pending' | 'invoking' | 'done' | 'error'
}
export interface BaseToolUsePluginConfig {
enabled?: boolean
}
export interface PromptToolUseConfig extends BaseToolUsePluginConfig {
// 自定义系统提示符构建函数(可选,有默认实现)
buildSystemPrompt?: (userSystemPrompt: string, tools: ToolSet) => string
// 自定义工具解析函数(可选,有默认实现)
parseToolUse?: (content: string, tools: ToolSet) => { results: ToolUseResult[]; content: string }
createSystemMessage?: (systemPrompt: string, originalParams: any, context: AiRequestContext) => string | null
}
/**
* 扩展的 AI 请求上下文,支持 MCP 工具存储
*/
export interface ToolUseRequestContext extends AiRequestContext {
mcpTools: ToolSet
}

View File

@@ -1,89 +0,0 @@
import { anthropic } from '@ai-sdk/anthropic'
import { google } from '@ai-sdk/google'
import { openai } from '@ai-sdk/openai'
import { InferToolInput, InferToolOutput } from 'ai'
import { ProviderOptionsMap } from '../../../options/types'
import { OpenRouterSearchConfig } from './openrouter'
/**
* 从 AI SDK 的工具函数中提取参数类型,以确保类型安全。
*/
export type OpenAISearchConfig = NonNullable<Parameters<typeof openai.tools.webSearch>[0]>
export type OpenAISearchPreviewConfig = NonNullable<Parameters<typeof openai.tools.webSearchPreview>[0]>
export type AnthropicSearchConfig = NonNullable<Parameters<typeof anthropic.tools.webSearch_20250305>[0]>
export type GoogleSearchConfig = NonNullable<Parameters<typeof google.tools.googleSearch>[0]>
export type XAISearchConfig = NonNullable<ProviderOptionsMap['xai']['searchParameters']>
/**
* 插件初始化时接收的完整配置对象
*
* 其结构与 ProviderOptions 保持一致,方便上游统一管理配置
*/
export interface WebSearchPluginConfig {
openai?: OpenAISearchConfig
'openai-chat'?: OpenAISearchPreviewConfig
anthropic?: AnthropicSearchConfig
xai?: ProviderOptionsMap['xai']['searchParameters']
google?: GoogleSearchConfig
'google-vertex'?: GoogleSearchConfig
openrouter?: OpenRouterSearchConfig
}
/**
* 插件的默认配置
*/
export const DEFAULT_WEB_SEARCH_CONFIG: WebSearchPluginConfig = {
google: {},
'google-vertex': {},
openai: {},
'openai-chat': {},
xai: {
mode: 'on',
returnCitations: true,
maxSearchResults: 5,
sources: [{ type: 'web' }, { type: 'x' }, { type: 'news' }]
},
anthropic: {
maxUses: 5
},
openrouter: {
plugins: [
{
id: 'web',
max_results: 5
}
]
}
}
export type WebSearchToolOutputSchema = {
// Anthropic 工具 - 手动定义
anthropic: InferToolOutput<ReturnType<typeof anthropic.tools.webSearch_20250305>>
// OpenAI 工具 - 基于实际输出
// TODO: 上游定义不规范,是unknown
// openai: InferToolOutput<ReturnType<typeof openai.tools.webSearch>>
openai: {
status: 'completed' | 'failed'
}
'openai-chat': {
status: 'completed' | 'failed'
}
// Google 工具
// TODO: 上游定义不规范,是unknown
// google: InferToolOutput<ReturnType<typeof google.tools.googleSearch>>
google: {
webSearchQueries?: string[]
groundingChunks?: Array<{
web?: { uri: string; title: string }
}>
}
}
export type WebSearchToolInputSchema = {
anthropic: InferToolInput<ReturnType<typeof anthropic.tools.webSearch_20250305>>
openai: InferToolInput<ReturnType<typeof openai.tools.webSearch>>
google: InferToolInput<ReturnType<typeof google.tools.googleSearch>>
'openai-chat': InferToolInput<ReturnType<typeof openai.tools.webSearchPreview>>
}

View File

@@ -1,84 +0,0 @@
/**
* Web Search Plugin
* 提供统一的网络搜索能力,支持多个 AI Provider
*/
import { anthropic } from '@ai-sdk/anthropic'
import { google } from '@ai-sdk/google'
import { openai } from '@ai-sdk/openai'
import { createOpenRouterOptions, createXaiOptions, mergeProviderOptions } from '../../../options'
import { definePlugin } from '../../'
import type { AiRequestContext } from '../../types'
import { DEFAULT_WEB_SEARCH_CONFIG, WebSearchPluginConfig } from './helper'
/**
* 网络搜索插件
*
* @param config - 在插件初始化时传入的静态配置
*/
export const webSearchPlugin = (config: WebSearchPluginConfig = DEFAULT_WEB_SEARCH_CONFIG) =>
definePlugin({
name: 'webSearch',
enforce: 'pre',
transformParams: async (params: any, context: AiRequestContext) => {
const { providerId } = context
switch (providerId) {
case 'openai': {
if (config.openai) {
if (!params.tools) params.tools = {}
params.tools.web_search = openai.tools.webSearch(config.openai)
}
break
}
case 'openai-chat': {
if (config['openai-chat']) {
if (!params.tools) params.tools = {}
params.tools.web_search_preview = openai.tools.webSearchPreview(config['openai-chat'])
}
break
}
case 'anthropic': {
if (config.anthropic) {
if (!params.tools) params.tools = {}
params.tools.web_search = anthropic.tools.webSearch_20250305(config.anthropic)
}
break
}
case 'google': {
// case 'google-vertex':
if (!params.tools) params.tools = {}
params.tools.web_search = google.tools.googleSearch(config.google || {})
break
}
case 'xai': {
if (config.xai) {
const searchOptions = createXaiOptions({
searchParameters: { ...config.xai, mode: 'on' }
})
params.providerOptions = mergeProviderOptions(params.providerOptions, searchOptions)
}
break
}
case 'openrouter': {
if (config.openrouter) {
const searchOptions = createOpenRouterOptions(config.openrouter)
params.providerOptions = mergeProviderOptions(params.providerOptions, searchOptions)
}
break
}
}
return params
}
})
// 导出类型定义供开发者使用
export type { WebSearchPluginConfig, WebSearchToolOutputSchema } from './helper'
// 默认导出
export default webSearchPlugin

View File

@@ -1,26 +0,0 @@
export type OpenRouterSearchConfig = {
plugins?: Array<{
id: 'web'
/**
* Maximum number of search results to include (default: 5)
*/
max_results?: number
/**
* Custom search prompt to guide the search query
*/
search_prompt?: string
}>
/**
* Built-in web search options for models that support native web search
*/
web_search_options?: {
/**
* Maximum number of search results to include
*/
max_results?: number
/**
* Custom search prompt to guide the search query
*/
search_prompt?: string
}
}

View File

@@ -1,35 +0,0 @@
// 核心类型和接口
export type { AiPlugin, AiRequestContext, HookResult, PluginManagerConfig } from './types'
import type { ImageModelV2 } from '@ai-sdk/provider'
import type { LanguageModel } from 'ai'
import type { ProviderId } from '../providers'
import type { AiPlugin, AiRequestContext } from './types'
// 插件管理器
export { PluginManager } from './manager'
// 工具函数
export function createContext<T extends ProviderId>(
providerId: T,
model: LanguageModel | ImageModelV2,
originalParams: any
): AiRequestContext {
return {
providerId,
model,
originalParams,
metadata: {},
startTime: Date.now(),
requestId: `${providerId}-${typeof model === 'string' ? model : model?.modelId}-${Date.now()}-${Math.random().toString(36).slice(2)}`,
// 占位
recursiveCall: () => Promise.resolve(null)
}
}
// 插件构建器 - 便于创建插件
export function definePlugin(plugin: AiPlugin): AiPlugin
export function definePlugin<T extends (...args: any[]) => AiPlugin>(pluginFactory: T): T
export function definePlugin(plugin: AiPlugin | ((...args: any[]) => AiPlugin)) {
return plugin
}

View File

@@ -1,184 +0,0 @@
import { AiPlugin, AiRequestContext } from './types'
/**
* 插件管理器
*/
export class PluginManager {
private plugins: AiPlugin[] = []
constructor(plugins: AiPlugin[] = []) {
this.plugins = this.sortPlugins(plugins)
}
/**
* 添加插件
*/
use(plugin: AiPlugin): this {
this.plugins = this.sortPlugins([...this.plugins, plugin])
return this
}
/**
* 移除插件
*/
remove(pluginName: string): this {
this.plugins = this.plugins.filter((p) => p.name !== pluginName)
return this
}
/**
* 插件排序pre -> normal -> post
*/
private sortPlugins(plugins: AiPlugin[]): AiPlugin[] {
const pre: AiPlugin[] = []
const normal: AiPlugin[] = []
const post: AiPlugin[] = []
plugins.forEach((plugin) => {
if (plugin.enforce === 'pre') {
pre.push(plugin)
} else if (plugin.enforce === 'post') {
post.push(plugin)
} else {
normal.push(plugin)
}
})
return [...pre, ...normal, ...post]
}
/**
* 执行 First 钩子 - 返回第一个有效结果
*/
async executeFirst<T>(
hookName: 'resolveModel' | 'loadTemplate',
arg: any,
context: AiRequestContext
): Promise<T | null> {
for (const plugin of this.plugins) {
const hook = plugin[hookName]
if (hook) {
const result = await hook(arg, context)
if (result !== null && result !== undefined) {
return result as T
}
}
}
return null
}
/**
* 执行 Sequential 钩子 - 链式数据转换
*/
async executeSequential<T>(
hookName: 'transformParams' | 'transformResult',
initialValue: T,
context: AiRequestContext
): Promise<T> {
let result = initialValue
for (const plugin of this.plugins) {
const hook = plugin[hookName]
if (hook) {
result = await hook<T>(result, context)
}
}
return result
}
/**
* 执行 ConfigureContext 钩子 - 串行配置上下文
*/
async executeConfigureContext(context: AiRequestContext): Promise<void> {
for (const plugin of this.plugins) {
const hook = plugin.configureContext
if (hook) {
await hook(context)
}
}
}
/**
* 执行 Parallel 钩子 - 并行副作用
*/
async executeParallel(
hookName: 'onRequestStart' | 'onRequestEnd' | 'onError',
context: AiRequestContext,
result?: any,
error?: Error
): Promise<void> {
const promises = this.plugins
.map((plugin) => {
const hook = plugin[hookName]
if (!hook) return null
if (hookName === 'onError' && error) {
return (hook as any)(error, context)
} else if (hookName === 'onRequestEnd' && result !== undefined) {
return (hook as any)(context, result)
} else if (hookName === 'onRequestStart') {
return (hook as any)(context)
}
return null
})
.filter(Boolean)
// 使用 Promise.all 而不是 allSettled让插件错误能够抛出
await Promise.all(promises)
}
/**
* 收集所有流转换器返回数组AI SDK 原生支持)
*/
collectStreamTransforms(params: any, context: AiRequestContext) {
return this.plugins
.filter((plugin) => plugin.transformStream)
.map((plugin) => plugin.transformStream?.(params, context))
}
/**
* 获取所有插件信息
*/
getPlugins(): AiPlugin[] {
return [...this.plugins]
}
/**
* 获取插件统计信息
*/
getStats() {
const stats = {
total: this.plugins.length,
pre: 0,
normal: 0,
post: 0,
hooks: {
resolveModel: 0,
loadTemplate: 0,
transformParams: 0,
transformResult: 0,
onRequestStart: 0,
onRequestEnd: 0,
onError: 0,
transformStream: 0
}
}
this.plugins.forEach((plugin) => {
// 统计 enforce 类型
if (plugin.enforce === 'pre') stats.pre++
else if (plugin.enforce === 'post') stats.post++
else stats.normal++
// 统计钩子数量
Object.keys(stats.hooks).forEach((hookName) => {
if (plugin[hookName as keyof AiPlugin]) {
stats.hooks[hookName as keyof typeof stats.hooks]++
}
})
})
return stats
}
}

View File

@@ -1,79 +0,0 @@
import type { ImageModelV2 } from '@ai-sdk/provider'
import type { LanguageModel, TextStreamPart, ToolSet } from 'ai'
import { type ProviderId } from '../providers/types'
/**
* 递归调用函数类型
* 使用 any 是因为递归调用时参数和返回类型可能完全不同
*/
export type RecursiveCallFn = (newParams: any) => Promise<any>
/**
* AI 请求上下文
*/
export interface AiRequestContext {
providerId: ProviderId
model: LanguageModel | ImageModelV2
originalParams: any
metadata: Record<string, any>
startTime: number
requestId: string
recursiveCall: RecursiveCallFn
isRecursiveCall?: boolean
mcpTools?: ToolSet
[key: string]: any
}
/**
* 钩子分类
*/
export interface AiPlugin {
name: string
enforce?: 'pre' | 'post'
// 【First】首个钩子 - 只执行第一个返回值的插件
resolveModel?: (
modelId: string,
context: AiRequestContext
) => Promise<LanguageModel | ImageModelV2 | null> | LanguageModel | ImageModelV2 | null
loadTemplate?: (templateName: string, context: AiRequestContext) => any | null | Promise<any | null>
// 【Sequential】串行钩子 - 链式执行,支持数据转换
configureContext?: (context: AiRequestContext) => void | Promise<void>
transformParams?: <T>(params: T, context: AiRequestContext) => T | Promise<T>
transformResult?: <T>(result: T, context: AiRequestContext) => T | Promise<T>
// 【Parallel】并行钩子 - 不依赖顺序,用于副作用
onRequestStart?: (context: AiRequestContext) => void | Promise<void>
onRequestEnd?: (context: AiRequestContext, result: any) => void | Promise<void>
onError?: (error: Error, context: AiRequestContext) => void | Promise<void>
// 【Stream】流处理 - 直接使用 AI SDK
transformStream?: (
params: any,
context: AiRequestContext
) => <TOOLS extends ToolSet>(options?: {
tools: TOOLS
stopStream: () => void
}) => TransformStream<TextStreamPart<TOOLS>, TextStreamPart<TOOLS>>
// AI SDK 原生中间件
// aiSdkMiddlewares?: LanguageModelV1Middleware[]
}
/**
* 插件管理器配置
*/
export interface PluginManagerConfig {
plugins: AiPlugin[]
context: Partial<AiRequestContext>
}
/**
* 钩子执行结果
*/
export interface HookResult<T = any> {
value: T
stop?: boolean
}

