- 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.
- Introduced a new global phase agent resolver to streamline agent ID retrieval for various robot pipeline phases, enhancing flexibility in agent configuration.
- Updated existing phase agent retrieval logic to prioritize per-robot configurations, falling back to global settings when necessary.
- Enhanced error handling to provide clearer messages when no agent is configured for specific phases.
- Added tests to validate the new resolution logic and ensure proper functionality across different configurations.
- 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.
- Implement V2 execution model in the standard executor, simplifying task execution to a single call without validation loops.
- Introduce support for resuming suspended executions, allowing for human input during task processing.
- Enhance event handling by pushing task completion and failure events to the event bus for better tracking and integration.
- Update tests to reflect changes in execution flow and ensure robust handling of task statuses and results.
- Updated the `RunConfig` to include parameters for multi-turn conversation control, such as `ContinueOnFailure`, `ValidationThreshold`, and `MaxTurnsPerTask`.
- Implemented a new multi-turn conversation flow for assistant tasks, allowing for iterative interactions until completion or maximum turns are reached.
- Enhanced the `ValidationResult` structure to support multi-turn states, including fields for `Complete`, `NeedReply`, and `ReplyContent`.
- Refined the `ExecuteWithRetry` method to accommodate the new conversation flow, ensuring proper handling of task execution and validation.
- Revised the `Validator` to include logic for determining when to continue conversations based on validation results.
- Updated documentation and tests to reflect the new multi-turn capabilities and validation mechanisms, ensuring comprehensive coverage of the changes.
- Completed the implementation of the P3 Run phase, integrating task execution and validation mechanisms.
- Introduced a new `RunConfig` struct to manage execution parameters such as retries and validation thresholds.
- Developed a two-layer validation system using the new `yao/assert` package, supporting both natural language and structured JSON rules.
- Enhanced the `RunExecution` method to execute tasks sequentially with progress tracking and a retry mechanism for validation failures.
- Updated task structures to include comprehensive validation rules and expected outputs, ensuring robust task management.
- Added unit tests for the new execution and validation features, achieving high test coverage across the implementation.
- Revised documentation to reflect changes in the architecture and functionality of the P3 phase.
