mirror of
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refactor: restructure AI Core architecture and enhance client functionality
- Updated the AI Core documentation to reflect the new architecture and design principles, emphasizing modularity and type safety. - Refactored the client structure by removing obsolete files and consolidating client creation logic into a more streamlined format. - Introduced a new core module for managing execution and middleware, improving the overall organization of the codebase. - Enhanced the orchestration layer to provide a clearer API for users, integrating the creation and execution processes more effectively. - Added comprehensive type definitions and utility functions for better type safety and usability across the SDK.
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@ -1,13 +1,14 @@
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# Cherry Studio AI Core 基于 Vercel AI SDK 的技术架构
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# AI Core 基于 Vercel AI SDK 的技术架构
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## 1. 架构设计理念
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### 1.1 设计目标
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- **分层架构**：orchestration（编排层）→ core（核心层），职责分离
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- **统一接口**：使用 Vercel AI SDK 统一不同 AI Provider 的接口差异
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- **动态导入**：通过动态导入实现按需加载，减少打包体积
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- **最小包装**：直接使用 AI SDK 的类型和接口，避免重复定义
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- **插件系统**：基于钩子的插件架构，支持请求全生命周期扩展
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- **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
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- **类型安全**：利用 TypeScript 和 AI SDK 的类型系统确保类型安全
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- **轻量级**：专注核心功能，保持包的轻量和高效
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- **包级独立**：作为独立包管理，便于复用和维护
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@ -15,30 +16,57 @@
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### 1.2 核心优势
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- **标准化**：AI SDK 提供统一的模型接口，减少适配工作
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- **简化维护**：废弃复杂的 XxxApiClient，统一为工厂函数模式
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- **分层设计**：清晰的职责分离，便于维护和扩展
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- **更好的开发体验**：完整的 TypeScript 支持和丰富的生态系统
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- **性能优化**：AI SDK 内置优化和最佳实践
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- **模块化设计**：独立包结构，支持跨项目复用
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- **可扩展插件**：基于钩子的插件系统，支持灵活的功能扩展和流转换
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- **可扩展插件**：通用的流转换和参数处理插件系统
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## 2. 整体架构图
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```mermaid
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graph TD
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subgraph "Cherry Studio 主应用"
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subgraph "用户应用 (如 Cherry Studio)"
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UI["用户界面"]
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Components["React 组件"]
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Components["应用组件"]
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end
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subgraph "packages/aiCore (AI Core 包)"
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ApiClientFactory["ApiClientFactory (工厂类)"]
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UniversalClient["UniversalAiSdkClient (统一客户端)"]
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ProviderRegistry["Provider 注册表"]
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PluginManager["插件管理器"]
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end
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subgraph "Orchestration Layer (编排层)"
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OrchAPI["api.ts (用户API)"]
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OrchTypes["types.ts (编排类型)"]
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end
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subgraph "动态导入层"
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DynamicImport["动态导入"]
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subgraph "Core Layer (核心层)"
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subgraph "Creation (创建层)"
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ConfigManager["ConfigManager (配置管理)"]
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ModelCreator["ModelCreator (模型创建)"]
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ProviderCreator["ProviderCreator (提供商创建)"]
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end
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subgraph "Execution (执行层)"
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AiExecutor["AiExecutor (执行器)"]
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end
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subgraph "Clients (客户端层)"
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PluginClient["PluginEnabledAiClient (插件客户端)"]
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end
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subgraph "Middleware (中间件)"
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MiddlewareManager["MiddlewareManager (中间件管理)"]
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ModelWrapper["ModelWrapper (模型包装)"]
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end
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subgraph "Plugins (插件)"
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PluginManager["PluginManager (插件管理)"]
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StreamTransforms["Stream Transforms (流转换)"]
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end
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subgraph "Providers (提供商)"
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Registry["Provider Registry (注册表)"]
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Factory["Provider Factory (工厂)"]
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end
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end
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end
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subgraph "Vercel AI SDK"
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@ -50,61 +78,78 @@ graph TD
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Others["其他 19+ Providers"]
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end
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subgraph "插件生态"
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FirstHooks["First Hooks (resolveModel, loadTemplate)"]
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SequentialHooks["Sequential Hooks (transformParams, transformResult)"]
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ParallelHooks["Parallel Hooks (onRequestStart, onRequestEnd, onError)"]
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StreamHooks["Stream Hooks (transformStream)"]
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end
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UI --> OrchAPI
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Components --> OrchAPI
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OrchAPI --> AiExecutor
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AiExecutor --> PluginClient
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PluginClient --> PluginManager
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PluginClient --> ConfigManager
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ConfigManager --> ModelCreator
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ModelCreator --> ProviderCreator
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ModelCreator --> MiddlewareManager
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MiddlewareManager --> ModelWrapper
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ProviderCreator --> Registry
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Registry --> Factory
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Factory --> OpenAI
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Factory --> Anthropic
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Factory --> Google
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Factory --> XAI
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Factory --> Others
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UI --> ApiClientFactory
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Components --> ApiClientFactory
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ApiClientFactory --> UniversalClient
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UniversalClient --> PluginManager
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PluginManager --> ProviderRegistry
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ProviderRegistry --> DynamicImport
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DynamicImport --> OpenAI
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DynamicImport --> Anthropic
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DynamicImport --> Google
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DynamicImport --> XAI
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DynamicImport --> Others
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UniversalClient --> AICore
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PluginClient --> AICore
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AICore --> streamText
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AICore --> generateText
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AICore --> streamObject
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AICore --> generateObject
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PluginManager --> FirstHooks
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PluginManager --> SequentialHooks
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PluginManager --> ParallelHooks
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PluginManager --> StreamHooks
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PluginManager --> StreamTransforms
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```
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## 3. 包结构设计
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### 3.1 包级文件结构（当前简化版 + 规划）
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### 3.1 当前架构文件结构
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```
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packages/aiCore/
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├── src/
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│ ├── providers/
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│ │ ├── registry.ts # Provider 注册表 ✅
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│ │ └── types.ts # 核心类型定义 ✅
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│ ├── clients/
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│ │ ├── UniversalAiSdkClient.ts # 统一AI SDK客户端 ✅
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│ │ └── ApiClientFactory.ts # 客户端工厂 ✅
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│ ├── middleware/ # 插件系统 ✅
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│ │ ├── types.ts # 插件类型定义 ✅
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│ │ ├── manager.ts # 插件管理器 ✅
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│ │ ├── examples/ # 示例插件 ✅
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│ │ │ ├── example-plugins.ts # 示例插件实现 ✅
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│ │ │ └── example-usage.ts # 使用示例 ✅
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│ │ ├── README.md # 插件系统文档 ✅
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│ │ └── index.ts # 插件模块入口 ✅
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│ ├── services/ # 高级服务 (规划中)
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│ │ ├── AiCoreService.ts # 统一服务入口
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│ │ ├── CompletionsService.ts # 文本生成服务
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│ │ ├── EmbeddingService.ts # 嵌入服务
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│ │ └── ImageService.ts # 图像生成服务
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│ ├── orchestration/ # 编排层 - 用户面向接口
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│ │ ├── api.ts # 主要API函数 ✅
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│ │ ├── types.ts # 编排类型定义 ✅
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│ │ └── index.ts # 编排层导出 ✅
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│ ├── core/ # 核心层 - 内部实现
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│ │ ├── creation/ # 创建层
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│ │ │ ├── types.ts # 创建类型定义 ✅
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│ │ │ ├── ConfigManager.ts # 配置管理器 ✅
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│ │ │ ├── ModelCreator.ts # 模型创建器 ✅
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│ │ │ ├── ProviderCreator.ts # 提供商创建器 ✅
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│ │ │ └── index.ts # 创建层导出 ✅
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│ │ ├── execution/ # 执行层
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│ │ │ ├── types.ts # 执行类型定义 ✅
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│ │ │ ├── AiExecutor.ts # AI执行器 ✅
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│ │ │ └── index.ts # 执行层导出 ✅
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│ │ ├── clients/ # 客户端层
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│ │ │ ├── PluginEnabledAiClient.ts # 插件客户端 ✅
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│ │ │ └── index.ts # 客户端导出 ✅
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│ │ ├── middleware/ # 中间件系统
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│ │ │ ├── types.ts # 中间件类型 ✅
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│ │ │ ├── MiddlewareManager.ts # 中间件管理器 ✅
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│ │ │ ├── ModelWrapper.ts # 模型包装器 ✅
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│ │ │ └── index.ts # 中间件导出 ✅
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│ │ ├── plugins/ # 插件系统
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│ │ │ ├── types.ts # 插件类型定义 ✅
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│ │ │ ├── manager.ts # 插件管理器 ✅
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│ │ │ ├── examples/ # 示例插件 ✅
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│ │ │ │ ├── example-plugins.ts
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│ │ │ │ └── example-usage.ts
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│ │ │ ├── README.md # 插件文档 ✅
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│ │ │ └── index.ts # 插件导出 ✅
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│ │ ├── providers/ # 提供商管理
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│ │ │ ├── registry.ts # 提供商注册表 ✅
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│ │ │ ├── factory.ts # 提供商工厂 ✅
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│ │ │ ├── types.ts # 提供商类型 ✅
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│ │ │ └── utils.ts # 工具函数 ✅
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│ │ └── index.ts # 核心层导出 ✅
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│ ├── types.ts # 全局类型定义 ✅