View File

@@ -1,101 +0,0 @@
/**
* Hub Provider - 支持路由到多个底层provider
*
* 支持格式: hubId:providerId:modelId
* 例如: aihubmix:anthropic:claude-3.5-sonnet
*/
import { ProviderV2 } from '@ai-sdk/provider'
import { customProvider } from 'ai'
import { globalRegistryManagement } from './RegistryManagement'
import type { AiSdkMethodName, AiSdkModelReturn, AiSdkModelType } from './types'
export interface HubProviderConfig {
/** Hub的唯一标识符 */
hubId: string
/** 是否启用调试日志 */
debug?: boolean
}
export class HubProviderError extends Error {
constructor(
message: string,
public readonly hubId: string,
public readonly providerId?: string,
public readonly originalError?: Error
) {
super(message)
this.name = 'HubProviderError'
}
}
/**
* 解析Hub模型ID
*/
function parseHubModelId(modelId: string): { provider: string; actualModelId: string } {
const parts = modelId.split(':')
if (parts.length !== 2) {
throw new HubProviderError(`Invalid hub model ID format. Expected "provider:modelId", got: ${modelId}`, 'unknown')
}
return {
provider: parts[0],
actualModelId: parts[1]
}
}
/**
* 创建Hub Provider
*/
export function createHubProvider(config: HubProviderConfig): ProviderV2 {
const { hubId } = config
function getTargetProvider(providerId: string): ProviderV2 {
// 从全局注册表获取provider实例
try {
const provider = globalRegistryManagement.getProvider(providerId)
if (!provider) {
throw new HubProviderError(
`Provider "${providerId}" is not initialized. Please call initializeProvider("${providerId}", options) first.`,
hubId,
providerId
)
}
return provider
} catch (error) {
throw new HubProviderError(
`Failed to get provider "${providerId}": ${error instanceof Error ? error.message : 'Unknown error'}`,
hubId,
providerId,
error instanceof Error ? error : undefined
)
}
}
function resolveModel<T extends AiSdkModelType>(
modelId: string,
modelType: T,
methodName: AiSdkMethodName<T>
): AiSdkModelReturn<T> {
const { provider, actualModelId } = parseHubModelId(modelId)
const targetProvider = getTargetProvider(provider)
const fn = targetProvider[methodName] as (id: string) => AiSdkModelReturn<T>
if (!fn) {
throw new HubProviderError(`Provider "${provider}" does not support ${modelType}`, hubId, provider)
}
return fn(actualModelId)
}
return customProvider({
fallbackProvider: {
languageModel: (modelId: string) => resolveModel(modelId, 'text', 'languageModel'),
textEmbeddingModel: (modelId: string) => resolveModel(modelId, 'embedding', 'textEmbeddingModel'),
imageModel: (modelId: string) => resolveModel(modelId, 'image', 'imageModel'),
transcriptionModel: (modelId: string) => resolveModel(modelId, 'transcription', 'transcriptionModel'),
speechModel: (modelId: string) => resolveModel(modelId, 'speech', 'speechModel')
}
})
}

View File

@@ -1,221 +0,0 @@
/**
* Provider 注册表管理器
* 纯粹的管理功能:存储、检索已配置好的 provider 实例
* 基于 AI SDK 原生的 createProviderRegistry
*/
import { EmbeddingModelV2, ImageModelV2, LanguageModelV2, ProviderV2 } from '@ai-sdk/provider'
import { createProviderRegistry, type ProviderRegistryProvider } from 'ai'
type PROVIDERS = Record<string, ProviderV2>
export const DEFAULT_SEPARATOR = '|'
// export type MODEL_ID = `${string}${typeof DEFAULT_SEPARATOR}${string}`
export class RegistryManagement<SEPARATOR extends string = typeof DEFAULT_SEPARATOR> {
private providers: PROVIDERS = {}
private aliases: Set<string> = new Set() // 记录哪些key是别名
private separator: SEPARATOR
private registry: ProviderRegistryProvider<PROVIDERS, SEPARATOR> | null = null
constructor(options: { separator: SEPARATOR } = { separator: DEFAULT_SEPARATOR as SEPARATOR }) {
this.separator = options.separator
}
/**
* 注册已配置好的 provider 实例
*/
registerProvider(id: string, provider: ProviderV2, aliases?: string[]): this {
// 注册主provider
this.providers[id] = provider
// 注册别名都指向同一个provider实例
if (aliases) {
aliases.forEach((alias) => {
this.providers[alias] = provider // 直接存储引用
this.aliases.add(alias) // 标记为别名
})
}
this.rebuildRegistry()
return this
}
/**
* 获取已注册的provider实例
*/
getProvider(id: string): ProviderV2 | undefined {
return this.providers[id]
}
/**
* 批量注册 providers
*/
registerProviders(providers: Record<string, ProviderV2>): this {
Object.assign(this.providers, providers)
this.rebuildRegistry()
return this
}
/**
* 移除 provider同时清理相关别名
*/
unregisterProvider(id: string): this {
const provider = this.providers[id]
if (!provider) return this
// 如果移除的是真实ID需要清理所有指向它的别名
if (!this.aliases.has(id)) {
// 找到所有指向此provider的别名并删除
const aliasesToRemove: string[] = []
this.aliases.forEach((alias) => {
if (this.providers[alias] === provider) {
aliasesToRemove.push(alias)
}
})
aliasesToRemove.forEach((alias) => {
delete this.providers[alias]
this.aliases.delete(alias)
})
} else {
// 如果移除的是别名,只删除别名记录
this.aliases.delete(id)
}
delete this.providers[id]
this.rebuildRegistry()
return this
}
/**
* 立即重建 registry - 每次变更都重建
*/
private rebuildRegistry(): void {
if (Object.keys(this.providers).length === 0) {
this.registry = null
return
}
this.registry = createProviderRegistry<PROVIDERS, SEPARATOR>(this.providers, {
separator: this.separator
})
}
/**
* 获取语言模型 - AI SDK 原生方法
*/
languageModel(id: `${string}${SEPARATOR}${string}`): LanguageModelV2 {
if (!this.registry) {
throw new Error('No providers registered')
}
return this.registry.languageModel(id)
}
/**
* 获取文本嵌入模型 - AI SDK 原生方法
*/
textEmbeddingModel(id: `${string}${SEPARATOR}${string}`): EmbeddingModelV2<string> {
if (!this.registry) {
throw new Error('No providers registered')
}
return this.registry.textEmbeddingModel(id)
}
/**
* 获取图像模型 - AI SDK 原生方法
*/
imageModel(id: `${string}${SEPARATOR}${string}`): ImageModelV2 {
if (!this.registry) {
throw new Error('No providers registered')
}
return this.registry.imageModel(id)
}
/**
* 获取转录模型 - AI SDK 原生方法
*/
transcriptionModel(id: `${string}${SEPARATOR}${string}`): any {
if (!this.registry) {
throw new Error('No providers registered')
}
return this.registry.transcriptionModel(id)
}
/**
* 获取语音模型 - AI SDK 原生方法
*/
speechModel(id: `${string}${SEPARATOR}${string}`): any {
if (!this.registry) {
throw new Error('No providers registered')
}
return this.registry.speechModel(id)
}
/**
* 获取已注册的 provider 列表
*/
getRegisteredProviders(): string[] {
return Object.keys(this.providers)
}
/**
* 检查是否有已注册的 providers
*/
hasProviders(): boolean {
return Object.keys(this.providers).length > 0
}
/**
* 清除所有 providers
*/
clear(): this {
this.providers = {}
this.aliases.clear()
this.registry = null
return this
}
/**
* 解析真实的Provider ID供getAiSdkProviderId使用
* 如果传入的是别名返回真实的Provider ID
* 如果传入的是真实ID直接返回
*/
resolveProviderId(id: string): string {
if (!this.aliases.has(id)) return id // 不是别名,直接返回
// 是别名找到真实ID
const targetProvider = this.providers[id]
for (const [realId, provider] of Object.entries(this.providers)) {
if (provider === targetProvider && !this.aliases.has(realId)) {
return realId
}
}
return id
}
/**
* 检查是否为别名
*/
isAlias(id: string): boolean {
return this.aliases.has(id)
}
/**
* 获取所有别名映射关系
*/
getAllAliases(): Record<string, string> {
const result: Record<string, string> = {}
this.aliases.forEach((alias) => {
result[alias] = this.resolveProviderId(alias)
})
return result
}
}
/**
* 全局注册表管理器实例
* 使用 | 作为分隔符,因为 : 会和 :free 等suffix冲突
*/
export const globalRegistryManagement = new RegistryManagement()

