- Added support for a new `RobotPrompt` field in the `Uses` struct to allow for custom robot system prompts.
- Updated the `Load` function to initialize `RobotPrompt` with a default value if not provided.
- Modified the `SystemConfig` struct to include a connector for the new `RobotPrompt` agent.
- Enhanced the asset binding to include new files related to the `robot_prompt` assistant.
- Updated related documentation and tests to reflect the addition of the `RobotPrompt` functionality.
- 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.
- Updated the ExecutionRecord structure in TECHNICAL.md to include new fields such as ExecutionID and improved status tracking with cancellation support.
- Revised the ExecutionStore implementation in store/execution.go to add methods for updating execution status and current state, as well as deleting records.
- Marked the completion of the execution record model in TODO.md, reflecting the integration of new features and ensuring comprehensive tracking of execution history.
- Updated bindata.go and model.go to include the new execution model, enhancing the overall architecture for better data management.
- 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.
- Introduced support for OpenAPI mode, allowing dynamic routing and OAuth guards for API endpoints.
- Updated API root path handling to accommodate OpenAPI configurations, ensuring consistent URL structures.
- Added well-known routes for Yao metadata and OAuth discovery, improving API discoverability.
- Refactored middleware and guards to streamline OpenAPI integration, enhancing overall service functionality.
- Removed deprecated agent TypeScript file, simplifying the codebase and improving maintainability.
- Updated the `build` and `watch` commands to accept a single argument for `<sui>` and made the `<template>` argument optional, improving usability.
- Introduced a default template assignment for the `agent` SUI, ensuring a more intuitive setup for users.
- Enhanced error messages for command usage to provide clearer guidance on expected input format.
- Added new OpenAPI file to the bindata, improving the framework's capabilities for API integration.
- Replaced all instances of `ctx.Space` with `ctx.Memory.Context` in the context management code, ensuring a more structured approach to handling temporary request-scoped data.
- Updated related test cases to reflect the changes in context memory usage, enhancing the reliability and clarity of tests.
- Removed the deprecated `Space` references and adjusted comments and documentation to align with the new memory management strategy.
- Replaced Badger with Xun as the primary data store across various components, including OAuth, agent memory, and knowledge base stores, enhancing performance and flexibility.
- Updated the configuration files to reflect the new Xun store paths and removed obsolete Badger store files.
- Refactored test cases to utilize the new Xun store, ensuring compatibility and improved test reliability.
- Enhanced test setup functions to initialize the Xun store correctly, streamlining the testing process and ensuring a consistent environment.
- Updated the search handling to incorporate keyword extraction with weights, improving the relevance of search results.
- Refactored the `shouldAutoSearch` method to return a `SearchIntent` struct, allowing for more nuanced control over search execution based on context.
- Enhanced the `buildSearchRequests` function to utilize extracted keywords, optimizing search queries based on user input.
- Improved the handling of search types and conditions, ensuring that the system can dynamically adjust search behavior based on intent and configuration.
- Updated documentation and prompts to reflect changes in keyword extraction and search intent classification, providing clearer guidelines for usage.
- Refactored the Search method to support context-aware execution, allowing handlers to utilize context when performing searches.
- Introduced a new SearchWithContext method in the handler interface to facilitate context-based search operations.
- Updated the DB handler to implement the context-aware search, ensuring proper QueryDSL generation and execution.
- Enhanced test cases to validate the new context requirements and scenarios for database searches, improving error handling and robustness.
- Added scenario type support for QueryDSL generation, allowing for more complex query handling.
- Updated documentation to reflect the new context handling and scenario features in search operations.
- Added support for a new `Metadata` field in the `Options` struct to allow passing custom data to hooks, enhancing flexibility in context management.
- Updated the `ToMap` and `OptionsFromMap` methods to include serialization and deserialization of the `Metadata` field.
- Enhanced the test case structure to include an `Options` field, allowing for per-test-case configuration, including metadata and skip options.
- Updated documentation to reflect the new `options` and `metadata` fields, providing clear examples for users on how to utilize these features in test cases.
- Updated the search intent classification prompt for the Need Search agent to provide clearer instructions and rules for classifying user queries.
