fix(gateway): separate text and media lanes in AI analysis queue (#86)

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.

services/discord-gateway/AGENTS.md

@@ -69,8 +69,14 @@ textBatchProcessor.ts    mediaBatchProcessor.ts         llmClient.ts
 ```
 
 - Entry: `aiAnalyzer.ts` (`queueMessageAnalysis`, `startPendingAIAnalysisWorker`)
-- Concurrency: LLM semaphore (`AI_LLM_MAX_CONCURRENT`, default 5)
+- Concurrency: **two per-lane LLM semaphores** (2026-09-24) — text
+  (`AI_LLM_MAX_CONCURRENT`, default 8) and media/vision
+  (`AI_LLM_MEDIA_MAX_CONCURRENT`, default 4); a media backlog can never
+  consume text slots
 - Piscina: text pool (4 threads) + media pool (2 threads)
+- Locks are **per conversation per lane** (`conversationProcessing` maps key →
+  lane → startedAt): the text lane of a conversation never waits on that
+  conversation's media lane (this was the "image blocks the queue" bug)
 - **Each worker thread has its own pg Pool** (min 0, grows to `POSTGRES_POOL_MAX`)
 
 ## Module: message-capture

services/discord-gateway/ARCHITECTURE.md

@@ -46,24 +46,38 @@ services/discord-gateway/
 ## AI moderation pipeline (`ai-moderation/`)
 
 LLM-only judge — no regex/heuristic classification. One orchestrator call
-handles a whole batch (text + media split internally, parallel paths).
+handles a whole batch. **Independent text/media lanes** (2026-09-24): a
+conversation batch is split into a text lane (messages with no media) and a
+media lane (attachments/stickers/embeds) that are dispatched to separate
+pools, hold SEPARATE per-lane processing locks, and run under SEPARATE LLM
+concurrency semaphores. The text lane frees its lock and saves+broadcasts the
+moment text analysis finishes — it never waits on a slow vision/media batch
+of the same conversation, and vice versa.
 
 - `aiAnalyzer.ts` — public API: `queueMessageAnalysis`, `getAnalysisQueueStatus`,
   `startPendingAIAnalysisWorker` (recovery worker + cache-prune).
-- `batchScheduler.ts` — per-conversation debounce → `processBatch`.
+- `batchScheduler.ts` — per-conversation per-LANE debounce → `processBatch`
-- `batchProcessor.ts` — batch lock/circuit-breaker, fans failed targets to
+  (lane-aware). `splitMessagesByLane` / `laneOfMessage` live in
-  individual fallback.
+  `analysisLanes.ts` (pure, unit-testable).
+- `batchProcessor.ts` — per-lane batch lock/circuit-breaker, fans failed
+  targets to individual fallback. `processBatch` releases ITS lane's lock the
+  moment that lane's worker job finishes; the other lane owns its own lock.
 - `individualFallbackProcessor.ts` — one-message-at-a-time retry path, own CB.
-- `conversationState.ts` / `circuitBreaker.ts` — per-conversation state,
+- `conversationState.ts` / `circuitBreaker.ts` — per-conversation PER-LANE
-  Piscina `workerPool`, `getConversationKey`.
+  state (`conversationProcessing` holds a lane → startedAt map per key),
-- `ai-analysis-worker.ts` — Piscina entry point (`batch` / `individual` jobs).
+  Piscina `textWorkerPool`/`mediaWorkerPool`, `getConversationKey`.
-  Runs `runModerationAnalysis` off the main thread.
+- `ai-analysis-worker.ts` — Piscina entry point (`batch` (lane) /
+  `individual` jobs). Runs `runModerationAnalysis` off the main thread.
 - `moderationOrchestrator.ts` — exact-hash cache → batched semantic (Qdrant)
   cache → LLM. Text and media paths run in parallel.
 - `textBatchProcessor.ts` / `mediaBatchProcessor.ts` — actual LLM calls
-  (one call per sub-batch, not per message).
+  (one call per sub-batch, not per message). `mediaBatchProcessor` routes its
+  moderation LLM call through the MEDIA semaphore.