View File

@@ -1,632 +0,0 @@
/**
* 测试真正的 AiProviderRegistry 功能
*/
import { beforeEach, describe, expect, it, vi } from 'vitest'
// 模拟 AI SDK
vi.mock('@ai-sdk/openai', () => ({
createOpenAI: vi.fn(() => ({ name: 'openai-mock' }))
}))
vi.mock('@ai-sdk/anthropic', () => ({
createAnthropic: vi.fn(() => ({ name: 'anthropic-mock' }))
}))
vi.mock('@ai-sdk/azure', () => ({
createAzure: vi.fn(() => ({ name: 'azure-mock' }))
}))
vi.mock('@ai-sdk/deepseek', () => ({
createDeepSeek: vi.fn(() => ({ name: 'deepseek-mock' }))
}))
vi.mock('@ai-sdk/google', () => ({
createGoogleGenerativeAI: vi.fn(() => ({ name: 'google-mock' }))
}))
vi.mock('@ai-sdk/openai-compatible', () => ({
createOpenAICompatible: vi.fn(() => ({ name: 'openai-compatible-mock' }))
}))
vi.mock('@ai-sdk/xai', () => ({
createXai: vi.fn(() => ({ name: 'xai-mock' }))
}))
import {
cleanup,
clearAllProviders,
createAndRegisterProvider,
createProvider,
getAllProviderConfigAliases,
getAllProviderConfigs,
getInitializedProviders,
getLanguageModel,
getProviderConfig,
getProviderConfigByAlias,
getSupportedProviders,
hasInitializedProviders,
hasProviderConfig,
hasProviderConfigByAlias,
isProviderConfigAlias,
ProviderInitializationError,
providerRegistry,
registerMultipleProviderConfigs,
registerProvider,
registerProviderConfig,
resolveProviderConfigId
} from '../registry'
import type { ProviderConfig } from '../schemas'
describe('Provider Registry 功能测试', () => {
beforeEach(() => {
// 清理状态
cleanup()
})
describe('基础功能', () => {
it('能够获取支持的 providers 列表', () => {
const providers = getSupportedProviders()
expect(Array.isArray(providers)).toBe(true)
expect(providers.length).toBeGreaterThan(0)
// 检查返回的数据结构
providers.forEach((provider) => {
expect(provider).toHaveProperty('id')
expect(provider).toHaveProperty('name')
expect(typeof provider.id).toBe('string')
expect(typeof provider.name).toBe('string')
})
// 包含基础 providers
const providerIds = providers.map((p) => p.id)
expect(providerIds).toContain('openai')
expect(providerIds).toContain('anthropic')
expect(providerIds).toContain('google')
})
it('能够获取已初始化的 providers', () => {
// 初始状态下没有已初始化的 providers
expect(getInitializedProviders()).toEqual([])
expect(hasInitializedProviders()).toBe(false)
})
it('能够访问全局注册管理器', () => {
expect(providerRegistry).toBeDefined()
expect(typeof providerRegistry.clear).toBe('function')
expect(typeof providerRegistry.getRegisteredProviders).toBe('function')
expect(typeof providerRegistry.hasProviders).toBe('function')
})
it('能够获取语言模型', () => {
// 在没有注册 provider 的情况下,这个函数应该会抛出错误
expect(() => getLanguageModel('non-existent')).toThrow('No providers registered')
})
})
describe('Provider 配置注册', () => {
it('能够注册自定义 provider 配置', () => {
const config: ProviderConfig = {
id: 'custom-provider',
name: 'Custom Provider',
creator: vi.fn(() => ({ name: 'custom' })),
supportsImageGeneration: false
}
const success = registerProviderConfig(config)
expect(success).toBe(true)
expect(hasProviderConfig('custom-provider')).toBe(true)
expect(getProviderConfig('custom-provider')).toEqual(config)
})
it('能够注册带别名的 provider 配置', () => {
const config: ProviderConfig = {
id: 'custom-provider-with-aliases',
name: 'Custom Provider with Aliases',
creator: vi.fn(() => ({ name: 'custom-aliased' })),
supportsImageGeneration: false,
aliases: ['alias-1', 'alias-2']
}
const success = registerProviderConfig(config)
expect(success).toBe(true)
expect(hasProviderConfigByAlias('alias-1')).toBe(true)
expect(hasProviderConfigByAlias('alias-2')).toBe(true)
expect(getProviderConfigByAlias('alias-1')).toEqual(config)
expect(resolveProviderConfigId('alias-1')).toBe('custom-provider-with-aliases')
})
it('拒绝无效的配置', () => {
// 缺少必要字段
const invalidConfig = {
id: 'invalid-provider'
// 缺少 name, creator 等
}
const success = registerProviderConfig(invalidConfig as any)
expect(success).toBe(false)
})
it('能够批量注册 provider 配置', () => {
const configs: ProviderConfig[] = [
{
id: 'provider-1',
name: 'Provider 1',
creator: vi.fn(() => ({ name: 'provider-1' })),
supportsImageGeneration: false
},
{
id: 'provider-2',
name: 'Provider 2',
creator: vi.fn(() => ({ name: 'provider-2' })),
supportsImageGeneration: true
},
{
id: '', // 无效配置
name: 'Invalid Provider',
creator: vi.fn(() => ({ name: 'invalid' })),
supportsImageGeneration: false
} as any
]
const successCount = registerMultipleProviderConfigs(configs)
expect(successCount).toBe(2) // 只有前两个成功
expect(hasProviderConfig('provider-1')).toBe(true)
expect(hasProviderConfig('provider-2')).toBe(true)
expect(hasProviderConfig('')).toBe(false)
})
it('能够获取所有配置和别名信息', () => {
// 注册一些配置
registerProviderConfig({
id: 'test-provider',
name: 'Test Provider',
creator: vi.fn(),
supportsImageGeneration: false,
aliases: ['test-alias']
})
const allConfigs = getAllProviderConfigs()
expect(Array.isArray(allConfigs)).toBe(true)
expect(allConfigs.some((config) => config.id === 'test-provider')).toBe(true)
const aliases = getAllProviderConfigAliases()
expect(aliases['test-alias']).toBe('test-provider')
expect(isProviderConfigAlias('test-alias')).toBe(true)
})
})
describe('Provider 创建和注册', () => {
it('能够创建 provider 实例', async () => {
const config: ProviderConfig = {
id: 'test-create-provider',
name: 'Test Create Provider',
creator: vi.fn(() => ({ name: 'test-created' })),
supportsImageGeneration: false
}
// 先注册配置
registerProviderConfig(config)
// 创建 provider 实例
const provider = await createProvider('test-create-provider', { apiKey: 'test' })
expect(provider).toBeDefined()
expect(config.creator).toHaveBeenCalledWith({ apiKey: 'test' })
})
it('能够注册 provider 到全局管理器', () => {
const mockProvider = { name: 'mock-provider' }
const config: ProviderConfig = {
id: 'test-register-provider',
name: 'Test Register Provider',
creator: vi.fn(() => mockProvider),
supportsImageGeneration: false
}
// 先注册配置
registerProviderConfig(config)
// 注册 provider 到全局管理器
const success = registerProvider('test-register-provider', mockProvider)
expect(success).toBe(true)
// 验证注册成功
const registeredProviders = getInitializedProviders()
expect(registeredProviders).toContain('test-register-provider')
expect(hasInitializedProviders()).toBe(true)
})
it('能够一步完成创建和注册', async () => {
const config: ProviderConfig = {
id: 'test-create-and-register',
name: 'Test Create and Register',
creator: vi.fn(() => ({ name: 'test-both' })),
supportsImageGeneration: false
}
// 先注册配置
registerProviderConfig(config)
// 一步完成创建和注册
const success = await createAndRegisterProvider('test-create-and-register', { apiKey: 'test' })
expect(success).toBe(true)
// 验证注册成功
const registeredProviders = getInitializedProviders()
expect(registeredProviders).toContain('test-create-and-register')
})
})
describe('Registry 管理', () => {
it('能够清理所有配置和注册的 providers', () => {
// 注册一些配置
registerProviderConfig({
id: 'temp-provider',
name: 'Temp Provider',
creator: vi.fn(() => ({ name: 'temp' })),
supportsImageGeneration: false
})
expect(hasProviderConfig('temp-provider')).toBe(true)
// 清理
cleanup()
expect(hasProviderConfig('temp-provider')).toBe(false)
// 但基础配置应该重新加载
expect(hasProviderConfig('openai')).toBe(true) // 基础 providers 会重新初始化
})
it('能够单独清理已注册的 providers', () => {
// 清理所有 providers
clearAllProviders()
expect(getInitializedProviders()).toEqual([])
expect(hasInitializedProviders()).toBe(false)
})
it('ProviderInitializationError 错误类工作正常', () => {
const error = new ProviderInitializationError('Test error', 'test-provider')
expect(error.message).toBe('Test error')
expect(error.providerId).toBe('test-provider')
expect(error.name).toBe('ProviderInitializationError')
})
})
describe('错误处理', () => {
it('优雅处理空配置', () => {
const success = registerProviderConfig(null as any)
expect(success).toBe(false)
})
it('优雅处理未定义配置', () => {
const success = registerProviderConfig(undefined as any)
expect(success).toBe(false)
})
it('处理空字符串 ID', () => {
const config = {
id: '',
name: 'Empty ID Provider',
creator: vi.fn(() => ({ name: 'empty' })),
supportsImageGeneration: false
}
const success = registerProviderConfig(config)
expect(success).toBe(false)
})
it('处理创建不存在配置的 provider', async () => {
await expect(createProvider('non-existent-provider', {})).rejects.toThrow(
'ProviderConfig not found for id: non-existent-provider'
)
})
it('处理注册不存在配置的 provider', () => {
const mockProvider = { name: 'mock' }
const success = registerProvider('non-existent-provider', mockProvider)
expect(success).toBe(false)
})
it('处理获取不存在配置的情况', () => {
expect(getProviderConfig('non-existent')).toBeUndefined()
expect(getProviderConfigByAlias('non-existent-alias')).toBeUndefined()
expect(hasProviderConfig('non-existent')).toBe(false)
expect(hasProviderConfigByAlias('non-existent-alias')).toBe(false)
})
it('处理批量注册时的部分失败', () => {
const mixedConfigs: ProviderConfig[] = [
{
id: 'valid-provider-1',
name: 'Valid Provider 1',
creator: vi.fn(() => ({ name: 'valid-1' })),
supportsImageGeneration: false
},
{
id: '', // 无效配置
name: 'Invalid Provider',
creator: vi.fn(() => ({ name: 'invalid' })),
supportsImageGeneration: false
} as any,
{
id: 'valid-provider-2',
name: 'Valid Provider 2',
creator: vi.fn(() => ({ name: 'valid-2' })),
supportsImageGeneration: true
}
]
const successCount = registerMultipleProviderConfigs(mixedConfigs)
expect(successCount).toBe(2) // 只有两个有效配置成功
expect(hasProviderConfig('valid-provider-1')).toBe(true)
expect(hasProviderConfig('valid-provider-2')).toBe(true)
expect(hasProviderConfig('')).toBe(false)
})
it('处理动态导入失败的情况', async () => {
const config: ProviderConfig = {
id: 'import-test-provider',
name: 'Import Test Provider',
import: vi.fn().mockRejectedValue(new Error('Import failed')),
creatorFunctionName: 'createTest',
supportsImageGeneration: false
}
registerProviderConfig(config)
await expect(createProvider('import-test-provider', {})).rejects.toThrow('Import failed')
})
})
describe('集成测试', () => {
it('正确处理复杂的配置、创建、注册和清理场景', async () => {
// 初始状态验证
const initialConfigs = getAllProviderConfigs()
expect(initialConfigs.length).toBeGreaterThan(0) // 有基础配置
expect(getInitializedProviders()).toEqual([])
// 注册多个带别名的 provider 配置
const configs: ProviderConfig[] = [
{
id: 'integration-provider-1',
name: 'Integration Provider 1',
creator: vi.fn(() => ({ name: 'integration-1' })),
supportsImageGeneration: false,
aliases: ['alias-1', 'short-name-1']
},
{
id: 'integration-provider-2',
name: 'Integration Provider 2',
creator: vi.fn(() => ({ name: 'integration-2' })),
supportsImageGeneration: true,
aliases: ['alias-2', 'short-name-2']
}
]
const successCount = registerMultipleProviderConfigs(configs)
expect(successCount).toBe(2)
// 验证配置注册成功
expect(hasProviderConfig('integration-provider-1')).toBe(true)
expect(hasProviderConfig('integration-provider-2')).toBe(true)
expect(hasProviderConfigByAlias('alias-1')).toBe(true)
expect(hasProviderConfigByAlias('alias-2')).toBe(true)
// 验证别名映射
const aliases = getAllProviderConfigAliases()
expect(aliases['alias-1']).toBe('integration-provider-1')
expect(aliases['alias-2']).toBe('integration-provider-2')
// 创建和注册 providers
const success1 = await createAndRegisterProvider('integration-provider-1', { apiKey: 'test1' })
const success2 = await createAndRegisterProvider('integration-provider-2', { apiKey: 'test2' })
expect(success1).toBe(true)
expect(success2).toBe(true)
// 验证注册成功
const registeredProviders = getInitializedProviders()
expect(registeredProviders).toContain('integration-provider-1')
expect(registeredProviders).toContain('integration-provider-2')
expect(hasInitializedProviders()).toBe(true)
// 清理
cleanup()
// 验证清理后的状态
expect(getInitializedProviders()).toEqual([])
expect(hasProviderConfig('integration-provider-1')).toBe(false)
expect(hasProviderConfig('integration-provider-2')).toBe(false)
expect(getAllProviderConfigAliases()).toEqual({})
// 基础配置应该重新加载
expect(hasProviderConfig('openai')).toBe(true)
})
it('正确处理动态导入配置的 provider', async () => {
const mockModule = { createCustomProvider: vi.fn(() => ({ name: 'custom-dynamic' })) }
const dynamicImportConfig: ProviderConfig = {
id: 'dynamic-import-provider',
name: 'Dynamic Import Provider',
import: vi.fn().mockResolvedValue(mockModule),
creatorFunctionName: 'createCustomProvider',
supportsImageGeneration: false
}
// 注册配置
const configSuccess = registerProviderConfig(dynamicImportConfig)
expect(configSuccess).toBe(true)
// 创建和注册 provider
const registerSuccess = await createAndRegisterProvider('dynamic-import-provider', { apiKey: 'test' })
expect(registerSuccess).toBe(true)
// 验证导入函数被调用
expect(dynamicImportConfig.import).toHaveBeenCalled()
expect(mockModule.createCustomProvider).toHaveBeenCalledWith({ apiKey: 'test' })
// 验证注册成功
expect(getInitializedProviders()).toContain('dynamic-import-provider')
})
it('正确处理大量配置的注册和管理', () => {
const largeConfigList: ProviderConfig[] = []
// 生成50个配置
for (let i = 0; i < 50; i++) {
largeConfigList.push({
id: `bulk-provider-${i}`,
name: `Bulk Provider ${i}`,
creator: vi.fn(() => ({ name: `bulk-${i}` })),
supportsImageGeneration: i % 2 === 0, // 偶数支持图像生成
aliases: [`alias-${i}`, `short-${i}`]
})
}
const successCount = registerMultipleProviderConfigs(largeConfigList)
expect(successCount).toBe(50)
// 验证所有配置都被正确注册
const allConfigs = getAllProviderConfigs()
expect(allConfigs.filter((config) => config.id.startsWith('bulk-provider-')).length).toBe(50)
// 验证别名数量
const aliases = getAllProviderConfigAliases()
const bulkAliases = Object.keys(aliases).filter(
(alias) => alias.startsWith('alias-') || alias.startsWith('short-')
)
expect(bulkAliases.length).toBe(100) // 每个 provider 有2个别名
// 随机验证几个配置
expect(hasProviderConfig('bulk-provider-0')).toBe(true)
expect(hasProviderConfig('bulk-provider-25')).toBe(true)
expect(hasProviderConfig('bulk-provider-49')).toBe(true)
// 验证别名工作正常
expect(resolveProviderConfigId('alias-25')).toBe('bulk-provider-25')
expect(isProviderConfigAlias('short-30')).toBe(true)
// 清理能正确处理大量数据
cleanup()
const cleanupAliases = getAllProviderConfigAliases()
expect(
Object.keys(cleanupAliases).filter((alias) => alias.startsWith('alias-') || alias.startsWith('short-'))
).toEqual([])
})
})
describe('边界测试', () => {
it('处理包含特殊字符的 provider IDs', () => {
const specialCharsConfigs: ProviderConfig[] = [
{
id: 'provider-with-dashes',
name: 'Provider With Dashes',
creator: vi.fn(() => ({ name: 'dashes' })),
supportsImageGeneration: false
},
{
id: 'provider_with_underscores',
name: 'Provider With Underscores',
creator: vi.fn(() => ({ name: 'underscores' })),
supportsImageGeneration: false
},
{
id: 'provider.with.dots',
name: 'Provider With Dots',
creator: vi.fn(() => ({ name: 'dots' })),
supportsImageGeneration: false
}
]
const successCount = registerMultipleProviderConfigs(specialCharsConfigs)
expect(successCount).toBeGreaterThan(0) // 至少有一些成功
// 验证支持的特殊字符格式
if (hasProviderConfig('provider-with-dashes')) {
expect(getProviderConfig('provider-with-dashes')).toBeDefined()
}
if (hasProviderConfig('provider_with_underscores')) {
expect(getProviderConfig('provider_with_underscores')).toBeDefined()
}
})
it('处理空的批量注册', () => {
const successCount = registerMultipleProviderConfigs([])
expect(successCount).toBe(0)
// 确保没有额外的配置被添加
const configsBefore = getAllProviderConfigs().length
expect(configsBefore).toBeGreaterThan(0) // 应该有基础配置
})
it('处理重复的配置注册', () => {
const config: ProviderConfig = {
id: 'duplicate-test-provider',
name: 'Duplicate Test Provider',
creator: vi.fn(() => ({ name: 'duplicate' })),
supportsImageGeneration: false
}
// 第一次注册成功
expect(registerProviderConfig(config)).toBe(true)
expect(hasProviderConfig('duplicate-test-provider')).toBe(true)
// 重复注册相同的配置(允许覆盖)
const updatedConfig: ProviderConfig = {
...config,
name: 'Updated Duplicate Test Provider'
}
expect(registerProviderConfig(updatedConfig)).toBe(true)
expect(hasProviderConfig('duplicate-test-provider')).toBe(true)
// 验证配置被更新
const retrievedConfig = getProviderConfig('duplicate-test-provider')
expect(retrievedConfig?.name).toBe('Updated Duplicate Test Provider')
})
it('处理极长的 ID 和名称', () => {
const longId = 'very-long-provider-id-' + 'x'.repeat(100)
const longName = 'Very Long Provider Name ' + 'Y'.repeat(100)
const config: ProviderConfig = {
id: longId,
name: longName,
creator: vi.fn(() => ({ name: 'long-test' })),
supportsImageGeneration: false
}
const success = registerProviderConfig(config)
expect(success).toBe(true)
expect(hasProviderConfig(longId)).toBe(true)
const retrievedConfig = getProviderConfig(longId)
expect(retrievedConfig?.name).toBe(longName)
})
it('处理大量别名的配置', () => {
const manyAliases = Array.from({ length: 50 }, (_, i) => `alias-${i}`)
const config: ProviderConfig = {
id: 'provider-with-many-aliases',
name: 'Provider With Many Aliases',
creator: vi.fn(() => ({ name: 'many-aliases' })),
supportsImageGeneration: false,
aliases: manyAliases
}
const success = registerProviderConfig(config)
expect(success).toBe(true)
// 验证所有别名都能正确解析
manyAliases.forEach((alias) => {
expect(hasProviderConfigByAlias(alias)).toBe(true)
expect(resolveProviderConfigId(alias)).toBe('provider-with-many-aliases')
expect(isProviderConfigAlias(alias)).toBe(true)
})
})
})
})