- Revised the output format to specify JSON structure requirements, ensuring consistency in responses.
- Expanded classification rules to include additional categories and examples, improving the agent's ability to accurately determine the need for external searches.
- Enhanced clarity in the prompt content to facilitate better understanding and implementation by users.
- Replaced `json.Parse` with `text.ExtractJSON` in the `Next` function of both the `keyword` and `needsearch` assistants for improved fault-tolerant JSON extraction from LLM output.
- Simplified content handling by removing unnecessary markdown code block processing, enhancing clarity and efficiency in keyword extraction.
- Updated comments to reflect the changes in the extraction method, ensuring better understanding of the functionality.
- Renamed several assistant packages for clarity, including "Entity Extraction" to "Entity Extractor" and "Keyword Extraction" to "Keyword Extractor."
- Revised descriptions for various assistants to enhance understanding of their functionalities, such as changing "Extract keywords from text content" to "Extract search keywords."
- Added a "uses" field with "search" set to "disabled" in the configuration of each assistant, standardizing their setup.
- Updated the "Prompt Optimizer" description to "Optimize prompts for better results" and modified the "QueryDSL Generator" to "Query Builder" for improved clarity.
- Ensured consistent naming conventions and descriptions across all assistant packages to enhance user experience and documentation clarity.
- Updated the `shouldAutoSearch` method to include additional parameters for improved intent detection, allowing for better decision-making on whether to execute auto search.
- Introduced a new `checkSearchIntent` method to utilize the `__yao.needsearch` agent for determining the necessity of a search based on user input.
- Implemented a `ClearExcept` method in the cache to selectively clear non-system agents while preserving essential system agents during cache management.
- Updated the `LoadBuiltIn` function to maintain system agents in the cache, ensuring they remain available for use.
- Enhanced test coverage for loading system agents and validating search intent detection, ensuring robustness in the assistant's search capabilities.
- Revised localization files to include new messages for search intent feedback, improving user experience during search operations.
- Added configuration support for system agents in the assistant initialization process, allowing for custom connectors for agents like __yao.keyword and __yao.querydsl.
- Implemented the loading mechanism for system agents from bindata, ensuring that essential agents are available during runtime.
- Updated the LoadBuiltIn function to exclude system agents from being removed, enhancing the management of built-in and system agents.
- Enhanced test coverage by introducing tests for loading system agents, verifying their presence and correctness in the cache.
- Updated documentation to reflect the new system agents configuration and loading processes.
- Introduced a new `Search` type to store intermediate processing results, including extracted keywords, entities, relations, and generated QueryDSL for improved debugging and citation support.
- Updated the `executeAutoSearch` method to populate the new `Search` structure, ensuring all relevant data is captured during search execution.
- Implemented methods for saving and retrieving search records in MongoDB and Redis, enhancing data persistence across sessions.
- Revised localization files to include new keys for search-related messages, improving user experience.
- Updated DESIGN.md to reflect changes in the search result structure and data flow, ensuring comprehensive documentation of the new features.
- Introduced a new search configuration structure, allowing for detailed settings for web, knowledge base, database, citation, and weights.
- Updated the `Assistant` model to include a `Search` field, enabling assistant-specific search configurations.
- Enhanced the loading and merging logic for search configurations, ensuring global defaults can be overridden by assistant-specific settings.
- Added comprehensive tests for loading, saving, and updating assistants with search configurations, verifying the integrity of search settings.
- Updated documentation in DESIGN.md to reflect the new search configuration hierarchy and usage, clarifying the interaction between global and assistant-level settings.
- Introduced `GetInfo` method in the Assistant struct to return basic assistant information with optional locale support for internationalization.
- Implemented `GetInfoByIDs` function to retrieve information for multiple assistants based on their IDs, enhancing batch processing capabilities.
- Updated chat buffer management to include a mode parameter, allowing for dynamic switching between chat and task modes.
- Enhanced message handling to store and retrieve the mode associated with each message, improving context tracking during chat sessions.
- Revised tests to validate the new functionalities, ensuring accurate retrieval of assistant information and proper mode management in chat operations.
