Image messages previously blocked the whole analysis pipeline:
- conversationProcessing was a single lock per conversation; processBatch
awaited BOTH text and media worker jobs before releasing it, so a fast
text verdict sat unused until the slow vision/media batch finished
- one global LLM semaphore (AI_LLM_MAX_CONCURRENT) was shared by text and
media, so a vision backlog could starve text inference
- recovery worker gated on conversationProcessing.size
Now the queue is split into independent text/media lanes:
- conversationProcessing maps key -> Partial<Record<lane, startedAt>>;
each lane holds its own lock and frees it the moment ITS worker job
resolves (ownership-guarded clear prevents stale timers clearing newer
slots)
- two LLM semaphores: AI_LLM_MAX_CONCURRENT (text, default 8) and
AI_LLM_MEDIA_MAX_CONCURRENT (media, default 4) via
withLlmConcurrency(fn, { lane })
- batchScheduler schedules per conversation+lane (timer keys
'<key>::<lane>'); splitMessagesByLane/laneOfMessage moved to pure
analysisLanes.ts (unit-testable without Piscina)
- ai-analysis-worker batch jobs carry a lane field; per-lane active
request gauges (active_text_requests / active_media_requests)
- added tests/analysisLaneLock.test.ts (7 tests: independent lane locks,
preserving other-lane lock, clear-all, ownership guard, lane split)
Docs: ARCHITECTURE.md + AGENTS.md concurrency model updated.
typecheck/lint/test(138)/build all green.
* feat(gateway): Jev (System One) as primary text moderator with LLM fallback
Add TypeSafe Jev via @typesafe-ai/sdk v0.6.0 as the PRIMARY analyzer for
text-only moderation sub-batches; the existing LLM stays as the fallback
for anything Jev cannot decide confidently (per-message gate rejection or
API failure) and for media batches.
- jevAnalyzer.ts: TypeSafeClient wrapper, declarative state builder
(System One models MUST get factual state, not chat-XML — chat framing
made Jev confidently wrong on clean messages at 0.98 confidence),
message-id-keyed question builder (5 typed questions per message),
cross-consistency acceptance gate (noul↔status↔severity↔action↔category),
answer→AnalysisResult mapper, fail-open outcome.
- textBatchProcessor.ts: Jev-first per sub-batch, rejected ids + API
failures fall back to callModerationLLM; no cross-batch pollution.
- config: AI_LLM_JEV_ENABLED/API_KEY/BASE_URL/MODEL/TIMEOUT_MS/MIN_CONFIDENCE.
- .env.example: documented all 6 Jev env vars.
- tests: unit (question/state builders, gate, mapper) + live smoke
(gated behind AI_LLM_JEV_SMOKE=1) verified 4/4 accepted vs real 9router.
* fix: auto-fix code quality [skip ci]
asepharyana