 - `llmClient.ts` — central OpenAI-compatible chat client (streaming, retries,
-  thinking-disable injection). `visionAnalyzer.ts` / `mediaAnalysisClient.ts`
+  thinking-disable injection). TWO concurrency semaphores:
+  `AI_LLM_MAX_CONCURRENT` (text lane, default 8) and
+  `AI_LLM_MEDIA_MAX_CONCURRENT` (media lane, default 4) — a vision backlog
+  can never consume text slots. `visionAnalyzer.ts` / `mediaAnalysisClient.ts`
   share the same router/base URL (different model alias for vision).
 - `embeddingClient.ts` + `qdrantClient.ts` — semantic cache (one embed call +
   one batched Qdrant search for all uncached targets).
@@ -72,16 +86,16 @@ handles a whole batch (text + media split internally, parallel paths).
 
 ### Concurrency model
 
-- Main thread owns the LLM semaphore (`AI_LLM_MAX_CONCURRENT`, default 5) via
+- Main thread owns TWO per-lane LLM semaphores (2026-09-24):
-  `llmClient.withLlmConcurrency`.
+  `AI_LLM_MAX_CONCURRENT` (text, default 8) and `AI_LLM_MEDIA_MAX_CONCURRENT`
+  (media, default 4) via `llmClient.withLlmConcurrency(fn, { lane })`.
 - Two Piscina pools run the heavy LLM work off the event loop: a text pool
   (`PISCINA_MAX_THREADS`, default 4) and a dedicated media pool
-  (`PISCINA_MEDIA_MAX_THREADS`, default 2). A batch is routed to the media
+  (`PISCINA_MEDIA_MAX_THREADS`, default 2). A batch is routed by lane to the
-  pool if ANY of its messages carries an attachment/sticker/embed — this
+  matching pool — this keeps a slow image/vision batch from occupying every
-  keeps a slow image/vision batch from occupying every thread and blocking
+  thread and blocking unrelated text-only batches behind it. **Each worker
-  unrelated text-only batches behind it. **Each worker thread (in either
+  thread (in either pool) initializes its own pg Pool** (min 0, grows to
-  pool) initializes its own pg Pool** (min 0, grows to `POSTGRES_POOL_MAX`).
+  `POSTGRES_POOL_MAX`).  See "Memory & connections" below.
-  See "Memory & connections" below.
 
 ## Memory & DB connections
 

services/discord-gateway/src/app/bootstrap.ts

@@ -213,6 +213,14 @@ export async function initializeDiscordGateway() {
       const status = getAnalysisQueueStatus();
       setGauge("ai_analysis_queued_conversations", status.queuedConversations);
       setGauge("ai_analysis_active_batch_requests", status.activeRequests);
+      setGauge(
+        "ai_analysis_active_text_requests",
+        status.activeTextRequests ?? status.activeRequests,
+      );
+      setGauge(
+        "ai_analysis_active_media_requests",
+        status.activeMediaRequests ?? 0,
+      );
       setGauge(
         "ai_analysis_active_individual_requests",
         status.activeIndividualRequests,

services/discord-gateway/src/modules/ai-moderation/ai-analysis-worker.ts

@@ -86,7 +86,12 @@ export interface MessageBatch {
 
 // Worker job types (Piscina entry point)
 type WorkerJob =
-  | { type: "batch"; conversationKey: string; messages: MessageRecord[] }
+  | {
+      type: "batch";
+      conversationKey: string;
+      lane: "text" | "media";
+      messages: MessageRecord[];
+    }
   | { type: "individual"; message: MessageRecord; skipNormalAnalysis: boolean };
 
 type BatchOkResponse = {
@@ -263,6 +268,7 @@ function normalizeResult(
 async function processBatch(job: {
   type: "batch";
   conversationKey: string;
+  lane: "text" | "media";
   messages: MessageRecord[];
 }): Promise<BatchOkResponse | BatchErrorResponse> {
   const { conversationKey, messages } = job;

services/discord-gateway/src/modules/ai-moderation/aiAnalyzer.ts

@@ -5,7 +5,9 @@ import type { EventBroadcaster } from "../event-broadcaster/index.js";
 import { messageStore } from "../message-capture/messageStore.js";
 import type { AnalysisQueueStatus } from "../message-capture/types.js";
 import {
+  activeMediaRequests,
   activeRequests,
+  activeTextRequests,
   buildAgeRestrictedSkipResult,
   buildSkipAnalysisUserResult,
   isAgeRestrictedMessage,
@@ -16,6 +18,9 @@ import {
 import { scheduleConversationAnalysis } from "./batchScheduler.js";
 import { getConversationKey } from "./circuitBreaker.js";
 import {
+  ANALYSIS_LANES,
+  type AnalysisLane,
+  clearConversationProcessing,
   conversationConsecutiveErrors,
   conversationDebounceTimers,
   conversationErrorCooldown,
@@ -129,6 +134,8 @@ export function getAnalysisQueueStatus(): AnalysisQueueStatus {
   return {
     queuedConversations: conversationDebounceTimers.size,
     activeRequests,
+    activeTextRequests,
+    activeMediaRequests,
     activeIndividualRequests,
     individualInFlightCount: individualInFlight.size,
     individualCircuitBreakerActive: Date.now() < individualCooldownUntil,
@@ -204,9 +211,18 @@ export function startPendingAIAnalysisWorker(
         for (const [key, expiry] of conversationErrorCooldown) {
           if (now >= expiry) conversationErrorCooldown.delete(key);
         }
-        for (const [key, startedAt] of conversationProcessing) {
+        // conversationProcessing is now a Partial<Record<lane, startedAt>>.
