1. Add the "Skills" module;
2. The loading of the model square has been modified to be controlled through environment variables;
3. Dynamic scheduling of the skill binding tool;
4. Agent Integration Skills
* [changes]Add 'id' as the secondary sorting key, and 'scene_id' now returns a UUID object
* [fix]Fix the "end_user" return to be sorted by update time.
* [fix]Set the default values of the memory configuration model based on the spatial model.
* [fix]Remove the entity extraction check combination model, read the configuration list, and add the return of scene_id
* [fix]Fix the "end_user" return to be sorted by update time.
* [fix]
* [changes]add user_summary language unification
* [add]Entity extraction, user memory, emotion suggestions, unified language type for writing
* [add]Complete the switch between Chinese and English for the emotion labels and emotion suggestions fields.
* [changes]add user_summary language unification
* [add]Entity extraction, user memory, emotion suggestions, unified language type for writing
* [add]Complete the switch between Chinese and English for the emotion labels and emotion suggestions fields.
* [changes]Modify the code based on the AI review
- Remove get_memory_config_id function from end_user_repository.py as it's no longer needed
- Remove get_end_user_memory_config_id function from memory_agent_service.py to reduce duplication
- Simplify get_end_user_connected_config to use MemoryConfigService.get_config_with_fallback
- Update get_config_with_fallback signature to accept memory_config_id directly instead of end_user_id
- Remove unnecessary AppRelease query and config parsing logic from get_end_user_connected_config
- Streamline memory config retrieval flow to use service layer abstraction
- Improves code maintainability by centralizing config fallback logic in MemoryConfigService
* [modify] migration script
* [add] migration script
* fix(web): change form message
* fix(web): the memoryContent field is compatible with numbers and strings
* feat(web): code node hidden
* fix(model):
1. create a basic model to check if the name and provider are duplicated.
2. The result shows error models because the provider created API Keys for all matching models.
---------
Co-authored-by: Mark <zhuwenhui5566@163.com>
Co-authored-by: zhaoying <yzhao96@best-inc.com>
Co-authored-by: yingzhao <zhaoyingyz@126.com>
Co-authored-by: Timebomb2018 <18868801967@163.com>
1. create a basic model to check if the name and provider are duplicated.
2. The result shows error models because the provider created API Keys for all matching models.
- Extract default memory config retrieval logic from AppService to MemoryConfigService
- Make get_workspace_default_config method public (remove underscore prefix)
- Update AppService to delegate to MemoryConfigService for cleaner separation of concerns
- Add legacy int config_id handling in delete_config method with appropriate warnings
- Update delete_config signature to accept UUID or int types for backward compatibility
- Improve code reusability and maintainability by centralizing memory config operations
- Add .hypothesis/ to .gitignore for test framework artifacts
- Remove outdated comment from EndUser model memory_config_id field
- Update memory config extraction methods to return tuple with legacy format flag
- Add detection for legacy int-formatted memory_config_id in Agent and Workflow configs
- Implement workspace default memory config fallback when legacy int format detected
- Add _get_workspace_default_memory_config_id method to retrieve default or earliest active config
- Update return types from Optional[uuid.UUID] to Tuple[Optional[uuid.UUID], bool] for extraction methods
- Add comprehensive logging for legacy format detection and fallback behavior
- Improve backward compatibility for applications with old int-based memory configuration data
- Add force parameter to delete_config endpoint for controlled deletion of in-use configs
- Implement MemoryConfigService.delete_config with protection against deleting default configs
- Add validation to prevent deletion of configs with connected end-users unless force=True
- Reorganize controller imports to remove duplicates and improve maintainability
- Clean up unused database connection management code from memory_storage_controller
- Add detailed docstring to delete_config endpoint explaining protection mechanisms
- Update error handling with specific BizCode.RESOURCE_IN_USE for configs in active use
- Add comprehensive logging for deletion attempts, warnings, and affected users
- Refactor ConfigParamsDelete schema usage to use MemoryConfigService directly
- Improve API response structure with affected_users count and force_required flag
- Add memory_config_id field to EndUser model for lazy caching of memory configuration
- Create get_end_user_memory_config_id() function for fast retrieval of cached config ID
- Implement lazy update mechanism in get_end_user_connected_config() to cache memory_config_id
- Optimize memory config lookup by storing config ID directly on end_user record
- Improve import organization and formatting in memory_agent_service.py
- Add indexed foreign key relationship to data_config table for efficient queries