View File

@@ -1,264 +0,0 @@
import { describe, expect, it, vi } from 'vitest'
import {
type BaseProviderId,
baseProviderIds,
baseProviderIdSchema,
baseProviders,
type CustomProviderId,
customProviderIdSchema,
providerConfigSchema,
type ProviderId,
providerIdSchema
} from '../schemas'
describe('Provider Schemas', () => {
describe('baseProviders', () => {
it('包含所有预期的基础 providers', () => {
expect(baseProviders).toBeDefined()
expect(Array.isArray(baseProviders)).toBe(true)
expect(baseProviders.length).toBeGreaterThan(0)
const expectedIds = [
'openai',
'openai-responses',
'openai-compatible',
'anthropic',
'google',
'xai',
'azure',
'deepseek'
]
const actualIds = baseProviders.map((p) => p.id)
expectedIds.forEach((id) => {
expect(actualIds).toContain(id)
})
})
it('每个基础 provider 有必要的属性', () => {
baseProviders.forEach((provider) => {
expect(provider).toHaveProperty('id')
expect(provider).toHaveProperty('name')
expect(provider).toHaveProperty('creator')
expect(provider).toHaveProperty('supportsImageGeneration')
expect(typeof provider.id).toBe('string')
expect(typeof provider.name).toBe('string')
expect(typeof provider.creator).toBe('function')
expect(typeof provider.supportsImageGeneration).toBe('boolean')
})
})
it('provider ID 是唯一的', () => {
const ids = baseProviders.map((p) => p.id)
const uniqueIds = [...new Set(ids)]
expect(ids).toEqual(uniqueIds)
})
})
describe('baseProviderIds', () => {
it('正确提取所有基础 provider IDs', () => {
expect(baseProviderIds).toBeDefined()
expect(Array.isArray(baseProviderIds)).toBe(true)
expect(baseProviderIds.length).toBe(baseProviders.length)
baseProviders.forEach((provider) => {
expect(baseProviderIds).toContain(provider.id)
})
})
})
describe('baseProviderIdSchema', () => {
it('验证有效的基础 provider IDs', () => {
baseProviderIds.forEach((id) => {
expect(baseProviderIdSchema.safeParse(id).success).toBe(true)
})
})
it('拒绝无效的基础 provider IDs', () => {
const invalidIds = ['invalid', 'not-exists', '']
invalidIds.forEach((id) => {
expect(baseProviderIdSchema.safeParse(id).success).toBe(false)
})
})
})
describe('customProviderIdSchema', () => {
it('接受有效的自定义 provider IDs', () => {
const validIds = ['custom-provider', 'my-ai-service', 'company-llm-v2']
validIds.forEach((id) => {
expect(customProviderIdSchema.safeParse(id).success).toBe(true)
})
})
it('拒绝与基础 provider IDs 冲突的 IDs', () => {
baseProviderIds.forEach((id) => {
expect(customProviderIdSchema.safeParse(id).success).toBe(false)
})
})
it('拒绝空字符串', () => {
expect(customProviderIdSchema.safeParse('').success).toBe(false)
})
})
describe('providerIdSchema', () => {
it('接受基础 provider IDs', () => {
baseProviderIds.forEach((id) => {
expect(providerIdSchema.safeParse(id).success).toBe(true)
})
})
it('接受有效的自定义 provider IDs', () => {
const validCustomIds = ['custom-provider', 'my-ai-service']
validCustomIds.forEach((id) => {
expect(providerIdSchema.safeParse(id).success).toBe(true)
})
})
it('拒绝无效的 IDs', () => {
const invalidIds = ['', undefined, null, 123]
invalidIds.forEach((id) => {
expect(providerIdSchema.safeParse(id).success).toBe(false)
})
})
})
describe('providerConfigSchema', () => {
it('验证带有 creator 的有效配置', () => {
const validConfig = {
id: 'custom-provider',
name: 'Custom Provider',
creator: vi.fn(),
supportsImageGeneration: true
}
expect(providerConfigSchema.safeParse(validConfig).success).toBe(true)
})
it('验证带有 import 配置的有效配置', () => {
const validConfig = {
id: 'custom-provider',
name: 'Custom Provider',
import: vi.fn(),
creatorFunctionName: 'createCustom',
supportsImageGeneration: false
}
expect(providerConfigSchema.safeParse(validConfig).success).toBe(true)
})
it('拒绝既没有 creator 也没有 import 配置的配置', () => {
const invalidConfig = {
id: 'invalid',
name: 'Invalid Provider',
supportsImageGeneration: false
}
expect(providerConfigSchema.safeParse(invalidConfig).success).toBe(false)
})
it('为 supportsImageGeneration 设置默认值', () => {
const config = {
id: 'test',
name: 'Test',
creator: vi.fn()
}
const result = providerConfigSchema.safeParse(config)
expect(result.success).toBe(true)
if (result.success) {
expect(result.data.supportsImageGeneration).toBe(false)
}
})
it('拒绝使用基础 provider ID 的配置', () => {
const invalidConfig = {
id: 'openai', // 基础 provider ID
name: 'Should Fail',
creator: vi.fn()
}
expect(providerConfigSchema.safeParse(invalidConfig).success).toBe(false)
})
it('拒绝缺少必需字段的配置', () => {
const invalidConfigs = [
{ name: 'Missing ID', creator: vi.fn() },
{ id: 'missing-name', creator: vi.fn() },
{ id: '', name: 'Empty ID', creator: vi.fn() },
{ id: 'valid-custom', name: '', creator: vi.fn() }
]
invalidConfigs.forEach((config) => {
expect(providerConfigSchema.safeParse(config).success).toBe(false)
})
})
})
describe('Schema 验证功能', () => {
it('baseProviderIdSchema 正确验证基础 provider IDs', () => {
baseProviderIds.forEach((id) => {
expect(baseProviderIdSchema.safeParse(id).success).toBe(true)
})
expect(baseProviderIdSchema.safeParse('invalid-id').success).toBe(false)
})
it('customProviderIdSchema 正确验证自定义 provider IDs', () => {
const customIds = ['custom-provider', 'my-service', 'company-llm']
customIds.forEach((id) => {
expect(customProviderIdSchema.safeParse(id).success).toBe(true)
})
// 拒绝基础 provider IDs
baseProviderIds.forEach((id) => {
expect(customProviderIdSchema.safeParse(id).success).toBe(false)
})
})
it('providerIdSchema 接受基础和自定义 provider IDs', () => {
// 基础 IDs
baseProviderIds.forEach((id) => {
expect(providerIdSchema.safeParse(id).success).toBe(true)
})
// 自定义 IDs
const customIds = ['custom-provider', 'my-service']
customIds.forEach((id) => {
expect(providerIdSchema.safeParse(id).success).toBe(true)
})
})
it('providerConfigSchema 验证完整的 provider 配置', () => {
const validConfig = {
id: 'custom-provider',
name: 'Custom Provider',
creator: vi.fn(),
supportsImageGeneration: true
}
expect(providerConfigSchema.safeParse(validConfig).success).toBe(true)
const invalidConfig = {
id: 'openai', // 不允许基础 provider ID
name: 'OpenAI',
creator: vi.fn()
}
expect(providerConfigSchema.safeParse(invalidConfig).success).toBe(false)
})
})
describe('类型推导', () => {
it('BaseProviderId 类型正确', () => {
const id: BaseProviderId = 'openai'
expect(baseProviderIds).toContain(id)
})
it('CustomProviderId 类型是字符串', () => {
const id: CustomProviderId = 'custom-provider'
expect(typeof id).toBe('string')
})
it('ProviderId 类型支持基础和自定义 IDs', () => {
const baseId: ProviderId = 'openai'
const customId: ProviderId = 'custom-provider'
expect(typeof baseId).toBe('string')
expect(typeof customId).toBe('string')
})
})
})

View File

@@ -1,291 +0,0 @@
/**
* AI Provider 配置工厂
* 提供类型安全的 Provider 配置构建器
*/
import type { ProviderId, ProviderSettingsMap } from './types'
/**
* 通用配置基础类型,包含所有 Provider 共有的属性
*/
export interface BaseProviderConfig {
apiKey?: string
baseURL?: string
timeout?: number
headers?: Record<string, string>
fetch?: typeof globalThis.fetch
}
/**
* 完整的配置类型结合基础配置、AI SDK 配置和特定 Provider 配置
*/
type CompleteProviderConfig<T extends ProviderId> = BaseProviderConfig & Partial<ProviderSettingsMap[T]>
type ConfigHandler<T extends ProviderId> = (
builder: ProviderConfigBuilder<T>,
provider: CompleteProviderConfig<T>
) => void
const configHandlers: {
[K in ProviderId]?: ConfigHandler<K>
} = {
azure: (builder, provider) => {
const azureBuilder = builder as ProviderConfigBuilder<'azure'>
const azureProvider = provider as CompleteProviderConfig<'azure'>
azureBuilder.withAzureConfig({
apiVersion: azureProvider.apiVersion,
resourceName: azureProvider.resourceName
})
}
}
export class ProviderConfigBuilder<T extends ProviderId = ProviderId> {
private config: CompleteProviderConfig<T> = {} as CompleteProviderConfig<T>
constructor(private providerId: T) {}
/**
* 设置 API Key
*/
withApiKey(apiKey: string): this
withApiKey(apiKey: string, options: T extends 'openai' ? { organization?: string; project?: string } : never): this
withApiKey(apiKey: string, options?: any): this {
this.config.apiKey = apiKey
// 类型安全的 OpenAI 特定配置
if (this.providerId === 'openai' && options) {
const openaiConfig = this.config as CompleteProviderConfig<'openai'>
if (options.organization) {
openaiConfig.organization = options.organization
}
if (options.project) {
openaiConfig.project = options.project
}
}
return this
}
/**
* 设置基础 URL
*/
withBaseURL(baseURL: string) {
this.config.baseURL = baseURL
return this
}
/**
* 设置请求配置
*/
withRequestConfig(options: { headers?: Record<string, string>; fetch?: typeof fetch }): this {
if (options.headers) {
this.config.headers = { ...this.config.headers, ...options.headers }
}
if (options.fetch) {
this.config.fetch = options.fetch
}
return this
}
/**
* Azure OpenAI 特定配置
*/
withAzureConfig(options: { apiVersion?: string; resourceName?: string }): T extends 'azure' ? this : never
withAzureConfig(options: any): any {
if (this.providerId === 'azure') {
const azureConfig = this.config as CompleteProviderConfig<'azure'>
if (options.apiVersion) {
azureConfig.apiVersion = options.apiVersion
}
if (options.resourceName) {
azureConfig.resourceName = options.resourceName
}
}
return this
}
/**
* 设置自定义参数
*/
withCustomParams(params: Record<string, any>) {
Object.assign(this.config, params)
return this
}
/**
* 构建最终配置
*/
build(): ProviderSettingsMap[T] {
return this.config as ProviderSettingsMap[T]
}
}
/**
* Provider 配置工厂
* 提供便捷的配置创建方法
*/
export class ProviderConfigFactory {
/**
* 创建配置构建器
*/
static builder<T extends ProviderId>(providerId: T): ProviderConfigBuilder<T> {
return new ProviderConfigBuilder(providerId)
}
/**
* 从通用Provider对象创建配置 - 使用更优雅的处理器模式
*/
static fromProvider<T extends ProviderId>(
providerId: T,
provider: CompleteProviderConfig<T>,
options?: {
headers?: Record<string, string>
[key: string]: any
}
): ProviderSettingsMap[T] {
const builder = new ProviderConfigBuilder<T>(providerId)
// 设置基本配置
if (provider.apiKey) {
builder.withApiKey(provider.apiKey)
}
if (provider.baseURL) {
builder.withBaseURL(provider.baseURL)
}
// 设置请求配置
if (options?.headers) {
builder.withRequestConfig({
headers: options.headers
})
}
// 使用配置处理器模式 - 更加优雅和可扩展
const handler = configHandlers[providerId]
if (handler) {
handler(builder, provider)
}
// 添加其他自定义参数
if (options) {
const customOptions = { ...options }
delete customOptions.headers // 已经处理过了
if (Object.keys(customOptions).length > 0) {
builder.withCustomParams(customOptions)
}
}
return builder.build()
}
/**
* 快速创建 OpenAI 配置
*/
static createOpenAI(
apiKey: string,
options?: {
baseURL?: string
organization?: string
project?: string
}
) {
const builder = this.builder('openai')
// 使用类型安全的重载
if (options?.organization || options?.project) {
builder.withApiKey(apiKey, {
organization: options.organization,
project: options.project
})
} else {
builder.withApiKey(apiKey)
}
return builder.withBaseURL(options?.baseURL || 'https://api.openai.com').build()
}
/**
* 快速创建 Anthropic 配置
*/
static createAnthropic(
apiKey: string,
options?: {
baseURL?: string
}
) {
return this.builder('anthropic')
.withApiKey(apiKey)
.withBaseURL(options?.baseURL || 'https://api.anthropic.com')
.build()
}
/**
* 快速创建 Azure OpenAI 配置
*/
static createAzureOpenAI(
apiKey: string,
options: {
baseURL: string
apiVersion?: string
resourceName?: string
}
) {
return this.builder('azure')
.withApiKey(apiKey)
.withBaseURL(options.baseURL)
.withAzureConfig({
apiVersion: options.apiVersion,
resourceName: options.resourceName
})
.build()
}
/**
* 快速创建 Google 配置
*/
static createGoogle(
apiKey: string,
options?: {
baseURL?: string
projectId?: string
location?: string
}
) {
return this.builder('google')
.withApiKey(apiKey)
.withBaseURL(options?.baseURL || 'https://generativelanguage.googleapis.com')
.build()
}
/**
* 快速创建 Vertex AI 配置
*/
static createVertexAI() {
// credentials: {
// clientEmail: string
// privateKey: string
// },
// options?: {
// project?: string
// location?: string
// }
// return this.builder('google-vertex')
// .withGoogleCredentials(credentials)
// .withGoogleVertexConfig({
// project: options?.project,
// location: options?.location
// })
// .build()
}
static createOpenAICompatible(baseURL: string, apiKey: string) {
return this.builder('openai-compatible').withBaseURL(baseURL).withApiKey(apiKey).build()
}
}
/**
* 便捷的配置创建函数
*/
export const createProviderConfig = ProviderConfigFactory.fromProvider
export const providerConfigBuilder = ProviderConfigFactory.builder