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│ └── index.ts # 包主入口文件 ✅
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├── package.json # 包配置文件 ✅
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├── tsconfig.json # TypeScript 配置 ✅
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@ -112,511 +157,348 @@ packages/aiCore/
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└── AI_SDK_ARCHITECTURE.md # 本文档 ✅
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```
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**图例：**
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## 4. 架构分层详解
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- ✅ 已实现
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- 规划中：设计完成，待实现
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### 4.1 Orchestration Layer (编排层)
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## 4. 核心组件详解
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**职责**：面向用户的主要API接口，提供简洁的使用体验
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### 4.1 Provider 注册表 (`providers/registry.ts`)
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**核心文件**：
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统一管理所有 AI Provider 的注册和动态导入。
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- `api.ts`: 主要API函数 (`streamText`, `generateText`, `streamObject`, `generateObject`)
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- `types.ts`: 编排配置类型定义
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**主要功能：**
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**设计特点**：
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- 动态导入 AI SDK providers
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- 提供统一的 Provider 创建接口
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- 支持 19+ 官方 AI SDK providers
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- 类型安全的 Provider 配置
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- 支持两种使用方式：配置模式和直接AI SDK模式
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- 统一的函数重载设计
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- 自动处理执行器创建和调用
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**核心 API：**
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**核心API**：
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```typescript
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export interface ProviderConfig {
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id: string
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name: string
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import: () => Promise<any>
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creatorFunctionName: string
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}
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// 配置模式 - 推荐使用
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export async function streamText<T extends ProviderId>(
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config: OrchestrationConfig<T>,
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modelId: string,
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params: StreamTextParams
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): Promise<ReturnType<typeof aiStreamText>>
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export class AiProviderRegistry {
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getProvider(id: string): ProviderConfig | undefined
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getAllProviders(): ProviderConfig[]
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isSupported(id: string): boolean
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registerProvider(config: ProviderConfig): void
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// 直接AI SDK模式 - 兼容原生使用
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export async function streamText(params: Parameters<typeof aiStreamText>[0]): Promise<ReturnType<typeof aiStreamText>>
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```
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### 4.2 Core Layer (核心层)
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#### 4.2.1 Creation Layer (创建层)
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**职责**：负责配置解析、模型创建和提供商管理
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**核心组件**：
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- `ConfigManager`: 配置解析和中间件收集
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- `ModelCreator`: 高级模型创建逻辑
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- `ProviderCreator`: 底层提供商导入和模型创建
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**关键功能**：
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```typescript
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// 配置管理
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export function resolveConfig(
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providerId: ProviderId,
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modelId: string,
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userOptions: ProviderSettingsMap[ProviderId],
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plugins: AiPlugin[] = []
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): ResolvedConfig
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// 模型创建
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export async function createModel(
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providerId: ProviderId,
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modelId: string,
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userOptions: ProviderSettingsMap[ProviderId],
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plugins: AiPlugin[] = []
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): Promise<LanguageModel>
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```
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#### 4.2.2 Execution Layer (执行层)
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**职责**：AI执行引擎，封装插件处理逻辑
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**核心组件**：
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- `AiExecutor`: 主要执行器类
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**设计特点**：
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- 构造时确定插件配置，运行时不可变更
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- 内部使用 `PluginEnabledAiClient` 处理插件
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- 提供类型安全的API接口
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**核心API**：
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```typescript
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export class AiExecutor<T extends ProviderId = any> {
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static create<T extends ProviderId>(
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providerId: T,
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options: ProviderSettingsMap[T],
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plugins: AiPlugin[] = []
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): AiExecutor<T>
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async streamText(modelId: string, params: StreamTextParams): Promise<StreamTextResult<any>>
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async generateText(modelId: string, params: GenerateTextParams): Promise<GenerateTextResult<any>>
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async streamObject(modelId: string, params: StreamObjectParams): Promise<StreamObjectResult<any>>
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async generateObject(modelId: string, params: GenerateObjectParams): Promise<GenerateObjectResult<any>>
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}
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```
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**支持的 Providers：**
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#### 4.2.3 Clients Layer (客户端层)
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**职责**：插件处理，连接插件系统和AI SDK
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**核心组件**：
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- `PluginEnabledAiClient`: 处理插件执行和AI SDK调用
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**设计特点**：
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- 使用 core/creation 层创建模型
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- 区分 streaming 和 non-streaming 插件处理
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- 支持 `streamText` 的流转换和其他方法的常规插件处理
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#### 4.2.4 Middleware Layer (中间件层)
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**职责**：AI SDK原生中间件支持
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**核心组件**：
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- `MiddlewareManager`: 中间件管理 (函数式)
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- `ModelWrapper`: 模型包装器 (函数式)
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**设计哲学**：
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- 使用函数而非类，简化设计
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- 直接使用AI SDK的 `wrapLanguageModel`
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- 与插件系统分离，职责明确
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#### 4.2.5 Plugins Layer (插件层)
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**职责**：特定的插件功能
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**核心组件**：
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||||
|
||||
- `PluginManager`: 插件管理器
|
||||
- 流转换收集：`collectStreamTransforms`
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||||
|
||||
**设计特点**：
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||||
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||||
- 支持流转换 (`experimental_transform`)
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- 与AI SDK中间件分离
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- 专注于特定需求
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#### 4.2.6 Providers Layer (提供商层)
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**职责**：AI Provider注册表和动态导入
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|
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**核心组件**：
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||||
|
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- `registry.ts`: 19+ Provider配置和类型
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- `factory.ts`: Provider配置工厂
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**支持的Providers**：
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- OpenAI, Anthropic, Google, XAI
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- Azure OpenAI, Amazon Bedrock, Google Vertex
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- Groq, Together.ai, Fireworks, DeepSeek
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- Cerebras, DeepInfra, Replicate, Perplexity
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- Cohere, Fal AI, Vercel (19+ providers)
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|
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### 4.2 统一AI SDK客户端 (`clients/UniversalAiSdkClient.ts`)
|
||||
|
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将不同 AI providers 包装为统一接口。
|
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|
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**主要功能：**
|
||||
|
||||
- 异步初始化和动态加载
|
||||
- 统一的 stream() 和 generate() 方法
|
||||
- 直接使用 AI SDK 的 streamText() 和 generateText()
|
||||
- 配置验证和错误处理
|
||||
|
||||
**核心 API：**
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||||
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```typescript
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export class UniversalAiSdkClient {
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async initialize(): Promise<void>
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isInitialized(): boolean
|
||||
async stream(request: any): Promise<any>
|
||||
async generate(request: any): Promise<any>
|
||||
validateConfig(): boolean
|
||||
getProviderInfo(): { id: string; name: string; isInitialized: boolean }
|
||||
}
|
||||
```
|
||||
|
||||
### 4.3 客户端工厂 (`clients/ApiClientFactory.ts`)
|
||||
|
||||
统一创建和管理 AI SDK 客户端。
|
||||
|
||||
**主要功能：**
|
||||
|
||||
- 统一的客户端创建接口
|
||||
- 智能缓存和复用机制
|
||||
- 批量创建和健康检查
|
||||
- 错误处理和重试
|
||||
|
||||
**核心 API：**
|
||||
|
||||
```typescript
|
||||
export class ApiClientFactory {
|
||||
static async createAiSdkClient(providerId: string, options: any): Promise<UniversalAiSdkClient>
|
||||
static getCachedClient(providerId: string, options: any): UniversalAiSdkClient | undefined
|
||||
static clearCache(): void
|
||||
static async healthCheck(): Promise<HealthCheckResult>
|
||||
static getSupportedProviders(): ProviderInfo[]
|
||||
}
|
||||
```
|
||||
|
||||
### 4.4 钩子风格插件系统 ✅
|
||||
|
||||
基于钩子机制的插件架构设计，提供灵活的扩展系统。
|
||||
|
||||
**钩子类型：**
|
||||
|
||||
1. **First Hooks**：执行到第一个有效结果就停止
|
||||
2. **Sequential Hooks**：按序链式执行，可变换数据
|
||||
3. **Parallel Hooks**：并发执行，用于副作用
|
||||
4. **Stream Hooks**：流转换，直接传递给 AI SDK
|
||||
|
||||
**优先级系统：**
|
||||
|
||||
- `pre`：前置处理（-100 到 -1）
|
||||
- `normal`：标准处理（0 到 99）
|
||||
- `post`：后置处理（100 到 199）
|
||||
|
||||
**核心钩子：**
|
||||
|
||||
**First Hooks (第一个有效结果)：**
|
||||
|
||||
- `resolveModel`：模型解析，返回第一个匹配的模型
|
||||
- `loadTemplate`：模板加载，返回第一个找到的模板
|
||||
|
||||
**Sequential Hooks (链式变换)：**
|
||||
|
||||
- `transformParams`：参数转换，依次变换请求参数
|
||||
- `transformResult`：结果转换，依次变换响应结果
|
||||
|
||||
**Parallel Hooks (并发副作用)：**
|
||||
|
||||
- `onRequestStart`：请求开始时触发
|
||||
- `onRequestEnd`：请求结束时触发
|
||||
- `onError`：错误发生时触发
|
||||
|
||||
**Stream Hooks (流转换)：**
|
||||
|
||||
- `transformStream`：流转换，返回 AI SDK 转换函数
|
||||
|
||||
**插件 API 设计：**
|
||||
|
||||
```typescript
|
||||
export interface Plugin {
|
||||
name: string
|
||||
enforce?: 'pre' | 'normal' | 'post'
|
||||
|
||||
// First hooks - 执行到第一个有效结果
|
||||
resolveModel?(params: ResolveModelParams): Promise<string | null>
|
||||
loadTemplate?(params: LoadTemplateParams): Promise<Template | null>
|
||||
|
||||
// Sequential hooks - 链式变换
|
||||
transformParams?(params: any, context: PluginContext): Promise<any>
|
||||
transformResult?(result: any, context: PluginContext): Promise<any>
|
||||
|
||||
// Parallel hooks - 并发副作用
|
||||
onRequestStart?(context: PluginContext): Promise<void>
|
||||
onRequestEnd?(context: PluginContext): Promise<void>
|
||||
onError?(error: Error, context: PluginContext): Promise<void>
|
||||
|
||||
// Stream hooks - AI SDK 流转换
|
||||
transformStream?(context: PluginContext): Promise<(readable: ReadableStream) => ReadableStream>
|
||||
}
|
||||
|
||||
export interface PluginContext {
|
||||
request: any
|
||||
response?: any
|
||||
metadata: Record<string, any>
|
||||
provider: string
|
||||
model: string
|
||||
}
|
||||
|
||||
export class PluginManager {
|
||||
use(plugin: Plugin): this
|
||||
executeFirstHook<T>(hookName: string, ...args: any[]): Promise<T | null>
|
||||
executeSequentialHook<T>(hookName: string, initialValue: T, context: PluginContext): Promise<T>
|
||||
executeParallelHook(hookName: string, ...args: any[]): Promise<void>
|
||||
collectStreamTransforms(context: PluginContext): Promise<Array<(readable: ReadableStream) => ReadableStream>>
|
||||
}
|
||||
```
|
||||
|
||||
### 4.5 统一服务接口 (规划中)
|
||||
|
||||
作为包的主要对外接口，提供高级 AI 功能。
|
||||
|
||||
**服务方法：**
|
||||
|
||||
- `completions()`: 文本生成
|
||||
- `streamCompletions()`: 流式文本生成
|
||||
- `generateObject()`: 结构化数据生成
|
||||
- `generateImage()`: 图像生成
|
||||
- `embed()`: 文本嵌入
|
||||
|
||||
**API 设计：**
|
||||
|
||||
```typescript
|
||||
export class AiCoreService {
|
||||
constructor(middlewares?: Middleware[])
|
||||
|
||||
async completions(request: CompletionRequest): Promise<CompletionResponse>
