- Revised DESIGN.md to update the DeliveryRequest structure, replacing exec_id with member_id and adding context for execution_id and trigger.
- Expanded TECHNICAL.md to clarify the DeliveryContext structure, including detailed comments on RobotID and MemberID for better understanding of their roles.
- Updated TODO.md to reflect changes in the execution record model, ensuring accurate tracking of the new fields and their implications for delivery processes.
- Enhanced documentation to improve clarity on the updated context and execution tracking, facilitating better developer understanding and implementation.
- Revised DESIGN.md to incorporate support for multiple delivery targets across email, webhook, and process channels, enhancing the flexibility of the delivery system.
- Expanded TECHNICAL.md with detailed descriptions of the new DeliveryPreferences structure, including EmailPreference, WebhookPreference, and ProcessPreference, to clarify their configurations and usage.
- Updated TODO.md to reflect the integration of multiple targets in delivery preferences, ensuring comprehensive tracking of the ongoing enhancements in the delivery architecture.
- Enhanced documentation to outline the new delivery channels and their configurations, improving clarity and usability for developers and users.
- Revised DESIGN.md to clarify the architecture of the P4 delivery process, emphasizing the separation of content generation and channel decision-making.
- Expanded TECHNICAL.md with detailed notes on the DeliveryRequest structure, DeliveryContent generation, and the role of the Delivery Center in managing delivery channels.
- Updated TODO.md to reflect the completion of the Delivery Agent setup and the integration of delivery preferences, ensuring comprehensive tracking of the P4 implementation progress.
- Enhanced documentation to outline the new delivery channels and their configurations, including email and webhook options, for improved clarity and usability.
- 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.
- Revised DESIGN.md to clarify the architecture of the P3 entry point, including updated RunConfig parameters and task execution flow.
- Expanded TECHNICAL.md with detailed implementation notes on multi-turn conversation flow, validation rules format, task dependencies, and resource management.
- Removed outdated architecture diagrams from TODO.md and added comprehensive notes on the new multi-turn conversation handling and validation mechanisms.
- Documented the functionality of the new `yao/assert` package and its integration into the validation process.
- Marked several tests as completed, including those for task execution order, status updates, and validation logic.
- Added new tests for multi-turn conversation flow and error handling in the Runner tests.
- Updated the Validator tests to include scenarios for natural language rules and semantic validation.
- Revised the TODO section to outline future testing needs, specifically for the ContinueOnFailure option.
- 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.
- Added a User-Agent header to HTTP requests in the OpenAI provider to improve request identification.
- Updated TODO.md to reflect the completion status of various agent configurations and test scenarios, marking several tasks as done.
- Ensured all relevant agents and expert configurations are now marked as complete, enhancing clarity on project progress.
- Introduced a validation mechanism for task results, including a detailed validation structure with scores and issues.
- Updated the input formatter to include validation results in the output, improving clarity on task success and validation status.
- Enhanced test cases to cover the new validation fields and ensure comprehensive testing of task results.
- Revised TODO.md to reflect the addition of validation features and the current status of the agent's development phases.
- Established a unified calling mechanism for agents, enabling streaming support and multi-turn conversations.
- Developed input formatters for various phases, ensuring proper data preparation for assistant prompts.
- Created test assistants for single and multi-turn interactions, along with comprehensive test cases for the AgentCaller and InputFormatter.
- Updated the TODO.md to reflect the new structure and progress of the agent call infrastructure, including future phases for assistant setup and implementation.
- Added assertions in multiple integration tests to verify that robots are correctly loaded into the cache during various execution scenarios.
- Updated tests for clock triggers, concurrent executions, control tests, event triggers, and human interventions to ensure comprehensive coverage of cache functionality.
- Improved test reliability by confirming the presence of expected robots in the cache, enhancing overall test robustness.
- Marked Phase 3 of the scheduling system as complete in TODO.md, highlighting the successful implementation of all sub-tasks and the passing of over 80 integration tests.
- Updated the integration test section to reflect completed tests for various triggers and execution scenarios, ensuring comprehensive coverage of the scheduling pipeline.
