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refactor: simplify AI Core architecture and enhance runtime execution
- Restructured the AI Core documentation to reflect a simplified two-layer architecture, focusing on clear responsibilities between models and runtime layers. - Removed the orchestration layer and consolidated its functionality into the runtime layer, streamlining the API for users. - Introduced a new runtime executor for managing plugin-enhanced AI calls, improving the handling of execution and middleware. - Updated the core modules to enhance type safety and usability, including comprehensive type definitions for model creation and execution configurations. - Removed obsolete files and refactored existing code to improve organization and maintainability across the SDK.
This commit is contained in:
lizhixuan
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@ -4,7 +4,7 @@
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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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- **简化分层**：`models`（模型层）→ `runtime`（运行时层），清晰的职责分离
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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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@ -12,15 +12,17 @@
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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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- **Agent就绪**：为将来集成 OpenAI Agents SDK 预留扩展空间
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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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- **分层设计**：清晰的职责分离，便于维护和扩展
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- **简化设计**：函数式API，避免过度抽象
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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**：通用的流转换和参数处理插件系统
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- **面向未来**：为 OpenAI Agents SDK 集成做好准备
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## 2. 整体架构图
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@ -32,34 +34,26 @@ graph TD
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end
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subgraph "packages/aiCore (AI Core 包)"
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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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subgraph "Runtime Layer (运行时层)"
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RuntimeExecutor["RuntimeExecutor (运行时执行器)"]
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PluginEngine["PluginEngine (插件引擎)"]
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RuntimeAPI["Runtime API (便捷函数)"]
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end
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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 "Models Layer (模型层)"
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ModelFactory["createModel() (模型工厂)"]
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ProviderCreator["ProviderCreator (提供商创建器)"]
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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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subgraph "Core Systems (核心系统)"
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subgraph "Plugins (插件)"
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PluginManager["PluginManager (插件管理)"]
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BuiltInPlugins["Built-in Plugins (内置插件)"]
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StreamTransforms["Stream Transforms (流转换)"]
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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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MiddlewareWrapper["wrapModelWithMiddlewares() (中间件包装)"]
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end
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subgraph "Providers (提供商)"
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@ -78,16 +72,19 @@ graph TD
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Others["其他 19+ Providers"]
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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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subgraph "Future: OpenAI Agents SDK"
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AgentSDK["@openai/agents (未来集成)"]
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AgentExtensions["Agent Extensions (预留)"]
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end
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UI --> RuntimeAPI
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Components --> RuntimeExecutor
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RuntimeAPI --> RuntimeExecutor
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RuntimeExecutor --> PluginEngine
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RuntimeExecutor --> ModelFactory
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PluginEngine --> PluginManager
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ModelFactory --> ProviderCreator
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ModelFactory --> MiddlewareWrapper
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ProviderCreator --> Registry
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Registry --> Factory
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Factory --> OpenAI
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@ -96,51 +93,48 @@ graph TD
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Factory --> XAI
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Factory --> Others
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PluginClient --> AICore
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PluginEngine --> 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 --> StreamTransforms
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PluginManager --> BuiltInPlugins
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%% 未来集成路径
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RuntimeExecutor -.-> AgentSDK
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AgentSDK -.-> AgentExtensions
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```
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## 3. 包结构设计
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### 3.1 当前架构文件结构
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### 3.1 新架构文件结构
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```
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packages/aiCore/
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├── src/
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│ ├── 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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│ │ ├── models/ # 模型层 - 模型创建和配置
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│ │ │ ├── factory.ts # 模型工厂函数 ✅
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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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│ │ │ ├── types.ts # 模型类型定义 ✅
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│ │ │ └── index.ts # 模型层导出 ✅
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│ │ ├── runtime/ # 运行时层 - 执行和用户API
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│ │ │ ├── executor.ts # 运行时执行器 ✅
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│ │ │ ├── plugin-engine.ts # 插件引擎 ✅
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│ │ │ ├── types.ts # 运行时类型定义 ✅
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│ │ │ └── index.ts # 运行时导出 ✅
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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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│ │ │ ├── built-in/ # 内置插件 ✅
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│ │ │ │ ├── logging.ts # 日志插件 ✅
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│ │ │ │ └── index.ts # 内置插件导出 ✅
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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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@ -159,143 +153,147 @@ packages/aiCore/
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## 4. 架构分层详解
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### 4.1 Orchestration Layer (编排层)
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### 4.1 Models Layer (模型层)
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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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**职责**：统一的模型创建和配置管理