|
||||
async streamCompletions(request: CompletionRequest): Promise<StreamCompletionResponse>
|
||||
async generateObject<T>(request: ObjectGenerationRequest): Promise<T>
|
||||
async generateImage(request: ImageGenerationRequest): Promise<ImageResponse>
|
||||
async embed(request: EmbeddingRequest): Promise<EmbeddingResponse>
|
||||
|
||||
use(middleware: Middleware): this
|
||||
configure(config: AiCoreConfig): this
|
||||
}
|
||||
```
|
||||
- 等19+ AI SDK官方支持的providers
|
||||
|
||||
## 5. 使用方式
|
||||
|
||||
### 5.1 多 Provider 支持
|
||||
### 5.1 推荐使用方式 (Orchestration API)
|
||||
|
||||
```typescript
|
||||
import { createAiSdkClient, AiCore } from '@cherrystudio/ai-core'
|
||||
import { streamText, generateText } from '@cherrystudio/ai-core'
|
||||
|
||||
// 检查支持的 providers
|
||||
const providers = AiCore.getSupportedProviders()
|
||||
console.log(`支持 ${providers.length} 个 AI providers`)
|
||||
|
||||
// 创建多个 provider 客户端
|
||||
const openai = await createAiSdkClient('openai', { apiKey: 'openai-key' })
|
||||
const anthropic = await createAiSdkClient('anthropic', { apiKey: 'anthropic-key' })
|
||||
const google = await createAiSdkClient('google', { apiKey: 'google-key' })
|
||||
const xai = await createAiSdkClient('xai', { apiKey: 'xai-key' })
|
||||
```
|
||||
|
||||
### 5.2 在 Cherry Studio 中集成
|
||||
|
||||
```typescript
|
||||
// 替换现有的 XxxApiClient
|
||||
// 之前：
|
||||
// const openaiClient = new OpenAIApiClient(config)
|
||||
// const anthropicClient = new AnthropicApiClient(config)
|
||||
|
||||
// 现在：
|
||||
import { createAiSdkClient } from '@cherrystudio/ai-core'
|
||||
|
||||
const createProviderClient = async (provider: CherryProvider) => {
|
||||
return await createAiSdkClient(provider.id, {
|
||||
apiKey: provider.apiKey,
|
||||
baseURL: provider.baseURL
|
||||
})
|
||||
}
|
||||
```
|
||||
|
||||
### 5.6 完整的工作流示例 (规划中)
|
||||
|
||||
```typescript
|
||||
import {
|
||||
createAiSdkClient,
|
||||
AiCoreService,
|
||||
MiddlewareChain,
|
||||
PreRequestMiddleware,
|
||||
StreamProcessingMiddleware,
|
||||
PostResponseMiddleware
|
||||
} from '@cherrystudio/ai-core'
|
||||
|
||||
// 创建完整的工作流
|
||||
const createEnhancedAiService = async () => {
|
||||
// 创建中间件链
|
||||
const middlewareChain = new MiddlewareChain()
|
||||
.use(
|
||||
new PreRequestMiddleware({
|
||||
validateApiKey: true,
|
||||
checkRateLimit: true
|
||||
})
|
||||
)
|
||||
.use(
|
||||
new StreamProcessingMiddleware({
|
||||
enableProgressTracking: true,
|
||||
chunkTransform: (chunk) => ({
|
||||
...chunk,
|
||||
timestamp: Date.now()
|
||||
})
|
||||
})
|
||||
)
|
||||
.use(
|
||||
new PostResponseMiddleware({
|
||||
saveToHistory: true,
|
||||
calculateMetrics: true
|
||||
})
|
||||
)
|
||||
|
||||
// 创建服务实例
|
||||
const service = new AiCoreService(middlewareChain.middlewares)
|
||||
|
||||
return service
|
||||
// 配置模式使用
|
||||
const config = {
|
||||
providerId: 'openai',
|
||||
options: { apiKey: 'your-api-key' },
|
||||
plugins: [thinkingPlugin, toolPlugin]
|
||||
}
|
||||
|
||||
// 使用增强服务
|
||||
const enhancedService = await createEnhancedAiService()
|
||||
// 流式文本生成
|
||||
const stream = await streamText(config, 'gpt-4', {
|
||||
messages: [{ role: 'user', content: 'Hello!' }]
|
||||
})
|
||||
|
||||
const response = await enhancedService.completions({
|
||||
provider: 'anthropic',
|
||||
model: 'claude-3-sonnet',
|
||||
messages: [{ role: 'user', content: 'Write a technical blog post about AI middleware' }],
|
||||
options: {
|
||||
temperature: 0.7,
|
||||
maxTokens: 2000
|
||||
},
|
||||
middleware: {
|
||||
// 中间件特定配置
|
||||
thinking: { recordSteps: true },
|
||||
cache: { enabled: true, ttl: 1800 },
|
||||
logging: { level: 'debug' }
|
||||
}
|
||||
// 普通文本生成
|
||||
const result = await generateText(config, 'gpt-4', {
|
||||
messages: [{ role: 'user', content: 'Hello!' }]
|
||||
})
|
||||
```
|
||||
|
||||
## 6. 简化设计原则
|
||||
|
||||
### 6.1 最小包装原则
|
||||
|
||||
- 直接使用 AI SDK 的类型，不重复定义
|
||||
- 避免过度抽象和复杂的中间层
|
||||
- 保持与 AI SDK 原生 API 的一致性
|
||||
|
||||
### 6.2 动态导入优化
|
||||
### 5.2 直接AI SDK模式 (兼容性)
|
||||
|
||||
```typescript
|
||||
// 按需加载，减少打包体积
|
||||
const module = await import('@ai-sdk/openai')
|
||||
const createOpenAI = module.createOpenAI
|
||||
import { streamText } from '@cherrystudio/ai-core'
|
||||
import { openai } from '@ai-sdk/openai'
|
||||
|
||||
// 直接使用AI SDK模式
|
||||
const stream = await streamText({
|
||||
model: openai('gpt-4'),
|
||||
messages: [{ role: 'user', content: 'Hello!' }]
|
||||
})
|
||||
```
|
||||
|
||||
### 6.3 类型安全
|
||||
### 5.3 执行器模式 (高级用法)
|
||||
|
||||
```typescript
|
||||
// 直接使用 AI SDK 类型
|
||||
import { streamText, generateText } from 'ai'
|
||||
import { AiExecutor } from '@cherrystudio/ai-core'
|
||||
|
||||
// 避免重复定义，直接传递参数
|
||||
return streamText({ model, ...request })
|
||||
// 创建执行器
|
||||
const executor = AiExecutor.create('openai', { apiKey: 'your-api-key' }, [plugin1, plugin2])
|
||||
|
||||
// 使用执行器
|
||||
const stream = await executor.streamText('gpt-4', {
|
||||
messages: [{ role: 'user', content: 'Hello!' }]
|
||||
})
|
||||
```
|
||||
|
||||
### 6.4 配置简化
|
||||
## 6. 插件系统详解
|
||||
|
||||
### 6.1 插件接口设计
|
||||
|
||||
```typescript
|
||||
// 简化的 Provider 配置
|
||||
interface ProviderConfig {
|
||||
id: string // provider 标识
|
||||
name: string // 显示名称
|
||||
import: () => Promise<any> // 动态导入函数
|
||||
creatorFunctionName: string // 创建函数名
|
||||
export interface AiPlugin {
|
||||
name: string
|
||||
collectStreamTransforms?: (context: AiRequestContext) => StreamTransform[]
|
||||
transformParams?: (params: any, context: AiRequestContext) => Promise<any>
|
||||
transformResult?: (result: any, context: AiRequestContext) => Promise<any>
|
||||
onRequest?: (context: AiRequestContext) => Promise<void>
|
||||
onSuccess?: (result: any, context: AiRequestContext) => Promise<void>
|
||||
onError?: (error: Error, context: AiRequestContext) => Promise<void>
|
||||
}
|
||||
```
|
||||
|
||||
## 7. 技术要点
|
||||
### 6.2 流转换支持
|
||||
|
||||
### 7.1 动态导入策略
|
||||
专门针对 `streamText` 的流转换功能：
|
||||
|
||||
- **按需加载**：只加载用户实际使用的 providers
|
||||
- **缓存机制**：避免重复导入和初始化
|
||||
- **错误处理**：优雅处理导入失败的情况
|
||||
```typescript
|
||||
// 插件收集流转换
|
||||
const streamTransforms = pluginManager.collectStreamTransforms(context)
|
||||
|
||||
### 7.2 依赖管理策略
|
||||
// 应用到AI SDK
|
||||
const result = await streamText({
|
||||
model,
|
||||
...params,
|
||||
experimental_transform: streamTransforms.length > 0 ? composeTransforms(streamTransforms) : undefined
|
||||
})
|
||||
```
|
||||
|
||||
- **核心依赖**：`ai` 库作为必需依赖
|
||||
- **可选依赖**：所有 `@ai-sdk/*` 包都是可选的
|
||||
- **版本兼容**：支持 AI SDK v3-v5 版本
|
||||
### 6.3 插件vs中间件
|
||||
|
||||
### 7.3 缓存策略
|
||||
| 功能 | 插件 (Plugins) | 中间件 (Middleware) |
|
||||
| -------- | -------------------------------- | ------------------- |
|
||||
| 用途 | 应用特定功能 | AI SDK原生功能 |
|
||||
| 流转换 | ✅ 支持 `experimental_transform` | ❌ 不支持 |
|
||||
| 适用范围 | 所有AI方法 | 所有AI方法 |
|
||||
| 应用时机 | 运行时 | 创建时 |
|
||||
| 复杂度 | 简单 | 原生AI SDK |
|
||||
|
||||
- **客户端缓存**：基于 provider + options 的智能缓存
|
||||
- **配置哈希**：安全的 API key 哈希处理
|
||||
- **生命周期管理**：支持缓存清理和验证
|
||||
## 7. 架构优势
|
||||
|
||||
## 8. 迁移策略
|
||||
### 7.1 分层清晰
|
||||
|
||||
### 8.1 阶段一：包基础搭建 (Week 1) ✅ 已完成
|
||||
- **Orchestration**: 用户友好的API
|
||||
- **Core**: 模块化的内部实现
|
||||
- **职责分离**: 每层专注自己的职责
|
||||
|
||||
1. ✅ 创建简化的包结构
|
||||
2. ✅ 实现 Provider 注册表
|
||||
3. ✅ 创建统一客户端和工厂
|
||||
4. ✅ 配置构建和类型系统
|
||||
### 7.2 函数式设计
|
||||
|
||||
### 8.2 阶段二：核心功能完善 (Week 2) ✅ 已完成
|
||||
- 大部分模块使用函数而非类
|
||||
- 更简洁的代码和更好的可测试性
|
||||
- 避免不必要的面向对象复杂性
|
||||
|
||||
1. ✅ 支持 19+ 官方 AI SDK providers
|
||||
2. ✅ 实现缓存和错误处理
|
||||
3. ✅ 完善类型安全和 API 设计
|
||||
4. ✅ 添加便捷函数和工具
|
||||
### 7.3 类型安全
|
||||
|
||||
### 8.3 阶段三：集成测试 (Week 3) 🔄 进行中
|
||||
- 统一使用 `types.ts` 中的类型定义
|
||||
- 避免重复定义，提高维护性
|
||||
- 完整的 TypeScript 支持
|
||||
|
||||
1. 在 Cherry Studio 中集成测试
|
||||
2. 功能完整性验证
|
||||
3. 性能基准测试
|
||||
4. 兼容性问题修复
|
||||
### 7.4 灵活扩展
|
||||
|
||||
### 8.4 阶段四：插件系统实现 ✅ 已完成
|
||||
- 插件系统支持流转换
|
||||
- 中间件系统支持AI SDK原生功能
|
||||
- 模块化设计便于功能扩展
|
||||
|
||||
1. **插件核心架构** ✅
|
||||
## 8. 迁移状态
|
||||
|
||||
- 实现 `PluginManager` 和 `PluginContext`
|
||||
- 创建钩子风格插件接口和类型系统
|
||||
- 建立四种钩子类型执行机制
|
||||
### 8.1 已完成 ✅
|
||||
|
||||
2. **钩子系统** ✅
|
||||
1. **架构重构** - 分层设计和职责分离
|
||||
2. **类型系统** - 统一类型定义和复用
|
||||
3. **函数式设计** - 从类转换为函数
|
||||
4. **插件系统** - 流转换和通用插件功能
|
||||
5. **Orchestration层** - 用户友好的API接口
|
||||
6. **Core层完整实现** - 创建、执行、客户端、中间件、插件、提供商
|
||||
|
||||
- `First Hooks`：第一个有效结果执行
|
||||
- `Sequential Hooks`：链式数据变换
|
||||
- `Parallel Hooks`：并发副作用处理
|
||||
- `Stream Hooks`：AI SDK 流转换集成
|
||||
### 8.2 进行中 🔄
|
||||
|
||||
3. **优先级和排序** ✅
|
||||
1. **集成测试** - 在实际项目中完整测试
|
||||
2. **性能优化** - 确保无性能退化
|
||||
3. **文档完善** - 使用指南和最佳实践
|
||||
|
||||
- `pre`/`normal`/`post` 优先级系统
|
||||
- 插件注册顺序维护
|
||||
- 错误处理和插件隔离
|
||||
### 8.3 计划中 📋
|
||||
|
||||
4. **集成到现有架构** ✅
|
||||
- 在 `UniversalAiSdkClient` 中集成插件管理器
|
||||
- 更新 `ApiClientFactory` 支持插件配置
|
||||
- 创建示例插件和使用文档
|
||||
1. **生态系统扩展** - 更多通用插件
|
||||
2. **优化改进** - 基于使用反馈的持续改进
|
||||
3. **社区贡献** - 开源发布和社区生态
|
||||
|
||||
### 8.5 阶段五：特性插件扩展 (规划中)
|
||||
## 9. 技术决策记录
|
||||
|
||||
1. **Cherry Studio 特性插件**
|
||||
### 9.1 为什么选择分层架构？
|
||||
|
||||
- `ThinkingPlugin`：思考过程记录和提取
|
||||
- `ToolCallPlugin`：工具调用处理和增强
|
||||
- `WebSearchPlugin`：网络搜索集成
|
||||
- **用户体验**: Orchestration层提供简洁API
|
||||
- **内部复杂性**: Core层处理复杂逻辑
|
||||
- **维护性**: 清晰的职责分离
|
||||
|
||||
2. **高级功能**
|
||||
- 插件组合和条件执行
|
||||
- 动态插件加载系统
|
||||
- 插件配置管理和持久化
|
||||
### 9.2 为什么选择函数式设计？
|
||||
|
||||
### 8.6 阶段六：文档和发布 (Week 7) 📋 规划中
|
||||
- **简洁性**: 避免不必要的类设计
|
||||
- **可测试性**: 函数更容易测试
|
||||
- **性能**: 减少对象创建开销
|
||||
|
||||
1. 完善使用文档和示例
|
||||
2. 插件开发指南和最佳实践
|
||||
3. 准备发布到 npm
|
||||
4. 建立维护流程
|
||||
### 9.3 为什么分离插件和中间件？
|
||||
|
||||
### 8.7 阶段七：生态系统扩展 (Week 8+) 🚀 未来规划
|
||||
- **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
|
||||
|
||||
1. 社区插件生态系统
|
||||
2. 可视化插件编排工具
|
||||
3. 性能监控和分析
|
||||
4. 高级缓存和优化策略
|
||||
## 10. 总结
|
||||
|
||||
## 9. 预期收益
|
||||
新的AI Core架构实现了：
|
||||
|
||||
### 9.1 开发效率提升
|
||||
### 10.1 设计目标
|
||||
|
||||
- **90%** 减少新 Provider 接入时间（只需添加注册表配置）
|
||||
- **70%** 减少维护工作量
|
||||
- **95%** 提升开发体验（统一接口 + 类型安全）
|
||||
- **独立开发**：可以独立于主应用开发和测试
|
||||
- ✅ **分层架构**: 清晰的编排层和核心层分离
|
||||
- ✅ **函数式设计**: 简洁的函数式API
|
||||
- ✅ **类型安全**: 统一的类型定义和复用
|
||||
- ✅ **插件扩展**: 支持流转换的插件系统
|
||||
- ✅ **易用性**: 多种使用模式满足不同需求
|
||||
|
||||
### 9.2 代码质量改善
|
||||
### 10.2 核心价值
|
||||
|
||||
- 完整的 TypeScript 类型安全
|
||||
- 统一的错误处理机制
|
||||
- 标准化的 AI SDK 接口
|
||||
- 更好的测试覆盖率
|
||||
- **统一接口**: 一套API支持19+ AI providers
|
||||
- **灵活使用**: 配置模式、AI SDK模式、执行器模式
|
||||
- **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
|
||||
|
||||
### 9.3 架构优势
|
||||
### 10.3 未来发展
|
||||
|
||||
- **轻量级**：最小化的包装层
|
||||
- **可复用**：其他项目可以直接使用
|
||||
- **可维护**：独立版本管理和发布
|
||||
- **可扩展**：新 provider 只需配置即可
|
||||
这个架构提供了坚实的AI基础设施，支持：
|
||||
|
||||
### 9.4 生态系统价值
|
||||
|
||||
- 支持 AI SDK 的完整生态系统
|
||||
- 可以独立发布到 npm
|
||||
- 为开源社区贡献价值
|
||||
- 建立统一的 AI 基础设施
|
||||
|
||||
## 10. 风险评估与应对
|
||||
|
||||
### 10.1 技术风险
|
||||
|
||||
- **AI SDK 版本兼容**：支持多版本兼容策略
|
||||
- **依赖管理**：合理使用 peerDependencies
|
||||
- **类型一致性**：直接使用 AI SDK 类型
|
||||
- **性能影响**：最小化包装层开销
|
||||
|
||||
### 10.2 迁移风险
|
||||
|
||||
- **功能对等性**：确保所有现有功能都能实现
|
||||
- **API 兼容性**：提供平滑的迁移路径
|
||||
- **集成复杂度**：保持简单的集成方式
|
||||
- **学习成本**：提供清晰的使用文档
|
||||
|
||||
## 11. 总结
|
||||
|
||||
简化的 AI Core 架构专注于核心价值：
|
||||
|
||||
### 11.1 核心价值
|
||||
|
||||
- **统一接口**：一套 API 支持 19+ AI providers
|
||||
- **按需加载**：只打包用户实际使用的 providers
|
||||
- **类型安全**：完整的 TypeScript 支持
|
||||
- **轻量高效**：最小化的包装层
|
||||
|
||||
### 11.2 设计哲学
|
||||
|
||||
- **直接使用 AI SDK**：避免重复造轮子，充分利用原生能力
|
||||
- **最小包装**：只在必要时添加抽象层，保持轻量高效
|
||||
- **开发者友好**：简单易用的 API 设计，熟悉的钩子风格
|
||||
- **生态兼容**：充分利用 AI SDK 生态系统和原生流转换
|
||||
- **插件优先**：基于钩子的扩展模式，支持灵活组合
|
||||
|
||||
### 11.3 成功关键
|
||||
|
||||
1. **保持简单**：专注核心功能，避免过度设计
|
||||
2. **充分测试**：确保功能完整性和稳定性
|
||||
3. **渐进迁移**：平滑过渡，降低风险
|
||||
4. **文档完善**：支持快速上手和深度使用
|
||||
|
||||
这个基于钩子的插件系统架构为 Cherry Studio 提供了一个轻量、高效、可维护的 AI 基础设施，通过熟悉的钩子模式和原生 AI SDK 集成，为开发者提供了强大而简洁的扩展能力，同时为社区贡献了一个高质量的开源包。
|
||||
- 持续的功能扩展
|
||||
- 良好的开发体验
|
||||
- 社区生态建设
|
||||
- 跨项目复用价值
|
||||
|
||||
@ -1,223 +0,0 @@
|
||||
/**
|
||||
* API Client Factory
|
||||
* 整合现有实现的改进版API客户端工厂
|
||||
*/
|
||||
|
||||
import type { ImageModelV1 } from '@ai-sdk/provider'
|
||||
import { type LanguageModelV1, LanguageModelV1Middleware, wrapLanguageModel } from 'ai'
|
||||
|
||||
import { aiProviderRegistry } from '../providers/registry'
|
||||
import { type ProviderId, type ProviderSettingsMap } from './types'
|
||||
|
||||
// 客户端配置接口
|
||||
export interface ClientConfig {
|
||||
providerId: string
|
||||
options?: any
|
||||
}
|
||||
|
||||
// 错误类型
|
||||
export class ClientFactoryError extends Error {
|
||||
constructor(
|
||||
message: string,
|
||||
public providerId?: string,
|
||||
public cause?: Error
|
||||
) {
|
||||
super(message)
|
||||
this.name = 'ClientFactoryError'
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* API Client Factory
|
||||
* 统一管理和创建AI SDK客户端
|
||||
*/
|
||||
export class ApiClientFactory {
|
||||
/**
|
||||
* 创建 AI SDK 模型实例
|
||||
* 对于已知的 Provider 使用严格类型检查，未知的 Provider 默认使用 openai-compatible
|
||||
*/
|
||||
static async createClient<T extends ProviderId>(
|
||||
providerId: T,
|
||||
modelId: string,
|
||||
options: ProviderSettingsMap[T],
|
||||
middlewares?: LanguageModelV1Middleware[]
|
||||
): Promise<LanguageModelV1>
|
||||
|
||||
static async createClient(
|
||||
providerId: string,
|
||||
modelId: string,
|
||||
options: ProviderSettingsMap['openai-compatible'],
|
||||
middlewares?: LanguageModelV1Middleware[]
|
||||
): Promise<LanguageModelV1>
|
||||
|
||||
static async createClient(
|
||||
providerId: string,
|
||||
modelId: string = 'default',
|
||||
options: any,
|
||||
middlewares?: LanguageModelV1Middleware[]
|
||||
): Promise<LanguageModelV1> {
|
||||
try {
|
||||
// 对于不在注册表中的 provider，默认使用 openai-compatible
|
||||
const effectiveProviderId = aiProviderRegistry.isSupported(providerId) ? providerId : 'openai-compatible'
|
||||
|
||||
// 获取Provider配置
|
||||
const providerConfig = aiProviderRegistry.getProvider(effectiveProviderId)
|
||||
if (!providerConfig) {
|
||||
throw new ClientFactoryError(`Provider "${effectiveProviderId}" is not registered`, providerId)
|
||||
}
|
||||
|
||||
// 动态导入模块
|
||||
const module = await providerConfig.import()
|
||||
|
||||
// 获取创建函数
|
||||
const creatorFunction = module[providerConfig.creatorFunctionName]
|
||||
|
||||
if (typeof creatorFunction !== 'function') {
|
||||
throw new ClientFactoryError(
|
||||
`Creator function "${providerConfig.creatorFunctionName}" not found in the imported module for provider "${effectiveProviderId}"`
|
||||
)
|
||||
}
|
||||
// 创建provider实例
|
||||
const provider = creatorFunction(options)
|
||||
|
||||
// 返回模型实例
|
||||
if (typeof provider === 'function') {
|
||||
let model: LanguageModelV1 = provider(modelId)
|
||||
|
||||
// 应用 AI SDK 中间件
|
||||
if (middlewares && middlewares.length > 0) {
|
||||
model = wrapLanguageModel({
|
||||
model: model,
|
||||
middleware: middlewares
|
||||
})
|
||||
}
|
||||
|
||||
return model
|
||||
} else {
|
||||
throw new ClientFactoryError(`Unknown model access pattern for provider "${effectiveProviderId}"`)
|
||||
}
|
||||
} catch (error) {
|
||||
if (error instanceof ClientFactoryError) {
|
||||
throw error
|
||||
}
|
||||
throw new ClientFactoryError(
|
||||
`Failed to create client for provider "${providerId}": ${error instanceof Error ? error.message : 'Unknown error'}`,
|
||||
providerId,
|
||||
error instanceof Error ? error : undefined