- Updated the `ChatBuffer` to support streaming messages, allowing for content to be appended and finalized with `SendStream` and `End` methods.
- Modified the `AddAssistantMessage` method to include a message ID, improving message tracking and retrieval.
- Implemented new methods for appending content to streaming messages and completing them, ensuring accurate message storage and event handling.
- Revised tests to validate the new streaming functionality and ensure proper integration with existing message handling processes.
- Updated `CHAT_STORAGE_DESIGN.md` to reflect changes in message storage and indexing, including unique constraints for message IDs within requests.
- Enhanced chat buffer and message handling to support dynamic connector switching, allowing users to change the connector during a chat session.
- Updated the `ChatBuffer` and `BufferedMessage` structures to include a `connector` field, enabling tracking of the connector used for each message.
- Modified the `EnsureChat` method to skip chat creation when history is disabled, improving chat session management.
- Revised tests to validate the new connector functionality, ensuring accurate message retrieval and connector state management.
- Updated `CHAT_STORAGE_DESIGN.md` to reflect the addition of the `last_connector` field in chat metadata and message structures.
- Added CreateChat, GetChat, UpdateChat, and DeleteChat methods to manage chat sessions effectively.
- Implemented validation for required fields and handling of nullable fields during chat creation and updates.
- Enhanced chat retrieval with pagination and filtering options, including time-based grouping.
- Introduced helper functions for converting database rows to Chat structs and grouping chats by time.
- Updated message and resume models to support soft deletes, improving data management and integrity.
- Removed the `history` model and replaced it with a new `message` model to streamline chat message storage and retrieval.
- Introduced a `resume` model to enhance the chat's ability to recover from interruptions, capturing essential execution state data.
- Updated the `CHAT_STORAGE_DESIGN.md` to reflect these changes, including new fields and relationships for the message and resume models.
- Revised related functions and tests to support the new data structures, ensuring improved integrity and performance in chat interactions.
- Updated `GetText` and `SaveText` methods to support both full content and a preview (first 2000 characters) for improved performance and usability.
- Added comprehensive tests in `manager_test.go` to validate the new functionality, including UTF-8 character handling and content retrieval scenarios.
- Modified the attachment model to include a `content_preview` field alongside the existing `content` field, ensuring efficient data management.
- Enhanced the README.md to document the new dual storage feature, providing clear examples for users on how to utilize the updated methods.
- Implemented `GetText` and `SaveText` methods in the attachment manager to handle storing and retrieving parsed text content from files.
- Enhanced the `manager_test.go` with comprehensive tests for various scenarios, including saving, updating, and retrieving text, as well as handling non-existent file IDs.
- Updated the README.md to document the new text content storage features, providing examples for saving and retrieving parsed text.
- Modified the attachment model to include a new `content` field for storing text content, improving the overall functionality of the attachment management system.
- Introduced `modes` field to support multiple operational modes for the assistant, allowing for flexible functionality (e.g., chat, task).
- Added `default_mode` field to specify the primary mode of operation for the assistant.
- Updated the `Map`, `Clone`, and `Update` methods to handle the new fields appropriately.
- Enhanced the `ToAssistantModel` conversion function to include the new fields.
- Added tests to validate the integration and functionality of modes and default mode within the assistant model.
- Introduced a new `Database` type to encapsulate database models and options.
- Updated the `Assistant` model to include a `DB` field for database configuration.
- Enhanced the `Map`, `Clone`, and `Update` methods to handle the new `DB` field appropriately.
- Implemented the `ToDatabase` conversion function to support various input types for database initialization.
- Added comprehensive tests to validate the integration of the database functionality within the assistant model.
- Updated relevant fields and methods to ensure consistent handling of the new database configuration.
- Introduced the `disable_global_prompts` field in the Assistant model to control the usage of global prompts.
- Updated the Load and Get methods to initialize and retrieve global prompts from the configuration.
- Refactored tests to validate the new global prompts functionality and ensure proper loading and context handling.
- Improved the overall structure and clarity of the assistant's capabilities and configurations.
- Enhanced the getConnectorCapabilities method to prioritize model capabilities and connector settings, improving capability retrieval logic.
