[codex] fix celery worker stability and workflow tracking

[earayu]

What Changed

• disable LiteLLM async logging callbacks during Celery worker initialization to avoid cross-event-loop crashes in worker processes
• follow the real child chord workflow when reporting Celery workflow status instead of reporting success as soon as fan-out is dispatched
• treat skipped index tasks as skipped in workflow aggregation instead of misclassifying them as failures
• initialize the evaluation system API key state safely when no key exists yet
• remove a stale Celery task route that points at a task name no longer present in the repo

Why

The Celery review found both correctness issues and a likely worker-stability issue.

On the live cluster, the last celeryworker restart exited with code 133, and the previous worker logs showed LiteLLM Queue ... is bound to a different event loop errors before process termination. The worker currently runs threaded Celery tasks while some task paths create fresh event loops via asyncio.run() / manual loop wrappers. LiteLLM's process-global async logging worker is not safe under that pattern, so this change disables that async callback path inside Celery worker processes.

Separately, workflow status tracking was reporting the outer trigger task rather than the terminal chord result, and skipped tasks could be misreported as failures.

Impact

• reduces the chance of Celery worker crashes caused by LiteLLM async logging worker loop affinity issues
• makes workflow status and workflow result summaries match real execution much more closely
• fixes a latent evaluation API key bootstrap bug
• removes stale config that could mislead future Celery routing/debugging work

Validation

• python3 -m py_compile config/celery.py config/celery_tasks.py aperag/tasks/scheduler.py aperag/service/evaluation_service.py aperag/llm/litellm_logging.py
• inspected live Kubernetes pod state and previous celeryworker logs to confirm the restart signature and LiteLLM event-loop errors

[apecloud-bot]

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