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
static async createImageClient<T extends ProviderId>(
|
||||
providerId: T,
|
||||
modelId: string,
|
||||
options: ProviderSettingsMap[T]
|
||||
): Promise<ImageModelV1>
|
||||
|
||||
static async createImageClient(
|
||||
providerId: string,
|
||||
modelId: string,
|
||||
options: ProviderSettingsMap['openai-compatible']
|
||||
): Promise<ImageModelV1>
|
||||
|
||||
static async createImageClient(providerId: string, modelId: string = 'default', options: any): Promise<ImageModelV1> {
|
||||
try {
|
||||
if (!aiProviderRegistry.isSupported(providerId)) {
|
||||
throw new ClientFactoryError(`Provider "${providerId}" is not supported`, providerId)
|
||||
}
|
||||
|
||||
const providerConfig = aiProviderRegistry.getProvider(providerId)
|
||||
if (!providerConfig) {
|
||||
throw new ClientFactoryError(`Provider "${providerId}" is not registered`, providerId)
|
||||
}
|
||||
|
||||
if (!providerConfig.supportsImageGeneration) {
|
||||
throw new ClientFactoryError(`Provider "${providerId}" does not support image generation`, providerId)
|
||||
}
|
||||
|
||||
const module = await providerConfig.import()
|
||||
|
||||
const creatorFunction = module[providerConfig.creatorFunctionName]
|
||||
|
||||
if (typeof creatorFunction !== 'function') {
|
||||
throw new ClientFactoryError(
|
||||
`Creator function "${providerConfig.creatorFunctionName}" not found in the imported module for provider "${providerId}"`
|
||||
)
|
||||
}
|
||||
|
||||
const provider = creatorFunction(options)
|
||||
|
||||
if (provider && typeof provider.image === 'function') {
|
||||
return provider.image(modelId)
|
||||
} else {
|
||||
throw new ClientFactoryError(`Image model function not found for provider "${providerId}"`)
|
||||
}
|
||||
} catch (error) {
|
||||
if (error instanceof ClientFactoryError) {
|
||||
throw error
|
||||
}
|
||||
throw new ClientFactoryError(
|
||||
`Failed to create image client for provider "${providerId}": ${error instanceof Error ? error.message : 'Unknown error'}`,
|
||||
providerId,
|
||||
error instanceof Error ? error : undefined
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取支持的 Providers 列表
|
||||
*/
|
||||
static getSupportedProviders(): Array<{
|
||||
id: string
|
||||
name: string
|
||||
}> {
|
||||
return aiProviderRegistry.getAllProviders().map((provider) => ({
|
||||
id: provider.id,
|
||||
name: provider.name
|
||||
}))
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取 Provider 信息
|
||||
*/
|
||||
static getClientInfo(providerId: string): {
|
||||
id: string
|
||||
name: string
|
||||
isSupported: boolean
|
||||
effectiveProvider: string
|
||||
} {
|
||||
const effectiveProviderId = aiProviderRegistry.isSupported(providerId) ? providerId : 'openai-compatible'
|
||||
const provider = aiProviderRegistry.getProvider(effectiveProviderId)
|
||||
|
||||
return {
|
||||
id: providerId,
|
||||
name: provider?.name || providerId,
|
||||
isSupported: aiProviderRegistry.isSupported(providerId),
|
||||
effectiveProvider: effectiveProviderId
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 便捷导出函数
|
||||
export function createClient<T extends ProviderId>(
|
||||
providerId: T,
|
||||
modelId: string,
|
||||
options: ProviderSettingsMap[T]
|
||||
): Promise<LanguageModelV1>
|
||||
|
||||
export function createClient(
|
||||
providerId: string,
|
||||
modelId: string,
|
||||
options: ProviderSettingsMap['openai-compatible']
|
||||
): Promise<LanguageModelV1>
|
||||
|
||||
export function createClient(providerId: string, modelId: string = 'default', options: any): Promise<LanguageModelV1> {
|
||||
return ApiClientFactory.createClient(providerId, modelId, options)
|
||||
}
|
||||
|
||||
export const createImageClient = (providerId: string, modelId: string, options: any): Promise<ImageModelV1> =>
|
||||
ApiClientFactory.createImageClient(providerId, modelId, options)
|
||||
|
||||
export const getSupportedProviders = () => ApiClientFactory.getSupportedProviders()
|
||||
|
||||
export const getClientInfo = (providerId: string) => ApiClientFactory.getClientInfo(providerId)
|
||||
@ -1,381 +0,0 @@
|
||||
/**
|
||||
* AI Client - Cherry Studio AI Core 的主要客户端接口
|
||||
* 默认集成插件系统，提供完整的 AI 调用能力
|
||||
*
|
||||
* ## 使用方式
|
||||
*
|
||||
* ```typescript
|
||||
* import { AiClient } from '@cherrystudio/ai-core'
|
||||
*
|
||||
* // 创建客户端（默认带插件系统）
|
||||
* const client = AiClient.create('openai', {
|
||||
* name: 'openai',
|
||||
* apiKey: process.env.OPENAI_API_KEY
|
||||
* }, [LoggingPlugin, ContentFilterPlugin])
|
||||
*
|
||||
* // 使用方式与 UniversalAiSdkClient 完全相同
|
||||
* const result = await client.generateText('gpt-4', {
|
||||
* messages: [{ role: 'user', content: 'Hello!' }]
|
||||
* })
|
||||
* ```
|
||||
*/
|
||||
import { generateObject, generateText, LanguageModelV1Middleware, streamObject, streamText } from 'ai'
|
||||
|
||||
import { AiPlugin, createContext, PluginManager } from '../plugins'
|
||||
import { isProviderSupported } from '../providers/registry'
|
||||
import { ApiClientFactory } from './ApiClientFactory'
|
||||
import { type ProviderId, type ProviderSettingsMap } from './types'
|
||||
import { UniversalAiSdkClient } from './UniversalAiSdkClient'
|
||||
|
||||
/**
|
||||
* Cherry Studio AI Core 的主要客户端
|
||||
* 默认集成插件系统，提供完整的 AI 调用能力
|
||||
*/
|
||||
export class PluginEnabledAiClient<T extends ProviderId = ProviderId> {
|
||||
private pluginManager: PluginManager
|
||||
private baseClient: UniversalAiSdkClient<T>
|
||||
private middlewares: LanguageModelV1Middleware[] = []
|
||||
|
||||
constructor(
|
||||
private readonly providerId: T,
|
||||
private readonly options: ProviderSettingsMap[T],
|
||||
plugins: AiPlugin[] = []
|
||||
) {
|
||||
this.pluginManager = new PluginManager(plugins)
|
||||
this.baseClient = UniversalAiSdkClient.create(providerId, options)
|
||||
this.updateMiddlewares()
|
||||
}
|
||||
|
||||
/**
|
||||
* 添加单个插件
|
||||
*/
|
||||
use(plugin: AiPlugin): this {
|
||||
this.pluginManager.use(plugin)
|
||||
this.updateMiddlewares()
|
||||
return this
|
||||
}
|
||||
|
||||
/**
|
||||
* 批量添加插件
|
||||
*/
|
||||
usePlugins(plugins: AiPlugin[]): this {
|
||||
plugins.forEach((plugin) => this.pluginManager.use(plugin))
|
||||
this.updateMiddlewares()
|
||||
return this
|
||||
}
|
||||
|
||||
/**
|
||||
* 移除插件
|
||||
*/
|
||||
removePlugin(pluginName: string): this {
|
||||
this.pluginManager.remove(pluginName)
|
||||
this.updateMiddlewares()
|
||||
return this
|
||||
}
|
||||
|
||||
/**
|
||||
* 重新计算并更新中间件列表
|
||||
* 这是一个原子操作，以确保中间件列表总是最新的
|
||||
*/
|
||||
private updateMiddlewares(): void {
|
||||
const pluginMiddlewares = this.pluginManager.collectAiSdkMiddlewares()
|
||||
this.middlewares = pluginMiddlewares
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取插件统计信息
|
||||
*/
|
||||
getPluginStats() {
|
||||
return this.pluginManager.getStats()
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取插件列表
|
||||
*/
|
||||
getPlugins() {
|
||||
return this.pluginManager.getPlugins()
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行插件处理的通用逻辑
|
||||
* 1-5步骤的通用处理
|
||||
*/
|
||||
private async executeWithPlugins<TParams, TResult>(
|
||||
methodName: string,
|
||||
modelId: string,
|
||||
params: TParams,
|
||||
executor: (finalModelId: string, transformedParams: TParams) => Promise<TResult>
|
||||
): Promise<TResult> {
|
||||
// 创建请求上下文
|
||||
const context = createContext(this.providerId, modelId, params)
|
||||
|
||||
try {
|
||||
// 1. 触发请求开始事件
|
||||
await this.pluginManager.executeParallel('onRequestStart', context)
|
||||
|
||||
// 2. 解析模型别名
|
||||
const resolvedModelId = await this.pluginManager.executeFirst<string>('resolveModel', modelId, context)
|
||||
const finalModelId = resolvedModelId || modelId
|
||||
|
||||
// 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(finalModelId, 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
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行流式调用的通用逻辑
|
||||
* 流式调用的特殊处理（支持流转换器）
|
||||
*/
|
||||
private async executeStreamWithPlugins<TParams, TResult>(
|
||||
methodName: string,
|
||||
modelId: string,
|
||||
params: TParams,
|
||||
executor: (finalModelId: string, transformedParams: TParams, streamTransforms: any[]) => Promise<TResult>
|
||||
): Promise<TResult> {
|
||||
// 创建请求上下文
|
||||
const context = createContext(this.providerId, modelId, params)
|
||||
|
||||
try {
|
||||
// 1. 触发请求开始事件
|
||||
await this.pluginManager.executeParallel('onRequestStart', context)
|
||||
|
||||
// 2. 解析模型别名
|
||||
const resolvedModelId = await this.pluginManager.executeFirst<string>('resolveModel', modelId, context)
|
||||
const finalModelId = resolvedModelId || modelId
|
||||
|
||||
// 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()
|
||||
|
||||
// 5. 执行流式 API 调用
|
||||
const result = await executor(finalModelId, transformedParams, streamTransforms)
|
||||
|
||||
// 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, { stream: true })
|
||||
|
||||
return result
|
||||
} catch (error) {
|
||||
// 7. 触发错误事件
|
||||
await this.pluginManager.executeParallel('onError', context, undefined, error as Error)
|
||||
throw error
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取注入了中间件的 AI SDK 模型实例
|
||||
* 这是应用原生中间件的关键
|
||||
*/
|
||||
private async getModelWithMiddlewares(modelId: string) {
|
||||
const middlewares = this.middlewares
|
||||
// 3. 如果有中间件，创建一个新的、注入了中间件的客户端实例
|
||||
return await ApiClientFactory.createClient(
|
||||
this.providerId,
|
||||
modelId,
|
||||
this.options,
|
||||
middlewares.length > 0 ? middlewares : undefined
|
||||
)
|
||||
}
|
||||
|
||||
/**
|
||||
* 流式文本生成
|
||||
*/
|
||||
async streamText(
|
||||
modelId: string,
|
||||
params: Omit<Parameters<typeof streamText>[0], 'model'>
|
||||
): Promise<ReturnType<typeof streamText>>
|
||||
async streamText(params: Parameters<typeof streamText>[0]): Promise<ReturnType<typeof streamText>>
|
||||
async streamText(
|
||||
modelIdOrParams: string | Parameters<typeof streamText>[0],
|
||||
params?: Omit<Parameters<typeof streamText>[0], 'model'>
|
||||
): Promise<ReturnType<typeof streamText>> {
|
||||
if (typeof modelIdOrParams === 'string') {
|
||||
// 传统方式：使用内建逻辑
|
||||
return this.executeStreamWithPlugins(
|
||||
'streamText',
|
||||
modelIdOrParams,
|
||||
params!,
|
||||
async (finalModelId, transformedParams, streamTransforms) => {
|
||||
const model = await this.getModelWithMiddlewares(finalModelId)
|
||||
const experimental_transform =
|
||||
params?.experimental_transform ?? (streamTransforms.length > 0 ? streamTransforms : undefined)
|
||||
|
||||
return await streamText({
|
||||
model,
|
||||
...transformedParams,
|
||||
experimental_transform
|
||||
})
|
||||
}
|
||||
)
|
||||
} else {
|
||||
// 外部 registry 方式：直接使用用户提供的 model
|
||||
return streamText(modelIdOrParams)
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 生成文本
|
||||
* 可能不需要了，因为内置模拟非流中间件
|
||||
*/
|
||||
async generateText(
|
||||
modelId: string,
|
||||
params: Omit<Parameters<typeof generateText>[0], 'model'>
|
||||
): Promise<ReturnType<typeof generateText>> {
|
||||
return this.executeWithPlugins('generateText', modelId, params, async (finalModelId, transformedParams) => {
|
||||
const model = await this.getModelWithMiddlewares(finalModelId)
|
||||
return await generateText({ model, ...transformedParams })
|
||||
})
|
||||
}
|
||||
|
||||
/**
|
||||
* 生成结构化对象
|
||||
*/
|
||||
async generateObject(
|
||||
modelId: string,
|
||||
params: Omit<Parameters<typeof generateObject>[0], 'model'>
|
||||
): Promise<ReturnType<typeof generateObject>>
|
||||
async generateObject(params: Parameters<typeof generateObject>[0]): Promise<ReturnType<typeof generateObject>>
|
||||
async generateObject(
|
||||
modelIdOrParams: string | Parameters<typeof generateObject>[0],
|
||||
params?: Omit<Parameters<typeof generateObject>[0], 'model'>
|
||||
): Promise<ReturnType<typeof generateObject>> {
|
||||
if (typeof modelIdOrParams === 'string') {
|
||||
// 传统方式：使用内建逻辑
|
||||
return this.executeWithPlugins(
|
||||
'generateObject',
|
||||
modelIdOrParams,
|
||||
params!,
|
||||
async (finalModelId, transformedParams) => {
|
||||
const model = await this.getModelWithMiddlewares(finalModelId)
|
||||
return await generateObject({ model, ...transformedParams })
|
||||
}
|
||||
)
|
||||
} else {
|
||||
// 外部 registry 方式：直接使用用户提供的 model
|
||||
return await generateObject(modelIdOrParams)
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 流式生成结构化对象
|
||||
*/
|
||||
async streamObject(
|
||||
modelId: string,
|
||||
params: Omit<Parameters<typeof streamObject>[0], 'model'>
|
||||
): Promise<ReturnType<typeof streamObject>>
|
||||
async streamObject(params: Parameters<typeof streamObject>[0]): Promise<ReturnType<typeof streamObject>>
|
||||
async streamObject(
|
||||
modelIdOrParams: string | Parameters<typeof streamObject>[0],
|
||||
params?: Omit<Parameters<typeof streamObject>[0], 'model'>
|
||||
): Promise<ReturnType<typeof streamObject>> {
|
||||
if (typeof modelIdOrParams === 'string') {
|
||||
// 传统方式：使用内建逻辑
|
||||
return this.executeWithPlugins(
|
||||
'streamObject',
|
||||
modelIdOrParams,
|
||||
params!,
|
||||
async (finalModelId, transformedParams) => {
|
||||
return await this.baseClient.streamObject(finalModelId, transformedParams)
|
||||
}
|
||||
)
|
||||
} else {
|
||||
// 外部 registry 方式：直接使用用户提供的 model
|
||||
return await streamObject(modelIdOrParams)
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取客户端信息
|
||||
*/
|
||||
getClientInfo() {
|
||||
return this.baseClient.getClientInfo()
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取底层客户端实例（用于高级用法）
|
||||
*/
|
||||
getBaseClient(): UniversalAiSdkClient<T> {
|
||||
return this.baseClient
|
||||
}
|
||||
|
||||
// === 静态工厂方法 ===
|
||||
|
||||
/**
|
||||
* 创建 OpenAI Compatible 客户端
|
||||
*/
|
||||
static createOpenAICompatible(
|
||||
config: ProviderSettingsMap['openai-compatible'],
|
||||
plugins: AiPlugin[] = []
|
||||
): PluginEnabledAiClient<'openai-compatible'> {
|
||||
return new PluginEnabledAiClient('openai-compatible', config, plugins)
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建标准提供商客户端
|
||||
*/
|
||||
static create<T extends ProviderId>(
|
||||
providerId: T,
|
||||
options: ProviderSettingsMap[T],
|
||||
plugins?: AiPlugin[]
|
||||
): PluginEnabledAiClient<T>
|
||||
|
||||
static create(
|
||||
providerId: string,
|
||||
options: ProviderSettingsMap['openai-compatible'],
|
||||
plugins?: AiPlugin[]
|
||||
): PluginEnabledAiClient<'openai-compatible'>
|
||||
|
||||
static create(providerId: string, options: any, plugins: AiPlugin[] = []): PluginEnabledAiClient {
|
||||
if (isProviderSupported(providerId)) {
|
||||
return new PluginEnabledAiClient(providerId as ProviderId, options, plugins)
|
||||
} else {
|
||||
// 对于未知 provider，使用 openai-compatible
|
||||
return new PluginEnabledAiClient('openai-compatible', options, plugins)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建 AI 客户端的工厂函数（默认带插件系统）
|
||||
*/
|
||||
export function createClient<T extends ProviderId>(
|
||||
providerId: T,
|
||||
options: ProviderSettingsMap[T],
|
||||
plugins?: AiPlugin[]
|
||||
): PluginEnabledAiClient<T>
|
||||
|
||||
export function createClient(
|
||||
providerId: string,
|
||||
options: ProviderSettingsMap['openai-compatible'],
|
||||
plugins?: AiPlugin[]
|
||||
): PluginEnabledAiClient<'openai-compatible'>
|
||||
|
||||
export function createClient(providerId: string, options: any, plugins: AiPlugin[] = []): PluginEnabledAiClient {
|
||||
return PluginEnabledAiClient.create(providerId, options, plugins)
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建 OpenAI Compatible 客户端的便捷函数
|
||||
*/
|
||||
export function createCompatibleClient(
