* [fix]The log retains genuine alerts and errors, while filtering out unnecessary noise.
* [fix]Scenario English and Chinese, emotion specifications
* [fix]Change the "no data" scenario from 0.0 to None
* [fix]The emotional health indicators, emotional advice, and emotional distribution analysis are all linked together.
* [fix]The emotional health indicators, emotional advice, and emotional distribution analysis are all linked together.
* [fix]Separate expected errors from unexpected errors
* [fix]The log retains genuine alerts and errors, while filtering out unnecessary noise.
* [fix]Scenario English and Chinese, emotion specifications
* [fix]Change the "no data" scenario from 0.0 to None
- Correct loop variable type detection to handle actual Python types
- Update StreamOutput control_nodes to support list of branches and fix upstream control node analysis
- Fix full_content aggregation in WorkflowExecutor for streaming outputs
- Initialize VariablePool with default "sys" and "conv" scopes
* [fix]Fix ID: 1004684 - Bug fixed. New "end_user_id" field added to the implicit memory interface.
* [fix]Fix bug ID1004858 and standardize Neo4j log output
* [changes]The main warehouse is associated with the sub-warehouse.
* [fix]Fix ID: 1004684 - Bug fixed. New "end_user_id" field added to the implicit memory interface.
* [fix]Fix bug ID1004858 and standardize Neo4j log output
* [changes]The main warehouse is associated with the sub-warehouse.
* [changes]Based on the AI review, the code has been corrected.
* [changes]Recovery of Implicit Memory Interface
* [add]Integration of the core engineering and memory extraction
* [add]The import and export function of the main body engineering files
* [add]Improve the import interface
* [add]Introducing generic types helps with entity extraction
* [add]Modify the references of the main repository to the sub-repositories
* [add]The extraction trial run introduces the ontology type.
* [add]Integration of the core engineering and memory extraction
* [add]The import and export function of the main body engineering files
* [add]Improve the import interface
* [add]Introducing generic types helps with entity extraction
* [add]Modify the references of the main repository to the sub-repositories
* [add]The extraction trial run introduces the ontology type.
* [add]Complete the second phase of the main project content
* [add]The dependencies and configurations of the main body project
* [add]Modify the code based on the AI review
- Add support for both memory_config_id (new) and memory_content (legacy) field names
- Implement detection and handling of legacy int format memory configurations
- Add validation for numeric string formats with appropriate warning logs
- Support case-insensitive memory node type matching (MemoryRead/MemoryWrite and memory-read/memory-write)
- Improve error handling with more descriptive logging for invalid UUID strings
- Fix config_id field reference in memory config resolution
- Ensure backward compatibility with existing agent configurations while supporting new format
- Add workspace_id fallback parameter to memory config loading across all services
- Update hot_memory_tags.py to pass workspace_id when resolving memory configuration
- Enhance emotion_analytics_service.py to support workspace_id as fallback for config resolution
- Improve implicit_memory_service.py with workspace_id fallback in config loading
- Update memory_agent_service.py to handle workspace_id resolution and add refactoring TODO
- Enhance preference_analysis.jinja2 prompt with critical guidance on supporting_evidence extraction
- Add validation to check both config_id and workspace_id before raising configuration errors
- Improve error handling and logging for memory configuration resolution across services
- This enables more flexible memory configuration resolution when config_id is unavailable