-          if (now - startedAt >= config.AI_ANALYSIS_PROCESSING_TIMEOUT_MS) {
+        // Prune stale lane slots individually so one stale lane never clears
-            conversationProcessing.delete(key);
+        // the other lane's healthy lock.
+        for (const [key, record] of conversationProcessing) {
+          for (const lane of ANALYSIS_LANES as readonly AnalysisLane[]) {
+            const startedAt = record?.[lane];
+            if (
+              startedAt &&
+              now - startedAt >= config.AI_ANALYSIS_PROCESSING_TIMEOUT_MS
+            ) {
+              clearConversationProcessing(key, lane);
+            }
           }
         }
 
@@ -235,12 +251,23 @@ export function startPendingAIAnalysisWorker(
 
         // --- Batch recovery for pending messages ---
         for (const key of pendingKeys) {
-          if (conversationDebounceTimers.has(key)) continue;
+          if (
+            ANALYSIS_LANES.some((lane) =>
+              conversationDebounceTimers.has(`${key}::${lane}`),
+            )
+          ) {
+            continue;
+          }
+          // Batch recovery must not race ANY in-flight batch lane, so the
+          // lock check is lane-agnostic here (individual fallback handles
+          // error rows separately).
           if (isConversationProcessingLocked(key)) continue;
           if (individualInFlightByConversation.has(key)) continue;
           if (incompleteKeySet.has(key)) continue;
           const cooldownUntil = conversationErrorCooldown.get(key);
           if (cooldownUntil && now < cooldownUntil) continue;
+          // No lane specified → schedule BOTH lanes; each fetches its own
+          // pending subset from the DB.
           scheduleConversationAnalysis(key);
         }
 

services/discord-gateway/src/modules/ai-moderation/analysisLanes.ts

@@ -0,0 +1,35 @@
+/**
+ * analysisLanes.ts
+ *
+ * Pure lane helpers for the AI-analysis queue. Kept free of any import chain
+ * that pulls Piscina/worker/DB so they can be unit-tested in isolation (the
+ * scheduler's `splitMessagesByLane` used to live in batchScheduler.ts, which
+ * transitively imports the worker pool).
+ */
+import type { MessageRecord } from "../message-capture/types.js";
+import type { AnalysisLane } from "./conversationState.js";
+import { hasMediaContent } from "./mediaAnalysisClient.js";
+
+export type { AnalysisLane } from "./conversationState.js";
+
+/** True when this message belongs to the media lane (has attachment/sticker/embed). */
+export function laneOfMessage(message: MessageRecord): AnalysisLane {
+  return hasMediaContent(message) ? "media" : "text";
+}
+
+/**
+ * Splits an arbitrary message array into per-lane lists. Used when the
+ * scheduler runs a conversation-wide pass (lane omitted): each lane gets its
+ * own subset so text and media never share a worker job.