|
||||
config: ProviderSettingsMap['openai-compatible'],
|
||||
plugins: AiPlugin[] = []
|
||||
): PluginEnabledAiClient<'openai-compatible'> {
|
||||
return PluginEnabledAiClient.createOpenAICompatible(config, plugins)
|
||||
}
|
||||
@ -1,216 +0,0 @@
|
||||
/**
|
||||
* Universal AI SDK Client
|
||||
* 统一的AI SDK客户端实现
|
||||
*
|
||||
* ## 使用方式
|
||||
*
|
||||
* ### 1. 官方提供商
|
||||
* ```typescript
|
||||
* import { UniversalAiSdkClient } from '@cherrystudio/ai-core'
|
||||
*
|
||||
* // OpenAI
|
||||
* const openai = UniversalAiSdkClient.create('openai', {
|
||||
* name: 'openai',
|
||||
* apiHost: 'https://api.openai.com/v1',
|
||||
* apiKey: process.env.OPENAI_API_KEY
|
||||
* })
|
||||
*
|
||||
* // Anthropic
|
||||
* const anthropic = UniversalAiSdkClient.create('anthropic', {
|
||||
* name: 'anthropic',
|
||||
* apiHost: 'https://api.anthropic.com',
|
||||
* apiKey: process.env.ANTHROPIC_API_KEY
|
||||
* })
|
||||
* ```
|
||||
*
|
||||
* ### 2. OpenAI Compatible 第三方提供商
|
||||
* ```typescript
|
||||
* // LM Studio (本地运行)
|
||||
* const lmStudio = UniversalAiSdkClient.createOpenAICompatible({
|
||||
* name: 'lm-studio',
|
||||
* baseURL: 'http://localhost:1234/v1'
|
||||
* })
|
||||
*
|
||||
* // Ollama (本地运行)
|
||||
* const ollama = UniversalAiSdkClient.createOpenAICompatible({
|
||||
* name: 'ollama',
|
||||
* baseURL: 'http://localhost:11434/v1'
|
||||
* })
|
||||
*
|
||||
* // 自定义第三方 API
|
||||
* const customProvider = UniversalAiSdkClient.createOpenAICompatible({
|
||||
* name: 'my-provider',
|
||||
* apiKey: process.env.CUSTOM_API_KEY,
|
||||
* baseURL: 'https://api.customprovider.com/v1',
|
||||
* headers: {
|
||||
* 'X-Custom-Header': 'value',
|
||||
* 'User-Agent': 'MyApp/1.0'
|
||||
* },
|
||||
* queryParams: {
|
||||
* 'api-version': '2024-01'
|
||||
* }
|
||||
* })
|
||||
* ```
|
||||
*
|
||||
* ### 3. 使用客户端进行 AI 调用
|
||||
* ```typescript
|
||||
* // 流式文本生成
|
||||
* const stream = await client.streamText('gpt-4', {
|
||||
* messages: [{ role: 'user', content: 'Hello!' }]
|
||||
* })
|
||||
*
|
||||
* // 生成文本
|
||||
* const { text } = await client.generateText('gpt-4', {
|
||||
* messages: [{ role: 'user', content: 'Hello!' }]
|
||||
* })
|
||||
*
|
||||
* // 生成结构化对象
|
||||
* const { object } = await client.generateObject('gpt-4', {
|
||||
* messages: [{ role: 'user', content: 'Generate a user profile' }],
|
||||
* schema: z.object({
|
||||
* name: z.string(),
|
||||
* age: z.number()
|
||||
* })
|
||||
* })
|
||||
* ```
|
||||
*/
|
||||
|
||||
import { experimental_generateImage as generateImage, generateObject, generateText, streamObject, streamText } from 'ai'
|
||||
|
||||
import { ApiClientFactory } from './ApiClientFactory'
|
||||
import { type ProviderId, type ProviderSettingsMap } from './types'
|
||||
|
||||
/**
|
||||
* 通用 AI SDK 客户端
|
||||
* 为特定 AI 提供商创建的客户端实例
|
||||
*/
|
||||
export class UniversalAiSdkClient<T extends ProviderId = ProviderId> {
|
||||
constructor(
|
||||
private readonly providerId: T,
|
||||
private readonly options: ProviderSettingsMap[T]
|
||||
) {}
|
||||
|
||||
/**
|
||||
* 流式文本生成
|
||||
* 直接使用 AI SDK 的 streamText 参数类型
|
||||
*/
|
||||
async streamText(modelId: string, params: Omit<Parameters<typeof streamText>[0], 'model'>) {
|
||||
const model = await ApiClientFactory.createClient(this.providerId, modelId, this.options)
|
||||
return await streamText({
|
||||
model,
|
||||
...params
|
||||
})
|
||||
}
|
||||
|
||||
/**
|
||||
* 生成文本
|
||||
* 直接使用 AI SDK 的 generateText 参数类型
|
||||
*/
|
||||
async generateText(modelId: string, params: Omit<Parameters<typeof generateText>[0], 'model'>) {
|
||||
const model = await ApiClientFactory.createClient(this.providerId, modelId, this.options)
|
||||
return await generateText({
|
||||
model,
|
||||
...params
|
||||
})
|
||||
}
|
||||
|
||||
/**
|
||||
* 生成结构化对象
|
||||
* 直接使用 AI SDK 的 generateObject 参数类型
|
||||
*/
|
||||
async generateObject(modelId: string, params: Omit<Parameters<typeof generateObject>[0], 'model'>) {
|
||||
const model = await ApiClientFactory.createClient(this.providerId, modelId, this.options)
|
||||
return await generateObject({
|
||||
model,
|
||||
...params
|
||||
})
|
||||
}
|
||||
|
||||
/**
|
||||
* 流式生成结构化对象
|
||||
* 直接使用 AI SDK 的 streamObject 参数类型
|
||||
*/
|
||||
async streamObject(modelId: string, params: Omit<Parameters<typeof streamObject>[0], 'model'>) {
|
||||
const model = await ApiClientFactory.createClient(this.providerId, modelId, this.options)
|
||||
return await streamObject({
|
||||
model,
|
||||
...params
|
||||
})
|
||||
}
|
||||
|
||||
async generateImage(
|
||||
modelId: string,
|
||||
params: Omit<Parameters<typeof generateImage>[0], 'model'>
|
||||
): Promise<ReturnType<typeof generateImage>> {
|
||||
const model = await ApiClientFactory.createImageClient(this.providerId, modelId, this.options)
|
||||
return generateImage({
|
||||
model,
|
||||
...params
|
||||
})
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取客户端信息
|
||||
*/
|
||||
getClientInfo() {
|
||||
return ApiClientFactory.getClientInfo(this.providerId)
|
||||
}
|
||||
|
||||
// === 静态工厂方法 ===
|
||||
|
||||
/**
|
||||
* 创建 OpenAI Compatible 客户端
|
||||
* 用于那些实现 OpenAI API 的第三方提供商
|
||||
*/
|
||||
static createOpenAICompatible(
|
||||
config: ProviderSettingsMap['openai-compatible']
|
||||
): UniversalAiSdkClient<'openai-compatible'> {
|
||||
return new UniversalAiSdkClient('openai-compatible', config)
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建标准提供商客户端
|
||||
* 对于已知的 Provider 使用严格类型检查，未知的 Provider 默认使用 openai-compatible
|
||||
*/
|
||||
static create<T extends ProviderId>(providerId: T, options: ProviderSettingsMap[T]): UniversalAiSdkClient<T>
|
||||
|
||||
static create(
|
||||
providerId: string,
|
||||
options: ProviderSettingsMap['openai-compatible']
|
||||
): UniversalAiSdkClient<'openai-compatible'>
|
||||
|
||||
static create(providerId: string, options: any): UniversalAiSdkClient {
|
||||
if (providerId in ({} as ProviderSettingsMap)) {
|
||||
return new UniversalAiSdkClient(providerId as ProviderId, options)
|
||||
} else {
|
||||
// 对于未知 provider，使用 openai-compatible
|
||||
return new UniversalAiSdkClient('openai-compatible', options)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建客户端实例的工厂函数
|
||||
*/
|
||||
export function createUniversalClient<T extends ProviderId>(
|
||||
providerId: T,
|
||||
options: ProviderSettingsMap[T]
|
||||
): UniversalAiSdkClient<T>
|
||||
|
||||
export function createUniversalClient(
|
||||
providerId: string,
|
||||
options: ProviderSettingsMap['openai-compatible']
|
||||
): UniversalAiSdkClient<'openai-compatible'>
|
||||
|
||||
export function createUniversalClient(providerId: string, options: any): UniversalAiSdkClient {
|
||||
return UniversalAiSdkClient.create(providerId, options)
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建 OpenAI Compatible 客户端的便捷函数
|
||||
*/
|
||||
export function createOpenAICompatibleClient(
|
||||
config: ProviderSettingsMap['openai-compatible']
|
||||
): UniversalAiSdkClient<'openai-compatible'> {
|
||||
return UniversalAiSdkClient.createOpenAICompatible(config)
|
||||
}
|
||||
3
packages/aiCore/src/core/README.MD
Normal file
3
packages/aiCore/src/core/README.MD
Normal file
@ -0,0 +1,3 @@
|
||||
# @cherryStudio-aiCore
|
||||
|
||||
Core
|
||||
238
packages/aiCore/src/core/clients/PluginEnabledAiClient.ts
Normal file
238
packages/aiCore/src/core/clients/PluginEnabledAiClient.ts
Normal file
@ -0,0 +1,238 @@
|
||||
/**
|
||||
* AI Client - Cherry Studio AI Core 的主要客户端接口
|
||||
* 默认集成插件系统，提供完整的 AI 调用能力
|
||||
*
|
||||
* ## 使用方式
|
||||
*
|
||||
* ```typescript
|
||||
* import { AiClient } from '@cherrystudio/ai-core'
|
||||
*
|
||||
* // 创建客户端（默认带插件系统）
|
||||
* const client = AiClient.create('openai', {
|
||||
* name: 'openai',
|
||||
* apiKey: process.env.OPENAI_API_KEY
|
||||
* }, [LoggingPlugin, ContentFilterPlugin])
|
||||
*
|
||||
* // 使用方式与 UniversalAiSdkClient 完全相同
|
||||
* const result = await client.generateText('gpt-4', {
|
||||
* messages: [{ role: 'user', content: 'Hello!' }]
|
||||
* })
|
||||
* ```
|
||||
*/
|
||||
|
||||
import { type ProviderId, type ProviderSettingsMap } from '../../types'
|
||||
import { getProviderInfo } from '..'
|
||||
import { type AiPlugin, createContext, PluginManager } from '../plugins'
|
||||
import { isProviderSupported } from '../providers/registry'
|
||||
|
||||
/**
|
||||
* 插件增强的 AI 客户端
|
||||
* 专注于插件处理，不暴露用户API
|
||||
*/
|
||||
export class PluginEnabledAiClient<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()
|
||||
}
|
||||
|
||||
// /**
|
||||
// * 使用core模块创建模型（包含中间件）
|
||||
// */
|
||||
// async createModelWithMiddlewares(modelId: string): Promise<any> {
|
||||
// // 使用core模块的resolveConfig解析配置
|
||||
// const config = resolveConfig(this.providerId, modelId, this.options, this.pluginManager.getPlugins())
|
||||
|
||||
// // 使用core模块创建包装好的模型
|
||||
// return createModelFromConfig(config)
|
||||
// }
|
||||
|
||||
/**
|
||||
* 执行带插件的操作（非流式）
|
||||
* 提供给AiExecutor使用
|
||||
*/
|
||||
async executeWithPlugins<TParams, TResult>(
|
||||
methodName: string,
|
||||
modelId: string,
|
||||
params: TParams,
|
||||
executor: (finalModelId: string, transformedParams: TParams) => Promise<TResult>
|
||||
): Promise<TResult> {
|
||||
// 使用正确的createContext创建请求上下文
|
||||
const context = createContext(this.providerId, modelId, params)
|
||||
|
||||
try {
|
||||
// 1. 触发请求开始事件
|
||||
await this.pluginManager.executeParallel('onRequestStart', context)
|
||||
|
||||
// 2. 解析模型别名
|
||||
const resolvedModelId = await this.pluginManager.executeFirst<string>('resolveModel', modelId, context)
|
||||
const finalModelId = resolvedModelId || modelId
|
||||
|
||||
// 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(finalModelId, 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
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行流式调用的通用逻辑（支持流转换器）
|
||||
* 提供给AiExecutor使用
|
||||
*/
|
||||
async executeStreamWithPlugins<TParams, TResult>(
|
||||
methodName: string,
|
||||
modelId: string,
|
||||
params: TParams,
|
||||
executor: (finalModelId: string, transformedParams: TParams, streamTransforms: any[]) => Promise<TResult>
|
||||
): Promise<TResult> {
|
||||
// 创建请求上下文
|
||||
const context = createContext(this.providerId, modelId, params)
|
||||
|
||||
try {
|
||||
// 1. 触发请求开始事件
|
||||
await this.pluginManager.executeParallel('onRequestStart', context)
|
||||
|
||||
// 2. 解析模型别名
|
||||
const resolvedModelId = await this.pluginManager.executeFirst<string>('resolveModel', modelId, context)
|
||||
const finalModelId = resolvedModelId || modelId
|
||||
|
||||
// 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()
|
||||
|
||||
// 5. 执行流式 API 调用
|
||||
const result = await executor(finalModelId, transformedParams, streamTransforms)
|
||||
|
||||
// 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, { stream: true })
|
||||
|
||||
return result
|
||||
} catch (error) {
|
||||
// 7. 触发错误事件
|
||||
await this.pluginManager.executeParallel('onError', context, undefined, error as Error)
|
||||
throw error
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取客户端信息
|
||||
*/
|
||||
getClientInfo() {
|
||||
return getProviderInfo(this.providerId)
|
||||
}
|
||||
|
||||
// /**
|
||||
// * 获取底层客户端实例（用于高级用法）
|
||||
// */
|
||||
// getBaseClient(): UniversalAiSdkClient<T> {
|
||||
// return this.baseClient
|
||||
// }
|
||||
|
||||
// === 静态工厂方法 ===
|
||||
|
||||
/**
|
||||
* 创建 OpenAI Compatible 客户端
|
||||
*/
|
||||
static createOpenAICompatible(
|
||||
config: ProviderSettingsMap['openai-compatible'],
|
||||
plugins: AiPlugin[] = []
|
||||
): PluginEnabledAiClient<'openai-compatible'> {
|
||||
return new PluginEnabledAiClient('openai-compatible', plugins)
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建标准提供商客户端
|
||||
*/
|
||||
static create<T extends ProviderId>(providerId: T, plugins?: AiPlugin[]): PluginEnabledAiClient<T>
|
||||
|
||||
static create(providerId: string, plugins?: AiPlugin[]): PluginEnabledAiClient<'openai-compatible'>
|
||||
|
||||
static create(providerId: string, plugins: AiPlugin[] = []): PluginEnabledAiClient {
|
||||
if (isProviderSupported(providerId)) {
|
||||
return new PluginEnabledAiClient(providerId as ProviderId, plugins)
|
||||
} else {
|
||||
// 对于未知 provider，使用 openai-compatible
|
||||
return new PluginEnabledAiClient('openai-compatible', plugins)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建 AI 客户端的工厂函数（默认带插件系统）
|
||||
* @deprecated 建议使用 AiExecutor 代替
|
||||
*/
|
||||
export function createClient<T extends ProviderId>(providerId: T, plugins?: AiPlugin[]): PluginEnabledAiClient<T>
|
||||
|
||||
export function createClient(providerId: string, plugins?: AiPlugin[]): PluginEnabledAiClient<'openai-compatible'>
|
||||
|
||||
export function createClient(providerId: string, plugins: AiPlugin[] = []): PluginEnabledAiClient {
|
||||
return PluginEnabledAiClient.create(providerId, plugins)
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建 OpenAI Compatible 客户端的便捷函数
|
||||
* @deprecated 建议使用 AiExecutor 代替
|
||||
*/
|
||||
export function createCompatibleClient(
|
||||
config: ProviderSettingsMap['openai-compatible'],
|
||||
plugins: AiPlugin[] = []
|
||||
): PluginEnabledAiClient<'openai-compatible'> {
|
||||
return PluginEnabledAiClient.createOpenAICompatible(config, plugins)
|
||||
}
|
||||
37
packages/aiCore/src/core/creation/ConfigManager.ts
Normal file
37
packages/aiCore/src/core/creation/ConfigManager.ts
Normal file
@ -0,0 +1,37 @@
|
||||
/**
|
||||
* 配置管理器
|
||||
* 整合options、plugins、middlewares等配置
|
||||
*/
|
||||
import { LanguageModelV1Middleware } from 'ai'
|
||||
|
||||
import { ProviderId, ProviderSettingsMap } from '../../types'
|
||||
import { createMiddlewares } from '../middleware/MiddlewareManager'
|
||||
import { AiPlugin } from '../plugins'
|
||||
import { ResolvedConfig } from './types'
|
||||
|
||||
/**
|
||||
* 解析配置
|
||||
* 整合provider配置、插件、中间件、provider选项等
|
||||
*/
|
||||
export function resolveConfig(
|
||||
providerId: ProviderId,
|
||||
modelId: string,
|
||||
providerSettings: ProviderSettingsMap[ProviderId],
|
||||
plugins: AiPlugin[] = [],
|
||||
middlewares: LanguageModelV1Middleware[] = []
|
||||
): ResolvedConfig {
|
||||
// 使用独立的中间件管理器处理中间件
|
||||
const resolvedMiddlewares = createMiddlewares(middlewares)
|
||||
|
||||
return {
|
||||
provider: {
|
||||
id: providerId,
|
||||
options: providerSettings
|
||||
},
|
||||
model: {
|
||||
id: modelId
|
||||
},
|
||||
plugins,
|
||||
middlewares: resolvedMiddlewares
|
||||
}
|
||||
}
|
||||
31
packages/aiCore/src/core/creation/ModelCreator.ts
Normal file
31
packages/aiCore/src/core/creation/ModelCreator.ts
Normal file
@ -0,0 +1,31 @@
|
||||
/**
|
||||
* 模型创建器
|
||||
* 负责创建模型并应用中间件，不暴露原始model给用户
|
||||
*/
|
||||
import { LanguageModel } from 'ai'
|
||||
|
||||
import { wrapModelWithMiddlewares } from '../middleware'
|
||||
import { createBaseModel } from './ProviderCreator'
|
||||
import { ModelCreationRequest, ResolvedConfig } from './types'
|
||||
|
||||
/**
|
||||
* 根据解析后的配置创建包装好的模型
|
||||
*/
|
||||
export async function createModelFromConfig(config: ResolvedConfig): Promise<LanguageModel> {
|
||||
// 使用ProviderCreator创建基础模型（不应用中间件）
|
||||
const baseModel = await createBaseModel(config.provider.id, config.model.id, config.provider.options)
|
||||
|
||||
// 在creation层应用中间件，用户不直接接触原始model
|
||||
return wrapModelWithMiddlewares(baseModel, config.middlewares)
|
||||
}
|
||||
|
||||
/**
|
||||
* 直接根据请求参数创建模型
|
||||
*/
|
||||
export async function createModel(request: ModelCreationRequest): Promise<LanguageModel> {
|
||||
// 使用ProviderCreator创建基础模型（不应用中间件）
|
||||
const baseModel = await createBaseModel(request.providerId, request.modelId, request.options)