- Added new test files for core scheduling flow, clock trigger modes, human intervention, event triggers, concurrent executions, and control tests, enhancing overall test coverage and stability.
- Improved assertions in existing tests to utilize the Eventually pattern for better handling of timing variations in CI environments.
- Marked the Executor Stub Enhancement section in TODO.md as complete, detailing the enhancements made to the executor's functionality.
- Improved the Executor to simulate full execution with Job integration, including phase transitions and logging.
- Introduced a Config struct for customizable executor behavior, allowing for testing with callbacks and job integration control.
- Implemented phase-specific methods for modular execution, preparing for future real phase implementations.
- Added comprehensive tests for the executor, including smoke tests and verification of phase progression and job logs.
- Updated progress tracking in TODO.md to reflect the current status of the executor and integration testing.
- Added error handling for missing 'data' field in the ListLogs result, improving robustness.
- Implemented handling for nil data, returning an empty log slice as needed.
- Expanded data type handling to include generic []interface{}, ensuring compatibility with various log formats.
- Enhanced logging structure by extracting message, level, and job_id fields from different data types, improving log consistency and usability.
- Marked the Job Integration section in TODO.md as complete, detailing the implementation of job creation, execution lifecycle, and logging functionalities.
- Introduced a new Options struct for job creation, allowing for extensibility with fields like Priority, MaxRetryCount, and Metadata.
- Implemented methods for job status updates, including handling for completed, failed, and cancelled states, with corresponding updates to job configurations.
- Enhanced localization support for job names and logs, ensuring better usability across different languages.
- Updated tests for job creation, execution tracking, and logging, achieving full test coverage with all tests passing.
- Reflected changes in the job model to include new statuses and improved handling of job execution states.
- Updated the auto-refresh tests in cache_test.go to utilize fresh cache instances for each test, ensuring isolation and reliability.
- Improved assertions to verify cache stability after stopping auto-refresh and confirmed that multiple start calls replace previous ones without leaking goroutines.
- Added tests to check for safe behavior during rapid start/stop cycles and ensured that stopping without starting does not cause panics.
- Enhanced overall test coverage and clarity, contributing to better maintainability and understanding of the cache's auto-refresh functionality.
- Integrated trigger handling directly into the Manager, consolidating the logic for clock, human intervention, and event triggers.
- Updated the Manager to include methods for processing human interventions and event triggers, ensuring robust execution control.
- Refactored the trigger package to provide validation and utility functions, enhancing the overall structure and clarity of trigger-related logic.
- Improved documentation and comments throughout the Manager and trigger implementations for better understanding and maintainability.
- Updated tests to cover new functionalities, ensuring comprehensive validation of the Manager's behavior with various trigger types.
- Simplified comments and assertions in the timezone deduplication test for the Manager to enhance clarity and focus on the expected behavior of the times robot.
- Ensured that the test accurately verifies that the times robot does not trigger multiple times within the same minute, while allowing for daemon and interval robots to operate as expected.
- Improved the overall readability of the test code by removing redundant comments and emphasizing key assertions.
- Enhanced the test for the Manager's timezone deduplication functionality to ensure the times robot does not trigger multiple times within the same minute on the same day.
- Added detailed assertions to clarify expected behavior and improve test accuracy, particularly regarding the interaction between the times, daemon, and interval robots.
- Updated comments to provide better context and understanding of the test logic and expected outcomes.
- Introduced comprehensive tests for the Manager's timezone deduplication functionality, ensuring correct behavior across different timezones.
- Verified that the robot does not trigger multiple times within the same minute on the same day and correctly triggers on different days.
- Added tests for handling cross-timezone day boundaries and comparisons between UTC and local timezones, enhancing the robustness of the time management logic.
- Updated the shouldTriggerTimes method to utilize the correct timezone for LastRun comparisons, improving accuracy in execution triggers.
- Completed the Manager implementation, including methods for starting, stopping, and managing clock triggers for robot executions.
- Integrated context handling for background operations and added synchronization to ensure thread safety.
- Updated the TODO.md to reflect the completion of the Manager implementation and outlined the next steps for the Trigger and Dedup functionalities.