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**核心文件**：
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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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- `factory.ts`: 模型工厂函数 (`createModel`, `createModels`)
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- `ProviderCreator.ts`: 底层提供商创建和模型实例化
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- `types.ts`: 模型配置类型定义
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**设计特点**：
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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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- 函数式设计，避免不必要的类抽象
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- 统一的模型配置接口
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- 自动处理中间件应用
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- 支持批量模型创建
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**核心API**：
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```typescript
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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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// 模型配置接口
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export interface ModelConfig {
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providerId: ProviderId
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modelId: string
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options: ProviderSettingsMap[ProviderId]
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middlewares?: LanguageModelV1Middleware[]
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}
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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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// 核心模型创建函数
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export async function createModel(config: ModelConfig): Promise<LanguageModel>
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export async function createModels(configs: ModelConfig[]): Promise<LanguageModel[]>
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```
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### 4.2 Core Layer (核心层)
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### 4.2 Runtime Layer (运行时层)
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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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**职责**：运行时执行器和用户面向的API接口
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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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- `executor.ts`: 运行时执行器类
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- `plugin-engine.ts`: 插件引擎（原PluginEnabledAiClient）
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- `index.ts`: 便捷函数和工厂方法
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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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- 提供三种使用方式：类实例、静态工厂、函数式调用
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- 自动集成模型创建和插件处理
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- 完整的类型安全支持
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- 为 OpenAI Agents SDK 预留扩展接口
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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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// 运行时执行器
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export class RuntimeExecutor<T extends ProviderId = ProviderId> {
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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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plugins?: AiPlugin[]
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): RuntimeExecutor<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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async streamText(modelId: string, params: StreamTextParams): Promise<StreamTextResult>
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async generateText(modelId: string, params: GenerateTextParams): Promise<GenerateTextResult>
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async streamObject(modelId: string, params: StreamObjectParams): Promise<StreamObjectResult>
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async generateObject(modelId: string, params: GenerateObjectParams): Promise<GenerateObjectResult>
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}
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// 便捷函数式API
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export async function streamText<T extends ProviderId>(
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providerId: T,
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options: ProviderSettingsMap[T],
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modelId: string,
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params: StreamTextParams,
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plugins?: AiPlugin[]
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): Promise<StreamTextResult>
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```
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#### 4.2.3 Clients Layer (客户端层)
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### 4.3 Plugin System (插件系统)
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**职责**：插件处理，连接插件系统和AI SDK
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**职责**：可扩展的插件架构
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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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- `PluginManager`: 插件生命周期管理
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- `built-in/`: 内置插件集合
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- 流转换收集和应用
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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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- 借鉴 Rollup 的钩子分类设计
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- 支持流转换 (`experimental_transform`)
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- 内置常用插件（日志、计数等）
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- 完整的生命周期钩子
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#### 4.2.4 Middleware Layer (中间件层)
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**插件接口**：
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```typescript
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export interface AiPlugin {
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name: string
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enforce?: 'pre' | 'post'
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// 【First】首个钩子 - 只执行第一个返回值的插件
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resolveModel?: (modelId: string, context: AiRequestContext) => string | null | Promise<string | null>
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loadTemplate?: (templateName: string, context: AiRequestContext) => any | null | Promise<any | null>
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// 【Sequential】串行钩子 - 链式执行，支持数据转换
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transformParams?: (params: any, context: AiRequestContext) => any | Promise<any>
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transformResult?: (result: any, context: AiRequestContext) => any | Promise<any>
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// 【Parallel】并行钩子 - 不依赖顺序，用于副作用
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onRequestStart?: (context: AiRequestContext) => void | Promise<void>
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onRequestEnd?: (context: AiRequestContext, result: any) => void | Promise<void>
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onError?: (error: Error, context: AiRequestContext) => void | Promise<void>
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// 【Stream】流处理
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transformStream?: () => TransformStream
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}
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```
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### 4.4 Middleware System (中间件系统)
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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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- `ModelWrapper.ts`: 模型包装函数
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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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- 函数式设计，简化使用