View File

@@ -1,83 +0,0 @@
/**
* Providers 模块统一导出 - 独立Provider包
*/
// ==================== 核心管理器 ====================
// Provider 注册表管理器
export { globalRegistryManagement, RegistryManagement } from './RegistryManagement'
// Provider 核心功能
export {
// 状态管理
cleanup,
clearAllProviders,
createAndRegisterProvider,
createProvider,
getAllProviderConfigAliases,
getAllProviderConfigs,
getImageModel,
// 工具函数
getInitializedProviders,
getLanguageModel,
getProviderConfig,
getProviderConfigByAlias,
getSupportedProviders,
getTextEmbeddingModel,
hasInitializedProviders,
// 工具函数
hasProviderConfig,
// 别名支持
hasProviderConfigByAlias,
isProviderConfigAlias,
// 错误类型
ProviderInitializationError,
// 全局访问
providerRegistry,
registerMultipleProviderConfigs,
registerProvider,
// 统一Provider系统
registerProviderConfig,
resolveProviderConfigId
} from './registry'
// ==================== 基础数据和类型 ====================
// 基础Provider数据源
export { baseProviderIds, baseProviders } from './schemas'
// 类型定义和Schema
export type {
BaseProviderId,
CustomProviderId,
DynamicProviderRegistration,
ProviderConfig,
ProviderId
} from './schemas' // 从 schemas 导出的类型
export { baseProviderIdSchema, customProviderIdSchema, providerConfigSchema, providerIdSchema } from './schemas' // Schema 导出
export type {
DynamicProviderRegistry,
ExtensibleProviderSettingsMap,
ProviderError,
ProviderSettingsMap,
ProviderTypeRegistrar
} from './types'
// ==================== 工具函数 ====================
// Provider配置工厂
export {
type BaseProviderConfig,
createProviderConfig,
ProviderConfigBuilder,
providerConfigBuilder,
ProviderConfigFactory
} from './factory'
// 工具函数
export { formatPrivateKey } from './utils'
// ==================== 扩展功能 ====================
// Hub Provider 功能
export { createHubProvider, type HubProviderConfig, HubProviderError } from './HubProvider'

View File

@@ -1,320 +0,0 @@
/**
* Provider 初始化器
* 负责根据配置创建 providers 并注册到全局管理器
* 集成了来自 ModelCreator 的特殊处理逻辑
*/
import { customProvider } from 'ai'
import { globalRegistryManagement } from './RegistryManagement'
import { baseProviders, type ProviderConfig } from './schemas'
/**
* Provider 初始化错误类型
*/
class ProviderInitializationError extends Error {
constructor(
message: string,
public providerId?: string,
public cause?: Error
) {
super(message)
this.name = 'ProviderInitializationError'
}
}
// ==================== 全局管理器导出 ====================
export { globalRegistryManagement as providerRegistry }
// ==================== 便捷访问方法 ====================
export const getLanguageModel = (id: string) => globalRegistryManagement.languageModel(id as any)
export const getTextEmbeddingModel = (id: string) => globalRegistryManagement.textEmbeddingModel(id as any)
export const getImageModel = (id: string) => globalRegistryManagement.imageModel(id as any)
// ==================== 工具函数 ====================
/**
* 获取支持的 Providers 列表
*/
export function getSupportedProviders(): Array<{
id: string
name: string
}> {
return baseProviders.map((provider) => ({
id: provider.id,
name: provider.name
}))
}
/**
* 获取所有已初始化的 providers
*/
export function getInitializedProviders(): string[] {
return globalRegistryManagement.getRegisteredProviders()
}
/**
* 检查是否有任何已初始化的 providers
*/
export function hasInitializedProviders(): boolean {
return globalRegistryManagement.hasProviders()
}
// ==================== 统一Provider配置系统 ====================
// 全局Provider配置存储
const providerConfigs = new Map<string, ProviderConfig>()
// 全局ProviderConfig别名映射 - 借鉴RegistryManagement模式
const providerConfigAliases = new Map<string, string>() // alias -> realId
/**
* 初始化内置配置 - 将baseProviders转换为统一格式
*/
function initializeBuiltInConfigs(): void {
baseProviders.forEach((provider) => {
const config: ProviderConfig = {
id: provider.id,
name: provider.name,
creator: provider.creator as any, // 类型转换以兼容多种creator签名
supportsImageGeneration: provider.supportsImageGeneration || false
}
providerConfigs.set(provider.id, config)
})
}
// 启动时自动注册内置配置
initializeBuiltInConfigs()
/**
* 步骤1: 注册Provider配置 - 仅存储配置,不执行创建
*/
export function registerProviderConfig(config: ProviderConfig): boolean {
try {
// 验证配置
if (!config || !config.id || !config.name) {
return false
}
// 检查是否与已有配置冲突(包括内置配置)
if (providerConfigs.has(config.id)) {
console.warn(`ProviderConfig "${config.id}" already exists, will override`)
}
// 存储配置(内置和用户配置统一处理)
providerConfigs.set(config.id, config)
// 处理别名
if (config.aliases && config.aliases.length > 0) {
config.aliases.forEach((alias) => {
if (providerConfigAliases.has(alias)) {
console.warn(`ProviderConfig alias "${alias}" already exists, will override`)
}
providerConfigAliases.set(alias, config.id)
})
}
return true
} catch (error) {
console.error(`Failed to register ProviderConfig:`, error)
return false
}
}
/**
* 步骤2: 创建Provider - 根据配置执行实际创建
*/
export async function createProvider(providerId: string, options: any): Promise<any> {
// 支持通过别名查找配置
const config = getProviderConfigByAlias(providerId)
if (!config) {
throw new Error(`ProviderConfig not found for id: ${providerId}`)
}
try {
let creator: (options: any) => any
if (config.creator) {
// 方式1: 直接执行 creator
creator = config.creator
} else if (config.import && config.creatorFunctionName) {
// 方式2: 动态导入并执行
const module = await config.import()
creator = (module as any)[config.creatorFunctionName]
if (!creator || typeof creator !== 'function') {
throw new Error(`Creator function "${config.creatorFunctionName}" not found in imported module`)
}
} else {
throw new Error('No valid creator method provided in ProviderConfig')
}
// 使用真实配置创建provider实例
return creator(options)
} catch (error) {
console.error(`Failed to create provider "${providerId}":`, error)
throw error
}
}
/**
* 步骤3: 注册Provider到全局管理器
*/
export function registerProvider(providerId: string, provider: any): boolean {
try {
const config = providerConfigs.get(providerId)
if (!config) {
console.error(`ProviderConfig not found for id: ${providerId}`)
return false
}
// 获取aliases配置
const aliases = config.aliases
// 处理特殊provider逻辑
if (providerId === 'openai') {
// 注册默认 openai
globalRegistryManagement.registerProvider(providerId, provider, aliases)
// 创建并注册 openai-chat 变体
const openaiChatProvider = customProvider({
fallbackProvider: {
...provider,
languageModel: (modelId: string) => provider.chat(modelId)
}
})
globalRegistryManagement.registerProvider(`${providerId}-chat`, openaiChatProvider)
} else if (providerId === 'azure') {
globalRegistryManagement.registerProvider(`${providerId}-chat`, provider, aliases)
// 跟上面相反,creator产出的默认会调用chat
const azureResponsesProvider = customProvider({
fallbackProvider: {
...provider,
languageModel: (modelId: string) => provider.responses(modelId)
}
})
globalRegistryManagement.registerProvider(providerId, azureResponsesProvider)
} else {
// 其他provider直接注册
globalRegistryManagement.registerProvider(providerId, provider, aliases)
}
return true
} catch (error) {
console.error(`Failed to register provider "${providerId}" to global registry:`, error)
return false
}
}
/**
* 便捷函数: 一次性完成创建+注册
*/
export async function createAndRegisterProvider(providerId: string, options: any): Promise<boolean> {
try {
// 步骤2: 创建provider
const provider = await createProvider(providerId, options)
// 步骤3: 注册到全局管理器
return registerProvider(providerId, provider)
} catch (error) {
console.error(`Failed to create and register provider "${providerId}":`, error)
return false
}
}
/**
* 批量注册Provider配置
*/
export function registerMultipleProviderConfigs(configs: ProviderConfig[]): number {
let successCount = 0
configs.forEach((config) => {
if (registerProviderConfig(config)) {
successCount++
}
})
return successCount
}
/**
* 检查是否有对应的Provider配置
*/
export function hasProviderConfig(providerId: string): boolean {
return providerConfigs.has(providerId)
}
/**
* 通过别名或ID检查是否有对应的Provider配置
*/
export function hasProviderConfigByAlias(aliasOrId: string): boolean {
const realId = resolveProviderConfigId(aliasOrId)
return providerConfigs.has(realId)
}
/**
* 获取所有Provider配置
*/
export function getAllProviderConfigs(): ProviderConfig[] {
return Array.from(providerConfigs.values())
}
/**
* 根据ID获取Provider配置
*/
export function getProviderConfig(providerId: string): ProviderConfig | undefined {
return providerConfigs.get(providerId)
}
/**
* 通过别名或ID获取Provider配置
*/
export function getProviderConfigByAlias(aliasOrId: string): ProviderConfig | undefined {
// 先检查是否为别名如果是则解析为真实ID
const realId = providerConfigAliases.get(aliasOrId) || aliasOrId
return providerConfigs.get(realId)
}
/**
* 解析真实的ProviderConfig ID去别名化
*/
export function resolveProviderConfigId(aliasOrId: string): string {
return providerConfigAliases.get(aliasOrId) || aliasOrId
}
/**
* 检查是否为ProviderConfig别名
*/
export function isProviderConfigAlias(id: string): boolean {
return providerConfigAliases.has(id)
}
/**
* 获取所有ProviderConfig别名映射关系
*/
export function getAllProviderConfigAliases(): Record<string, string> {
const result: Record<string, string> = {}
providerConfigAliases.forEach((realId, alias) => {
result[alias] = realId
})
return result
}
/**
* 清理所有Provider配置和已注册的providers
*/
export function cleanup(): void {
providerConfigs.clear()
providerConfigAliases.clear() // 清理别名映射
globalRegistryManagement.clear()
// 重新初始化内置配置
initializeBuiltInConfigs()
}
export function clearAllProviders(): void {
globalRegistryManagement.clear()
}
// ==================== 导出错误类型 ====================
export { ProviderInitializationError }

View File

@@ -1,194 +0,0 @@
/**
* Provider Config 定义
*/
import { createAnthropic } from '@ai-sdk/anthropic'
import { createAzure } from '@ai-sdk/azure'
import { type AzureOpenAIProviderSettings } from '@ai-sdk/azure'
import { createDeepSeek } from '@ai-sdk/deepseek'
import { createGoogleGenerativeAI } from '@ai-sdk/google'
import { createOpenAI, type OpenAIProviderSettings } from '@ai-sdk/openai'
import { createOpenAICompatible } from '@ai-sdk/openai-compatible'
import { LanguageModelV2 } from '@ai-sdk/provider'
import { createXai } from '@ai-sdk/xai'
import { createOpenRouter } from '@openrouter/ai-sdk-provider'
import { customProvider, Provider } from 'ai'
import { z } from 'zod'
/**
* 基础 Provider IDs
*/
export const baseProviderIds = [
'openai',
'openai-chat',
'openai-compatible',
'anthropic',
'google',
'xai',
'azure',
'azure-responses',
'deepseek',
'openrouter'
] as const
/**
* 基础 Provider ID Schema
*/
export const baseProviderIdSchema = z.enum(baseProviderIds)
/**
* 基础 Provider ID
*/
export type BaseProviderId = z.infer<typeof baseProviderIdSchema>
export const isBaseProvider = (id: ProviderId): id is BaseProviderId => {
return baseProviderIdSchema.safeParse(id).success
}
type BaseProvider = {
id: BaseProviderId
name: string
creator: (options: any) => Provider | LanguageModelV2
supportsImageGeneration: boolean
}
/**
* 基础 Providers 定义
* 作为唯一数据源,避免重复维护
*/
export const baseProviders = [
{
id: 'openai',
name: 'OpenAI',
creator: createOpenAI,
supportsImageGeneration: true
},
{
id: 'openai-chat',
name: 'OpenAI Chat',
creator: (options: OpenAIProviderSettings) => {
const provider = createOpenAI(options)
return customProvider({
fallbackProvider: {
...provider,
languageModel: (modelId: string) => provider.chat(modelId)
}
})
},
supportsImageGeneration: true
},
{
id: 'openai-compatible',
name: 'OpenAI Compatible',
creator: createOpenAICompatible,
supportsImageGeneration: true
},
{
id: 'anthropic',
name: 'Anthropic',
creator: createAnthropic,
supportsImageGeneration: false
},
{
id: 'google',
name: 'Google Generative AI',
creator: createGoogleGenerativeAI,
supportsImageGeneration: true
},
{
id: 'xai',
name: 'xAI (Grok)',
creator: createXai,
supportsImageGeneration: true
},
{
id: 'azure',
name: 'Azure OpenAI',
creator: createAzure,
supportsImageGeneration: true
},
{
id: 'azure-responses',
name: 'Azure OpenAI Responses',
creator: (options: AzureOpenAIProviderSettings) => {
const provider = createAzure(options)
return customProvider({
fallbackProvider: {
...provider,
languageModel: (modelId: string) => provider.responses(modelId)
}
})
},
supportsImageGeneration: true
},
{
id: 'deepseek',
name: 'DeepSeek',
creator: createDeepSeek,
supportsImageGeneration: false
},
{
id: 'openrouter',
name: 'OpenRouter',
creator: createOpenRouter,
supportsImageGeneration: true
}
] as const satisfies BaseProvider[]
/**
* 用户自定义 Provider ID Schema
* 允许任意字符串,但排除基础 provider IDs 以避免冲突
*/
export const customProviderIdSchema = z
.string()
.min(1)
.refine((id) => !baseProviderIds.includes(id as any), {
message: 'Custom provider ID cannot conflict with base provider IDs'
})
/**
* Provider ID Schema - 支持基础和自定义
*/
export const providerIdSchema = z.union([baseProviderIdSchema, customProviderIdSchema])
/**
* Provider 配置 Schema
* 用于Provider的配置验证
*/
export const providerConfigSchema = z
.object({
id: customProviderIdSchema, // 只允许自定义ID
name: z.string().min(1),
creator: z
.function({
input: z.any(),
output: z.any()
})
.optional(),
import: z.function().optional(),
creatorFunctionName: z.string().optional(),
supportsImageGeneration: z.boolean().default(false),
imageCreator: z.function().optional(),
validateOptions: z.function().optional(),
aliases: z.array(z.string()).optional()
})
.refine((data) => data.creator || (data.import && data.creatorFunctionName), {
message: 'Must provide either creator function or import configuration'
})
/**
* Provider ID 类型 - 基于 zod schema 推导
*/
export type ProviderId = z.infer<typeof providerIdSchema>
export type CustomProviderId = z.infer<typeof customProviderIdSchema>
/**
* Provider 配置类型
*/
export type ProviderConfig = z.infer<typeof providerConfigSchema>
/**
* 兼容性类型别名
* @deprecated 使用 ProviderConfig 替代
*/
export type DynamicProviderRegistration = ProviderConfig

