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@glin93 glin93 commented Nov 29, 2025

Description

Summary: (summary)

Fix: #(issue)

Docs Issue/PR: (docs-issue-or-pr-link)

Reviewer: @(reviewer)

Checklist:

  • I have performed a self-review of my own code | 我已自行检查了自己的代码
  • I have commented my code in hard-to-understand areas | 我已在难以理解的地方对代码进行了注释
  • I have added tests that prove my fix is effective or that my feature works | 我已添加测试以证明我的修复有效或功能正常
  • I have created related documentation issue/PR in MemOS-Docs (if applicable) | 我已在 MemOS-Docs 中创建了相关的文档 issue/PR(如果适用)
  • I have linked the issue to this PR (if applicable) | 我已将 issue 链接到此 PR(如果适用)
  • I have mentioned the person who will review this PR | 我已提及将审查此 PR 的人

glin1993@outlook.com and others added 19 commits November 29, 2025 11:26
Fix(Scheduler): Correct create_event_log indentation
Reverts previous incorrect fix to scheduler_logger.py and correctly fixes the TypeError at the call sites in general_scheduler.py by removing the invalid 'log_content' kwarg and adding the missing memory_type kwargs.
This completes the fix for the task_id loss. The 'to_dict' method was previously fixed to serialize the task_id, but the corresponding 'from_dict' method was not updated to deserialize it, causing the value to be lost when messages were read from the queue.
Moves all environment variable override logic into initialize_rabbitmq for a single source of truth. This ensures Nacos-provided environment variables for all RabbitMQ settings are respected over file configurations. Also removes now-redundant logging from the publish method.
Resolves DataError in Redis Streams when task_id is None by ensuring
it's serialized as an empty string instead of None, which Redis does
not support. Applies to ScheduleMessageItem.to_dict method.
Adds an INFO level diagnostic log message at the beginning of the
create_memory function to help verify code deployment.
Introduces detailed INFO level diagnostic logs across the entire call chain
for the /product/add API endpoint. These logs include relevant context,
such as full request bodies, message items before scheduler submission,
and messages before RabbitMQ publication, to aid in debugging deployment
discrepancies and tracing data flow, especially concerning task_id
propagation.

Logs added/enhanced in:
- src/memos/api/routers/product_router.py
- src/memos/api/handlers/add_handler.py
- src/memos/multi_mem_cube/single_cube.py
- src/memos/mem_os/core.py
- src/memos/mem_scheduler/general_scheduler.py
- src/memos/mem_scheduler/base_scheduler.py
- src/memos/mem_scheduler/webservice_modules/rabbitmq_service.py
…d apply ruff formatting

Introduces detailed INFO level diagnostic logs across the entire call chain
for the /product/add API endpoint. These logs include relevant context,
such as full request bodies, message items before scheduler submission,
and messages before RabbitMQ publication, to aid in debugging deployment
discrepancies and tracing data flow, especially concerning task_id
propagation.

Also applies automatic code formatting using ruff format to all modified files.

Logs added/enhanced in:
- src/memos/api/routers/product_router.py
- src/memos/api/handlers/add_handler.py
- src/memos/multi_mem_cube/single_cube.py
- src/memos/mem_os/core.py
- src/memos/mem_scheduler/general_scheduler.py
- src/memos/mem_scheduler/base_scheduler.py
- src/memos/mem_scheduler/webservice_modules/rabbitmq_service.py
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2 participants