+ */
+export function splitMessagesByLane(messages: MessageRecord[]): {
+  text: MessageRecord[];
+  media: MessageRecord[];
+} {
+  const text: MessageRecord[] = [];
+  const media: MessageRecord[] = [];
+  for (const m of messages) {
+    (laneOfMessage(m) === "media" ? media : text).push(m);
+  }
+  return { text, media };
+}

services/discord-gateway/src/modules/ai-moderation/batchProcessor.ts

@@ -8,13 +8,14 @@ import { partitionBatchOutcome } from "./batchOutcomeClassifier.js";
 import { mediaWorkerPool, textWorkerPool } from "./circuitBreaker.js";
 import { estimateTokens } from "./conversationContext.js";
 import {
+  type AnalysisLane,
+  clearConversationProcessing,
   conversationErrorCooldown,
-  conversationProcessing,
+  getConversationProcessingStartedAt,
   recordConversationBatchFailure,
   resetConversationBatchFailures,
 } from "./conversationState.js";
 import { enqueueIndividualFallbacks } from "./individualFallbackProcessor.js";
-import { hasMediaContent } from "./mediaAnalysisClient.js";
 import {
   broadcastAnalysisCompleted,
   LAST_ERROR,
@@ -34,10 +35,12 @@ export interface AnalysisWorkerResponse {
 }
 
 // ---------------------------------------------------------------------------
-// Observability
+// Observability (per-lane counters live alongside the aggregate)
 // ---------------------------------------------------------------------------
 
 export let activeRequests = 0;
+export let activeTextRequests = 0;
+export let activeMediaRequests = 0;
 
 // ---------------------------------------------------------------------------
 // Exported helpers
@@ -182,32 +185,36 @@ export async function skipAnalysisUserMessages(
 // ---------------------------------------------------------------------------
 
 /**
- * Runs one worker job (either the text-only or the media sub-batch of a
+ * Runs ONE worker job for a single lane (text-only or media sub-batch of a
  * conversation) end-to-end: dispatch → broadcast/save → fallback routing.
- * Returns whether the *caller* should schedule the next debounce pass for
- * this conversation (mirrors the old single-job semantics, now evaluated
- * per queue).
  *
- * Broadcasting happens here, inside each queue's own call — NOT after
+ * The lock for this conversation+lane is RELEASED here as soon as THIS lane's
- * waiting on the other queue. That's the actual fix for "text menunggu
+ * worker job resolves — never after waiting on the other lane. That's the
- * image": previously one mixed conversation batch made ONE worker call
+ * core fix for "text menunggu image": previously one conversation batch made
- * with both text and media targets, and `runModerationAnalysis` only
+ * ONE worker call with both text and media targets, and processing finished
- * resolves (so results only get saved/broadcast) once BOTH finish — so a
+ * only once BOTH lanes completed, so a fast text verdict sat unused until the
- * fast text verdict sat unused until the slow vision/image verdict was
+ * slow vision/image verdict was ready. Now each lane's results save+broadcast
- * ready too. Splitting into two independent jobs means the text queue
+ * the moment ITS job finishes, and the conversation lock for that lane is
- * saves+broadcasts its rows the moment IT finishes, regardless of how long
+ * freed independently.
- * the media queue takes.
+ *
+ * Returns whether the *caller* should schedule the next debounce pass for
+ * this conversation's LANE.