- Deprecated the tools field in the Assistant model, transitioning to MCP for tool management, and updated related methods accordingly.
- Introduced new fields for connector options and prompt presets in the Assistant model, allowing for more flexible configurations.
- Updated the GetAssistant method to support field selection, improving data retrieval efficiency and flexibility.
- Refactored tests and documentation to reflect changes in the assistant structure and capabilities, ensuring clarity and maintainability.
- Added global uses configuration to the assistant, allowing for centralized management of vision, audio, search, and fetch settings.
- Updated the Assistant struct and related methods to support the new Uses configuration, improving flexibility in assistant operations.
- Refactored the Stream method to utilize the new CompletionResponse type, enhancing response handling.
- Introduced new methods for building requests and managing capabilities, streamlining the assistant's interaction with various connectors.
- Updated assistant data handling to utilize structured models, improving code clarity and maintainability.
- Enhanced the assistant save and load functions to work with the new AssistantModel structure.
- Refactored mention handling to streamline the conversion process from raw data to structured mentions.
- Improved error handling in the assistant save process, ensuring better feedback for invalid data.
- Updated API responses to use the new gin.H format for consistency across the application.
- Deleted session-related functions (UserID, GuestID, UserRoles, UserOrGuestID) from the agent package to streamline the codebase.
- Removed RAG-related code and references, simplifying the agent's architecture.
- Updated API and load functions to reflect these changes, ensuring consistency across the agent module.
- Enhanced test coverage by cleaning up deprecated test cases related to removed functionalities.
- Introduced new fields in the attachment model for public access control and sharing options, allowing attachments to be marked as public or shared with specific teams.
- Updated the upload process to handle new permission fields, ensuring proper handling of public and share options during file uploads.
- Implemented permission checks in the file retrieval and deletion processes to enforce access control based on user roles and attachment settings.
- Added comprehensive tests for the new permission fields to validate functionality and ensure correct behavior in various scenarios.
- Updated the modification times for various assets in `bindata.go` to reflect recent changes.
- Refactored import statements in `team_invitation.go` to maintain consistency and improve code organization by moving the `utils` import to the correct position.
- Updated the modification times for various assets in `bindata.go` to reflect recent changes.
- Enhanced the collection management in the API by adding new fields for `preset`, `public`, and `share` in the collection and document models, allowing for better control over collection visibility and sharing options.
- Updated the `CreateCollection` function to incorporate the new `share` field, improving the handling of collection data based on user permissions.
- Refactored utility functions to streamline type conversions, ensuring consistent data handling across the user and team management functionalities.
- Added `Parse` function to handle attachment wrapper strings, extracting uploader name and file ID.
- Introduced `Base64` function to convert attachment wrappers to Base64 format, with optional data URI support.
- Enhanced `readFilePathAsBase64` to read files from the filesystem and return Base64 encoded content.
- Updated `teamInvitationGetPublic` to process team logos and inviter pictures as Base64 for direct display in the response.
- Introduced the `robot_email`, `authorized_senders`, and `email_filter_rules` fields to the robot member model, enhancing the configuration options for robot members.
- Updated the member creation and existence check logic to ensure the uniqueness of `robot_email` globally, improving data integrity.
- Refactored API endpoints and request/response structures to accommodate the new fields, ensuring consistency across the member management system.
- Enhanced test cases to validate the new robot member features, including scenarios for email uniqueness and configuration updates, improving overall test coverage and reliability.
- Added the is_owner field to the member model to indicate if a member is the team owner, improving clarity and performance for queries related to team ownership.
- Updated the team creation process to automatically set the is_owner field for the creator of the team, ensuring accurate member status upon creation.
- Refactored related tests to verify the correct assignment of the is_owner field, enhancing test coverage and reliability in team membership scenarios.
- Removed redundant permission and restriction fields from the member model to streamline the data structure and improve maintainability.
- Introduced member_id as a unique identifier for members, improving data integrity and consistency across member operations.
- Updated member-related functions to utilize member_id instead of internal IDs, enhancing API usability and clarity.
- Implemented email existence checks for team members, allowing for better validation during member creation and updates.
