- 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.
- Bumped version in package.json to 1.0.0-alpha.4.
- Removed deprecated dependencies from package.json and yarn.lock for improved clarity.
- Updated README to reflect changes in supported providers and installation instructions.
- Refactored provider registration and usage examples for better clarity and usability.
Add React Native compatibility configuration to package.json, including the
react-native field and updated exports mapping. Include documentation for
React Native usage with metro.config.js setup instructions.
- Updated README to reflect the addition of a powerful plugin system and built-in web search capabilities.
- Refactored tool call handling in `ToolCallChunkHandler` to improve state management and response formatting.
- Introduced new components `MessageMcpTool`, `MessageTool`, and `MessageTools` for better handling of tool responses and user interactions.
- Updated type definitions to support new tool response structures and improved overall code organization.
- Enhanced spinner component to accept React nodes for more flexible content rendering.
- 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.
- Added detailed usage examples for the native provider registry in the README.md, demonstrating how to create and utilize custom provider registries.
- Updated ApiClientFactory to enforce type safety for model instances.
- Refactored PluginEnabledAiClient methods to support both built-in logic and custom registry usage for text and object generation, improving flexibility and usability.
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 `PluginEnabledAiClient` for a more flexible client interface with integrated plugin support.
- Updated `ApiClientFactory` and `UniversalAiSdkClient` to utilize new provider settings for improved type safety.
- Added a comprehensive plugin management system, allowing for dynamic plugin registration and execution.
- Enhanced the provider registry to include new AI providers and updated existing provider settings.
- Removed deprecated files and streamlined the codebase for better maintainability and clarity.
- Updated documentation to reflect new features and usage examples for the plugin system.
- 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.