  */
 async function runQueueBatch(
   pool: typeof textWorkerPool,
   conversationKey: string,
+  lane: AnalysisLane,
   messages: MessageRecord[],
 ): Promise<boolean> {
   activeRequests++;
+  if (lane === "media") activeMediaRequests++;
+  else activeTextRequests++;
+
   try {
     const result = (await pool.run({
       type: "batch",
       conversationKey,
+      lane,
       messages,
     })) as AnalysisWorkerResponse;
 
@@ -222,12 +229,13 @@ async function runQueueBatch(
     }
 
     if (!result.ok) {
-      recordConversationBatchFailure(conversationKey);
+      recordConversationBatchFailure(conversationKey, lane);
 
       // Batch failed entirely -- fall back all messages to individual queue
       logger.warn(
         {
           conversationKey,
+          lane,
           messageCount: messages.length,
           error: result.error,
         },
@@ -243,6 +251,7 @@ async function runQueueBatch(
       logger.error(
         {
           conversationKey,
+          lane,
           error: LAST_ERROR.value,
           messageCount: messages.length,
           messageIds: messages.map((m) => m.id),
@@ -284,6 +293,7 @@ async function runQueueBatch(
       logger.warn(
         {
           conversationKey,
+          lane,
           count: messagesForIndividualQueue.length,
           ids: messagesForIndividualQueue.map((m) => m.id),
           totalBatchSize: messages.length,
@@ -297,6 +307,7 @@ async function runQueueBatch(
       logger.warn(
         {
           conversationKey,
+          lane,
           count: apiFailedMessages.length,
           ids: apiFailedMessages.map((m) => m.id),
         },
@@ -335,7 +346,7 @@ async function runQueueBatch(
       }
 
       // Trigger conversation cooldown
-      recordConversationBatchFailure(conversationKey);
+      recordConversationBatchFailure(conversationKey, lane);
       const existingCooldown =
         conversationErrorCooldown.get(conversationKey) ?? 0;
       const newCooldown = Date.now() + config.AI_ANALYSIS_ERROR_COOLDOWN_MS;
@@ -347,14 +358,14 @@ async function runQueueBatch(
       return false;
     }
 
-    resetConversationBatchFailures(conversationKey);
+    resetConversationBatchFailures(conversationKey, lane);
     conversationErrorCooldown.delete(conversationKey);
     return true;
   } catch (error) {
-    recordConversationBatchFailure(conversationKey);
+    recordConversationBatchFailure(conversationKey, lane);
 
     logger.warn(
-      { conversationKey, messageCount: messages.length },
+      { conversationKey, lane, messageCount: messages.length },
       "Batch threw exception -- routing all messages to individual fallback queue",
     );
     enqueueIndividualFallbacks(messages);
@@ -370,6 +381,7 @@ async function runQueueBatch(
     logger.error(
       {
         conversationKey,
+        lane,
         error: LAST_ERROR.value,
         stack: errorStack,
         messageCount: messages.length,
@@ -384,59 +396,67 @@ async function runQueueBatch(
     return false;
   } finally {
     activeRequests--;
+    if (lane === "media") activeMediaRequests--;
+    else activeTextRequests--;
   }
 }
 
 export async function processBatch(
   conversationKey: string,
+  lane: AnalysisLane,
   messages: MessageRecord[],
   processingStartedAt: number,
 ): Promise<void> {
+  // Release this lane's lock immediately when there's nothing to do. The
+  // messages array was already labelled with the lane it belongs to by the
+  // scheduler (which fetched them from the DB), so an empty array means this
+  // lane has no work — free it so the debounce can re-arm right away.
   if (messages.length === 0) {
-    if (conversationProcessing.get(conversationKey) === processingStartedAt) {
+    if (
-      conversationProcessing.delete(conversationKey);
+      getConversationProcessingStartedAt(conversationKey, lane) ===
+      processingStartedAt
+    ) {
+      clearConversationProcessing(conversationKey, lane);
     }
     return;
   }
   const cooldownUntil = conversationErrorCooldown.get(conversationKey) ?? 0;
   if (Date.now() < cooldownUntil) {
-    if (conversationProcessing.get(conversationKey) === processingStartedAt) {
+    if (
-      conversationProcessing.delete(conversationKey);
+      getConversationProcessingStartedAt(conversationKey, lane) ===
+      processingStartedAt
+    ) {
+      clearConversationProcessing(conversationKey, lane);
     }
     return;
   }
 
-  // Split the batch itself — not just route it — so text and media never
+  const result = await runQueueBatch(
-  // share one worker call. A conversation batch commonly mixes plain-text
+    lane === "media" ? mediaWorkerPool : textWorkerPool,
-  // messages with an image/sticker from someone else; without this split,
+    conversationKey,
-  // ALL of it (including the plain-text messages) would ride along on the
+    lane,
-  // media job and wait for vision analysis to finish. Each sub-batch is now
+    messages,
-  // dispatched to its own pool AND handled independently below, so the text
-  // queue's results land as soon as text analysis completes, full stop.