View File

@@ -1,96 +0,0 @@
import { type AnthropicProviderSettings } from '@ai-sdk/anthropic'
import { type AzureOpenAIProviderSettings } from '@ai-sdk/azure'
import { type DeepSeekProviderSettings } from '@ai-sdk/deepseek'
import { type GoogleGenerativeAIProviderSettings } from '@ai-sdk/google'
import { type OpenAIProviderSettings } from '@ai-sdk/openai'
import { type OpenAICompatibleProviderSettings } from '@ai-sdk/openai-compatible'
import {
EmbeddingModelV2 as EmbeddingModel,
ImageModelV2 as ImageModel,
LanguageModelV2 as LanguageModel,
ProviderV2,
SpeechModelV2 as SpeechModel,
TranscriptionModelV2 as TranscriptionModel
} from '@ai-sdk/provider'
import { type XaiProviderSettings } from '@ai-sdk/xai'
// 导入基于 Zod 的 ProviderId 类型
import { type ProviderId as ZodProviderId } from './schemas'
export interface ExtensibleProviderSettingsMap {
// 基础的静态providers
openai: OpenAIProviderSettings
'openai-responses': OpenAIProviderSettings
'openai-compatible': OpenAICompatibleProviderSettings
anthropic: AnthropicProviderSettings
google: GoogleGenerativeAIProviderSettings
xai: XaiProviderSettings
azure: AzureOpenAIProviderSettings
deepseek: DeepSeekProviderSettings
}
// 动态扩展的provider类型注册表
export interface DynamicProviderRegistry {
[key: string]: any
}
// 合并基础和动态provider类型
export type ProviderSettingsMap = ExtensibleProviderSettingsMap & DynamicProviderRegistry
// 错误类型
export class ProviderError extends Error {
constructor(
message: string,
public providerId: string,
public code?: string,
public cause?: Error
) {
super(message)
this.name = 'ProviderError'
}
}
// 动态ProviderId类型 - 基于 Zod Schema支持运行时扩展和验证
export type ProviderId = ZodProviderId
export interface ProviderTypeRegistrar {
registerProviderType<T extends string, S>(providerId: T, settingsType: S): void
getProviderSettings<T extends string>(providerId: T): any
}
// 重新导出所有类型供外部使用
export type {
AnthropicProviderSettings,
AzureOpenAIProviderSettings,
DeepSeekProviderSettings,
GoogleGenerativeAIProviderSettings,
OpenAICompatibleProviderSettings,
OpenAIProviderSettings,
XaiProviderSettings
}
export type AiSdkModel = LanguageModel | ImageModel | EmbeddingModel<string> | TranscriptionModel | SpeechModel
export type AiSdkModelType = 'text' | 'image' | 'embedding' | 'transcription' | 'speech'
export const METHOD_MAP = {
text: 'languageModel',
image: 'imageModel',
embedding: 'textEmbeddingModel',
transcription: 'transcriptionModel',
speech: 'speechModel'
} as const satisfies Record<AiSdkModelType, keyof ProviderV2>
export type AiSdkModelMethodMap = Record<AiSdkModelType, keyof ProviderV2>
export type AiSdkModelReturnMap = {
text: LanguageModel
image: ImageModel
embedding: EmbeddingModel<string>
transcription: TranscriptionModel
speech: SpeechModel
}
export type AiSdkMethodName<T extends AiSdkModelType> = (typeof METHOD_MAP)[T]
export type AiSdkModelReturn<T extends AiSdkModelType> = AiSdkModelReturnMap[T]

View File

@@ -1,86 +0,0 @@
/**
* 格式化私钥确保它包含正确的PEM头部和尾部
*/
export function formatPrivateKey(privateKey: string): string {
if (!privateKey || typeof privateKey !== 'string') {
throw new Error('Private key must be a non-empty string')
}
// 先处理 JSON 字符串中的转义换行符
const key = privateKey.replace(/\\n/g, '\n')
// 检查是否已经是正确格式的 PEM 私钥
const hasBeginMarker = key.includes('-----BEGIN PRIVATE KEY-----')
const hasEndMarker = key.includes('-----END PRIVATE KEY-----')
if (hasBeginMarker && hasEndMarker) {
// 已经是 PEM 格式,但可能格式不规范,重新格式化
return normalizePemFormat(key)
}
// 如果没有完整的 PEM 头尾,尝试重新构建
return reconstructPemKey(key)
}
/**
* 标准化 PEM 格式
*/
function normalizePemFormat(pemKey: string): string {
// 分离头部、内容和尾部
const lines = pemKey
.split('\n')
.map((line) => line.trim())
.filter((line) => line.length > 0)
let keyContent = ''
let foundBegin = false
let foundEnd = false
for (const line of lines) {
if (line === '-----BEGIN PRIVATE KEY-----') {
foundBegin = true
continue
}
if (line === '-----END PRIVATE KEY-----') {
foundEnd = true
break
}
if (foundBegin && !foundEnd) {
keyContent += line
}
}
if (!foundBegin || !foundEnd || !keyContent) {
throw new Error('Invalid PEM format: missing BEGIN/END markers or key content')
}
// 重新格式化为 64 字符一行
const formattedContent = keyContent.match(/.{1,64}/g)?.join('\n') || keyContent
return `-----BEGIN PRIVATE KEY-----\n${formattedContent}\n-----END PRIVATE KEY-----`
}
/**
* 重新构建 PEM 私钥
*/
function reconstructPemKey(key: string): string {
// 移除所有空白字符和可能存在的不完整头尾
let cleanKey = key.replace(/\s+/g, '')
cleanKey = cleanKey.replace(/-----BEGIN[^-]*-----/g, '')
cleanKey = cleanKey.replace(/-----END[^-]*-----/g, '')
// 确保私钥内容不为空
if (!cleanKey) {
throw new Error('Private key content is empty after cleaning')
}
// 验证是否是有效的 Base64 字符
if (!/^[A-Za-z0-9+/=]+$/.test(cleanKey)) {
throw new Error('Private key contains invalid characters (not valid Base64)')
}
// 格式化为 64 字符一行
const formattedKey = cleanKey.match(/.{1,64}/g)?.join('\n') || cleanKey
return `-----BEGIN PRIVATE KEY-----\n${formattedKey}\n-----END PRIVATE KEY-----`
}

View File

@@ -1,523 +0,0 @@
import { ImageModelV2 } from '@ai-sdk/provider'
import { experimental_generateImage as aiGenerateImage, NoImageGeneratedError } from 'ai'
import { beforeEach, describe, expect, it, vi } from 'vitest'
import { type AiPlugin } from '../../plugins'
import { globalRegistryManagement } from '../../providers/RegistryManagement'
import { ImageGenerationError, ImageModelResolutionError } from '../errors'
import { RuntimeExecutor } from '../executor'
// Mock dependencies
vi.mock('ai', () => ({
experimental_generateImage: vi.fn(),
NoImageGeneratedError: class NoImageGeneratedError extends Error {
static isInstance = vi.fn()
constructor() {
super('No image generated')
this.name = 'NoImageGeneratedError'
}
}
}))
vi.mock('../../providers/RegistryManagement', () => ({
globalRegistryManagement: {
imageModel: vi.fn()
},
DEFAULT_SEPARATOR: '|'
}))
describe('RuntimeExecutor.generateImage', () => {
let executor: RuntimeExecutor<'openai'>
let mockImageModel: ImageModelV2
let mockGenerateImageResult: any
beforeEach(() => {
// Reset all mocks
vi.clearAllMocks()
// Create executor instance
executor = RuntimeExecutor.create('openai', {
apiKey: 'test-key'
})
// Mock image model
mockImageModel = {
modelId: 'dall-e-3',
provider: 'openai'
} as ImageModelV2
// Mock generateImage result
mockGenerateImageResult = {
image: {
base64: 'base64-encoded-image-data',
uint8Array: new Uint8Array([1, 2, 3]),
mediaType: 'image/png'
},
images: [
{
base64: 'base64-encoded-image-data',
uint8Array: new Uint8Array([1, 2, 3]),
mediaType: 'image/png'
}
],
warnings: [],
providerMetadata: {
openai: {
images: [{ revisedPrompt: 'A detailed prompt' }]
}
},
responses: []
}
// Setup mocks to avoid "No providers registered" error
vi.mocked(globalRegistryManagement.imageModel).mockReturnValue(mockImageModel)
vi.mocked(aiGenerateImage).mockResolvedValue(mockGenerateImageResult)
})
describe('Basic functionality', () => {
it('should generate a single image with minimal parameters', async () => {
const result = await executor.generateImage({ model: 'dall-e-3', prompt: 'A futuristic cityscape at sunset' })
expect(globalRegistryManagement.imageModel).toHaveBeenCalledWith('openai|dall-e-3')
expect(aiGenerateImage).toHaveBeenCalledWith({
model: mockImageModel,
prompt: 'A futuristic cityscape at sunset'
})
expect(result).toEqual(mockGenerateImageResult)
})
it('should generate image with pre-created model', async () => {
const result = await executor.generateImage({
model: mockImageModel,
prompt: 'A beautiful landscape'
})
// Note: globalRegistryManagement.imageModel may still be called due to resolveImageModel logic
expect(aiGenerateImage).toHaveBeenCalledWith({
model: mockImageModel,
prompt: 'A beautiful landscape'
})
expect(result).toEqual(mockGenerateImageResult)
})
it('should support multiple images generation', async () => {
await executor.generateImage({ model: 'dall-e-3', prompt: 'A futuristic cityscape', n: 3 })
expect(aiGenerateImage).toHaveBeenCalledWith({
model: mockImageModel,
prompt: 'A futuristic cityscape',
n: 3
})
})
it('should support size specification', async () => {
await executor.generateImage({ model: 'dall-e-3', prompt: 'A beautiful sunset', size: '1024x1024' })
expect(aiGenerateImage).toHaveBeenCalledWith({
model: mockImageModel,
prompt: 'A beautiful sunset',
size: '1024x1024'
})
})
it('should support aspect ratio specification', async () => {
await executor.generateImage({ model: 'dall-e-3', prompt: 'A mountain landscape', aspectRatio: '16:9' })
expect(aiGenerateImage).toHaveBeenCalledWith({
model: mockImageModel,
prompt: 'A mountain landscape',
aspectRatio: '16:9'
})
})
it('should support seed for consistent output', async () => {
await executor.generateImage({ model: 'dall-e-3', prompt: 'A cat in space', seed: 1234567890 })
expect(aiGenerateImage).toHaveBeenCalledWith({
model: mockImageModel,
prompt: 'A cat in space',
seed: 1234567890
})
})
it('should support abort signal', async () => {
const abortController = new AbortController()
await executor.generateImage({ model: 'dall-e-3', prompt: 'A cityscape', abortSignal: abortController.signal })
expect(aiGenerateImage).toHaveBeenCalledWith({
model: mockImageModel,
prompt: 'A cityscape',
abortSignal: abortController.signal
})
})
it('should support provider-specific options', async () => {
await executor.generateImage({
model: 'dall-e-3',
prompt: 'A space station',
providerOptions: {
openai: {
quality: 'hd',
style: 'vivid'
}
}
})
expect(aiGenerateImage).toHaveBeenCalledWith({
model: mockImageModel,
prompt: 'A space station',
providerOptions: {
openai: {
quality: 'hd',
style: 'vivid'
}
}
})
})
it('should support custom headers', async () => {
await executor.generateImage({
model: 'dall-e-3',
prompt: 'A robot',
headers: {
'X-Custom-Header': 'test-value'
}
})
expect(aiGenerateImage).toHaveBeenCalledWith({
model: mockImageModel,
prompt: 'A robot',
headers: {
'X-Custom-Header': 'test-value'
}
})
})
})
describe('Plugin integration', () => {
it('should execute plugins in correct order', async () => {
const pluginCallOrder: string[] = []
const testPlugin: AiPlugin = {
name: 'test-plugin',
onRequestStart: vi.fn(async () => {
pluginCallOrder.push('onRequestStart')
}),
transformParams: vi.fn(async (params) => {
pluginCallOrder.push('transformParams')
return { ...params, size: '512x512' }
}),
transformResult: vi.fn(async (result) => {
pluginCallOrder.push('transformResult')
return { ...result, processed: true }
}),
onRequestEnd: vi.fn(async () => {
pluginCallOrder.push('onRequestEnd')
})
}
const executorWithPlugin = RuntimeExecutor.create(
'openai',
{
apiKey: 'test-key'
},
[testPlugin]
)
const result = await executorWithPlugin.generateImage({ model: 'dall-e-3', prompt: 'A test image' })
expect(pluginCallOrder).toEqual(['onRequestStart', 'transformParams', 'transformResult', 'onRequestEnd'])
expect(testPlugin.transformParams).toHaveBeenCalledWith(
{ prompt: 'A test image' },
expect.objectContaining({
providerId: 'openai',
modelId: 'dall-e-3'
})
)
expect(aiGenerateImage).toHaveBeenCalledWith({
model: mockImageModel,
prompt: 'A test image',
size: '512x512' // Should be transformed by plugin
})
expect(result).toEqual({
...mockGenerateImageResult,
processed: true // Should be transformed by plugin
})
})
it('should handle model resolution through plugins', async () => {
const customImageModel = {
modelId: 'custom-model',
provider: 'openai'
} as ImageModelV2
const modelResolutionPlugin: AiPlugin = {
name: 'model-resolver',
resolveModel: vi.fn(async () => customImageModel)
}
const executorWithPlugin = RuntimeExecutor.create(
'openai',
{
apiKey: 'test-key'
},
[modelResolutionPlugin]
)
await executorWithPlugin.generateImage({ model: 'dall-e-3', prompt: 'A test image' })
expect(modelResolutionPlugin.resolveModel).toHaveBeenCalledWith(
'dall-e-3',
expect.objectContaining({
providerId: 'openai',
modelId: 'dall-e-3'
})
)
expect(aiGenerateImage).toHaveBeenCalledWith({
model: customImageModel,
prompt: 'A test image'
})
})
it('should support recursive calls from plugins', async () => {
const recursivePlugin: AiPlugin = {
name: 'recursive-plugin',
transformParams: vi.fn(async (params, context) => {
if (!context.isRecursiveCall && params.prompt === 'original') {
// Make a recursive call with modified prompt
await context.recursiveCall({
model: 'dall-e-3',
prompt: 'modified'
})
}
return params
})
}
const executorWithPlugin = RuntimeExecutor.create(
'openai',
{
apiKey: 'test-key'
},
[recursivePlugin]
)
await executorWithPlugin.generateImage({ model: 'dall-e-3', prompt: 'original' })
expect(recursivePlugin.transformParams).toHaveBeenCalledTimes(2)
expect(aiGenerateImage).toHaveBeenCalledTimes(2)
})
})
describe('Error handling', () => {
it('should handle model creation errors', async () => {
const modelError = new Error('Failed to get image model')
vi.mocked(globalRegistryManagement.imageModel).mockImplementation(() => {
throw modelError
})
await expect(executor.generateImage({ model: 'invalid-model', prompt: 'A test image' })).rejects.toThrow(
ImageGenerationError
)
})
it('should handle ImageModelResolutionError correctly', async () => {
const resolutionError = new ImageModelResolutionError('invalid-model', 'openai', new Error('Model not found'))
vi.mocked(globalRegistryManagement.imageModel).mockImplementation(() => {
throw resolutionError
})
const thrownError = await executor
.generateImage({ model: 'invalid-model', prompt: 'A test image' })
.catch((error) => error)
expect(thrownError).toBeInstanceOf(ImageGenerationError)
expect(thrownError.message).toContain('Failed to generate image:')
expect(thrownError.providerId).toBe('openai')
expect(thrownError.modelId).toBe('invalid-model')
expect(thrownError.cause).toBeInstanceOf(ImageModelResolutionError)
expect(thrownError.cause.message).toContain('Failed to resolve image model: invalid-model')
})
it('should handle ImageModelResolutionError without provider', async () => {
const resolutionError = new ImageModelResolutionError('unknown-model')
vi.mocked(globalRegistryManagement.imageModel).mockImplementation(() => {
throw resolutionError
})
await expect(executor.generateImage({ model: 'unknown-model', prompt: 'A test image' })).rejects.toThrow(
ImageGenerationError
)
})
it('should handle image generation API errors', async () => {
const apiError = new Error('API request failed')
vi.mocked(aiGenerateImage).mockRejectedValue(apiError)
await expect(executor.generateImage({ model: 'dall-e-3', prompt: 'A test image' })).rejects.toThrow(
'Failed to generate image:'
)
})
it('should handle NoImageGeneratedError', async () => {
const noImageError = new NoImageGeneratedError({
cause: new Error('No image generated'),
responses: []
})
vi.mocked(aiGenerateImage).mockRejectedValue(noImageError)
vi.mocked(NoImageGeneratedError.isInstance).mockReturnValue(true)
await expect(executor.generateImage({ model: 'dall-e-3', prompt: 'A test image' })).rejects.toThrow(
'Failed to generate image:'
)
})
it('should execute onError plugin hook on failure', async () => {
const error = new Error('Generation failed')
vi.mocked(aiGenerateImage).mockRejectedValue(error)
const errorPlugin: AiPlugin = {
name: 'error-handler',
onError: vi.fn()
}
const executorWithPlugin = RuntimeExecutor.create(
'openai',
{
apiKey: 'test-key'
},
[errorPlugin]
)
await expect(executorWithPlugin.generateImage({ model: 'dall-e-3', prompt: 'A test image' })).rejects.toThrow(
'Failed to generate image:'
)
expect(errorPlugin.onError).toHaveBeenCalledWith(
error,
expect.objectContaining({
providerId: 'openai',
modelId: 'dall-e-3'
})
)
})
it('should handle abort signal timeout', async () => {
const abortError = new Error('Operation was aborted')
abortError.name = 'AbortError'
vi.mocked(aiGenerateImage).mockRejectedValue(abortError)
const abortController = new AbortController()
setTimeout(() => abortController.abort(), 10)
await expect(
executor.generateImage({ model: 'dall-e-3', prompt: 'A test image', abortSignal: abortController.signal })
).rejects.toThrow('Failed to generate image:')
})
})
describe('Multiple providers support', () => {
it('should work with different providers', async () => {
const googleExecutor = RuntimeExecutor.create('google', {
apiKey: 'google-key'
})
await googleExecutor.generateImage({ model: 'imagen-3.0-generate-002', prompt: 'A landscape' })
expect(globalRegistryManagement.imageModel).toHaveBeenCalledWith('google|imagen-3.0-generate-002')
})
it('should support xAI Grok image models', async () => {
const xaiExecutor = RuntimeExecutor.create('xai', {
apiKey: 'xai-key'
})
await xaiExecutor.generateImage({ model: 'grok-2-image', prompt: 'A futuristic robot' })
expect(globalRegistryManagement.imageModel).toHaveBeenCalledWith('xai|grok-2-image')
})
})
describe('Advanced features', () => {
it('should support batch image generation with maxImagesPerCall', async () => {
await executor.generateImage({ model: 'dall-e-3', prompt: 'A test image', n: 10, maxImagesPerCall: 5 })
expect(aiGenerateImage).toHaveBeenCalledWith({
model: mockImageModel,
prompt: 'A test image',
n: 10,
maxImagesPerCall: 5
})
})
it('should support retries with maxRetries', async () => {
await executor.generateImage({ model: 'dall-e-3', prompt: 'A test image', maxRetries: 3 })
expect(aiGenerateImage).toHaveBeenCalledWith({
model: mockImageModel,
prompt: 'A test image',
maxRetries: 3
})
})
it('should handle warnings from the model', async () => {
const resultWithWarnings = {
...mockGenerateImageResult,
warnings: [
{
type: 'unsupported-setting',
message: 'Size parameter not supported for this model'
}
]
}
vi.mocked(aiGenerateImage).mockResolvedValue(resultWithWarnings)
const result = await executor.generateImage({
model: 'dall-e-3',
prompt: 'A test image',
size: '2048x2048' // Unsupported size
})
expect(result.warnings).toHaveLength(1)
expect(result.warnings[0].type).toBe('unsupported-setting')
})
it('should provide access to provider metadata', async () => {
const result = await executor.generateImage({ model: 'dall-e-3', prompt: 'A test image' })
expect(result.providerMetadata).toBeDefined()
expect(result.providerMetadata.openai).toBeDefined()
})
it('should provide response metadata', async () => {
const resultWithMetadata = {
...mockGenerateImageResult,
responses: [
{
timestamp: new Date(),
modelId: 'dall-e-3',
headers: { 'x-request-id': 'test-123' }
}
]
}
vi.mocked(aiGenerateImage).mockResolvedValue(resultWithMetadata)
const result = await executor.generateImage({ model: 'dall-e-3', prompt: 'A test image' })
expect(result.responses).toHaveLength(1)
expect(result.responses[0].modelId).toBe('dall-e-3')
expect(result.responses[0].headers).toEqual({ 'x-request-id': 'test-123' })
})
})
})