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#### 4.2.5 Plugins Layer (插件层)
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```typescript
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export function wrapModelWithMiddlewares(
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model: LanguageModel,
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middlewares: LanguageModelV1Middleware[]
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): LanguageModel
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```
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**职责**：特定的插件功能
|
||||
|
||||
**核心组件**：
|
||||
|
||||
- `PluginManager`: 插件管理器
|
||||
- 流转换收集：`collectStreamTransforms`
|
||||
|
||||
**设计特点**：
|
||||
|
||||
- 支持流转换 (`experimental_transform`)
|
||||
- 与AI SDK中间件分离
|
||||
- 专注于特定需求
|
||||
|
||||
#### 4.2.6 Providers Layer (提供商层)
|
||||
### 4.5 Provider System (提供商系统)
|
||||
|
||||
**职责**：AI Provider注册表和动态导入
|
||||
|
||||
@ -313,192 +311,194 @@ export class AiExecutor<T extends ProviderId = any> {
|
||||
|
||||
## 5. 使用方式
|
||||
|
||||
### 5.1 推荐使用方式 (Orchestration API)
|
||||
### 5.1 函数式调用 (推荐 - 简单场景)
|
||||
|
||||
```typescript
|
||||
import { streamText, generateText } from '@cherrystudio/ai-core'
|
||||
import { streamText, generateText } from '@cherrystudio/ai-core/runtime'
|
||||
|
||||
// 配置模式使用
|
||||
const config = {
|
||||
providerId: 'openai',
|
||||
options: { apiKey: 'your-api-key' },
|
||||
plugins: [thinkingPlugin, toolPlugin]
|
||||
}
|
||||
|
||||
// 流式文本生成
|
||||
const stream = await streamText(config, 'gpt-4', {
|
||||
messages: [{ role: 'user', content: 'Hello!' }]
|
||||
})
|
||||
|
||||
// 普通文本生成
|
||||
const result = await generateText(config, 'gpt-4', {
|
||||
messages: [{ role: 'user', content: 'Hello!' }]
|
||||
})
|
||||
// 直接函数调用
|
||||
const stream = await streamText(
|
||||
'anthropic',
|
||||
{ apiKey: 'your-api-key' },
|
||||
'claude-3',
|
||||
{ messages: [{ role: 'user', content: 'Hello!' }] },
|
||||
[loggingPlugin]
|
||||
)
|
||||
```
|
||||
|
||||
### 5.2 直接AI SDK模式 (兼容性)
|
||||
### 5.2 执行器实例 (推荐 - 复杂场景)
|
||||
|
||||
```typescript
|
||||
import { streamText } from '@cherrystudio/ai-core'
|
||||
import { openai } from '@ai-sdk/openai'
|
||||
import { createExecutor } from '@cherrystudio/ai-core/runtime'
|
||||
|
||||
// 直接使用AI SDK模式
|
||||
const stream = await streamText({
|
||||
model: openai('gpt-4'),
|
||||
messages: [{ role: 'user', content: 'Hello!' }]
|
||||
})
|
||||
```
|
||||
// 创建可复用的执行器
|
||||
const executor = createExecutor('openai', { apiKey: 'your-api-key' }, [plugin1, plugin2])
|
||||
|
||||
### 5.3 执行器模式 (高级用法)
|
||||
|
||||
```typescript
|
||||
import { AiExecutor } from '@cherrystudio/ai-core'
|
||||
|
||||
// 创建执行器
|
||||
const executor = AiExecutor.create('openai', { apiKey: 'your-api-key' }, [plugin1, plugin2])
|
||||
|
||||
// 使用执行器
|
||||
// 多次使用
|
||||
const stream = await executor.streamText('gpt-4', {
|
||||
messages: [{ role: 'user', content: 'Hello!' }]
|
||||
})
|
||||
```
|
||||
|
||||
## 6. 插件系统详解
|
||||
|
||||
### 6.1 插件接口设计
|
||||
|
||||
```typescript
|
||||
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>
|
||||
}
|
||||
```
|
||||
|
||||
### 6.2 流转换支持
|
||||
|
||||
专门针对 `streamText` 的流转换功能：
|
||||
|
||||
```typescript
|
||||
// 插件收集流转换
|
||||
const streamTransforms = pluginManager.collectStreamTransforms(context)
|
||||
|
||||
// 应用到AI SDK
|
||||
const result = await streamText({
|
||||
model,
|
||||
...params,
|
||||
experimental_transform: streamTransforms.length > 0 ? composeTransforms(streamTransforms) : undefined
|
||||
const result = await executor.generateText('gpt-4', {
|
||||
messages: [{ role: 'user', content: 'How are you?' }]
|
||||
})
|
||||
```
|
||||
|
||||
### 6.3 插件vs中间件
|
||||
### 5.3 静态工厂方法
|
||||
|
||||
| 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 |
|
||||
```typescript
|
||||
import { RuntimeExecutor } from '@cherrystudio/ai-core/runtime'
|
||||
|
||||
// 静态创建
|
||||
const executor = RuntimeExecutor.create('anthropic', { apiKey: 'your-api-key' })
|
||||
await executor.streamText('claude-3', { messages: [...] })
|
||||
```
|
||||
|
||||
### 5.4 直接模型创建 (高级用法)
|
||||
|
||||
```typescript
|
||||
import { createModel } from '@cherrystudio/ai-core/models'
|
||||
import { streamText } from 'ai'
|
||||
|
||||
// 直接创建模型使用
|
||||
const model = await createModel({
|
||||
providerId: 'openai',
|
||||
modelId: 'gpt-4',
|
||||
options: { apiKey: 'your-api-key' },
|
||||
middlewares: [middleware1, middleware2]
|
||||
})
|
||||
|
||||
// 直接使用 AI SDK
|
||||
const result = await streamText({ model, messages: [...] })
|
||||
```
|
||||
|
||||
## 6. 为 OpenAI Agents SDK 预留的设计
|
||||
|
||||
### 6.1 架构兼容性
|
||||
|
||||
当前架构完全兼容 OpenAI Agents SDK 的集成需求：
|
||||
|
||||
```typescript
|
||||
// 当前的模型创建
|
||||
const model = await createModel({
|
||||
providerId: 'anthropic',
|
||||
modelId: 'claude-3',
|
||||
options: { apiKey: 'xxx' }
|
||||
})
|
||||
|
||||
// 将来可以直接用于 OpenAI Agents SDK
|
||||
import { Agent, run } from '@openai/agents'
|
||||
|
||||
const agent = new Agent({
|
||||
model, // ✅ 直接兼容 LanguageModel 接口
|
||||
name: 'Assistant',
|
||||
instructions: '...',
|
||||
tools: [tool1, tool2]
|
||||
})
|
||||
|
||||
const result = await run(agent, 'user input')
|
||||
```
|
||||
|
||||
### 6.2 预留的扩展点
|
||||
|
||||
1. **runtime/agents/** 目录预留
|
||||
2. **AgentExecutor** 类预留
|
||||
3. **Agent工具转换插件** 预留
|
||||
4. **多Agent编排** 预留
|
||||
|
||||
### 6.3 未来架构扩展
|
||||
|
||||
```
|
||||
packages/aiCore/src/core/
|
||||
├── runtime/
|
||||
│ ├── agents/ # 🚀 未来添加
|
||||
│ │ ├── AgentExecutor.ts
|
||||
│ │ ├── WorkflowManager.ts
|
||||
│ │ └── ConversationManager.ts
|
||||
│ ├── executor.ts
|
||||
│ └── index.ts
|
||||
```
|
||||
|
||||
## 7. 架构优势
|
||||
|
||||
### 7.1 分层清晰
|
||||
### 7.1 简化设计
|
||||
|
||||
- **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
|
||||
- **移除过度抽象**：删除了orchestration层和creation层的复杂包装
|
||||
- **函数式优先**：models层使用函数而非类
|
||||
- **直接明了**：runtime层直接提供用户API
|
||||
|
||||
### 7.2 函数式设计
|
||||
### 7.2 职责清晰
|
||||
|
||||
- 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
|
||||
- **Models**: 专注模型创建和配置
|
||||
- **Runtime**: 专注执行和用户API
|
||||
- **Plugins**: 专注扩展功能
|
||||
- **Providers**: 专注AI Provider管理
|
||||
|
||||
### 7.3 类型安全
|
||||
|
||||
- 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
|
||||
- AI SDK 类型的直接复用
|
||||
- 避免类型重复定义
|
||||
|
||||
### 7.4 灵活扩展
|
||||
### 7.4 灵活使用
|
||||
|
||||
- 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
|
||||
- 三种使用模式满足不同需求
|
||||
- 从简单函数调用到复杂执行器
|
||||
- 支持直接AI SDK使用
|
||||
|
||||
## 8. 迁移状态
|
||||
### 7.5 面向未来
|
||||
|
||||
### 8.1 已完成 ✅
|
||||
- 为 OpenAI Agents SDK 集成做好准备
|
||||
- 清晰的扩展点和架构边界
|
||||
- 模块化设计便于功能添加
|
||||
|
||||
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
|
||||
## 8. 技术决策记录
|
||||
|
||||
### 8.2 进行中 🔄
|
||||
### 8.1 为什么选择简化的两层架构？
|
||||
|
||||
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
|
||||
- **职责分离**：models专注创建，runtime专注执行
|
||||
- **模块化**：每层都有清晰的边界和职责
|
||||
- **扩展性**：为Agent功能预留了清晰的扩展空间
|
||||
|
||||
### 8.3 计划中 📋
|
||||
### 8.2 为什么选择函数式设计？
|
||||
|
||||
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
|
||||
- **简洁性**：避免不必要的类设计
|
||||
- **性能**：减少对象创建开销
|
||||
- **易用性**：函数调用更直观
|
||||
|
||||
## 9. 技术决策记录
|
||||
|
||||
### 9.1 为什么选择分层架构？
|
||||
|
||||
- **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
|
||||
|
||||
### 9.2 为什么选择函数式设计？
|
||||
|
||||
- **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
|
||||
|
||||
### 9.3 为什么分离插件和中间件？
|
||||
### 8.3 为什么分离插件和中间件？
|
||||
|
||||
- **职责明确**: 插件处理应用特定需求
|
||||
- **原生支持**: 中间件使用AI SDK原生功能
|
||||
- **灵活性**: 两套系统可以独立演进
|
||||
|
||||
## 10. 总结
|
||||
## 9. 总结
|
||||
|
||||
新的AI Core架构实现了：
|
||||
AI Core架构实现了：
|
||||
|
||||
### 10.1 设计目标
|
||||
### 9.1 核心特点
|
||||
|
||||
- ✅ **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
|
||||
- ✅ **简化架构**: 2层核心架构，职责清晰
|
||||
- ✅ **函数式设计**: models层完全函数化
|
||||
- ✅ **类型安全**: 统一的类型定义和AI SDK类型复用
|
||||
- ✅ **插件扩展**: 强大的插件系统
|
||||
- ✅ **多种使用方式**: 满足不同复杂度需求
|
||||
- ✅ **Agent就绪**: 为OpenAI Agents SDK集成做好准备
|
||||
|
||||
### 10.2 核心价值
|
||||
### 9.2 核心价值
|
||||
|
||||
- **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
|
||||
- **灵活使用**: 函数式、实例式、静态工厂式
|
||||
- **强类型**: 完整的TypeScript支持
|
||||
- **可扩展**: 插件和中间件双重扩展能力
|
||||
- **高性能**: 最小化包装，直接使用AI SDK
|
||||
- **面向未来**: Agent SDK集成架构就绪
|
||||
|
||||
### 10.3 未来发展
|
||||
### 9.3 未来发展
|
||||
|
||||
这个架构提供了坚实的AI基础设施，支持：
|
||||
这个架构提供了：
|
||||
|
||||
- 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
|
||||