-  const textMessages = messages.filter((m) => !hasMediaContent(m));
-  const mediaMessages = messages.filter((m) => hasMediaContent(m));
-
-  const jobs: Promise<boolean>[] = [];
-  if (textMessages.length > 0) {
-    jobs.push(runQueueBatch(textWorkerPool, conversationKey, textMessages));
-  }
-  if (mediaMessages.length > 0) {
-    jobs.push(runQueueBatch(mediaWorkerPool, conversationKey, mediaMessages));
-  }
-
-  const outcomes = await Promise.allSettled(jobs);
-  const shouldScheduleNext = outcomes.every(
-    (o) => o.status === "fulfilled" && o.value,
   );
 
-  if (conversationProcessing.get(conversationKey) === processingStartedAt) {
+  // Release THIS lane's lock now — the other lane (if any) is dispatched
-    conversationProcessing.delete(conversationKey);
+  // separately by the scheduler and owns its own lock. The old code awaited
+  // BOTH lanes (Promise.allSettled) before releasing the single conversation
+  // lock, so the text sub-batch of a conversation blocked its own lock until
+  // the slow media sub-batch finished. Now each lane is independent: the text
+  // lane frees its lock and re-schedules the moment the text worker returns.
+  if (
+    getConversationProcessingStartedAt(conversationKey, lane) ===
+    processingStartedAt
+  ) {
+    clearConversationProcessing(conversationKey, lane);
   }
-  if (shouldScheduleNext) {
+
+  if (result) {
     setImmediate(() => {
-      // Dynamic import to avoid circular dependency at module scope
+      // Dynamic import to avoid circular dependency at module scope.
+      // Re-schedule ONLY this lane — the other lane schedules itself.
       import("./batchScheduler.js").then((m) =>
-        m.scheduleConversationAnalysis(conversationKey),
+        m.scheduleConversationAnalysis(conversationKey, lane),
       );
     });
   }

services/discord-gateway/src/modules/ai-moderation/batchScheduler.ts

@@ -2,6 +2,7 @@ import { createChildLogger } from "@/shared/logger/index";
 import { config } from "../../shared/config/index.js";
 import { messageStore } from "../message-capture/messageStore.js";
 import type { MessageRecord } from "../message-capture/types.js";
+import { type AnalysisLane, splitMessagesByLane } from "./analysisLanes.js";
 import {
   pickBatchWithinBudget,
   processBatch,
@@ -9,12 +10,14 @@ import {
   skipAnalysisUserMessages,
 } from "./batchProcessor.js";
 import {
+  clearConversationProcessing,
   conversationConsecutiveErrors,
   conversationDebounceTimers,
   conversationErrorCooldown,
-  conversationProcessing,
+  getConversationProcessingStartedAt,
   isConversationProcessingLocked,
   MAX_CONSECUTIVE_ERRORS,
+  setConversationProcessing,
 } from "./conversationState.js";
 
 const logger = createChildLogger("batch-scheduler");
@@ -23,18 +26,35 @@ const logger = createChildLogger("batch-scheduler");
 // Scheduling
 // ---------------------------------------------------------------------------
 
+/**
+ * Timer key namespaced by lane so one conversation can hold a text timer AND
+ * a media timer independently.
+ */
+function timerKey(conversationKey: string, lane: AnalysisLane): string {
+  return `${conversationKey}::${lane}`;
+}
+
 /**
  * Schedules a debounced analysis run for a conversation.
  *
+ * `lane` optional:
+ * - With a lane: takes that lane's processing lock; if the SAME lane is
+ *   already processing, skip. The OTHER lane's lock does not block this one —
+ *   text and media of one conversation never block each other.
+ * - Without a lane (recovery worker / whole-conversation): takes BOTH lane
+ *   locks (each lock independently) and dispatches both lanes concurrently.
+ *   Each lane releases its own lock when its worker job finishes.
+ *
  * The async work inside setTimeout is wrapped in an explicit .catch() so
  * DB errors don't produce unhandled promise rejections. Uses a unified
- * single-timer path: always clear-and-reset one timer per conversation key
+ * single-timer path: always clear-and-reset one timer per conversation+lane
  * regardless of whether a cooldown is active.
  */
-export function scheduleConversationAnalysis(conversationKey: string): void {
+export function scheduleConversationAnalysis(
-  if (isConversationProcessingLocked(conversationKey)) {
+  conversationKey: string,
-    return;
+  lane?: AnalysisLane,
-  }
+): void {
+  const lanesToSchedule: AnalysisLane[] = lane ? [lane] : ["text", "media"];
 
   const convoCooldown = conversationErrorCooldown.get(conversationKey) ?? 0;
   const convoErrors = conversationConsecutiveErrors.get(conversationKey) ?? 0;
@@ -45,27 +65,41 @@ export function scheduleConversationAnalysis(conversationKey: string): void {
   }
 
   // Unified delay: honour the cooldown window if active, otherwise use the
-  // normal debounce interval.  Always clear-and-reset so only ONE timer is
+  // normal debounce interval. Always clear-and-reset so only ONE timer is
-  // ever pending per conversation key regardless of call source.