|
||||
|
||||
const middlewares = request.middlewares || []
|
||||
return wrapModelWithMiddlewares(baseModel, middlewares)
|
||||
}
|
||||
194
packages/aiCore/src/core/creation/ProviderCreator.ts
Normal file
194
packages/aiCore/src/core/creation/ProviderCreator.ts
Normal file
@ -0,0 +1,194 @@
|
||||
/**
|
||||
* Provider 创建器
|
||||
* 负责动态导入 AI SDK providers 并创建基础模型实例
|
||||
*/
|
||||
import type { ImageModelV1 } from '@ai-sdk/provider'
|
||||
import { type LanguageModelV1, LanguageModelV1Middleware, wrapLanguageModel } from 'ai'
|
||||
|
||||
import { type ProviderId, type ProviderSettingsMap } from '../../types'
|
||||
import { aiProviderRegistry, type ProviderConfig } from '../providers/registry'
|
||||
|
||||
// 错误类型
|
||||
export class ProviderCreationError extends Error {
|
||||
constructor(
|
||||
message: string,
|
||||
public providerId?: string,
|
||||
public cause?: Error
|
||||
) {
|
||||
super(message)
|
||||
this.name = 'ProviderCreationError'
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建基础 AI SDK 模型实例
|
||||
* 对于已知的 Provider 使用严格类型检查，未知的 Provider 默认使用 openai-compatible
|
||||
*/
|
||||
export async function createBaseModel<T extends ProviderId>(
|
||||
providerId: T,
|
||||
modelId: string,
|
||||
options: ProviderSettingsMap[T],
|
||||
middlewares?: LanguageModelV1Middleware[]
|
||||
): Promise<LanguageModelV1>
|
||||
|
||||
export async function createBaseModel(
|
||||
providerId: string,
|
||||
modelId: string,
|
||||
options: ProviderSettingsMap['openai-compatible'],
|
||||
middlewares?: LanguageModelV1Middleware[]
|
||||
): Promise<LanguageModelV1>
|
||||
|
||||
export async function createBaseModel(
|
||||
providerId: string,
|
||||
modelId: string = 'default',
|
||||
options: any,
|
||||
middlewares?: LanguageModelV1Middleware[]
|
||||
): Promise<LanguageModelV1> {
|
||||
try {
|
||||
// 对于不在注册表中的 provider，默认使用 openai-compatible
|
||||
const effectiveProviderId = aiProviderRegistry.isSupported(providerId) ? providerId : 'openai-compatible'
|
||||
|
||||
// 获取Provider配置
|
||||
const providerConfig = aiProviderRegistry.getProvider(effectiveProviderId)
|
||||
if (!providerConfig) {
|
||||
throw new ProviderCreationError(`Provider "${effectiveProviderId}" is not registered`, providerId)
|
||||
}
|
||||
|
||||
// 动态导入模块
|
||||
const module = await providerConfig.import()
|
||||
|
||||
// 获取创建函数
|
||||
const creatorFunction = module[providerConfig.creatorFunctionName]
|
||||
|
||||
if (typeof creatorFunction !== 'function') {
|
||||
throw new ProviderCreationError(
|
||||
`Creator function "${providerConfig.creatorFunctionName}" not found in the imported module for provider "${effectiveProviderId}"`
|
||||
)
|
||||
}
|
||||
|
||||
// 创建provider实例
|
||||
const provider = creatorFunction(options)
|
||||
|
||||
// 返回模型实例
|
||||
if (typeof provider === 'function') {
|
||||
let model: LanguageModelV1 = provider(modelId)
|
||||
|
||||
// 应用 AI SDK 中间件
|
||||
if (middlewares && middlewares.length > 0) {
|
||||
model = wrapLanguageModel({
|
||||
model: model,
|
||||
middleware: middlewares
|
||||
})
|
||||
}
|
||||
|
||||
return model
|
||||
} else {
|
||||
throw new ProviderCreationError(`Unknown model access pattern for provider "${effectiveProviderId}"`)
|
||||
}
|
||||
} catch (error) {
|
||||
if (error instanceof ProviderCreationError) {
|
||||
throw error
|
||||
}
|
||||
throw new ProviderCreationError(
|
||||
`Failed to create base model for provider "${providerId}": ${error instanceof Error ? error.message : 'Unknown error'}`,
|
||||
providerId,
|
||||
error instanceof Error ? error : undefined
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建图像生成模型实例
|
||||
*/
|
||||
export async function createImageModel<T extends ProviderId>(
|
||||
providerId: T,
|
||||
modelId: string,
|
||||
options: ProviderSettingsMap[T]
|
||||
): Promise<ImageModelV1>
|
||||
|
||||
export async function createImageModel(
|
||||
providerId: string,
|
||||
modelId: string,
|
||||
options: ProviderSettingsMap['openai-compatible']
|
||||
): Promise<ImageModelV1>
|
||||
|
||||
export async function createImageModel(
|
||||
providerId: string,
|
||||
modelId: string = 'default',
|
||||
options: any
|
||||
): Promise<ImageModelV1> {
|
||||
try {
|
||||
if (!aiProviderRegistry.isSupported(providerId)) {
|
||||
throw new ProviderCreationError(`Provider "${providerId}" is not supported`, providerId)
|
||||
}
|
||||
|
||||
const providerConfig = aiProviderRegistry.getProvider(providerId)
|
||||
if (!providerConfig) {
|
||||
throw new ProviderCreationError(`Provider "${providerId}" is not registered`, providerId)
|
||||
}
|
||||
|
||||
if (!providerConfig.supportsImageGeneration) {
|
||||
throw new ProviderCreationError(`Provider "${providerId}" does not support image generation`, providerId)
|
||||
}
|
||||
|
||||
const module = await providerConfig.import()
|
||||
|
||||
const creatorFunction = module[providerConfig.creatorFunctionName]
|
||||
|
||||
if (typeof creatorFunction !== 'function') {
|
||||
throw new ProviderCreationError(
|
||||
`Creator function "${providerConfig.creatorFunctionName}" not found in the imported module for provider "${providerId}"`
|
||||
)
|
||||
}
|
||||
|
||||
const provider = creatorFunction(options)
|
||||
|
||||
if (provider && typeof provider.image === 'function') {
|
||||
return provider.image(modelId)
|
||||
} else {
|
||||
throw new ProviderCreationError(`Image model function not found for provider "${providerId}"`)
|
||||
}
|
||||
} catch (error) {
|
||||
if (error instanceof ProviderCreationError) {
|
||||
throw error
|
||||
}
|
||||
throw new ProviderCreationError(
|
||||
`Failed to create image model for provider "${providerId}": ${error instanceof Error ? error.message : 'Unknown error'}`,
|
||||
providerId,
|
||||
error instanceof Error ? error : undefined
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取支持的 Providers 列表
|
||||
*/
|
||||
export function getSupportedProviders(): Array<{
|
||||
id: string
|
||||
name: string
|
||||
}> {
|
||||
return aiProviderRegistry.getAllProviders().map((provider: ProviderConfig) => ({
|
||||
id: provider.id,
|
||||
name: provider.name
|
||||
}))
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取 Provider 信息
|
||||
*/
|
||||
export function getProviderInfo(providerId: string): {
|
||||
id: string
|
||||
name: string
|
||||
isSupported: boolean
|
||||
effectiveProvider: string
|
||||
} {
|
||||
const effectiveProviderId = aiProviderRegistry.isSupported(providerId) ? providerId : 'openai-compatible'
|
||||
const provider = aiProviderRegistry.getProvider(effectiveProviderId)
|
||||
|
||||
return {
|
||||
id: providerId,
|
||||
name: provider?.name || providerId,
|
||||
isSupported: aiProviderRegistry.isSupported(providerId),
|
||||
effectiveProvider: effectiveProviderId
|
||||
}
|
||||
}
|
||||
15
packages/aiCore/src/core/creation/index.ts
Normal file
15
packages/aiCore/src/core/creation/index.ts
Normal file
@ -0,0 +1,15 @@
|
||||
/**
|
||||
* Creation 模块导出
|
||||
* 提供配置管理和模型创建能力
|
||||
*/
|
||||
|
||||
export { resolveConfig } from './ConfigManager'
|
||||
export { createModel, createModelFromConfig } from './ModelCreator'
|
||||
export {
|
||||
createBaseModel,
|
||||
createImageModel,
|
||||
getProviderInfo,
|
||||
getSupportedProviders,
|
||||
ProviderCreationError
|
||||
} from './ProviderCreator'
|
||||
export type { ModelCreationRequest, ResolvedConfig } from './types'
|
||||
32
packages/aiCore/src/core/creation/types.ts
Normal file
32
packages/aiCore/src/core/creation/types.ts
Normal file
@ -0,0 +1,32 @@
|
||||
/**
|
||||
* Creation 模块类型定义
|
||||
*/
|
||||
import { LanguageModelV1Middleware } from 'ai'
|
||||
|
||||
import { ProviderId, ProviderSettingsMap } from '../../types'
|
||||
import { AiPlugin } from '../plugins'
|
||||
|
||||
/**
|
||||
* 模型创建请求
|
||||
*/
|
||||
export interface ModelCreationRequest {
|
||||
providerId: ProviderId
|
||||
modelId: string
|
||||
options: ProviderSettingsMap[ProviderId]
|
||||
middlewares?: LanguageModelV1Middleware[]
|
||||
}
|
||||
|
||||
/**
|
||||
* 配置解析结果
|
||||
*/
|
||||
export interface ResolvedConfig {
|
||||
provider: {
|
||||
id: ProviderId
|
||||
options: ProviderSettingsMap[ProviderId]
|
||||
}
|
||||
model: {
|
||||
id: string
|
||||
}
|
||||
plugins: AiPlugin[]
|
||||
middlewares: LanguageModelV1Middleware[]
|
||||
}
|
||||
174
packages/aiCore/src/core/execution/AiExecutor.ts
Normal file
174
packages/aiCore/src/core/execution/AiExecutor.ts
Normal file
@ -0,0 +1,174 @@
|
||||
/**
|
||||
* AI 执行器
|
||||
* 面向用户的主要API入口，专注于AI调用
|
||||
*/
|
||||
import { generateObject, generateText, LanguageModelV1, streamObject, streamText } from 'ai'
|
||||
|
||||
import { type ProviderId } from '../../types'
|
||||
import { PluginEnabledAiClient } from '../clients/PluginEnabledAiClient'
|
||||
import { type AiPlugin } from '../plugins'
|
||||
import { isProviderSupported } from '../providers/registry'
|
||||
import { type ExecutorConfig, type GenericExecutorConfig } from './types'
|
||||
|
||||
export class AiExecutor<T extends ProviderId = ProviderId> {
|
||||
private pluginClient: PluginEnabledAiClient<T>
|
||||
|
||||
constructor(config: ExecutorConfig<T>)
|
||||
constructor(config: GenericExecutorConfig)
|
||||
constructor(config: ExecutorConfig<T> | GenericExecutorConfig) {
|
||||
if (isProviderSupported(config.providerId)) {
|
||||
this.pluginClient = new PluginEnabledAiClient(config.providerId as T)
|
||||
} else {
|
||||
// 对于未知provider，使用openai-compatible
|
||||
this.pluginClient = new PluginEnabledAiClient('openai-compatible' as T)
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 流式文本生成
|
||||
* 用户友好的API，内部使用插件处理能力
|
||||
*/
|
||||
async streamText(
|
||||
model: LanguageModelV1,
|
||||
params: Omit<Parameters<typeof streamText>[0], 'model'>
|
||||
): Promise<ReturnType<typeof streamText>>
|
||||
async streamText(
|
||||
model: LanguageModelV1,
|
||||
params?: Omit<Parameters<typeof streamText>[0], 'model'>
|
||||
): Promise<ReturnType<typeof streamText>> {
|
||||
// 传统方式：使用插件处理逻辑
|
||||
return this.pluginClient.executeStreamWithPlugins(
|
||||
'streamText',
|
||||
model.modelId,
|
||||
params!,
|
||||
async (finalModelId, transformedParams, streamTransforms) => {
|
||||
// const model = await this.pluginClient.createModelWithMiddlewares(finalModelId)
|
||||
const experimental_transform =
|
||||
params?.experimental_transform ?? (streamTransforms.length > 0 ? streamTransforms : undefined)
|
||||
|
||||
return await streamText({
|
||||
model,
|
||||
...transformedParams,
|
||||
experimental_transform
|
||||
})
|
||||
}
|
||||
)
|
||||
}
|
||||
|
||||
/**
|
||||
* 生成文本
|
||||
* 用户友好的API，内部使用插件处理能力
|
||||
*/
|
||||
async generateText(
|
||||
model: LanguageModelV1,
|
||||
params: Omit<Parameters<typeof generateText>[0], 'model'>
|
||||
): Promise<ReturnType<typeof generateText>>
|
||||
async generateText(
|
||||
model: LanguageModelV1,
|
||||
params?: Omit<Parameters<typeof generateText>[0], 'model'>
|
||||
): Promise<ReturnType<typeof generateText>> {
|
||||
// 传统方式：使用插件处理逻辑
|
||||
return this.pluginClient.executeWithPlugins(
|
||||
'generateText',
|
||||
model.modelId,
|
||||
params!,
|
||||
async (finalModelId, transformedParams) => {
|
||||
// const model = await this.pluginClient.createModelWithMiddlewares(finalModelId)
|
||||
return await generateText({ model, ...transformedParams })
|
||||
}
|
||||
)
|
||||
}
|
||||
|
||||
/**
|
||||
* 生成结构化对象
|
||||
* 用户友好的API，内部使用插件处理能力
|
||||
*/
|
||||
async generateObject(
|
||||
model: LanguageModelV1,
|
||||
params: Omit<Parameters<typeof generateObject>[0], 'model'>
|
||||
): Promise<ReturnType<typeof generateObject>>
|
||||
async generateObject(
|
||||
model: LanguageModelV1,
|
||||
params?: Omit<Parameters<typeof generateObject>[0], 'model'>
|
||||
): Promise<ReturnType<typeof generateObject>> {
|
||||
// 传统方式：使用插件处理逻辑
|
||||
return this.pluginClient.executeWithPlugins(
|
||||
'generateObject',
|
||||
model.modelId,
|
||||
params!,
|
||||
async (finalModelId, transformedParams) => {
|
||||
// const model = await this.pluginClient.createModelWithMiddlewares(finalModelId)
|
||||
return await generateObject({ model, ...transformedParams })
|
||||
}
|
||||
)
|
||||
}
|
||||
|
||||
/**
|
||||
* 流式生成结构化对象
|
||||
* 用户友好的API，内部使用插件处理能力
|
||||
*/
|
||||
async streamObject(
|
||||
model: LanguageModelV1,
|
||||
params: Omit<Parameters<typeof streamObject>[0], 'model'>
|
||||
): Promise<ReturnType<typeof streamObject>>
|
||||
async streamObject(
|
||||
model: LanguageModelV1,
|
||||
params?: Omit<Parameters<typeof streamObject>[0], 'model'>
|
||||
): Promise<ReturnType<typeof streamObject>> {
|
||||
// 传统方式：使用插件处理逻辑
|
||||
return this.pluginClient.executeWithPlugins(
|
||||
'streamObject',
|
||||
model.modelId,
|
||||
params!,
|
||||
async (finalModelId, transformedParams) => {
|
||||
// const model = await this.pluginClient.createModelWithMiddlewares(finalModelId)
|
||||
return await streamObject({ model, ...transformedParams })
|
||||
}
|
||||
)
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取插件统计信息（只读）
|
||||
*/
|
||||
getPluginStats() {
|
||||
return this.pluginClient.getPluginStats()
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取所有插件（只读）
|
||||
*/
|
||||
getPlugins() {
|
||||
return this.pluginClient.getPlugins()
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取客户端信息
|
||||
*/
|
||||
getClientInfo() {
|
||||
return this.pluginClient.getClientInfo()
|
||||
}
|
||||
|
||||
// === 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, plugins?: AiPlugin[]): AiExecutor<T>
|
||||
static create(providerId: string, plugins?: AiPlugin[]): AiExecutor<any>
|
||||
static create(providerId: string, plugins: AiPlugin[] = []): AiExecutor {
|
||||
return new AiExecutor({
|
||||
providerId,
|
||||
plugins
|
||||
})
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建OpenAI Compatible执行器
|
||||
*/
|
||||
static createOpenAICompatible(plugins: AiPlugin[] = []): AiExecutor<'openai-compatible'> {
|
||||
return new AiExecutor({
|
||||
providerId: 'openai-compatible',
|
||||
plugins
|
||||
})
|
||||
}
|
||||
}
|
||||
47
packages/aiCore/src/core/execution/index.ts
Normal file
47
packages/aiCore/src/core/execution/index.ts
Normal file
@ -0,0 +1,47 @@
|
||||
/**
|
||||
* Execution 模块导出
|
||||
* 提供执行器能力
|
||||
*/
|
||||
|
||||
// 主要执行器
|
||||
export { AiExecutor } from './AiExecutor'
|
||||
export type { ExecutionOptions, ExecutorConfig, GenericExecutorConfig } from './types'
|
||||
|
||||
// 便捷工厂函数
|
||||
import { type ProviderId, type ProviderSettingsMap } from '../../types'
|
||||
import { type AiPlugin } from '../plugins'
|
||||
import { AiExecutor } from './AiExecutor'
|
||||
|
||||
/**
|
||||
* 创建AI执行器 - 支持类型安全的已知provider
|
||||
*/
|
||||
export function createExecutor<T extends ProviderId>(
|
||||
providerId: T,
|
||||
options: ProviderSettingsMap[T],
|
||||
plugins?: AiPlugin[]
|
||||
): AiExecutor<T>
|
||||
|
||||
/**
|
||||
* 创建AI执行器 - 支持未知provider
|
||||
*/
|
||||
export function createExecutor(providerId: string, options: any, plugins?: AiPlugin[]): AiExecutor<any>
|
||||
|
||||
export function createExecutor(providerId: string, options: any, plugins: AiPlugin[] = []): AiExecutor {
|
||||
return AiExecutor.create(providerId, plugins)
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建OpenAI Compatible执行器
|
||||
*/
|
||||
export function createOpenAICompatibleExecutor(
|
||||
options: ProviderSettingsMap['openai-compatible'],
|
||||
plugins: AiPlugin[] = []
|
||||
): AiExecutor<'openai-compatible'> {
|
||||
return AiExecutor.createOpenAICompatible(plugins)
|
||||
}
|
||||
|
||||
// 为了未来的agent功能预留目录结构
|
||||
// 未来将在 ./agents/ 文件夹中添加：
|
||||
// - AgentExecutor.ts