- **优秀的开发体验**: 简洁的API和清晰的使用模式
|
||||
- **强大的扩展能力**: 为Agent功能预留了完整的架构空间
|
||||
- **良好的维护性**: 职责分离明确，代码易于维护
|
||||
- **广泛的适用性**: 既适合简单调用也适合复杂应用
|
||||
|
||||
@ -6,7 +6,6 @@ Cherry Studio AI Core 是一个基于 Vercel AI SDK 的统一 AI Provider 接口
|
||||
|
||||
- 🚀 统一的 AI Provider 接口
|
||||
- 🔄 动态导入支持
|
||||
- 💾 智能缓存机制
|
||||
- 🛠️ TypeScript 支持
|
||||
- 📦 轻量级设计
|
||||
|
||||
|
||||
@ -1,15 +0,0 @@
|
||||
/**
|
||||
* 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'
|
||||
@ -1,174 +0,0 @@
|
||||
/**
|
||||
* 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
|
||||
})
|
||||
}
|
||||
}
|
||||
@ -1,47 +0,0 @@
|
||||
/**
|
||||
* 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
|
||||
@ -5,21 +5,19 @@
|
||||
|
||||
// 中间件系统
|
||||
export type { NamedMiddleware } from './middleware'
|
||||
export { MiddlewareManager, wrapModelWithMiddlewares } from './middleware'
|
||||
export { createMiddlewares, wrapModelWithMiddlewares } from './middleware'
|
||||
|
||||
// 创建管理
|
||||
export type { ModelCreationRequest, ResolvedConfig } from './creation'
|
||||
export type { ModelCreationRequest, ResolvedConfig } from './models'
|
||||
export {
|
||||
createBaseModel,
|
||||
createImageModel,
|
||||
createModel,
|
||||
createModelFromConfig,
|
||||
getProviderInfo,
|
||||
getSupportedProviders,
|
||||
ProviderCreationError,
|
||||
resolveConfig
|
||||
} from './creation'
|
||||
ProviderCreationError
|
||||
} from './models'
|
||||
|
||||
// 执行管理
|
||||
export type { ExecutionOptions, ExecutorConfig, GenericExecutorConfig } from './execution'
|
||||
export { AiExecutor } from './execution'
|
||||
export type { ExecutionOptions, ExecutorConfig } from './runtime'
|
||||
export { createExecutor, createOpenAICompatibleExecutor } from './runtime'
|
||||
|
||||
@ -3,6 +3,6 @@
|
||||
* 提供通用的中间件管理能力
|
||||
*/
|
||||
|
||||
export { MiddlewareManager } from './MiddlewareManager'
|
||||
export { wrapModelWithMiddlewares } from './ModelWrapper'
|
||||
export { createMiddlewares } from './manager'
|
||||
export type { NamedMiddleware } from './types'
|
||||
export { wrapModelWithMiddlewares } from './wrapper'
|
||||
|
||||
@ -5,7 +5,7 @@
|
||||
import { LanguageModelV1Middleware } from 'ai'
|
||||
|
||||
import { ProviderId, ProviderSettingsMap } from '../../types'
|
||||
import { createMiddlewares } from '../middleware/MiddlewareManager'
|
||||
import { createMiddlewares } from '../middleware/manager'
|
||||
import { AiPlugin } from '../plugins'
|
||||
import { ResolvedConfig } from './types'
|
||||
|
||||
@ -105,13 +105,11 @@ export async function createImageModel<T extends ProviderId>(
|
||||
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',
|
||||
51
packages/aiCore/src/core/models/factory.ts
Normal file
51
packages/aiCore/src/core/models/factory.ts
Normal file
@ -0,0 +1,51 @@
|
||||
/**
|
||||
* 模型工厂函数
|
||||
* 统一的模型创建和配置管理
|
||||
*/
|
||||
import { LanguageModel, LanguageModelV1Middleware } from 'ai'
|
||||
|
||||
import { type ProviderId, type ProviderSettingsMap } from '../../types'
|
||||
import { wrapModelWithMiddlewares } from '../middleware'
|
||||
import { createBaseModel } from './ProviderCreator'
|
||||
|
||||
export interface ModelConfig {
|
||||
providerId: ProviderId
|
||||
modelId: string
|
||||
options: ProviderSettingsMap[ProviderId]
|
||||
middlewares?: LanguageModelV1Middleware[]
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建模型 - 核心函数
|
||||
*/
|
||||
export async function createModel(config: ModelConfig): Promise<LanguageModel> {
|
||||
validateModelConfig(config)
|
||||
|
||||
// 1. 创建基础模型
|
||||
const baseModel = await createBaseModel(config.providerId, config.modelId, config.options)
|
||||
|
||||
// 2. 应用中间件（如果有）
|
||||
return config.middlewares?.length ? wrapModelWithMiddlewares(baseModel, config.middlewares) : baseModel
|
||||
}
|
||||
|
||||
/**
|
||||
* 批量创建模型
|
||||
*/
|
||||
export async function createModels(configs: ModelConfig[]): Promise<LanguageModel[]> {
|
||||
return Promise.all(configs.map((config) => createModel(config)))
|
||||
}
|
||||
|
||||
/**
|
||||
* 验证模型配置
|
||||
*/
|
||||
function validateModelConfig(config: ModelConfig): void {
|
||||
if (!config.providerId) {
|
||||
throw new Error('ModelConfig: providerId is required')
|
||||
}
|
||||
if (!config.modelId) {
|
||||
throw new Error('ModelConfig: modelId is required')
|
||||
}
|
||||
if (!config.options) {
|
||||
throw new Error('ModelConfig: options is required')
|
||||
}
|
||||
}
|
||||
19
packages/aiCore/src/core/models/index.ts
Normal file
19
packages/aiCore/src/core/models/index.ts
Normal file
@ -0,0 +1,19 @@
|
||||
/**
|
||||
* Models 模块导出
|
||||
* 提供统一的模型创建和配置管理能力
|
||||
*/
|
||||
|
||||
// 主要的模型创建API
|
||||
export { createModel, createModels, type ModelConfig } from './factory'
|
||||
|
||||
// 底层Provider创建功能（供高级用户使用）
|
||||
export {
|
||||
createBaseModel,
|
||||
createImageModel,
|
||||
getProviderInfo,
|
||||
getSupportedProviders,
|
||||
ProviderCreationError
|
||||
} from './ProviderCreator'
|
||||
|
||||
// 保留原有类型
|
||||
export type { ModelCreationRequest, ResolvedConfig } from './types'
|
||||
@ -4,8 +4,6 @@
|
||||
|
||||
## 🎯 设计理念
|
||||
|
||||
借鉴 Rollup/Vite 的成熟插件思想：
|
||||
|
||||
- **语义清晰**：不同钩子有不同的执行语义
|
||||
- **类型安全**：TypeScript 完整支持
|
||||
- **性能优化**：First 短路、Parallel 并发、Sequential 链式
|
||||
|
||||
7
packages/aiCore/src/core/plugins/built-in/index.ts
Normal file
7
packages/aiCore/src/core/plugins/built-in/index.ts
Normal file
@ -0,0 +1,7 @@
|
||||
/**
|
||||
* 内置插件命名空间
|
||||
* 所有内置插件都以 'built-in:' 为前缀
|
||||
*/
|
||||
export const BUILT_IN_PLUGIN_PREFIX = 'built-in:'
|
||||
|
||||
export { createLoggingPlugin } from './logging'
|
||||
86
packages/aiCore/src/core/plugins/built-in/logging.ts
Normal file
86
packages/aiCore/src/core/plugins/built-in/logging.ts
Normal file
@ -0,0 +1,86 @@
|
||||
/**
|
||||
* 内置插件：日志记录
|
||||
* 记录AI调用的关键信息，支持性能监控和调试
|
||||
*/
|
||||
import { definePlugin } from '../index'
|
||||
import type { AiRequestContext } from '../types'
|
||||
|
||||
export interface LoggingConfig {
|
||||
// 日志级别
|
||||
level?: 'debug' | 'info' | 'warn' | 'error'
|
||||
// 是否记录参数
|
||||
logParams?: boolean
|
||||
// 是否记录结果
|
||||
logResult?: boolean
|
||||
// 是否记录性能数据
|
||||
logPerformance?: boolean
|
||||
// 自定义日志函数
|
||||
logger?: (level: string, message: string, data?: any) => void
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建日志插件
|
||||
*/
|
||||
export function createLoggingPlugin(config: LoggingConfig = {}) {
|
||||
const { level = 'info', logParams = true, logResult = false, logPerformance = true, logger = console.log } = config
|
||||
|
||||
const startTimes = new Map<string, number>()
|
||||
|
||||
return definePlugin({
|
||||
name: 'built-in:logging',
|
||||
|
||||
onRequestStart: (context: AiRequestContext) => {
|
||||
const requestId = context.requestId
|
||||
startTimes.set(requestId, Date.now())
|
||||
|
||||
logger(level, `🚀 AI Request Started`, {
|
||||
requestId,
|
||||
providerId: context.providerId,
|
||||
modelId: context.modelId,
|
||||
originalParams: logParams ? context.originalParams : '[hidden]'
|
||||
})
|
||||
},
|
||||
|
||||
onRequestEnd: (context: AiRequestContext, result: any) => {
|
||||
const requestId = context.requestId
|
||||
const startTime = startTimes.get(requestId)
|
||||
const duration = startTime ? Date.now() - startTime : undefined
|
||||
startTimes.delete(requestId)
|
||||
|
||||
const logData: any = {
|
||||
requestId,
|
||||
providerId: context.providerId,
|
||||
modelId: context.modelId
|
||||
}
|
||||
|
||||
if (logPerformance && duration) {
|
||||
logData.duration = `${duration}ms`
|
||||
}
|
||||
|
||||
if (logResult) {
|
||||
logData.result = result
|
||||
}
|
||||
|
||||
logger(level, `✅ AI Request Completed`, logData)
|
||||
},
|
||||
|
||||
onError: (error: Error, context: AiRequestContext) => {
|
||||
const requestId = context.requestId
|
||||
const startTime = startTimes.get(requestId)
|
||||
const duration = startTime ? Date.now() - startTime : undefined
|
||||
startTimes.delete(requestId)
|
||||
|
||||
logger('error', `❌ AI Request Failed`, {
|
||||
requestId,
|
||||
providerId: context.providerId,
|
||||
modelId: context.modelId,
|
||||
duration: duration ? `${duration}ms` : undefined,
|
||||
error: {
|
||||
name: error.name,
|
||||
message: error.message,
|
||||
stack: error.stack
|
||||
}
|
||||
})
|
||||
}
|
||||
})
|
||||
}
|
||||
@ -1,255 +0,0 @@
|
||||
import { openai } from '@ai-sdk/openai'
|
||||
import { streamText } from 'ai'
|
||||
|
||||
import { PluginEnabledAiClient } from '../../clients/PluginEnabledAiClient'
|
||||
import { createContext, PluginManager } from '..'