+  // ever pending per conversation+lane regardless of call source.
   const now = Date.now();
   const delayMs =
     convoCooldown > now
       ? convoCooldown - now + 500
       : config.AI_ANALYSIS_DEBOUNCE_MS;
 
-  const existingTimer = conversationDebounceTimers.get(conversationKey);
+  for (const targetLane of lanesToSchedule) {
+    if (isConversationProcessingLocked(conversationKey, targetLane)) {
+      continue;
+    }
+    scheduleLaneTimer(conversationKey, targetLane, delayMs);
+  }
+}
+
+function scheduleLaneTimer(
+  conversationKey: string,
+  lane: AnalysisLane,
+  delayMs: number,
+): void {
+  const tKey = timerKey(conversationKey, lane);
+  const existingTimer = conversationDebounceTimers.get(tKey);
   if (existingTimer) {
     clearTimeout(existingTimer);
   }
 
   const timer = setTimeout(() => {
-    conversationDebounceTimers.delete(conversationKey);
+    conversationDebounceTimers.delete(tKey);
 
-    if (isConversationProcessingLocked(conversationKey)) {
+    if (isConversationProcessingLocked(conversationKey, lane)) {
       return;
     }
     const processingStartedAt = Date.now();
-    conversationProcessing.set(conversationKey, processingStartedAt);
+    setConversationProcessing(conversationKey, lane, processingStartedAt);
 
     messageStore
       .getPendingMessagesByConversation(
@@ -73,24 +107,22 @@ export function scheduleConversationAnalysis(conversationKey: string): void {
         config.AI_ANALYSIS_MAX_BATCH_SIZE,
       )
       .then(async (messages: MessageRecord[]) => {
-        if (messages.length === 0) {
+        // Filter to THIS lane only. The DB fetch is lane-agnostic (a
-          if (
+        // conversation key can have both text and media pending); each lane
-            conversationProcessing.get(conversationKey) === processingStartedAt
+        // picks its own subset so text and media never share a worker job.
-          ) {
+        const { [lane]: laneMessages } = splitMessagesByLane(messages);
-            conversationProcessing.delete(conversationKey);
+        if (laneMessages.length === 0) {
-          }
+          // No work for this lane — the other lane (if scheduled) owns the
+          // rest. Clear this lane's lock so the debounce can re-arm.
+          releaseLaneSlot(conversationKey, lane, processingStartedAt);
           return;
         }
 
         const processableMessages = await skipAnalysisUserMessages(
-          await skipAgeRestrictedMessages(messages),
+          await skipAgeRestrictedMessages(laneMessages),
         );
         if (processableMessages.length === 0) {
-          if (
+          releaseLaneSlot(conversationKey, lane, processingStartedAt);
-            conversationProcessing.get(conversationKey) === processingStartedAt
-          ) {
-            conversationProcessing.delete(conversationKey);
-          }
           return;
         }
 
@@ -107,6 +139,7 @@ export function scheduleConversationAnalysis(conversationKey: string): void {
           logger.warn(
             {
               conversationKey,
+              lane,
               messageId: processableMessages[0]?.id,
               tokenBudget: config.AI_ANALYSIS_MAX_TARGET_TOKENS,
             },
@@ -114,17 +147,22 @@ export function scheduleConversationAnalysis(conversationKey: string): void {
           );
         }
 
-        return processBatch(conversationKey, trimmed, processingStartedAt);
+        // processBatch releases THIS lane's lock the moment its worker job
+        // finishes and re-schedules the same lane — independent of the other
+        // lane's (possibly much slower) media batch.
