Refactors the AI moderation pipeline to improve concurrency control and
cache efficiency by moving from user-centric to content-centric caching.
- Implements a distributed locking mechanism for media analysis using
`acquireMediaAnalysisLock` to prevent redundant LLM vision calls across
multiple pods.
- Transitions text moderation caching from `user_mod:userId:hash` to a
purely content-based `text_mod:hash` approach to increase hit rates.
- Enhances `getPendingMessagesByConversation` with atomic transactions
and `FOR UPDATE SKIP LOCKED` to safely transition messages from
`pending` to `processing` state.
- Adds `processing` status to the `AIStatus` type and database schema to
track active analysis lifecycles.
- Implements polling logic in `llmModerationClient.ts` to wait for
in-progress media analyses.
MythEclipse
f057bf1f0b