- Enhanced the `extractGoalName` function to skip empty lines, markdown headers, and horizontal rules while extracting the first meaningful line as the goal name.
- Implemented a new `stripMarkdownFormatting` function to remove various markdown formatting elements, including bold, italic, inline code, and link syntax.
- Added comprehensive unit tests for both `extractGoalName` and `stripMarkdownFormatting` to ensure correct functionality across various markdown scenarios.
- Introduced a new `Description` field in the `Task` struct for a human-readable task description, improving UI clarity.
- Updated the `ParseTask` function to save the description from input data and convert it to a message if no explicit messages are provided.
- Enhanced the `Executor` to update UI fields with localized messages during task execution phases, ensuring better user feedback.
- Implemented a new method in the `ExecutionStore` to persist task status updates, allowing real-time UI updates.
- Added unit tests to validate the new task description handling and UI updates during execution phases.
- Refactored failure message construction to use concise phase names instead of full error messages, improving clarity in UI feedback.
- Updated localization support for failure messages, ensuring accurate translations for various phases in both English and Chinese.
- Added unit tests to validate the new failure message format and localization functionality.
- Added `Name` and `CurrentTaskName` fields to the `Execution` struct for improved UI display during execution phases.
- Implemented localization support for UI messages, allowing dynamic updates based on the execution context and user locale.
- Updated the executor to manage these fields at various phases, ensuring accurate representation of execution status.
- Enhanced OpenAPI documentation to reflect the new fields and their usage in execution responses.
- Added unit tests to validate the functionality of UI fields and localization handling.
- Removed the job system integration from the robot execution flow, transitioning to a dedicated ExecutionStore for managing execution records.
- Updated the design documentation to reflect the new architecture, emphasizing the relationship between robots and concurrent executions.
- Revised the API to return execution IDs instead of job IDs, ensuring clarity in execution tracking.
- Enhanced logging mechanisms to utilize the kun/log package for better traceability of execution phases.
- Updated tests and documentation to align with the removal of job-related structures and the introduction of execution management.
- Added `robot_email` field to the Robot structure for specifying the sender's email address in email communications.
- Updated the EmailTarget structure by removing the CC field, simplifying the configuration for email targets.
- Revised TECHNICAL.md to include details on the new `robot_email` field and its usage in email delivery, ensuring clarity on the sender identity.
- Enhanced the Delivery Center's email handling to utilize the Robot's email as the From address, with a fallback to the provider's default if not configured.
- Updated DESIGN.md to reflect changes in email delivery architecture and added new sections for global email configuration.
- Marked completion of related tasks in TODO.md, confirming the integration of new email features and structures.
- Modified the DeliveryResult structure across multiple executors to include RequestID and Content fields, providing detailed summaries and bodies for dry-run, sandbox, and standard deliveries.
- Updated related test cases to reflect changes in the DeliveryResult structure, ensuring accurate validation of delivery types and content handling.
- Revised input formatting to display delivery summaries instead of types, improving clarity in execution summaries.
- Removed RobotID from ExecutionRecord and DeliveryContext structures, emphasizing the use of MemberID as the globally unique identifier.
- Updated relevant documentation in DESIGN.md, TECHNICAL.md, and TODO.md to reflect these changes, ensuring clarity on the new context handling.
- Revised methods in ExecutionStore and Executor to align with the updated model, enhancing data management and execution tracking.
- Improved test cases to validate the new structure and ensure comprehensive coverage of execution scenarios.
- Marked the P3 Run Implementation as complete in TODO.md, reflecting the successful integration of task execution and validation.
- Updated the status of tests related to the ContinueOnFailure option, indicating their completion with detailed test cases for various execution scenarios.
- Enhanced run_test.go with new tests to validate the behavior of task execution under different ContinueOnFailure configurations, ensuring robust error handling and task management.
- Revised the RunExecution method to accept configuration data, improving flexibility in execution parameters.
- Improved the multi-turn conversation handling in the `RunConfig`, adding parameters for better control over conversation execution.
- Enhanced the `ValidationResult` structure to better accommodate multi-turn states, ensuring accurate tracking of conversation progress.
- Updated the `ExecuteWithRetry` method to align with the new conversation flow, improving task execution reliability.
- Revised the `Validator` logic to effectively manage conversation continuation based on validation outcomes.
- Updated documentation and tests to ensure clarity and coverage of the new multi-turn capabilities and validation improvements.
- 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.
- Marked P1 Goals and P2 Tasks as completed in TODO.md, reflecting the successful implementation of goal generation and task planning functionalities.
- Updated the input formatter to include delivery target details in the goal output, ensuring tasks are designed for appropriate delivery methods.
- Enhanced the RunTasks method to validate goals and parse tasks from agent responses, including comprehensive error handling and task validation.
- Added unit tests for new task parsing and validation features, ensuring robust coverage of task generation and execution scenarios.
- Revised documentation to clarify the integration of validation rules and expected outputs in task management.
- Introduced a new method to format available resources, improving clarity on the tools and agents accessible to the robot.
- Updated the RunGoals and RunInspiration methods to include resource information in user prompts, ensuring achievable goals and insights.
- Revised error messages in the executor to provide more context, enhancing debugging capabilities.
- Added comprehensive tests for the new resource formatting functionality and updated existing tests to reflect changes in error handling.
- Improved documentation for robot configuration, emphasizing the importance of available resources in goal and task generation.
- Introduced a structured Goals type with delivery metadata for improved task management and output handling.
- Updated the DeliveryTarget type to include additional fields for recipients, format, and options, enhancing flexibility in result delivery.
- Enhanced the Executor's RunGoals method to parse and handle delivery information from agent responses.
- Revised input formatting to include robot identity context, improving clarity in generated goals.
- Updated tests to validate the new structure and ensure comprehensive coverage of delivery functionalities.
- Introduced multiple executor modes (Standard, DryRun, Sandbox) to accommodate various use cases, enhancing flexibility in execution strategies.
- Updated DESIGN.md to reflect the new executor modes and their respective use cases, including detailed descriptions and configuration examples.
- Revised TECHNICAL.md to outline the new executor package structure, emphasizing the modular design for future enhancements.
- Enhanced the TODO.md to track the progress of executor mode implementations and related tasks.
- Removed outdated executor stub files and tests, streamlining the codebase for improved maintainability.
- Updated integration tests to utilize the new DryRun executor, ensuring comprehensive coverage of execution scenarios without real agent calls.
