- 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.
- Updated logging in various methods to include detailed traces for better monitoring of execution flow, including assistantID and chatID.
- Improved context management by ensuring proper release of resources and tracking of execution durations in agent calls.
- Added heartbeat logging in the Claude parser to monitor stream processing and prevent potential issues with long-running tasks.
- Refined the .gitignore file to exclude additional markdown files in the sandbox directory.
- 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.
- Introduced tests for validating MCP task output, ensuring only structure validation is performed without semantic checks.
- Implemented the `validateMCPOutput` function to validate MCP task outputs, checking for non-empty results and expected structure.
- Updated the `ExecuteWithRetry` method to incorporate MCP-specific validation logic, improving error handling and output validation for MCP tasks.
- Enhanced test coverage for various output scenarios, including nil, empty string, empty map, and empty array cases, to ensure robust validation behavior.
- Updated MCP task executor ID format to use "mcp_server.mcp_tool" for better clarity and consistency.
- Added required MCP-specific fields (`mcp_server` and `mcp_tool`) to the Task struct and validation logic.
- Enhanced documentation in DESIGN.md and TECHNICAL.md to reflect changes in MCP task structure and requirements.
- Improved error handling in ExecuteMCPTask to ensure proper validation of MCP task fields before execution.
- 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.