View File

@@ -1,38 +0,0 @@
/**
* Error classes for runtime operations
*/
/**
* Error thrown when image generation fails
*/
export class ImageGenerationError extends Error {
constructor(
message: string,
public providerId?: string,
public modelId?: string,
public cause?: Error
) {
super(message)
this.name = 'ImageGenerationError'
// Maintain proper stack trace (for V8 engines)
if (Error.captureStackTrace) {
Error.captureStackTrace(this, ImageGenerationError)
}
}
}
/**
* Error thrown when model resolution fails during image generation
*/
export class ImageModelResolutionError extends ImageGenerationError {
constructor(modelId: string, providerId?: string, cause?: Error) {
super(
`Failed to resolve image model: ${modelId}${providerId ? ` for provider: ${providerId}` : ''}`,
providerId,
modelId,
cause
)
this.name = 'ImageModelResolutionError'
}
}

View File

@@ -1,310 +0,0 @@
/**
* 运行时执行器
* 专注于插件化的AI调用处理
*/
import { ImageModelV2, LanguageModelV2, LanguageModelV2Middleware } from '@ai-sdk/provider'
import {
experimental_generateImage as _generateImage,
generateObject as _generateObject,
generateText as _generateText,
LanguageModel,
streamObject as _streamObject,
streamText as _streamText
} from 'ai'
import { globalModelResolver } from '../models'
import { type ModelConfig } from '../models/types'
import { type AiPlugin, type AiRequestContext, definePlugin } from '../plugins'
import { type ProviderId } from '../providers'
import { ImageGenerationError, ImageModelResolutionError } from './errors'
import { PluginEngine } from './pluginEngine'
import type {
generateImageParams,
generateObjectParams,
generateTextParams,
RuntimeConfig,
streamObjectParams,
streamTextParams
} from './types'
export class RuntimeExecutor<T extends ProviderId = ProviderId> {
public pluginEngine: PluginEngine<T>
// private options: ProviderSettingsMap[T]
private config: RuntimeConfig<T>
constructor(config: RuntimeConfig<T>) {
// if (!isProviderSupported(config.providerId)) {
// throw new Error(`Unsupported provider: ${config.providerId}`)
// }
// 存储options供后续使用
// this.options = config.options
this.config = config
// 创建插件客户端
this.pluginEngine = new PluginEngine(config.providerId, config.plugins || [])
}
private createResolveModelPlugin(middlewares?: LanguageModelV2Middleware[]) {
return definePlugin({
name: '_internal_resolveModel',
enforce: 'post',
resolveModel: async (modelId: string) => {
// 注意extraModelConfig 暂时不支持,已在新架构中移除
return await this.resolveModel(modelId, middlewares)
}
})
}
private createResolveImageModelPlugin() {
return definePlugin({
name: '_internal_resolveImageModel',
enforce: 'post',
resolveModel: async (modelId: string) => {
return await this.resolveImageModel(modelId)
}
})
}
private createConfigureContextPlugin() {
return definePlugin({
name: '_internal_configureContext',
configureContext: async (context: AiRequestContext) => {
context.executor = this
}
})
}
// === 高阶重载:直接使用模型 ===
/**
* 流式文本生成
*/
async streamText(
params: streamTextParams,
options?: {
middlewares?: LanguageModelV2Middleware[]
}
): Promise<ReturnType<typeof _streamText>> {
const { model } = params
// 根据 model 类型决定插件配置
if (typeof model === 'string') {
this.pluginEngine.usePlugins([
this.createResolveModelPlugin(options?.middlewares),
this.createConfigureContextPlugin()
])
} else {
this.pluginEngine.usePlugins([this.createConfigureContextPlugin()])
}
return this.pluginEngine.executeStreamWithPlugins(
'streamText',
params,
(resolvedModel, transformedParams, streamTransforms) => {
const experimental_transform =
params?.experimental_transform ?? (streamTransforms.length > 0 ? streamTransforms : undefined)
return _streamText({
...transformedParams,
model: resolvedModel,
experimental_transform
})
}
)
}
// === 其他方法的重载 ===
/**
* 生成文本
*/
async generateText(
params: generateTextParams,
options?: {
middlewares?: LanguageModelV2Middleware[]
}
): Promise<ReturnType<typeof _generateText>> {
const { model } = params
// 根据 model 类型决定插件配置
if (typeof model === 'string') {
this.pluginEngine.usePlugins([
this.createResolveModelPlugin(options?.middlewares),
this.createConfigureContextPlugin()
])
} else {
this.pluginEngine.usePlugins([this.createConfigureContextPlugin()])
}
return this.pluginEngine.executeWithPlugins<Parameters<typeof _generateText>[0], ReturnType<typeof _generateText>>(
'generateText',
params,
(resolvedModel, transformedParams) => _generateText({ ...transformedParams, model: resolvedModel })
)
}
/**
* 生成结构化对象
*/
async generateObject(
params: generateObjectParams,
options?: {
middlewares?: LanguageModelV2Middleware[]
}
): Promise<ReturnType<typeof _generateObject>> {
const { model } = params
// 根据 model 类型决定插件配置
if (typeof model === 'string') {
this.pluginEngine.usePlugins([
this.createResolveModelPlugin(options?.middlewares),
this.createConfigureContextPlugin()
])
} else {
this.pluginEngine.usePlugins([this.createConfigureContextPlugin()])
}
return this.pluginEngine.executeWithPlugins<generateObjectParams, ReturnType<typeof _generateObject>>(
'generateObject',
params,
async (resolvedModel, transformedParams) => _generateObject({ ...transformedParams, model: resolvedModel })
)
}
/**
* 流式生成结构化对象
*/
streamObject(
params: streamObjectParams,
options?: {
middlewares?: LanguageModelV2Middleware[]
}
): Promise<ReturnType<typeof _streamObject>> {
const { model } = params
// 根据 model 类型决定插件配置
if (typeof model === 'string') {
this.pluginEngine.usePlugins([
this.createResolveModelPlugin(options?.middlewares),
this.createConfigureContextPlugin()
])
} else {
this.pluginEngine.usePlugins([this.createConfigureContextPlugin()])
}
return this.pluginEngine.executeStreamWithPlugins('streamObject', params, (resolvedModel, transformedParams) =>
_streamObject({ ...transformedParams, model: resolvedModel })
)
}
/**
* 生成图像
*/
generateImage(params: generateImageParams): Promise<ReturnType<typeof _generateImage>> {
try {
const { model } = params
// 根据 model 类型决定插件配置
if (typeof model === 'string') {
this.pluginEngine.usePlugins([this.createResolveImageModelPlugin(), this.createConfigureContextPlugin()])
} else {
this.pluginEngine.usePlugins([this.createConfigureContextPlugin()])
}
return this.pluginEngine.executeImageWithPlugins('generateImage', params, (resolvedModel, transformedParams) =>
_generateImage({ ...transformedParams, model: resolvedModel })
)
} catch (error) {
if (error instanceof Error) {
const modelId = typeof params.model === 'string' ? params.model : params.model.modelId
throw new ImageGenerationError(
`Failed to generate image: ${error.message}`,
this.config.providerId,
modelId,
error
)
}
throw error
}
}
// === 辅助方法 ===
/**
* 解析模型:如果是字符串则创建模型,如果是模型则直接返回
*/
private async resolveModel(
modelOrId: LanguageModel,
middlewares?: LanguageModelV2Middleware[]
): Promise<LanguageModelV2> {
if (typeof modelOrId === 'string') {
// 🎯 字符串modelId使用新的ModelResolver解析传递完整参数
return await globalModelResolver.resolveLanguageModel(
modelOrId, // 支持 'gpt-4' 和 'aihubmix:anthropic:claude-3.5-sonnet'
this.config.providerId, // fallback provider
this.config.providerSettings, // provider options
middlewares // 中间件数组
)
} else {
// 已经是模型,直接返回
return modelOrId
}
}
/**
* 解析图像模型:如果是字符串则创建图像模型,如果是模型则直接返回
*/
private async resolveImageModel(modelOrId: ImageModelV2 | string): Promise<ImageModelV2> {
try {
if (typeof modelOrId === 'string') {
// 字符串modelId使用新的ModelResolver解析
return await globalModelResolver.resolveImageModel(
modelOrId, // 支持 'dall-e-3' 和 'aihubmix:openai:dall-e-3'
this.config.providerId // fallback provider
)
} else {
// 已经是模型,直接返回
return modelOrId
}
} catch (error) {
throw new ImageModelResolutionError(
typeof modelOrId === 'string' ? modelOrId : modelOrId.modelId,
this.config.providerId,
error instanceof Error ? error : undefined
)
}
}
// === 静态工厂方法 ===
/**
* 创建执行器 - 支持已知provider的类型安全
*/
static create<T extends ProviderId>(
providerId: T,
options: ModelConfig<T>['providerSettings'],
plugins?: AiPlugin[]
): RuntimeExecutor<T> {
return new RuntimeExecutor({
providerId,
providerSettings: options,
plugins
})
}
/**
* 创建OpenAI Compatible执行器
*/
static createOpenAICompatible(
options: ModelConfig<'openai-compatible'>['providerSettings'],
plugins: AiPlugin[] = []
): RuntimeExecutor<'openai-compatible'> {
return new RuntimeExecutor({
providerId: 'openai-compatible',
providerSettings: options,
plugins
})
}
}

