- Introduced MCPHostCallbacks for optional host capabilities like sampling and logging.
- Implemented MCPHostLLMBridge to handle MCP Sampling requests and bridge to LLM service.
- Created models for structured data conversion between MCP SDK and internal data models, including tool content items, prompts, and resources.
- Enhanced error handling and logging for better traceability during sampling operations.
- Added a new `tooling` module to define a unified model for tool declarations, invocations, and execution results, facilitating compatibility between plugins, legacy actions, and MCP tools.
- Implemented `ToolProvider` interface for various tool providers including built-in tools, MCP tools, and plugin runtime tools.
- Enhanced `MCPManager` and `MCPConnection` to support unified tool invocation and execution results.
- Updated `ComponentRegistry` and related classes to accommodate the new tool specifications and descriptions.
- Refactored existing components to utilize the new tooling system, ensuring backward compatibility with legacy actions.
- Improved error handling and logging for tool invocations across different providers.
- Added support for scheduling background tasks to build emoji and image descriptions when not found in cache.
- Improved error handling and logging for emoji and image processing.
- Updated `SessionMessage` processing to allow for optional heavy media analysis and voice transcription.
- Refactored logging messages for better clarity and consistency across various modules.
- Introduced a new function to build outbound log previews for messages, enhancing logging capabilities.
- Refactored model fetching logic to support various authentication methods for OpenAI-compatible APIs.
- Introduced new data models for LLM service requests and responses to standardize interactions across layers.
- Added an adapter base class for unified request execution across different providers.
- Implemented utility functions for building OpenAI-compatible client configurations and request overrides.
- Introduced HookHandlerEntry to manage hook processing with attributes like hook name, mode, order, timeout, and error policy.
- Implemented normalization methods for hook attributes to ensure valid configurations.
- Updated ComponentRegistry to support retrieval of hook handlers based on hook names, with sorting by mode and order.
- Refactored HookDispatcher to handle invocation of hooks, separating blocking and non-blocking handlers, and managing execution results.
- Added support for registering hook specifications and invoking hooks across supervisors in PluginRuntimeManager.
- Removed deprecated workflow step handling from PluginRunner, streamlining hook invocation responses.