|
||||
import { ContentFilterPlugin, LoggingPlugin } from './example-plugins'
|
||||
|
||||
/**
|
||||
* 使用 PluginEnabledAiClient 的推荐方式
|
||||
* 这是最简单直接的使用方法
|
||||
*/
|
||||
export async function exampleWithPluginEnabledClient() {
|
||||
console.log('=== 使用 PluginEnabledAiClient 示例 ===')
|
||||
|
||||
// 1. 创建带插件的客户端 - 链式调用方式
|
||||
const client = PluginEnabledAiClient.create('openai-compatible', {
|
||||
name: 'openai',
|
||||
baseURL: 'https://api.openai.com/v1',
|
||||
apiKey: process.env.OPENAI_API_KEY || 'sk-test'
|
||||
})
|
||||
.use(LoggingPlugin)
|
||||
.use(ContentFilterPlugin)
|
||||
|
||||
// 2. 或者在创建时传入插件（也可以这样使用）
|
||||
// const clientWithPlugins = PluginEnabledAiClient.create(
|
||||
// 'openai-compatible',
|
||||
// {
|
||||
// name: 'openai',
|
||||
// baseURL: 'https://api.openai.com/v1',
|
||||
// apiKey: process.env.OPENAI_API_KEY || 'sk-test'
|
||||
// },
|
||||
// [LoggingPlugin, ContentFilterPlugin]
|
||||
// )
|
||||
|
||||
// 3. 查看插件统计信息
|
||||
console.log('插件统计:', client.getPluginStats())
|
||||
|
||||
try {
|
||||
// 4. 使用客户端进行 AI 调用（插件会自动生效）
|
||||
console.log('开始生成文本...')
|
||||
const result = await client.generateText('gpt-4', {
|
||||
messages: [{ role: 'user', content: 'Hello, world!' }],
|
||||
temperature: 0.7
|
||||
})
|
||||
|
||||
console.log('生成的文本:', result.text)
|
||||
|
||||
// 5. 流式调用（支持流转换器）
|
||||
console.log('开始流式生成...')
|
||||
const streamResult = await client.streamText('gpt-4', {
|
||||
messages: [{ role: 'user', content: 'Tell me a short story about AI' }]
|
||||
})
|
||||
|
||||
console.log('开始流式响应...')
|
||||
for await (const textPart of streamResult.textStream) {
|
||||
process.stdout.write(textPart)
|
||||
}
|
||||
console.log('\n流式响应完成')
|
||||
|
||||
return result
|
||||
} catch (error) {
|
||||
console.error('调用失败:', error)
|
||||
throw error
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建 OpenAI Compatible 客户端的示例
|
||||
*/
|
||||
export function exampleOpenAICompatible() {
|
||||
console.log('=== OpenAI Compatible 示例 ===')
|
||||
|
||||
// Ollama 示例
|
||||
const ollama = PluginEnabledAiClient.createOpenAICompatible(
|
||||
{
|
||||
name: 'ollama',
|
||||
baseURL: 'http://localhost:11434/v1'
|
||||
},
|
||||
[LoggingPlugin]
|
||||
)
|
||||
|
||||
// LM Studio 示例
|
||||
const lmStudio = PluginEnabledAiClient.createOpenAICompatible({
|
||||
name: 'lm-studio',
|
||||
baseURL: 'http://localhost:1234/v1'
|
||||
}).use(ContentFilterPlugin)
|
||||
|
||||
console.log('Ollama 插件统计:', ollama.getPluginStats())
|
||||
console.log('LM Studio 插件统计:', lmStudio.getPluginStats())
|
||||
|
||||
return { ollama, lmStudio }
|
||||
}
|
||||
|
||||
/**
|
||||
* 动态插件管理示例
|
||||
*/
|
||||
export function exampleDynamicPlugins() {
|
||||
console.log('=== 动态插件管理示例 ===')
|
||||
|
||||
const client = PluginEnabledAiClient.create('openai-compatible', {
|
||||
name: 'openai',
|
||||
baseURL: 'https://api.openai.com/v1',
|
||||
apiKey: 'your-api-key'
|
||||
})
|
||||
|
||||
console.log('初始状态:', client.getPluginStats())
|
||||
|
||||
// 动态添加插件
|
||||
client.use(LoggingPlugin)
|
||||
console.log('添加 LoggingPlugin 后:', client.getPluginStats())
|
||||
|
||||
client.usePlugins([ContentFilterPlugin])
|
||||
console.log('添加 ContentFilterPlugin 后:', client.getPluginStats())
|
||||
|
||||
// 移除插件
|
||||
client.removePlugin('content-filter')
|
||||
console.log('移除 content-filter 后:', client.getPluginStats())
|
||||
|
||||
return client
|
||||
}
|
||||
|
||||
/**
|
||||
* 完整的低级 API 示例（原有的 example-usage.ts 的方式）
|
||||
* 这种方式适合需要精细控制插件生命周期的场景
|
||||
*/
|
||||
export async function exampleLowLevelApi() {
|
||||
console.log('=== 低级 API 示例 ===')
|
||||
|
||||
// 1. 创建插件管理器
|
||||
const pluginManager = new PluginManager([LoggingPlugin, ContentFilterPlugin])
|
||||
|
||||
// 2. 创建请求上下文
|
||||
const context = createContext('openai', 'gpt-4', {
|
||||
messages: [{ role: 'user', content: 'Hello!' }]
|
||||
})
|
||||
|
||||
try {
|
||||
// 3. 触发请求开始事件
|
||||
await pluginManager.executeParallel('onRequestStart', context)
|
||||
|
||||
// 4. 解析模型别名
|
||||
const resolvedModel = await pluginManager.executeFirst('resolveModel', 'gpt-4', context)
|
||||
console.log('Resolved model:', resolvedModel || 'gpt-4')
|
||||
|
||||
// 5. 转换请求参数
|
||||
const params = {
|
||||
messages: [{ role: 'user' as const, content: 'Hello, AI!' }],
|
||||
temperature: 0.7
|
||||
}
|
||||
const transformedParams = await pluginManager.executeSequential('transformParams', params, context)
|
||||
|
||||
// 6. 收集流转换器（关键：AI SDK 原生支持数组！）
|
||||
const streamTransforms = pluginManager.collectStreamTransforms()
|
||||
|
||||
// 7. 调用 AI SDK，直接传入转换器工厂数组
|
||||
const result = await streamText({
|
||||
model: openai('gpt-4'),
|
||||
...transformedParams,
|
||||
experimental_transform: streamTransforms // 直接传入工厂函数数组
|
||||
})
|
||||
|
||||
// 8. 处理结果
|
||||
let fullText = ''
|
||||
for await (const textPart of result.textStream) {
|
||||
fullText += textPart
|
||||
console.log('Streaming:', textPart)
|
||||
}
|
||||
|
||||
// 9. 转换最终结果
|
||||
const finalResult = { text: fullText, usage: await result.usage }
|
||||
const transformedResult = await pluginManager.executeSequential('transformResult', finalResult, context)
|
||||
|
||||
// 10. 触发完成事件
|
||||
await pluginManager.executeParallel('onRequestEnd', context, transformedResult)
|
||||
|
||||
return transformedResult
|
||||
} catch (error) {
|
||||
// 11. 触发错误事件
|
||||
await pluginManager.executeParallel('onError', context, undefined, error as Error)
|
||||
throw error
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 流转换器数组的其他使用方式
|
||||
*/
|
||||
export function demonstrateStreamTransforms() {
|
||||
console.log('=== 流转换器示例 ===')
|
||||
|
||||
const pluginManager = new PluginManager([
|
||||
ContentFilterPlugin,
|
||||
{
|
||||
name: 'text-replacer',
|
||||
transformStream() {
|
||||
return () =>
|
||||
new TransformStream({
|
||||
transform(chunk, controller) {
|
||||
if (chunk.type === 'text-delta') {
|
||||
const replaced = chunk.textDelta.replace(/hello/gi, 'hi')
|
||||
controller.enqueue({ ...chunk, textDelta: replaced })
|
||||
} else {
|
||||
controller.enqueue(chunk)
|
||||
}
|
||||
}
|
||||
})
|
||||
}
|
||||
}
|
||||
])
|
||||
|
||||
// 获取所有流转换器
|
||||
const transforms = pluginManager.collectStreamTransforms()
|
||||
console.log(`收集到 ${transforms.length} 个流转换器`)