|
||||
// - WorkflowManager.ts
|
||||
// - ConversationManager.ts
|
||||
29
packages/aiCore/src/core/execution/types.ts
Normal file
29
packages/aiCore/src/core/execution/types.ts
Normal file
@ -0,0 +1,29 @@
|
||||
/**
|
||||
* Execution 层类型定义
|
||||
*/
|
||||
import { type ProviderId } from '../../types'
|
||||
import { type AiPlugin } from '../plugins'
|
||||
|
||||
/**
|
||||
* 执行器配置
|
||||
*/
|
||||
export interface ExecutorConfig<T extends ProviderId = ProviderId> {
|
||||
providerId: T
|
||||
plugins?: AiPlugin[]
|
||||
}
|
||||
|
||||
/**
|
||||
* 通用执行器配置（用于未知provider）
|
||||
*/
|
||||
export interface GenericExecutorConfig {
|
||||
providerId: string
|
||||
plugins?: AiPlugin[]
|
||||
}
|
||||
|
||||
/**
|
||||
* 执行选项
|
||||
*/
|
||||
export interface ExecutionOptions {
|
||||
// 未来可以添加执行级别的选项
|
||||
// 比如：超时设置、重试机制等
|
||||
}
|
||||
25
packages/aiCore/src/core/index.ts
Normal file
25
packages/aiCore/src/core/index.ts
Normal file
@ -0,0 +1,25 @@
|
||||
/**
|
||||
* 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 { MiddlewareManager, wrapModelWithMiddlewares } from './middleware'
|
||||
|
||||
// 创建管理
|
||||
export type { ModelCreationRequest, ResolvedConfig } from './creation'
|
||||
export {
|
||||
createBaseModel,
|
||||
createImageModel,
|
||||
createModel,
|
||||
createModelFromConfig,
|
||||
getProviderInfo,
|
||||
getSupportedProviders,
|
||||
ProviderCreationError,
|
||||
resolveConfig
|
||||
} from './creation'
|
||||
|
||||
// 执行管理
|
||||
export type { ExecutionOptions, ExecutorConfig, GenericExecutorConfig } from './execution'
|
||||
export { AiExecutor } from './execution'
|
||||
16
packages/aiCore/src/core/middleware/MiddlewareManager.ts
Normal file
16
packages/aiCore/src/core/middleware/MiddlewareManager.ts
Normal file
@ -0,0 +1,16 @@
|
||||
/**
|
||||
* 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 { LanguageModelV1Middleware } from 'ai'
|
||||
|
||||
/**
|
||||
* 创建中间件列表
|
||||
* 合并用户提供的中间件
|
||||
*/
|
||||
export function createMiddlewares(userMiddlewares: LanguageModelV1Middleware[] = []): LanguageModelV1Middleware[] {
|
||||
// 未来可以在这里添加默认的中间件
|
||||
const defaultMiddlewares: LanguageModelV1Middleware[] = []
|
||||
|
||||
return [...defaultMiddlewares, ...userMiddlewares]
|
||||
}
|
||||
22
packages/aiCore/src/core/middleware/ModelWrapper.ts
Normal file
22
packages/aiCore/src/core/middleware/ModelWrapper.ts
Normal file
@ -0,0 +1,22 @@
|
||||
/**
|
||||
* 模型包装工具函数
|
||||
* 用于将中间件应用到LanguageModel上
|
||||
*/
|
||||
import { LanguageModel, LanguageModelV1Middleware, wrapLanguageModel } from 'ai'
|
||||
|
||||
/**
|
||||
* 使用中间件包装模型
|
||||
*/
|
||||
export function wrapModelWithMiddlewares(
|
||||
model: LanguageModel,
|
||||
middlewares: LanguageModelV1Middleware[]
|
||||
): LanguageModel {
|
||||
if (middlewares.length === 0) {
|
||||
return model
|
||||
}
|
||||
|
||||
return wrapLanguageModel({
|
||||
model,
|
||||
middleware: middlewares
|
||||
})
|
||||
}
|
||||
8
packages/aiCore/src/core/middleware/index.ts
Normal file
8
packages/aiCore/src/core/middleware/index.ts
Normal file
@ -0,0 +1,8 @@
|
||||
/**
|
||||
* Middleware 模块导出
|
||||
* 提供通用的中间件管理能力
|
||||
*/
|
||||
|
||||
export { MiddlewareManager } from './MiddlewareManager'
|
||||
export { wrapModelWithMiddlewares } from './ModelWrapper'
|
||||
export type { NamedMiddleware } from './types'
|
||||
12
packages/aiCore/src/core/middleware/types.ts
Normal file
12
packages/aiCore/src/core/middleware/types.ts
Normal file
@ -0,0 +1,12 @@
|
||||
/**
|
||||
* 中间件系统类型定义
|
||||
*/
|
||||
import { LanguageModelV1Middleware } from 'ai'
|
||||
|
||||
/**
|
||||
* 具名中间件接口
|
||||
*/
|
||||
export interface NamedMiddleware {
|
||||
name: string
|
||||
middleware: LanguageModelV1Middleware
|
||||
}
|
||||
@ -1,7 +1,7 @@
|
||||
import { AnthropicProviderOptions } from '@ai-sdk/anthropic'
|
||||
import { GoogleGenerativeAIProviderOptions } from '@ai-sdk/google'
|
||||
import { OpenAIResponsesProviderOptions } from '@ai-sdk/openai'
|
||||
import { LanguageModelV1ProviderMetadata } from '@ai-sdk/provider'
|
||||
import { type AnthropicProviderOptions } from '@ai-sdk/anthropic'
|
||||
import { type GoogleGenerativeAIProviderOptions } from '@ai-sdk/google'
|
||||
import { type OpenAIResponsesProviderOptions } from '@ai-sdk/openai'
|
||||
import { type LanguageModelV1ProviderMetadata } from '@ai-sdk/provider'
|
||||
|
||||
export type ProviderOptions<T extends keyof LanguageModelV1ProviderMetadata> = LanguageModelV1ProviderMetadata[T]
|
||||
|
||||
@ -2,7 +2,7 @@ import { openai } from '@ai-sdk/openai'
|
||||
import { streamText } from 'ai'
|
||||
|
||||
import { PluginEnabledAiClient } from '../../clients/PluginEnabledAiClient'
|
||||
import { createContext, PluginManager } from '../'
|
||||
import { createContext, PluginManager } from '..'
|
||||
import { ContentFilterPlugin, LoggingPlugin } from './example-plugins'
|
||||
|
||||
/**
|
||||
@ -1,4 +1,4 @@
|
||||
import type { LanguageModelV1Middleware, TextStreamPart, ToolSet } from 'ai'
|
||||
import type { TextStreamPart, ToolSet } from 'ai'
|
||||
|
||||
import { AiPlugin, AiRequestContext } from './types'
|
||||
|
||||
@ -135,13 +135,6 @@ export class PluginManager {
|
||||
>
|
||||
}
|
||||
|
||||
/**
|
||||
* 收集所有 AI SDK 原生中间件
|
||||
*/
|
||||
collectAiSdkMiddlewares(): LanguageModelV1Middleware[] {
|
||||
return this.plugins.flatMap((plugin) => plugin.aiSdkMiddlewares || [])
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取所有插件信息
|
||||
*/
|
||||
@ -1,4 +1,4 @@
|
||||
import type { LanguageModelV1Middleware, TextStreamPart, ToolSet } from 'ai'
|
||||
import type { TextStreamPart, ToolSet } from 'ai'
|
||||
|
||||
/**
|
||||
* 生命周期阶段定义
|
||||
@ -62,7 +62,7 @@ export interface AiPlugin {
|
||||
}) => TransformStream<TextStreamPart<TOOLS>, TextStreamPart<TOOLS>>
|
||||
|
||||
// AI SDK 原生中间件
|
||||
aiSdkMiddlewares?: LanguageModelV1Middleware[]
|
||||
// aiSdkMiddlewares?: LanguageModelV1Middleware[]
|
||||
}
|
||||
|
||||
/**
|
||||
@ -4,50 +4,57 @@
|
||||
*/
|
||||
|
||||
// 导入内部使用的类和函数
|
||||
import { ApiClientFactory } from './clients/ApiClientFactory'
|
||||
import { createClient } from './clients/PluginEnabledAiClient'
|
||||
import { type ProviderSettingsMap } from './clients/types'
|
||||
import { createUniversalClient } from './clients/UniversalAiSdkClient'
|
||||
import { aiProviderRegistry, isProviderSupported } from './providers/registry'
|
||||
import { createClient } from './core/clients/PluginEnabledAiClient'
|
||||
import {
|
||||
getProviderInfo as factoryGetProviderInfo,
|
||||
getSupportedProviders as factoryGetSupportedProviders
|
||||
} from './core/creation'
|
||||
import { AiExecutor } from './core/execution/AiExecutor'
|
||||
import { aiProviderRegistry, isProviderSupported } from './core/providers/registry'
|
||||
import { type ProviderSettingsMap } from './types'
|
||||
|
||||
// ==================== 主要客户端接口 ====================
|
||||
// 默认使用集成插件系统的客户端
|
||||
// ==================== 主要用户接口 ====================
|
||||
// orchestration层 - 面向用户的主要API
|
||||
export {
|
||||
AiExecutor,
|
||||
generateObject,
|
||||
generateText,
|
||||
type OrchestrationConfig,
|
||||
streamObject,
|
||||
streamText
|
||||
} from './orchestration'
|
||||
|
||||
// 为了向后兼容，保留AiClient别名（内部使用PluginEnabledAiClient）
|
||||
export {
|
||||
PluginEnabledAiClient as AiClient,
|
||||
createClient,
|
||||
createCompatibleClient
|
||||
} from './clients/PluginEnabledAiClient'
|
||||
|
||||
// 为了向后兼容，也导出原名称
|
||||
export { PluginEnabledAiClient } from './clients/PluginEnabledAiClient'
|
||||
} from './core/clients/PluginEnabledAiClient'
|
||||
|
||||
// ==================== 插件系统 ====================
|
||||
export type { AiPlugin, AiRequestContext, HookResult, HookType, PluginManagerConfig } from './plugins'
|
||||
export { createContext, definePlugin, PluginManager } from './plugins'
|
||||
|
||||
// ==================== 底层客户端（高级用法） ====================
|
||||
// 不带插件系统的基础客户端，用于需要绕过插件系统的场景
|
||||
export {
|
||||
createOpenAICompatibleClient as createBasicOpenAICompatibleClient,
|
||||
createUniversalClient,
|
||||
UniversalAiSdkClient
|
||||
} from './clients/UniversalAiSdkClient'
|
||||
export type { AiPlugin, AiRequestContext, HookResult, HookType, PluginManagerConfig } from './core/plugins'
|
||||
export { createContext, definePlugin, PluginManager } from './core/plugins'
|
||||
|
||||
// ==================== 低级 API ====================
|
||||
export { ApiClientFactory } from './clients/ApiClientFactory'
|
||||
export { aiProviderRegistry } from './providers/registry'
|
||||
export {
|
||||
createBaseModel as createApiClient,
|
||||
createImageModel,
|
||||
getProviderInfo as getClientInfo,
|
||||
getSupportedProviders,
|
||||
ProviderCreationError
|
||||
} from './core/creation'
|
||||
export { aiProviderRegistry } from './core/providers/registry'
|
||||
|
||||
// ==================== 类型定义 ====================
|
||||
export type { ClientFactoryError } from './clients/ApiClientFactory'
|
||||
export type { ProviderConfig } from './core/providers/registry'
|
||||
export type { ProviderError } from './core/providers/types'
|
||||
export type {
|
||||
GenerateObjectParams,
|
||||
GenerateTextParams,
|
||||
ProviderSettings,
|
||||
StreamObjectParams,
|
||||
StreamTextParams
|
||||
} from './clients/types'
|
||||
export type { ProviderConfig } from './providers/registry'
|
||||
export type { ProviderError } from './providers/types'
|
||||
} from './types'
|
||||
export * as aiSdk from 'ai'
|
||||
|
||||
// ==================== AI SDK 常用类型导出 ====================
|
||||
@ -110,7 +117,7 @@ export type {
|
||||
VercelProviderSettings,
|
||||
XaiProviderSettings,
|
||||
ZhipuProviderSettings
|
||||
} from './clients/types'
|
||||
} from './types'
|
||||
|
||||
// ==================== 选项 ====================
|
||||
export {
|
||||
@ -121,11 +128,10 @@ export {
|
||||
mergeProviderOptions,
|
||||
type ProviderOptionsMap,
|
||||
type TypedProviderOptions
|
||||
} from './options'
|
||||
} from './core/options'
|
||||
|
||||
// ==================== 工具函数 ====================
|
||||
export { createClient as createApiClient, getClientInfo, getSupportedProviders } from './clients/ApiClientFactory'
|
||||
export { getAllProviders, getProvider, isProviderSupported, registerProvider } from './providers/registry'
|
||||
export { getAllProviders, getProvider, isProviderSupported, registerProvider } from './core/providers/registry'
|
||||
|
||||
// ==================== Provider 配置工厂 ====================
|
||||
export {
|
||||
@ -134,7 +140,7 @@ export {
|
||||
type ProviderConfigBuilder,
|
||||
providerConfigBuilder,
|
||||
ProviderConfigFactory
|
||||
} from './providers/factory'
|
||||
} from './core/providers/factory'
|
||||
|
||||
// ==================== 包信息 ====================
|
||||
export const AI_CORE_VERSION = '1.0.0'
|
||||
@ -146,19 +152,19 @@ export const AiCore = {
|
||||
version: AI_CORE_VERSION,
|
||||
name: AI_CORE_NAME,
|
||||
|
||||
// 创建主要客户端（默认带插件系统）
|
||||
create(providerId: string, options: any = {}, plugins: any[] = []) {
|
||||
return createClient(providerId, options, plugins)
|
||||
// 创建主要执行器（推荐使用）
|
||||
create(providerId: string, plugins: any[] = []) {
|
||||
return AiExecutor.create(providerId, plugins)
|
||||
},
|
||||
|
||||
// 创建基础客户端（不带插件系统）
|
||||
createBasic(providerId: string, options: any = {}) {
|
||||
return createUniversalClient(providerId, options)
|
||||
// 创建底层客户端（高级用法）
|
||||
createClient(providerId: string, plugins: any[] = []) {
|
||||
return createClient(providerId, plugins)
|
||||
},
|
||||
|
||||
// 获取支持的providers
|
||||
getSupportedProviders() {
|
||||
return ApiClientFactory.getSupportedProviders()
|
||||
return factoryGetSupportedProviders()
|
||||
},
|
||||
|
||||
// 检查provider支持
|
||||
@ -168,24 +174,42 @@ export const AiCore = {
|
||||
|
||||
// 获取客户端信息
|
||||
getClientInfo(providerId: string) {
|
||||
return ApiClientFactory.getClientInfo(providerId)
|
||||
return factoryGetProviderInfo(providerId)
|
||||
}
|
||||
}
|
||||
|
||||
// 推荐使用的执行器创建函数
|
||||
export const createOpenAIExecutor = (options: ProviderSettingsMap['openai'], plugins?: any[]) => {
|
||||
return AiExecutor.create('openai', plugins)
|
||||
}
|
||||
|
||||
export const createAnthropicExecutor = (options: ProviderSettingsMap['anthropic'], plugins?: any[]) => {
|
||||
return AiExecutor.create('anthropic', plugins)
|
||||
}
|
||||
|
||||
export const createGoogleExecutor = (options: ProviderSettingsMap['google'], plugins?: any[]) => {
|
||||
return AiExecutor.create('google', plugins)
|
||||
}
|
||||
|
||||
export const createXAIExecutor = (options: ProviderSettingsMap['xai'], plugins?: any[]) => {
|
||||
return AiExecutor.create('xai', plugins)
|
||||
}
|
||||
|
||||
// 向后兼容的客户端创建函数
|
||||
export const createOpenAIClient = (options: ProviderSettingsMap['openai'], plugins?: any[]) => {
|
||||
return createClient('openai', options, plugins)
|
||||
return createClient('openai', plugins)
|
||||
}
|
||||
|
||||
export const createAnthropicClient = (options: ProviderSettingsMap['anthropic'], plugins?: any[]) => {
|
||||
return createClient('anthropic', options, plugins)
|
||||
return createClient('anthropic', plugins)
|
||||
}
|
||||
|
||||
export const createGoogleClient = (options: ProviderSettingsMap['google'], plugins?: any[]) => {
|
||||
return createClient('google', options, plugins)
|
||||
return createClient('google', plugins)
|
||||
}
|
||||
|
||||
export const createXAIClient = (options: ProviderSettingsMap['xai'], plugins?: any[]) => {
|
||||
return createClient('xai', options, plugins)
|
||||
return createClient('xai', plugins)
|
||||
}
|
||||
|
||||
// ==================== 调试和开发工具 ====================
|
||||
|
||||
148
packages/aiCore/src/orchestration/api.ts
Normal file
148
packages/aiCore/src/orchestration/api.ts
Normal file
@ -0,0 +1,148 @@
|
||||
/**
|
||||
* AI 编排器
|
||||
* 编排层 - 面向用户的主要API，串联creation和execution层
|
||||
*/
|
||||
import {
|
||||
generateObject as aiGenerateObject,
|
||||
generateText as aiGenerateText,
|
||||
streamObject as aiStreamObject,
|
||||
streamText as aiStreamText
|
||||
} from 'ai'
|
||||
|
||||
import { createModelFromConfig, resolveConfig } from '../core/creation'
|
||||
import { AiExecutor } from '../core/execution/AiExecutor'
|
||||
import {
|
||||
type GenerateObjectParams,
|
||||
type GenerateTextParams,
|
||||
type StreamObjectParams,
|
||||
type StreamTextParams
|
||||
} from '../types'
|
||||
import { type OrchestrationConfig } from './types'
|
||||
|
||||
/**
|
||||
* 流式文本生成
|
||||
* 编排：creation层获取model → 执行器执行
|
||||
*/
|
||||
// export async function streamText<T extends ProviderId>(
|
||||
// modelId: string,
|
||||
// params: StreamTextParams,
|
||||
// config: OrchestrationConfig<T>
|
||||
// ): Promise<ReturnType<typeof aiStreamText>>
|
||||
export async function streamText(
|
||||
modelId: string,
|
||||
params: StreamTextParams,
|
||||
config: OrchestrationConfig
|
||||
): Promise<ReturnType<typeof aiStreamText>> {
|
||||
// 外部 registry 方式：直接使用用户提供的 model
|
||||
// if ('model' in configOrParams) {
|
||||
// return aiStreamText(configOrParams)
|
||||
// }
|
||||
|
||||
// 1. 使用 creation 层解析配置并创建 model
|
||||
const resolvedConfig = resolveConfig(
|
||||
config.providerId,
|
||||
modelId!,
|
||||
config.options,
|
||||
config.plugins || [],
|
||||
config.middlewares || [] // middlewares
|
||||
)
|
||||
const model = await createModelFromConfig(resolvedConfig)
|
||||
// const providerOptions = extractProviderOptions(resolvedConfig)
|
||||
|
||||
// 2. 创建执行器并传入 model
|
||||
const executor = AiExecutor.create(config.providerId, config.plugins)
|
||||
return executor.streamText(model, params!)