View File

@@ -1,117 +0,0 @@
/**
* Runtime 模块导出
* 专注于运行时插件化AI调用处理
*/
// 主要的运行时执行器
export { RuntimeExecutor } from './executor'
// 导出类型
export type { RuntimeConfig } from './types'
// === 便捷工厂函数 ===
import { LanguageModelV2Middleware } from '@ai-sdk/provider'
import { type AiPlugin } from '../plugins'
import { type ProviderId, type ProviderSettingsMap } from '../providers/types'
import { RuntimeExecutor } from './executor'
/**
* 创建运行时执行器 - 支持类型安全的已知provider
*/
export function createExecutor<T extends ProviderId>(
providerId: T,
options: ProviderSettingsMap[T] & { mode?: 'chat' | 'responses' },
plugins?: AiPlugin[]
): RuntimeExecutor<T> {
return RuntimeExecutor.create(providerId, options, plugins)
}
/**
* 创建OpenAI Compatible执行器
*/
export function createOpenAICompatibleExecutor(
options: ProviderSettingsMap['openai-compatible'] & { mode?: 'chat' | 'responses' },
plugins: AiPlugin[] = []
): RuntimeExecutor<'openai-compatible'> {
return RuntimeExecutor.createOpenAICompatible(options, plugins)
}
// === 直接调用API无需创建executor实例===
/**
* 直接流式文本生成 - 支持middlewares
*/
export async function streamText<T extends ProviderId>(
providerId: T,
options: ProviderSettingsMap[T] & { mode?: 'chat' | 'responses' },
params: Parameters<RuntimeExecutor<T>['streamText']>[0],
plugins?: AiPlugin[],
middlewares?: LanguageModelV2Middleware[]
): Promise<ReturnType<RuntimeExecutor<T>['streamText']>> {
const executor = createExecutor(providerId, options, plugins)
return executor.streamText(params, { middlewares })
}
/**
* 直接生成文本 - 支持middlewares
*/
export async function generateText<T extends ProviderId>(
providerId: T,
options: ProviderSettingsMap[T] & { mode?: 'chat' | 'responses' },
params: Parameters<RuntimeExecutor<T>['generateText']>[0],
plugins?: AiPlugin[],
middlewares?: LanguageModelV2Middleware[]
): Promise<ReturnType<RuntimeExecutor<T>['generateText']>> {
const executor = createExecutor(providerId, options, plugins)
return executor.generateText(params, { middlewares })
}
/**
* 直接生成结构化对象 - 支持middlewares
*/
export async function generateObject<T extends ProviderId>(
providerId: T,
options: ProviderSettingsMap[T] & { mode?: 'chat' | 'responses' },
params: Parameters<RuntimeExecutor<T>['generateObject']>[0],
plugins?: AiPlugin[],
middlewares?: LanguageModelV2Middleware[]
): Promise<ReturnType<RuntimeExecutor<T>['generateObject']>> {
const executor = createExecutor(providerId, options, plugins)
return executor.generateObject(params, { middlewares })
}
/**
* 直接流式生成结构化对象 - 支持middlewares
*/
export async function streamObject<T extends ProviderId>(
providerId: T,
options: ProviderSettingsMap[T] & { mode?: 'chat' | 'responses' },
params: Parameters<RuntimeExecutor<T>['streamObject']>[0],
plugins?: AiPlugin[],
middlewares?: LanguageModelV2Middleware[]
): Promise<ReturnType<RuntimeExecutor<T>['streamObject']>> {
const executor = createExecutor(providerId, options, plugins)
return executor.streamObject(params, { middlewares })
}
/**
* 直接生成图像 - 支持middlewares
*/
export async function generateImage<T extends ProviderId>(
providerId: T,
options: ProviderSettingsMap[T] & { mode?: 'chat' | 'responses' },
params: Parameters<RuntimeExecutor<T>['generateImage']>[0],
plugins?: AiPlugin[]
): Promise<ReturnType<RuntimeExecutor<T>['generateImage']>> {
const executor = createExecutor(providerId, options, plugins)
return executor.generateImage(params)
}
// === Agent 功能预留 ===
// 未来将在 ../agents/ 文件夹中添加:
// - AgentExecutor.ts
// - WorkflowManager.ts
// - ConversationManager.ts
// 并在此处导出相关API

View File

@@ -1,296 +0,0 @@
/* eslint-disable @eslint-react/naming-convention/context-name */
import { ImageModelV2 } from '@ai-sdk/provider'
import { experimental_generateImage, generateObject, generateText, LanguageModel, streamObject, streamText } from 'ai'
import { type AiPlugin, createContext, PluginManager } from '../plugins'
import { type ProviderId } from '../providers/types'
/**
* 插件增强的 AI 客户端
* 专注于插件处理不暴露用户API
*/
export class PluginEngine<T extends ProviderId = ProviderId> {
private pluginManager: PluginManager
constructor(
private readonly providerId: T,
// private readonly options: ProviderSettingsMap[T],
plugins: AiPlugin[] = []
) {
this.pluginManager = new PluginManager(plugins)
}
/**
* 添加插件
*/
use(plugin: AiPlugin): this {
this.pluginManager.use(plugin)
return this
}
/**
* 批量添加插件
*/
usePlugins(plugins: AiPlugin[]): this {
plugins.forEach((plugin) => this.use(plugin))
return this
}
/**
* 移除插件
*/
removePlugin(pluginName: string): this {
this.pluginManager.remove(pluginName)
return this
}
/**
* 获取插件统计
*/
getPluginStats() {
return this.pluginManager.getStats()
}
/**
* 获取所有插件
*/
getPlugins() {
return this.pluginManager.getPlugins()
}
/**
* 执行带插件的操作(非流式)
* 提供给AiExecutor使用
*/
async executeWithPlugins<
TParams extends Parameters<typeof generateText | typeof generateObject>[0],
TResult extends ReturnType<typeof generateText | typeof generateObject>
>(
methodName: string,
params: TParams,
executor: (model: LanguageModel, transformedParams: TParams) => TResult,
_context?: ReturnType<typeof createContext>
): Promise<TResult> {
// 统一处理模型解析
let resolvedModel: LanguageModel | undefined
let modelId: string
const { model } = params
if (typeof model === 'string') {
// 字符串:需要通过插件解析
modelId = model
} else {
// 模型对象:直接使用
resolvedModel = model
modelId = model.modelId
}
// 使用正确的createContext创建请求上下文
const context = _context ? _context : createContext(this.providerId, model, params)
// 🔥 为上下文添加递归调用能力
context.recursiveCall = async (newParams: any): Promise<TResult> => {
// 递归调用自身,重新走完整的插件流程
context.isRecursiveCall = true
const result = await this.executeWithPlugins(methodName, newParams, executor, context)
context.isRecursiveCall = false
return result
}
try {
// 0. 配置上下文
await this.pluginManager.executeConfigureContext(context)
// 1. 触发请求开始事件
await this.pluginManager.executeParallel('onRequestStart', context)
// 2. 解析模型(如果是字符串)
if (typeof model === 'string') {
const resolved = await this.pluginManager.executeFirst<LanguageModel>('resolveModel', modelId, context)
if (!resolved) {
throw new Error(`Failed to resolve model: ${modelId}`)
}
resolvedModel = resolved
}
if (!resolvedModel) {
throw new Error(`Model resolution failed: no model available`)
}
// 3. 转换请求参数
const transformedParams = await this.pluginManager.executeSequential('transformParams', params, context)
// 4. 执行具体的 API 调用
const result = await executor(resolvedModel, transformedParams)
// 5. 转换结果(对于非流式调用)
const transformedResult = await this.pluginManager.executeSequential('transformResult', result, context)
// 6. 触发完成事件
await this.pluginManager.executeParallel('onRequestEnd', context, transformedResult)
return transformedResult
} catch (error) {
// 7. 触发错误事件
await this.pluginManager.executeParallel('onError', context, undefined, error as Error)
throw error
}
}
/**
* 执行带插件的图像生成操作
* 提供给AiExecutor使用
*/
async executeImageWithPlugins<
TParams extends Omit<Parameters<typeof experimental_generateImage>[0], 'model'> & { model: string | ImageModelV2 },
TResult extends ReturnType<typeof experimental_generateImage>
>(
methodName: string,
params: TParams,
executor: (model: ImageModelV2, transformedParams: TParams) => TResult,
_context?: ReturnType<typeof createContext>
): Promise<TResult> {
// 统一处理模型解析
let resolvedModel: ImageModelV2 | undefined
let modelId: string
const { model } = params
if (typeof model === 'string') {
// 字符串:需要通过插件解析
modelId = model
} else {
// 模型对象:直接使用
resolvedModel = model
modelId = model.modelId
}
// 使用正确的createContext创建请求上下文
const context = _context ? _context : createContext(this.providerId, model, params)
// 🔥 为上下文添加递归调用能力
context.recursiveCall = async (newParams: any): Promise<TResult> => {
// 递归调用自身,重新走完整的插件流程
context.isRecursiveCall = true
const result = await this.executeImageWithPlugins(methodName, newParams, executor, context)
context.isRecursiveCall = false
return result
}
try {
// 0. 配置上下文
await this.pluginManager.executeConfigureContext(context)
// 1. 触发请求开始事件
await this.pluginManager.executeParallel('onRequestStart', context)
// 2. 解析模型(如果是字符串)
if (typeof model === 'string') {
const resolved = await this.pluginManager.executeFirst<ImageModelV2>('resolveModel', modelId, context)
if (!resolved) {
throw new Error(`Failed to resolve image model: ${modelId}`)
}
resolvedModel = resolved
}
if (!resolvedModel) {
throw new Error(`Image model resolution failed: no model available`)
}
// 3. 转换请求参数
const transformedParams = await this.pluginManager.executeSequential('transformParams', params, context)
// 4. 执行具体的 API 调用
const result = await executor(resolvedModel, transformedParams)
// 5. 转换结果
const transformedResult = await this.pluginManager.executeSequential('transformResult', result, context)
// 6. 触发完成事件
await this.pluginManager.executeParallel('onRequestEnd', context, transformedResult)
return transformedResult
} catch (error) {
// 7. 触发错误事件
await this.pluginManager.executeParallel('onError', context, undefined, error as Error)
throw error
}
}
/**
* 执行流式调用的通用逻辑(支持流转换器)
* 提供给AiExecutor使用
*/
async executeStreamWithPlugins<
TParams extends Parameters<typeof streamText | typeof streamObject>[0],
TResult extends ReturnType<typeof streamText | typeof streamObject>
>(
methodName: string,
params: TParams,
executor: (model: LanguageModel, transformedParams: TParams, streamTransforms: any[]) => TResult,
_context?: ReturnType<typeof createContext>
): Promise<TResult> {
// 统一处理模型解析
let resolvedModel: LanguageModel | undefined
let modelId: string
const { model } = params
if (typeof model === 'string') {
// 字符串:需要通过插件解析
modelId = model
} else {
// 模型对象:直接使用
resolvedModel = model
modelId = model.modelId
}
// 创建请求上下文
const context = _context ? _context : createContext(this.providerId, model, params)
// 🔥 为上下文添加递归调用能力
context.recursiveCall = async (newParams: any): Promise<TResult> => {
// 递归调用自身,重新走完整的插件流程
context.isRecursiveCall = true
const result = await this.executeStreamWithPlugins(methodName, newParams, executor, context)
context.isRecursiveCall = false
return result
}
try {
// 0. 配置上下文
await this.pluginManager.executeConfigureContext(context)
// 1. 触发请求开始事件
await this.pluginManager.executeParallel('onRequestStart', context)
// 2. 解析模型(如果是字符串)
if (typeof model === 'string') {
const resolved = await this.pluginManager.executeFirst<LanguageModel>('resolveModel', modelId, context)
if (!resolved) {
throw new Error(`Failed to resolve model: ${modelId}`)
}
resolvedModel = resolved
}
if (!resolvedModel) {
throw new Error(`Model resolution failed: no model available`)
}
// 3. 转换请求参数
const transformedParams = await this.pluginManager.executeSequential('transformParams', params, context)
// 4. 收集流转换器
const streamTransforms = this.pluginManager.collectStreamTransforms(transformedParams, context)
// 5. 执行流式 API 调用
const result = await executor(resolvedModel, transformedParams, streamTransforms)
const transformedResult = await this.pluginManager.executeSequential('transformResult', result, context)
// 6. 触发完成事件(注意:对于流式调用,这里触发的是开始流式响应的事件)
await this.pluginManager.executeParallel('onRequestEnd', context, transformedResult)
return transformedResult
} catch (error) {
// 7. 触发错误事件
await this.pluginManager.executeParallel('onError', context, undefined, error as Error)
throw error
}
}
}

View File

@@ -1,26 +0,0 @@
/**
* Runtime 层类型定义
*/
import { ImageModelV2 } from '@ai-sdk/provider'
import { experimental_generateImage, generateObject, generateText, streamObject, streamText } from 'ai'
import { type ModelConfig } from '../models/types'
import { type AiPlugin } from '../plugins'
import { type ProviderId } from '../providers/types'
/**
* 运行时执行器配置
*/
export interface RuntimeConfig<T extends ProviderId = ProviderId> {
providerId: T
providerSettings: ModelConfig<T>['providerSettings'] & { mode?: 'chat' | 'responses' }
plugins?: AiPlugin[]
}
export type generateImageParams = Omit<Parameters<typeof experimental_generateImage>[0], 'model'> & {
model: string | ImageModelV2
}
export type generateObjectParams = Parameters<typeof generateObject>[0]
export type generateTextParams = Parameters<typeof generateText>[0]
export type streamObjectParams = Parameters<typeof streamObject>[0]
export type streamTextParams = Parameters<typeof streamText>[0]

Some files were not shown because too many files have changed in this diff Show More