- Enhanced the Tick method to process clock triggers and submit jobs to the pool based on robot configurations.
- Added detailed comments and documentation for clarity on the Manager's functionality and its components.
- Updated the Executor to implement atomic slot acquisition for robot executions, preventing race conditions and ensuring proper quota management.
- Introduced the TryAcquireSlot method in the Robot struct for atomic checks and reservations of execution slots, enhancing concurrency handling.
- Adjusted the Worker to requeue tasks when quota is exceeded, improving error handling and system stability.
- Enhanced tests for concurrent access and quota management, ensuring robust functionality under load conditions.
- Updated comments and documentation for clarity on new methods and their intended use.
- Marked the Pool Implementation as complete in TODO.md, confirming all tasks are finished with comprehensive tests.
- Introduced a configurable worker pool with a priority queue for managing robot jobs, including graceful shutdown support.
- Enhanced the Executor with simulated execution delay and callback functionality for testing, tracking execution counts.
- Improved error handling in the pool's submission process and added methods for retrieving running and queued job counts.
- Updated tests to ensure robust functionality and performance of the pool and executor components.
- Implemented comprehensive tests for the auto-refresh feature in the cache, ensuring it operates without leaking goroutines.
- Verified that multiple start calls do not accumulate goroutines and that stopping the refresh does not panic.
- Included tests for concurrent start and stop operations to ensure thread safety and reliability in the cache's behavior.
- Enhanced overall test coverage for the cache module, contributing to improved stability and performance assurance.
- Marked the Cache Implementation as complete in TODO.md, confirming all tasks are finished with comprehensive integration tests.
- Updated cache.go to provide a thread-safe in-memory cache for Robot instances, improving performance and reliability.
- Enhanced the Load method to include pagination and configurable model name, ensuring efficient data handling.
- Added detailed comments and structured code for better readability and maintainability across the cache implementation.
- Improved validation and error handling in various utility functions to ensure robustness in data processing.
- Added descriptive comments for constants in enums.go to clarify their purpose and improve code readability.
- Updated error definitions in errors.go with comments to specify the meaning of each error, enhancing understanding of error handling in the codebase.
- Added a check for nil configuration in the CanRun method to ensure default behavior is maintained when no config is provided.
- Standardized comments in the Goals struct for improved clarity and consistency in task objectives.
- Updated the Execution struct's field formatting for better readability.
- Standardized field formatting in TriggerResult and Execution structs for improved code clarity.
- Added test cases in robot_test.go to ensure Robot can run with nil config and quota, verifying default behavior.
- Enhanced comments in the Goals struct to clarify task objectives and improve documentation consistency.
- Marked Phase 1: Types & Interfaces as complete with 88.4% test coverage and all tests passing.
- Updated Phase 2: Skeleton Implementation status to complete, confirming all packages compile successfully without circular dependencies.
- Checked off all tasks under both phases, indicating full implementation of types, interfaces, and skeleton structures.
- Updated the Task struct in DESIGN.md to replace the Messages field with a new Input field, allowing for more flexible user input options.
- Revised the TriggerRequest struct in TECHNICAL.md to incorporate the new Input field, improving clarity on user interactions.
- Enhanced related code examples and documentation to reflect these changes, ensuring consistency in task management and execution processes.
- Updated the Task struct in DESIGN.md to replace the Input field with Messages, allowing for rich content input (text, images, files, audio).
- Revised the TriggerRequest struct in TECHNICAL.md to utilize Messages instead of Input, enhancing the flexibility of user interactions.
- Improved related code examples to demonstrate the new Messages structure, ensuring consistency and clarity in task management and execution processes.
- Updated the TriggerRequest and InterveneRequest structs to replace the Description field with an Input field, enhancing clarity on user input for task actions.
- Revised related code examples to reflect the new Input field, ensuring consistency across the implementation.
- Improved documentation comments for better understanding of the changes and their impact on task management.
- Revised the Task struct in DESIGN.md to include an Input field for natural language descriptions and a Source field to indicate task origin (auto, human, event).
- Updated the Execution struct in TECHNICAL.md to add an Input field for storing original trigger input, improving traceability of task execution.