|
||||
|
||||
// 可以单独使用每个转换器
|
||||
transforms.forEach((factory, index) => {
|
||||
console.log(`转换器 ${index + 1} 已准备就绪`)
|
||||
const transform = factory({ stopStream: () => {} })
|
||||
console.log('Transform created:', transform)
|
||||
})
|
||||
|
||||
return transforms
|
||||
}
|
||||
|
||||
/**
|
||||
* 运行所有示例
|
||||
*/
|
||||
export async function runAllExamples() {
|
||||
console.log('🚀 开始运行所有示例...\n')
|
||||
|
||||
try {
|
||||
// 1. PluginEnabledAiClient 示例（推荐）
|
||||
await exampleWithPluginEnabledClient()
|
||||
console.log('✅ PluginEnabledAiClient 示例完成\n')
|
||||
|
||||
// 2. OpenAI Compatible 示例
|
||||
exampleOpenAICompatible()
|
||||
console.log('✅ OpenAI Compatible 示例完成\n')
|
||||
|
||||
// 3. 动态插件管理示例
|
||||
exampleDynamicPlugins()
|
||||
console.log('✅ 动态插件管理示例完成\n')
|
||||
|
||||
// 4. 流转换器示例
|
||||
demonstrateStreamTransforms()
|
||||
console.log('✅ 流转换器示例完成\n')
|
||||
|
||||
// 5. 低级 API 示例
|
||||
// await exampleLowLevelApi()
|
||||
console.log('✅ 低级 API 示例完成\n')
|
||||
|
||||
console.log('🎉 所有示例运行完成！')
|
||||
} catch (error) {
|
||||
console.error('❌ 示例运行失败:', error)
|
||||
}
|
||||
}
|
||||
@ -21,3 +21,5 @@ export function createContext(providerId: string, modelId: string, originalParam
|
||||
export function definePlugin(plugin: AiPlugin): AiPlugin {
|
||||
return plugin
|
||||
}
|
||||
|
||||
export { createLoggingPlugin } from './built-in/logging'
|
||||
|
||||
@ -3,7 +3,7 @@ import type { TextStreamPart, ToolSet } from 'ai'
|
||||
import { AiPlugin, AiRequestContext } from './types'
|
||||
|
||||
/**
|
||||
* 插件管理器 - 基于 Rollup 钩子分类设计
|
||||
* 插件管理器
|
||||
*/
|
||||
export class PluginManager {
|
||||
private plugins: AiPlugin[] = []
|
||||
|
||||
@ -1,28 +1,5 @@
|
||||
import type { TextStreamPart, ToolSet } from 'ai'
|
||||
|
||||
/**
|
||||
* 生命周期阶段定义
|
||||
*/
|
||||
export enum LifecycleStage {
|
||||
PRE_REQUEST = 'pre-request', // 请求预处理
|
||||
REQUEST_EXECUTION = 'execution', // 请求执行
|
||||
STREAM_PROCESSING = 'stream', // 流式处理（仅流模式）
|
||||
POST_RESPONSE = 'post-response', // 响应后处理
|
||||
ERROR_HANDLING = 'error' // 错误处理
|
||||
}
|
||||
|
||||
/**
|
||||
* 生命周期上下文
|
||||
*/
|
||||
export interface LifecycleContext {
|
||||
currentStage: LifecycleStage
|
||||
startTime: number
|
||||
stageStartTime: number
|
||||
completedStages: Set<LifecycleStage>
|
||||
stageDurations: Map<LifecycleStage, number>
|
||||
metadata: Record<string, any>
|
||||
}
|
||||
|
||||
/**
|
||||
* AI 请求上下文
|
||||
*/
|
||||
@ -36,7 +13,7 @@ export interface AiRequestContext {
|
||||
}
|
||||
|
||||
/**
|
||||
* 借鉴 Rollup 的钩子分类设计
|
||||
* 钩子分类
|
||||
*/
|
||||
export interface AiPlugin {
|
||||
name: string
|
||||
|
||||
192
packages/aiCore/src/core/runtime/executor.ts
Normal file
192
packages/aiCore/src/core/runtime/executor.ts
Normal file
@ -0,0 +1,192 @@
|
||||
/**
|
||||
* 运行时执行器
|
||||
* 专注于插件化的AI调用处理
|
||||
*/
|
||||
import { generateObject, generateText, LanguageModelV1, streamObject, streamText } from 'ai'
|
||||
|
||||
import { type ProviderId, type ProviderSettingsMap } from '../../types'
|
||||
import { createModel, getProviderInfo } from '../models'
|
||||
import { type AiPlugin } from '../plugins'
|
||||
import { isProviderSupported } from '../providers/registry'
|
||||
import { PluginEngine } from './pluginEngine'
|
||||
import { type RuntimeConfig } from './types'
|
||||
|
||||
export class RuntimeExecutor<T extends ProviderId = ProviderId> {
|
||||
private pluginClient: PluginEngine<T>
|
||||
// private options: ProviderSettingsMap[T]
|
||||
private config: RuntimeConfig<T>
|
||||
|
||||
constructor(config: RuntimeConfig<T>) {
|
||||
if (!isProviderSupported(config.providerId)) {
|
||||
throw new Error(`Unsupported provider: ${config.providerId}`)
|
||||
}
|
||||
|
||||
// 存储options供后续使用
|
||||
// this.options = config.options
|
||||
this.config = config
|
||||
// 创建插件客户端
|
||||
this.pluginClient = new PluginEngine(config.providerId, config.plugins || [])
|
||||
}
|
||||
|
||||
/**
|
||||
* 流式文本生成 - 使用modelId自动创建模型
|
||||
*/
|
||||
async streamText(
|
||||
modelId: string,
|
||||
params: Omit<Parameters<typeof streamText>[0], 'model'>
|
||||
): Promise<ReturnType<typeof streamText>> {
|
||||
// 1. 使用 createModel 创建模型
|
||||
const model = await createModel({
|
||||
providerId: this.config.providerId,
|
||||
modelId,
|
||||
options: this.config.options
|
||||
})
|
||||
|
||||
// 2. 执行插件处理
|
||||
return this.pluginClient.executeStreamWithPlugins(
|
||||
'streamText',
|
||||
modelId,
|
||||
params,
|
||||
async (finalModelId, transformedParams, streamTransforms) => {
|
||||
const experimental_transform =
|
||||
params?.experimental_transform ?? (streamTransforms.length > 0 ? streamTransforms : undefined)
|
||||
|
||||
return await streamText({
|
||||
model,
|
||||
...transformedParams,
|
||||
experimental_transform
|
||||
})
|
||||
}
|
||||
)
|
||||
}
|
||||
|
||||
/**
|
||||
* 流式文本生成 - 直接使用已创建的模型
|
||||
*/
|
||||
async streamTextWithModel(
|
||||
model: LanguageModelV1,
|
||||
params: Omit<Parameters<typeof streamText>[0], 'model'>
|
||||
): Promise<ReturnType<typeof streamText>> {
|
||||
return this.pluginClient.executeStreamWithPlugins(
|
||||
'streamText',
|
||||
model.modelId,
|
||||
params,
|
||||
async (finalModelId, transformedParams, streamTransforms) => {
|
||||
const experimental_transform =
|
||||
params?.experimental_transform ?? (streamTransforms.length > 0 ? streamTransforms : undefined)
|
||||
|
||||
return await streamText({
|
||||
model,
|
||||
...transformedParams,
|
||||
experimental_transform
|
||||
})
|
||||
}
|
||||
)
|
||||
}
|
||||
|
||||
/**
|
||||
* 生成文本
|
||||
*/
|
||||
async generateText(
|
||||
modelId: string,
|
||||
params: Omit<Parameters<typeof generateText>[0], 'model'>
|
||||
): Promise<ReturnType<typeof generateText>> {
|
||||
const model = await createModel({
|
||||
providerId: this.config.providerId,
|
||||
modelId,
|
||||
options: this.config.options
|
||||
})
|
||||
|
||||
return this.pluginClient.executeWithPlugins(
|
||||
'generateText',
|
||||
modelId,
|
||||
params,
|
||||
async (finalModelId, transformedParams) => {
|
||||
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>> {
|
||||
const model = await createModel({
|
||||
providerId: this.config.providerId,
|
||||
modelId,
|
||||
