- Added support for reading files from workspace URIs in the delivery process, allowing for more flexible attachment management.
- Introduced a new `convertWorkspaceAttachment` function to handle workspace-based file retrieval and integration into messenger attachments.
- Updated the `AgentCaller` to include execution mode in the context, improving task execution tracking.
- Enhanced the `RunDelivery` method to utilize workspace manifests for delivery input, reducing token usage and improving efficiency.
- Implemented locale handling in various request structures to support multi-language capabilities in user interfaces.
- Introduced a new `workspace` field across various robot-related structures, including `CreateRobotRequest`, `UpdateRobotRequest`, and `RobotResponse`, allowing for better organization and management of robots within specific workspaces.
- Updated database queries and response mappings to accommodate the new workspace field, ensuring seamless integration with existing functionalities.
- Enhanced agent execution context to include workspace information, improving the contextual awareness of agents during operations.
- Added tests to validate the creation and updating of robots with workspace data, ensuring robust functionality and backward compatibility.
- Add Telegram integration support by introducing a dispatcher for handling Telegram events and messages.
- Implement event notifications for robot configuration changes (creation, update, deletion) to facilitate integration with external services.
- Refactor the robot initialization process to load robots into cache and start the dispatcher, improving the overall system setup.
- Update the delivery event structure to include additional metadata for better context during message handling.
- Enhance logging capabilities for better observability during robot execution and event processing.
- Add `language_model` field to robot data structures for LLM connector overrides.
- Update `AgentCaller` to utilize the robot's language model and include logging capabilities for agent calls.
- Refactor task execution to log task outputs and inputs, improving observability during execution.
- Modify tests to accommodate changes in the runner initialization and ensure proper logging functionality.
