* 去掉MCP框架，重构
* 去掉MCP框架，重构
* 去掉MCP框架，重构
* 去掉MCP框架，重构
* 去掉MCP框架，重构
* 去掉MCP框架，重构
* 去掉MCP框架，重构
* feat(celery): add comprehensive logging to worker and write task
- Initialize logging system in Celery worker entry point with LoggingConfig
- Add logger instance and startup message to celery_worker.py
- Reorganize imports in tasks.py for better readability and consistency
- Add detailed logging to write_message_task for debugging and monitoring
- Log task start with group_id, config_id, and storage_type parameters
- Log service execution and completion status with results
- Add exception handling with error logging and stack trace capture
- Log task completion time and Celery task ID for performance tracking
- Improves observability and troubleshooting of async task execution
* 去掉MCP框架，重构
* 去掉MCP框架，重构
* 快速检索，需要在接口部分添加LLM整合
* 快速检索，需要在接口部分添加LLM整合
---------
Co-authored-by: Ke Sun <kesun5@illinois.edu>
* [changes]《Modify the interface》
1.Remove the "/search/entity_graph" interface
2.Reconstruct the "/updated_end_user/profile" interface
3.Remove the "Update Username" interface
4.Fix the batch query of user association memory configuration
* [changes]《Modify the interface》
1.Remove the "/search/entity_graph" interface
2.Reconstruct the "/updated_end_user/profile" interface
3.Remove the "Update Username" interface
4.Fix the batch query of user association memory configuration
* [fix]Fix the error response type
* refactor(celery): optimize task routing and worker configuration
- Simplify Celery queue configuration with single default 'io_tasks' queue
- Implement task routing strategy separating IO-bound and CPU-bound tasks
- Add Flower monitoring support with task event tracking enabled
- Add summary node search optimization to only retrieve summary nodes
- Clean up unused imports and reorganize import statements for consistency
- Update docker-compose configuration to support multi-queue worker setup
* chore(celery): simplify flower configuration and add gevent dependency
* chore(dependencies): add gevent dependency to requirements
- Add gevent==24.11.1 to api/requirements.txt
- Gevent is required for async worker support in Celery
- Complements existing flower and celery configuration
* refactor(celery): simplify async event loop handling and reorganize task queues
- Replace complex nest_asyncio and manual event loop management with asyncio.run() in read_message_task, write_message_task, regenerate_memory_cache, and workspace_reflection_task
- Rename task queues from io_tasks/cpu_tasks to memory_tasks/document_tasks for better semantic clarity
- Update task routing configuration to reflect new queue names for memory agent tasks and document processing tasks
- Remove redundant exception handling comments and simplify error handling logic
- Update README with improved community support section including GitHub Issues, Pull Requests, Discussions, and WeChat community links
- Simplifies event loop management by leveraging asyncio.run() which handles loop creation and cleanup automatically, reducing code complexity and potential race conditions
* [feature]A set of information for role recognition writing
* [feature]A set of information for role recognition writing
* [fix]Fix the code after rebasing.
* [feature]A set of information for role recognition writing
* [fix]Fix the code after rebasing.
* [fix]Based on the AI review to fix the code
* [changes]Disable the function of batch writing multiple groups of conversations in a cumulative manner
* [fix]Addressing vulnerability risks
* [fix]Fixing short-term memory writing
* [feature]A set of information for role recognition writing
* [fix]Fix the code after rebasing.
* [feature]A set of information for role recognition writing
* [fix]Fix the code after rebasing.
* [fix]Based on the AI review to fix the code
* [fix]Fixing short-term memory writing
* [feature]A set of information for role recognition writing
* [feature]A set of information for role recognition writing
* [fix]Fix the code after rebasing.
* [feature]A set of information for role recognition writing
* [fix]Fix the code after rebasing.
* [fix]Based on the AI review to fix the code
* [changes]Disable the function of batch writing multiple groups of conversations in a cumulative manner
* [fix]Addressing vulnerability risks
* 去掉MCP框架，重构
* 去掉MCP框架，重构
* 去掉MCP框架，重构
* 去掉MCP框架，重构
* 去掉MCP框架，重构
* 去掉MCP框架，重构
* 去掉MCP框架，重构
* feat(celery): add comprehensive logging to worker and write task
- Initialize logging system in Celery worker entry point with LoggingConfig
- Add logger instance and startup message to celery_worker.py
- Reorganize imports in tasks.py for better readability and consistency
- Add detailed logging to write_message_task for debugging and monitoring
- Log task start with group_id, config_id, and storage_type parameters
- Log service execution and completion status with results
- Add exception handling with error logging and stack trace capture
- Log task completion time and Celery task ID for performance tracking
- Improves observability and troubleshooting of async task execution
* 去掉MCP框架，重构
* 去掉MCP框架，重构
---------
Co-authored-by: Ke Sun <kesun5@illinois.edu>
* [feature]Emotional memory cache
* [feature]Implicit memory cache
* [changes]Modify the expiration time of implicit memory to 24 hours.
* [feature]Emotional memory cache
* [feature]Implicit memory cache
* [changes]Modify the expiration time of implicit memory to 24 hours.
* [changes]Modify the code based on the AI review
* [feature]Emotional memory cache
* [feature]Implicit memory cache
* [changes]Modify the expiration time of implicit memory to 24 hours.
* [feature]Implicit memory cache
* [changes]Modify the code based on the AI review
* [feature]Generate emotions, implicit cache
* [feature]Generate emotions, implicit cache
* [changes]Improve the code based on AI review
* [changes]Improve the code based on AI review
* [changes]Improve the code
* [feature]Generate emotions, implicit cache
* [changes]Improve the code based on AI review
* [changes]Improve the code
* [fix]The repair model does not allow null values and does not support relational networks.
* [fix]The repair model does not allow null values and does not support relational networks.
* [changes]Restore field restrictions
* [refactor]Reconstructing forgotten, emotional, situational, and explicit memory statistics
* [refactor]Reconstructing forgotten, emotional, situational, and explicit memory statistics
* [changes]Improve the code based on AI review
* [changes]Statistics on work, perception, short-term, and implicit memory
* [changes]Statistics on work, perception, short-term, and implicit memory
* [changes]Replace the invisible memory calculation method
* [changes]Statistics on work, perception, short-term, and implicit memory
* [refactor]Reconstructing forgotten, emotional, situational, and explicit memory statistics
* [changes]Statistics on work, perception, short-term, and implicit memory
* [changes]Replace the invisible memory calculation method
- Add [PERF] prefixed logging throughout hybrid search pipeline for better performance visibility
- Break down latency metrics with separate timing for config loading, embedder initialization, and rerank computation
- Format latency breakdown as JSON in performance summary logs
- Optimize batch_record_access to process node access records in parallel using asyncio.gather instead of sequential processing
- Add performance timing instrumentation for forgetting config loading and rerank computation stages
- Reorganize imports in access_history_manager for consistency
- Improve observability of search performance bottlenecks through structured logging
* [refactor]Reconstructing forgotten, emotional, situational, and explicit memory statistics
* [refactor]Reconstructing forgotten, emotional, situational, and explicit memory statistics
* [changes]Improve the code based on AI review
