- Extracted `StreamEventManager` and `ToolExecutor` classes from `promptToolUsePlugin.ts` to improve code organization and reduce complexity.
- Enhanced tool execution logic with better error handling and event management.
- Updated the `createPromptToolUsePlugin` function to utilize the new classes for cleaner implementation.
- Improved recursive call handling and result formatting for tool executions.
- Streamlined the overall flow of tool calls and event emissions within the plugin.
- Revised AI SDK architecture diagram to reflect changes in component relationships, replacing PluginEngine with RuntimeExecutor.
- Updated README to highlight core features, including a refined plugin system, improved architecture design, and new built-in plugins.
- Added detailed examples for using built-in plugins and creating custom plugins, enhancing documentation for better usability.
- Included future version roadmap and related resources for user reference.
- 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.
- 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.
feat: 为插件系统实现中间件
feat: 实现自定义的思考中间件
- Updated package.json and related files to reflect the correct naming convention for the @cherrystudio/ai-core package.
- Adjusted import paths in various files to ensure consistency with the new package name.
- Enhanced type resolution in tsconfig.web.json to align with the updated package structure.
- Introduced a plugin system in the AI Core package, allowing for flexible request handling and middleware integration.
- Added support for various hook types: First, Sequential, Parallel, and Stream, enabling developers to customize request processing.
- Implemented a PluginManager for managing and executing plugins, enhancing extensibility and modularity.
- Updated architecture documentation to reflect new plugin capabilities and usage examples.
- Included new middleware types and examples to demonstrate the plugin system's functionality.
This update aims to improve the developer experience by providing a robust framework for extending AI Core's capabilities.
- Added a new package `@cherry-studio/ai-core` that provides a unified interface for various AI providers based on the Vercel AI SDK.
- Implemented core components including `ApiClientFactory`, `UniversalAiSdkClient`, and a provider registry for dynamic imports.
- Included TypeScript support and a lightweight design for improved developer experience.
- Documented architecture and usage examples in `AI_SDK_ARCHITECTURE.md` and `README.md`.
- Updated `package.json` to include dependencies for supported AI providers.
This package aims to streamline the integration of multiple AI providers while ensuring type safety and modularity.
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