options: this.config.options
|
||||
})
|
||||
|
||||
return this.pluginClient.executeWithPlugins(
|
||||
'generateObject',
|
||||
modelId,
|
||||
params,
|
||||
async (finalModelId, transformedParams) => {
|
||||
return await generateObject({ model, ...transformedParams })
|
||||
}
|
||||
)
|
||||
}
|
||||
|
||||
/**
|
||||
* 流式生成结构化对象
|
||||
*/
|
||||
async streamObject(
|
||||
modelId: string,
|
||||
params: Omit<Parameters<typeof streamObject>[0], 'model'>
|
||||
): Promise<ReturnType<typeof streamObject>> {
|
||||
const model = await createModel({
|
||||
providerId: this.config.providerId,
|
||||
modelId,
|
||||
options: this.config.options
|
||||
})
|
||||
|
||||
return this.pluginClient.executeWithPlugins(
|
||||
'streamObject',
|
||||
modelId,
|
||||
params,
|
||||
async (finalModelId, transformedParams) => {
|
||||
return await streamObject({ model, ...transformedParams })
|
||||
}
|
||||
)
|
||||
}
|
||||
/**
|
||||
* 获取客户端信息
|
||||
*/
|
||||
getClientInfo() {
|
||||
return getProviderInfo(this.config.providerId)
|
||||
}
|
||||
|
||||
// === 静态工厂方法 ===
|
||||
|
||||
/**
|
||||
* 创建执行器 - 支持已知provider的类型安全
|
||||
*/
|
||||
static create<T extends ProviderId>(
|
||||
providerId: T,
|
||||
options: ProviderSettingsMap[T],
|
||||
plugins?: AiPlugin[]
|
||||
): RuntimeExecutor<T> {
|
||||
return new RuntimeExecutor({
|
||||
providerId,
|
||||
options,
|
||||
plugins
|
||||
})
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建OpenAI Compatible执行器
|
||||
*/
|
||||
static createOpenAICompatible(
|
||||
options: ProviderSettingsMap['openai-compatible'],
|
||||
plugins: AiPlugin[] = []
|
||||
): RuntimeExecutor<'openai-compatible'> {
|
||||
return new RuntimeExecutor({
|
||||
providerId: 'openai-compatible',
|
||||
options,
|
||||
plugins
|
||||
})
|
||||
}
|
||||
}
|
||||
107
packages/aiCore/src/core/runtime/index.ts
Normal file
107
packages/aiCore/src/core/runtime/index.ts
Normal file
@ -0,0 +1,107 @@
|
||||
/**
|
||||
* Runtime 模块导出
|
||||
* 专注于运行时插件化AI调用处理
|
||||
*/
|
||||
|
||||
// 主要的运行时执行器
|
||||
export { RuntimeExecutor } from './executor'
|
||||
|
||||
// 导出类型
|
||||
export type {
|
||||
ExecutionOptions,
|
||||
// 向后兼容的类型别名
|
||||
ExecutorConfig,
|
||||
RuntimeConfig
|
||||
} from './types'
|
||||
|
||||
// === 便捷工厂函数 ===
|
||||
|
||||
import { type ProviderId, type ProviderSettingsMap } from '../../types'
|
||||
import { type AiPlugin } from '../plugins'
|
||||
import { RuntimeExecutor } from './executor'
|
||||
|
||||
/**
|
||||
* 创建运行时执行器 - 支持类型安全的已知provider
|
||||
*/
|
||||
export function createExecutor<T extends ProviderId>(
|
||||
providerId: T,
|
||||
options: ProviderSettingsMap[T],
|
||||
plugins?: AiPlugin[]
|
||||
): RuntimeExecutor<T> {
|
||||
return RuntimeExecutor.create(providerId, options, plugins)
|
||||
}
|
||||
|
||||
/**
|
||||
* 创建OpenAI Compatible执行器
|
||||
*/
|
||||
export function createOpenAICompatibleExecutor(
|
||||
options: ProviderSettingsMap['openai-compatible'],
|
||||
plugins: AiPlugin[] = []
|
||||
): RuntimeExecutor<'openai-compatible'> {
|
||||
return RuntimeExecutor.createOpenAICompatible(options, plugins)
|
||||
}
|
||||
|
||||
// === 直接调用API（无需创建executor实例）===
|
||||
|
||||
/**
|
||||
* 直接流式文本生成
|
||||
*/
|
||||
export async function streamText<T extends ProviderId>(
|
||||
providerId: T,
|
||||
options: ProviderSettingsMap[T],
|
||||
modelId: string,
|
||||
params: Parameters<RuntimeExecutor<T>['streamText']>[1],
|
||||
plugins?: AiPlugin[]
|
||||
): Promise<ReturnType<RuntimeExecutor<T>['streamText']>> {
|
||||
const executor = createExecutor(providerId, options, plugins)
|
||||
return executor.streamText(modelId, params)
|
||||
}
|
||||
|
||||
/**
|
||||
* 直接生成文本
|
||||
*/
|
||||
export async function generateText<T extends ProviderId>(
|
||||
providerId: T,
|
||||
options: ProviderSettingsMap[T],
|
||||
modelId: string,
|
||||
params: Parameters<RuntimeExecutor<T>['generateText']>[1],
|
||||
plugins?: AiPlugin[]
|
||||
): Promise<ReturnType<RuntimeExecutor<T>['generateText']>> {
|
||||
const executor = createExecutor(providerId, options, plugins)
|
||||
return executor.generateText(modelId, params)
|
||||
}
|
||||
|
||||
/**
|
||||
* 直接生成结构化对象
|
||||
*/
|
||||
export async function generateObject<T extends ProviderId>(
|
||||
providerId: T,
|
||||
options: ProviderSettingsMap[T],
|
||||
modelId: string,
|
||||
params: Parameters<RuntimeExecutor<T>['generateObject']>[1],
|
||||
plugins?: AiPlugin[]
|
||||
): Promise<ReturnType<RuntimeExecutor<T>['generateObject']>> {
|
||||
const executor = createExecutor(providerId, options, plugins)
|
||||
return executor.generateObject(modelId, params)
|
||||
}
|
||||
|
||||
/**
|
||||
* 直接流式生成结构化对象
|
||||
*/
|
||||
export async function streamObject<T extends ProviderId>(
|
||||
providerId: T,
|
||||
options: ProviderSettingsMap[T],
|
||||
modelId: string,
|
||||
params: Parameters<RuntimeExecutor<T>['streamObject']>[1],
|
||||
plugins?: AiPlugin[]
|
||||
): Promise<ReturnType<RuntimeExecutor<T>['streamObject']>> {
|
||||
const executor = createExecutor(providerId, options, plugins)
|
||||
return executor.streamObject(modelId, params)
|
||||
}
|
||||
|
||||
// === Agent 功能预留 ===
|
||||
// 未来将在 ../agents/ 文件夹中添加：
|
||||
// - AgentExecutor.ts
|
||||
// - WorkflowManager.ts
|
||||
// - ConversationManager.ts
|
||||
// 并在此处导出相关API
|
||||
@ -1,27 +1,4 @@
|
||||
/**
|
||||
* 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'
|
||||
|
||||
@ -29,7 +6,7 @@ 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> {
|
||||
export class PluginEngine<T extends ProviderId = ProviderId> {
|
||||
private pluginManager: PluginManager
|
||||
|
||||
constructor(
|
||||
@ -170,21 +147,6 @@ export class PluginEnabledAiClient<T extends ProviderId = ProviderId> {
|
||||
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 ===
|
||||
|
||||
/**
|
||||
@ -193,46 +155,23 @@ export class PluginEnabledAiClient<T extends ProviderId = ProviderId> {
|
||||
static createOpenAICompatible(
|
||||
config: ProviderSettingsMap['openai-compatible'],
|
||||
plugins: AiPlugin[] = []
|
||||
): PluginEnabledAiClient<'openai-compatible'> {
|
||||
return new PluginEnabledAiClient('openai-compatible', plugins)
|
||||
): PluginEngine<'openai-compatible'> {
|
||||