- Refactored existing tests to accommodate changes in member identification and email validation, ensuring comprehensive coverage and reliability.
- Added new API endpoint for checking if an email exists within a team, improving user experience during member management.
- Enhanced the member model by adding 'avatar' and updating 'display_name' and 'bio' fields for improved identity representation.
- Refactored robot member creation and validation to utilize the new fields, ensuring consistency across user and robot profiles.
- Updated test cases to reflect changes in member data structure, improving coverage and accuracy in robot member operations.
- Adjusted database indices and constraints to accommodate new fields and ensure efficient querying.
- Added display_name, bio, and email fields to the member model for improved team-specific identity.
- Updated team invitation creation and acceptance logic to handle new profile fields, ensuring proper data management and user experience.
- Implemented logic to copy user profile fields when creating or updating members, enhancing data consistency.
- Added role_id field to the team model for specifying team owner roles.
- Enhanced team creation logic to set default role_id based on team configuration if not provided.
- Updated tests to reflect changes in team type and role handling, ensuring accurate assertions.
- Improved documentation for team configuration to clarify default role settings for team creators.
- Introduced the invitation model in bindata.go, including the new invitation.mod.yao file.
- Updated system models to include the invitation model for better integration.
- Added invitation code related error handling in default.go, enhancing user experience during invitation processes.
- Implemented invitation code management methods in the user provider interface, allowing for creation, usage, and deletion of invitation codes.
- Enhanced entry configuration to support invitation code verification, improving the user registration flow.
- Added a new endpoint for verifying invitation codes in user routing, streamlining the invitation redemption process.
- Updated modification times for various asset files in bindata.go to reflect recent changes.
- Enhanced user authentication by adding support for custom claims in the context during authorization, improving flexibility in handling user data.
- Refactored entry verification logic to generate and send OTPs for user registration, streamlining the registration process and improving user experience.
- Introduced new status handling for user accounts, ensuring proper feedback for pending, unverified, and disabled accounts during login attempts.
- Added 'locale' field to user type structure for language localization.
- Updated API methods to include locale in pricing and published types retrieval.
- Enhanced tests to validate locale handling in user type operations, ensuring robust support for multiple languages.
- Updated user type structure to include new fields for pricing: price_daily, price_monthly, price_yearly, and credits_monthly.
- Added status field to manage publishing states (draft, published, archived) for user types.
- Enhanced the user type API to support pricing operations, including retrieval and updates for pricing information.
- Refactored tests to cover new pricing functionalities and ensure robust handling of user type statuses.
- Updated the UpdateUserLastLogin method to accept a LoginContext, allowing for tracking of last login IP, user agent, device, and platform.
- Modified the LoginThirdParty and LoginByUserID functions to utilize the new LoginContext, improving the accuracy of login tracking.
- Enhanced the user model to include fields for last login details, ensuring comprehensive user activity logging.
- Refactored tests to validate the new login context handling, ensuring robust coverage of the updated functionality.
- Introduced invitation_id handling for member management, allowing for unique identification of pending invitations.
- Added methods to create, update, and remove members by invitation_id, improving the invitation workflow.
- Updated member data structures and API responses to include invitation-related fields, enhancing clarity and usability.
- Implemented tests for invitation ID operations, ensuring robust validation and error handling.
- Refactored team access checks to streamline member management processes.
- Updated the member model to include a new member_type field, allowing differentiation between human and robot members.
- Added fields specific to robot members, including robot_name, robot_description, and robot_avatar, to capture essential information.
- Introduced robot configuration fields such as robot_config, agents, tools, and data_access_permissions for enhanced functionality.
- Implemented scheduling and automation features for robots, including is_active_robot, schedule_config, and activity_frequency.
- Enhanced indexing to support efficient queries for robot members and their activities, improving overall system performance.
- Reorganized models by replacing the assistant and chat models with a new agent structure, including assistant, chat, and history models.
- Updated user model relationships to reflect changes in role and type references, ensuring consistency with the new model structure.
- Removed obsolete organization and user role models, streamlining the overall architecture.
- Adjusted system model mappings to incorporate new member and role models, enhancing clarity in user management.