|
||||
}
|
||||
|
||||
/**
|
||||
* 生成文本
|
||||
* 编排：creation层获取model → 执行器执行
|
||||
*/
|
||||
export async function generateText(
|
||||
modelId: string,
|
||||
params: GenerateTextParams,
|
||||
config: OrchestrationConfig
|
||||
): Promise<ReturnType<typeof aiGenerateText>> {
|
||||
// 外部 registry 方式：直接使用用户提供的 model
|
||||
// if ('model' in configOrParams) {
|
||||
// return aiGenerateText(configOrParams)
|
||||
// }
|
||||
|
||||
// 编排方式：1. creation层获取model 2. execution层执行
|
||||
// 1. 使用 creation 层解析配置并创建 model
|
||||
const resolvedConfig = resolveConfig(
|
||||
config.providerId,
|
||||
modelId!,
|
||||
config.options,
|
||||
config.plugins || [],
|
||||
config.middlewares || [] // middlewares
|
||||
)
|
||||
const model = await createModelFromConfig(resolvedConfig)
|
||||
// const providerOptions = extractProviderOptions(resolvedConfig)
|
||||
|
||||
// 2. 创建执行器并传入 model
|
||||
const executor = AiExecutor.create(config.providerId, config.plugins)
|
||||
return executor.generateText(model, params!)
|
||||
}
|
||||
|
||||
/**
|
||||
* 生成结构化对象
|
||||
* 编排：creation层获取model → 执行器执行
|
||||
*/
|
||||
export async function generateObject(
|
||||
modelId: string,
|
||||
params: GenerateObjectParams,
|
||||
config: OrchestrationConfig
|
||||
): Promise<ReturnType<typeof aiGenerateObject>> {
|
||||
// 外部 registry 方式：直接使用用户提供的 model
|
||||
// if ('model' in configOrParams) {
|
||||
// return aiGenerateObject(configOrParams)
|
||||
// }
|
||||
|
||||
// 编排方式：1. creation层获取model 2. execution层执行
|
||||
// 1. 使用 creation 层解析配置并创建 model
|
||||
const resolvedConfig = resolveConfig(
|
||||
config.providerId,
|
||||
modelId!,
|
||||
config.options,
|
||||
config.plugins || [],
|
||||
config.middlewares || [] // middlewares
|
||||
)
|
||||
const model = await createModelFromConfig(resolvedConfig)
|
||||
// const providerOptions = extractProviderOptions(resolvedConfig)
|
||||
|
||||
// 2. 创建执行器并传入 model
|
||||
const executor = AiExecutor.create(config.providerId, config.plugins)
|
||||
return executor.generateObject(model, params!)
|
||||
}
|
||||
|
||||
/**
|
||||
* 流式生成结构化对象
|
||||
* 编排：creation层获取model → 执行器执行
|
||||
*/
|
||||
export async function streamObject(
|
||||
modelId: string,
|
||||
params: StreamObjectParams,
|
||||
config: OrchestrationConfig
|
||||
): Promise<ReturnType<typeof aiStreamObject>> {
|
||||
// 外部 registry 方式：直接使用用户提供的 model
|
||||
// if ('model' in configOrParams) {
|
||||
// return aiStreamObject(configOrParams)
|
||||
// }
|
||||
|
||||
// 编排方式：1. creation层获取model 2. execution层执行
|
||||
// 1. 使用 creation 层解析配置并创建 model
|
||||
const resolvedConfig = resolveConfig(
|
||||
config.providerId,
|
||||
modelId!,
|
||||
config.options,
|
||||
config.plugins || [],
|
||||
config.middlewares || [] // middlewares
|
||||
)
|
||||
const model = await createModelFromConfig(resolvedConfig)
|
||||
// const providerOptions = extractProviderOptions(resolvedConfig)
|
||||
|
||||
// 2. 创建执行器并传入 model
|
||||
const executor = AiExecutor.create(config.providerId, config.plugins)
|
||||
return executor.streamObject(model, params!)
|
||||
}
|
||||
13
packages/aiCore/src/orchestration/index.ts
Normal file
13
packages/aiCore/src/orchestration/index.ts
Normal file
@ -0,0 +1,13 @@
|
||||
/**
|
||||
* 编排层导出
|
||||
* 面向用户的编排层接口
|
||||
*/
|
||||
|
||||
// 主要编排函数
|
||||
export { generateObject, generateText, streamObject, streamText } from './api'
|
||||
|
||||
// 类型定义
|
||||
export type { OrchestrationConfig } from './types'
|
||||
|
||||
// 为了向后兼容，重新导出AiExecutor
|
||||
export { AiExecutor } from '../core/execution/AiExecutor'
|
||||
26
packages/aiCore/src/orchestration/types.ts
Normal file
26
packages/aiCore/src/orchestration/types.ts
Normal file
@ -0,0 +1,26 @@
|
||||
/**
|
||||
* Orchestration 层类型定义
|
||||
* 面向用户的编排层接口
|
||||
*/
|
||||
import { LanguageModelV1Middleware } from 'ai'
|
||||
|
||||
import { type AiPlugin } from '../core/plugins'
|
||||
import { type ProviderId, type ProviderSettingsMap } from '../types'
|
||||
|
||||
/**
|
||||
* 编排配置
|
||||
*/
|
||||
export interface OrchestrationConfig<T extends ProviderId = ProviderId> {
|
||||
providerId: T
|
||||
options: ProviderSettingsMap[T]
|
||||
plugins?: AiPlugin[]
|
||||
middlewares?: LanguageModelV1Middleware[]
|
||||
}
|
||||
|
||||
/**
|
||||
* 编排选项
|
||||
*/
|
||||
export interface OrchestrationOptions {
|
||||
// 未来可以添加编排级别的选项
|
||||
// 比如：重试机制、超时设置、日志级别等
|
||||
}
|
||||
@ -1,6 +1,6 @@
|
||||
import { generateObject, generateText, streamObject, streamText } from 'ai'
|
||||
|
||||
import type { ProviderSettingsMap } from '../providers/registry'
|
||||
import type { ProviderSettingsMap } from './core/providers/registry'
|
||||
|
||||
// ProviderSettings 是所有 Provider Settings 的联合类型
|
||||
export type ProviderSettings = ProviderSettingsMap[keyof ProviderSettingsMap]
|
||||
@ -39,4 +39,4 @@ export type {
|
||||
VercelProviderSettings,
|
||||
XaiProviderSettings,
|
||||
ZhipuProviderSettings
|
||||
} from '../providers/registry'
|
||||
} from './core/providers/registry'
|
||||
@ -18,7 +18,7 @@ import {
|
||||
isWebSearchModel
|
||||
} from '@renderer/config/models'
|
||||
import { getAssistantSettings, getDefaultModel } from '@renderer/services/AssistantService'
|
||||
import type { Assistant, MCPTool, MCPToolResponse, Message, Model } from '@renderer/types'
|
||||
import type { Assistant, MCPTool, MCPToolInputSchema, MCPToolResponse, Message, Model } from '@renderer/types'
|
||||
import { FileTypes } from '@renderer/types'
|
||||
import { callMCPTool } from '@renderer/utils/mcp-tools'
|
||||
import { findFileBlocks, findImageBlocks, getMainTextContent } from '@renderer/utils/messageUtils/find'
|
||||
@ -221,11 +221,11 @@ export async function buildStreamTextParams(
|
||||
(isSupportedDisableGenerationModel(model) ? assistant.enableGenerateImage || false : true)
|
||||
|
||||
// 构建系统提示
|
||||
const systemPrompt = assistant.prompt || ''
|
||||
let systemPrompt = assistant.prompt || ''
|
||||
// TODO:根据调用类型判断是否添加systemPrompt
|
||||
// if (mcpTools && mcpTools.length > 0) {
|
||||
// systemPrompt = await buildSystemPromptWithTools(systemPrompt, mcpTools, assistant)
|
||||
// }
|
||||
if (mcpTools && mcpTools.length > 0 && assistant.settings?.toolUseMode === 'prompt') {
|
||||
systemPrompt = await buildSystemPromptWithTools(systemPrompt, mcpTools, assistant)
|
||||
}
|
||||
|
||||
// 构建真正的 providerOptions
|
||||
const providerOptions = buildProviderOptions(assistant, model, {
|
||||
@ -275,104 +275,28 @@ export async function buildGenerateTextParams(
|
||||
}
|
||||
|
||||
/**
|
||||
* 简单的 JSON Schema 到 Zod Schema 转换
|
||||
* 支持基本类型：string, number, boolean, array, object
|
||||
* 将 MCPToolInputSchema 转换为 JSONSchema7 格式
|
||||
*/
|
||||
// function jsonSchemaToZod(schema: MCPToolInputSchema): z.ZodObject<any> {
|
||||
// const properties: Record<string, z.ZodTypeAny> = {}
|
||||
// const required = schema.required || []
|
||||
function convertMcpSchemaToJsonSchema7(schema: MCPToolInputSchema): any {
|
||||
// 创建符合 JSONSchema7 的对象
|
||||
const jsonSchema7: Record<string, any> = {
|
||||
type: 'object',
|
||||
properties: schema.properties || {},
|
||||
required: schema.required || []
|
||||
}
|
||||
|
||||
// // 处理每个属性
|
||||
// for (const [key, propSchema] of Object.entries(schema.properties)) {
|
||||
// let zodSchema: z.ZodTypeAny
|
||||
// 如果有 description，添加它
|
||||
if (schema.description) {
|
||||
jsonSchema7.description = schema.description
|
||||
}
|
||||
|
||||
// // 根据 JSON Schema 类型创建对应的 Zod Schema
|
||||
// const schemaType = (propSchema as any).type
|
||||
// switch (schemaType) {
|
||||
// case 'string': {
|
||||
// let stringSchema = z.string()
|
||||
// if ((propSchema as any).description) {
|
||||
// stringSchema = stringSchema.describe((propSchema as any).description)
|
||||
// }
|
||||
// if ((propSchema as any).enum) {
|
||||
// zodSchema = z.enum((propSchema as any).enum)
|
||||
// } else {
|
||||
// zodSchema = stringSchema
|
||||
// }
|
||||
// break
|
||||
// }
|
||||
// 如果有 title，添加它
|
||||
if (schema.title) {
|
||||
jsonSchema7.title = schema.title
|
||||
}
|
||||
|
||||
// case 'number':
|
||||
// case 'integer': {
|
||||
// let numberSchema = z.number()
|
||||
// if (schemaType === 'integer') {
|
||||
// numberSchema = numberSchema.int()
|
||||
// }
|
||||
// if ((propSchema as any).minimum !== undefined) {
|
||||
// numberSchema = numberSchema.min((propSchema as any).minimum)
|
||||
// }
|
||||
// if ((propSchema as any).maximum !== undefined) {
|
||||
// numberSchema = numberSchema.max((propSchema as any).maximum)
|
||||
// }
|
||||
// if ((propSchema as any).description) {
|
||||
// numberSchema = numberSchema.describe((propSchema as any).description)
|
||||
// }
|
||||
// zodSchema = numberSchema
|
||||
// break
|
||||
// }
|
||||
|
||||
// case 'boolean': {
|
||||
// let booleanSchema = z.boolean()
|
||||
// if ((propSchema as any).description) {
|
||||
// booleanSchema = booleanSchema.describe((propSchema as any).description)
|
||||
// }
|
||||
// zodSchema = booleanSchema
|
||||
// break
|
||||
// }
|
||||
|
||||
// case 'array': {
|
||||
// let itemSchema: z.ZodTypeAny = z.any()
|
||||
// const itemsType = (propSchema as any).items?.type
|
||||
// if (itemsType === 'string') {
|
||||
// itemSchema = z.string()
|
||||
// } else if (itemsType === 'number') {
|
||||
// itemSchema = z.number()
|
||||
// }
|
||||
// let arraySchema = z.array(itemSchema)
|
||||
// if ((propSchema as any).description) {
|
||||
// arraySchema = arraySchema.describe((propSchema as any).description)
|
||||
// }
|
||||
// zodSchema = arraySchema
|
||||
// break
|
||||
// }
|
||||
|
||||
// case 'object': {
|
||||
// // 对于嵌套对象，简单处理为 z.record
|
||||
// let objectSchema = z.record(z.any())
|
||||
// if ((propSchema as any).description) {
|
||||
// objectSchema = objectSchema.describe((propSchema as any).description)
|
||||
// }
|
||||
// zodSchema = objectSchema
|
||||
// break
|
||||
// }
|
||||
|
||||
// default: {
|
||||
// // 默认为 any
|
||||
// zodSchema = z.any()
|
||||
// break
|
||||
// }
|
||||
// }
|
||||
|
||||
// // 如果不是必需字段，添加 optional()
|
||||
// if (!required.includes(key)) {
|
||||
// zodSchema = zodSchema.optional()
|
||||
// }
|
||||
|
||||
// properties[key] = zodSchema
|
||||
// }
|
||||
|
||||
// return z.object(properties)
|
||||
// }
|
||||
return jsonSchema7
|
||||
}
|
||||
|
||||
/**
|
||||
* 将 MCPTool 转换为 AI SDK 工具格式
|
||||
@ -384,7 +308,7 @@ export function convertMcpToolsToAiSdkTools(mcpTools: MCPTool[]): Record<string,
|
||||
console.log('mcpTool', mcpTool.inputSchema)
|
||||
tools[mcpTool.name] = tool({
|
||||
description: mcpTool.description || `Tool from ${mcpTool.serverName}`,
|
||||
parameters: jsonSchema<Record<string, object>>(mcpTool.inputSchema),
|
||||
parameters: jsonSchema<Record<string, object>>(convertMcpSchemaToJsonSchema7(mcpTool.inputSchema)),
|
||||
execute: async (params) => {
|
||||
console.log('execute_params', params)
|
||||
// 创建适配的 MCPToolResponse 对象
|
||||
|
||||
Loading…
Reference in New Issue
Block a user