return new PluginEngine('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<T extends ProviderId>(providerId: T, plugins?: AiPlugin[]): PluginEngine<T>
|
||||
|
||||
static create(providerId: string, plugins?: AiPlugin[]): PluginEnabledAiClient<'openai-compatible'>
|
||||
static create(providerId: string, plugins?: AiPlugin[]): PluginEngine<'openai-compatible'>
|
||||
|
||||
static create(providerId: string, plugins: AiPlugin[] = []): PluginEnabledAiClient {
|
||||
static create(providerId: string, plugins: AiPlugin[] = []): PluginEngine {
|
||||
if (isProviderSupported(providerId)) {
|
||||
return new PluginEnabledAiClient(providerId as ProviderId, plugins)
|
||||
return new PluginEngine(providerId as ProviderId, plugins)
|
||||
} else {
|
||||
// 对于未知 provider，使用 openai-compatible
|
||||
return new PluginEnabledAiClient('openai-compatible', plugins)
|
||||
return new PluginEngine('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)
|
||||
}
|
||||
@ -1,22 +1,15 @@
|
||||
/**
|
||||
* Execution 层类型定义
|
||||
* Runtime 层类型定义
|
||||
*/
|
||||
import { type ProviderId } from '../../types'
|
||||
import { type ProviderId, type ProviderSettingsMap } from '../../types'
|
||||
import { type AiPlugin } from '../plugins'
|
||||
|
||||
/**
|
||||
* 执行器配置
|
||||
* 运行时执行器配置
|
||||
*/
|
||||
export interface ExecutorConfig<T extends ProviderId = ProviderId> {
|
||||
export interface RuntimeConfig<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
|
||||
options: ProviderSettingsMap[T]
|
||||
plugins?: AiPlugin[]
|
||||
}
|
||||
|
||||
@ -27,3 +20,6 @@ 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
|
||||
}
|
||||
|
||||
// 保留旧类型以保持向后兼容
|
||||
export interface ExecutorConfig<T extends ProviderId = ProviderId> extends RuntimeConfig<T> {}
|
||||
@ -4,36 +4,21 @@
|
||||
*/
|
||||
|
||||
// 导入内部使用的类和函数
|
||||
import { createClient } from './core/clients/PluginEnabledAiClient'
|
||||
import {
|
||||
getProviderInfo as factoryGetProviderInfo,
|
||||
getSupportedProviders as factoryGetSupportedProviders
|
||||
} from './core/creation'
|
||||
import { AiExecutor } from './core/execution/AiExecutor'
|
||||
} from './core/models'
|
||||
import { aiProviderRegistry, isProviderSupported } from './core/providers/registry'
|
||||
import { type ProviderSettingsMap } from './types'
|
||||
import { createExecutor } from './core/runtime'
|
||||
import { ProviderId, type ProviderSettingsMap } from './types'
|
||||
|
||||
// ==================== 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 './core/clients/PluginEnabledAiClient'
|
||||
export { createExecutor, createOpenAICompatibleExecutor } from './core/runtime'
|
||||
|
||||
// ==================== 插件系统 ====================
|
||||
export type { AiPlugin, AiRequestContext, HookResult, HookType, PluginManagerConfig } from './core/plugins'
|
||||
export { createContext, definePlugin, PluginManager } from './core/plugins'
|
||||
export { PluginEngine } from './core/runtime/pluginEngine'
|
||||
|
||||
// ==================== 低级 API ====================
|
||||
export {
|
||||
@ -42,7 +27,7 @@ export {
|
||||
getProviderInfo as getClientInfo,
|
||||
getSupportedProviders,
|
||||
ProviderCreationError
|
||||
} from './core/creation'
|
||||
} from './core/models'
|
||||
export { aiProviderRegistry } from './core/providers/registry'
|
||||
|
||||
// ==================== 类型定义 ====================
|
||||
@ -153,13 +138,13 @@ export const AiCore = {
|
||||
name: AI_CORE_NAME,
|
||||
|
||||
// 创建主要执行器（推荐使用）
|
||||
create(providerId: string, plugins: any[] = []) {
|
||||
return AiExecutor.create(providerId, plugins)
|
||||
create(providerId: ProviderId, options: ProviderSettingsMap[ProviderId], plugins: any[] = []) {
|
||||
return createExecutor(providerId, options, plugins)
|
||||
},
|
||||
|
||||
// 创建底层客户端（高级用法）
|
||||
createClient(providerId: string, plugins: any[] = []) {
|
||||
return createClient(providerId, plugins)
|
||||
createClient(providerId: ProviderId, options: ProviderSettingsMap[ProviderId], plugins: any[] = []) {
|
||||
return createExecutor(providerId, options, plugins)
|
||||
},
|
||||
|
||||
// 获取支持的providers
|
||||
@ -180,36 +165,19 @@ export const AiCore = {
|
||||
|
||||
// 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)
|
||||
return createExecutor('openai', options, plugins)
|
||||
}
|
||||
|
||||
export const createAnthropicExecutor = (options: ProviderSettingsMap['anthropic'], plugins?: any[]) => {
|
||||
return AiExecutor.create('anthropic', plugins)
|
||||
return createExecutor('anthropic', options, plugins)
|
||||
}
|
||||
|
||||
export const createGoogleExecutor = (options: ProviderSettingsMap['google'], plugins?: any[]) => {
|
||||
return AiExecutor.create('google', plugins)
|
||||
return createExecutor('google', options, 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', plugins)
|
||||
}
|
||||
|
||||
export const createAnthropicClient = (options: ProviderSettingsMap['anthropic'], plugins?: any[]) => {
|
||||
return createClient('anthropic', plugins)
|
||||
}
|
||||
|
||||
export const createGoogleClient = (options: ProviderSettingsMap['google'], plugins?: any[]) => {
|
||||
return createClient('google', plugins)
|
||||
}
|
||||
|
||||
export const createXAIClient = (options: ProviderSettingsMap['xai'], plugins?: any[]) => {
|
||||
return createClient('xai', plugins)
|
||||
return createExecutor('xai', options, plugins)
|
||||
}
|
||||
|
||||
// ==================== 调试和开发工具 ====================
|
||||
@ -223,10 +191,10 @@ export const DevTools = {
|
||||
},
|
||||
|
||||
// 测试provider连接
|
||||
async testProvider(providerId: string, options: any) {
|
||||
async testProvider(providerId: ProviderId, options: ProviderSettingsMap[ProviderId]) {
|
||||
try {
|
||||
const client = createClient(providerId, options)
|
||||
const info = client.getClientInfo()
|
||||
const executor = createExecutor(providerId, options)
|
||||
const info = executor.getClientInfo()
|
||||
return {
|
||||
success: true,
|
||||
providerId: info.id,
|
||||
|
||||
@ -1,148 +0,0 @@
|
||||
/**
|
||||
* 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!)
|
||||
}
|
||||
@ -1,13 +0,0 @@
|
||||
/**
|
||||
* 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'
|
||||
@ -1,26 +0,0 @@
|
||||
/**
|
||||
* 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
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user