- Enhanced documentation for both structs to clarify their roles and improve overall understanding of the agent's task management and execution processes.
- Updated DESIGN.md to improve the structure of the InspirationReport and Goals, clarifying their roles in the agent's execution process.
- Revised the Task struct to include a reference to the goal in markdown, enhancing task management.
- Enhanced TECHNICAL.md by introducing new types for RobotStatus, ClockMode, and EventSource, improving type safety and clarity.
- Updated various structs and interfaces to reflect new types and improve documentation consistency across the codebase.
- Updated the DESIGN.md and TECHNICAL.md files to consolidate the knowledge base (KB) and database (DB) configurations into a unified structure, enhancing clarity on shared resources.
- Removed the PrivateKB and SharedKB fields, replacing them with a single KB field that includes collections and options for better organization.
- Introduced a new DB struct to define shared database models, streamlining the configuration process.
- Enhanced the Learn struct to clarify its purpose for the robot's private knowledge base, including comments for better understanding.
- Removed the Monitor and related types from the configuration, simplifying the overall structure and focusing on essential components.
- Updated the DESIGN.md to clarify the relationship between robots and executions, emphasizing that each trigger creates a new execution mapped to a job.Job for monitoring.
- Revised the RobotState struct to include fields for tracking multiple running executions and their IDs, improving concurrency management.
- Enhanced the TECHNICAL.md to reflect the global robot object for static methods, streamlining the API usage for robot management.
- Improved TypeScript interfaces to align with the new execution tracking structure, ensuring consistency across documentation.
- Added detailed comments and examples for job creation and execution handling, clarifying the integration of the job system within the robot's functionality.
- Updated the TriggerRequest struct to include new fields: InsertAt and AtIndex for improved task insertion control.
- Revised action descriptions for clarity, changing terms to better reflect their functionality.
- Added detailed comments and examples for the robot.Trigger method to clarify usage for human and event triggers.
- Introduced new types and constants for task insertion positions and sources, enhancing the overall structure and readability of the documentation.
- Deleted the DESIGN.md and TECHNICAL.md files to streamline the documentation structure and eliminate redundancy.
- This change reflects a shift towards a more concise documentation approach, focusing on essential information and reducing clutter for better usability.
- Removed extensive sections on Manager and Executor implementations to focus on high-level concepts and integration points.
- Consolidated error handling and global singleton sections for clarity and brevity.
- Updated the structure of the document to enhance readability and ensure a more cohesive presentation of the autonomous agent's functionality.
- Revised sections to improve clarity on execution phases, specifically detailing the roles of clock triggers and their impact on agent operations.
- Updated flowcharts and diagrams to accurately represent the new execution structure, ensuring a clear understanding of the agent's decision-making processes.
- Enhanced documentation for each phase, providing clearer guidance on input and output expectations, particularly in relation to trigger types.
- Introduced a new section highlighting Yao Agents, providing a link to the related GitHub repository for further exploration.
- Enhanced the README to better inform users about the capabilities and resources available for Yao Agents, improving overall documentation clarity.
- Introduced a new section detailing Go APIs for job management, replacing previous API references for clarity and consistency.
- Updated job creation and execution handling examples to utilize the new job package methods, improving code clarity and structure.
- Enhanced query examples for listing jobs, executions, and logs, providing clearer guidance on usage within the autonomous agent context.
- Revised the document to align with recent changes in job management and execution processes, ensuring accurate representation of the agent's functionality.
- Replaced references to "AI Members" with "Robot Members" and "Human Members" with "User Members" for clarity.
- Updated the `team_members` table description to reflect the use of the `__yao.member` model, enhancing consistency in terminology.
- Revised key fields and examples in the document to align with the new member structure, improving overall understanding of the agent's configuration and operational context.
- Enhanced flowcharts and diagrams to accurately represent the updated member types and their roles within the team structure.
- Renamed the `Status` type to `ExecStatus` for clarity in execution status representation.
- Introduced a new `AgentState` type to define the operational states of the agent, enhancing the structure of the design document.
- Updated relevant sections to reflect these changes, improving overall readability and understanding of the agent's execution and operational context.