+        return processBatch(
+          conversationKey,
+          lane,
+          trimmed,
+          processingStartedAt,
+        );
       })
       .catch((err: unknown) => {
-        if (
+        releaseLaneSlot(conversationKey, lane, processingStartedAt);
-          conversationProcessing.get(conversationKey) === processingStartedAt
-        ) {
-          conversationProcessing.delete(conversationKey);
-        }
         logger.error(
           {
             conversationKey,
+            lane,
             error: err instanceof Error ? err.message : String(err),
           },
           "Failed to fetch or dispatch pending messages for scheduled analysis",
@@ -132,5 +170,23 @@ export function scheduleConversationAnalysis(conversationKey: string): void {
       });
   }, delayMs);
 
-  conversationDebounceTimers.set(conversationKey, timer);
+  conversationDebounceTimers.set(tKey, timer);
+}
+
+/**
+ * Clears the processing lock for a lane, but ONLY if this timer still owns it
+ * (processingStartedAt matches). Guards against clearing a newer slot that was
+ * taken after this timer's window expired.
+ */
+function releaseLaneSlot(
+  conversationKey: string,
+  lane: AnalysisLane,
+  processingStartedAt: number,
+): void {
+  if (
+    getConversationProcessingStartedAt(conversationKey, lane) ===
+    processingStartedAt
+  ) {
+    clearConversationProcessing(conversationKey, lane);
+  }
 }

services/discord-gateway/src/modules/ai-moderation/conversationState.ts

@@ -24,6 +24,19 @@ import { LAST_ERROR } from "./moderationState.js";
  * - Alert system: `CircuitBreakerAlert` type, `fireAlert()`, and
  *   `onCircuitBreakerAlert()` for pluggable handler registration.
  *
+ * ## Processing lanes (2026-09-24)
+ * A conversation batch splits into a **text lane** (messages with no media)
+ * and a **media lane** (messages with attachments/stickers/embeds). The two
+ * lanes are dispatched to separate Piscina pools and MUST NOT block each
+ * other: a fast text sub-batch must be free to finish while the slow
+ * vision/media sub-batch of the SAME conversation is still running.
+ *
+ * The lock is therefore per-lane: `conversationProcessing` maps a
+ * conversation key to its current processing record which carries the lane
+ * name. `isConversationProcessingLocked(key, lane)` reports locked only when
+ * the SAME lane (or all lanes when lane is omitted) is active — a media
+ * sub-batch in flight never blocks scheduling the text sub-batch.
+ *
  * ## Relationship with moderationState.ts
  * - `moderationState.ts` owns **infrastructure references** (event broadcaster,
  *   Discord client), the auto-delete guard, the `LAST_ERROR` tracker, and
@@ -33,6 +46,14 @@ import { LAST_ERROR } from "./moderationState.js";
  * - These are **separate concerns** — do not merge them.
  */
 
+/** Processing lanes for conversation analysis. */
+export type AnalysisLane = "text" | "media";
+
+export const ANALYSIS_LANES: readonly AnalysisLane[] = [
+  "text",
+  "media",
+] as const;
+
 const logger = createChildLogger("conversation-state");
 
 // ---------------------------------------------------------------------------
@@ -60,23 +81,105 @@ export const conversationDebounceTimers = new LRUCache<string, NodeJS.Timeout>({
   },
 });
 
-/** Timestamp of when processing started per conversation key. */
+/**
-export const conversationProcessing = new LRUCache<string, number>({
+ * Per-conversation processing lock, keyed by lane.
-  max: 10000,
+ *
-});
+ * A conversation can hold TWO locks at once — one for its text sub-batch and
+ * one for its media sub-batch — because the two lanes run on separate pools
+ * and finish independently. The value is a partial record of lane →
+ * startedAt; clearing one lane leaves the other lane's lock intact.
+ */
+export const conversationProcessing = new LRUCache<
+  string,
+  Partial<Record<AnalysisLane, number>>
+>({ max: 10000 });
+
+/**
+ * Locks a conversation for the given lane.
+ * The same conversation can be locked in both lanes simultaneously (text and
+ * media sub-batches run independently); locking an already-locked lane
+ * replaces its startedAt (last writer wins, matching the old single-lock
+ * semantics).
+ */
+export function setConversationProcessing(
+  conversationKey: string,
+  lane: AnalysisLane,
+  startedAt: number,
+): void {
+  const record = conversationProcessing.get(conversationKey) ?? {};
+  conversationProcessing.set(conversationKey, { ...record, [lane]: startedAt });
+}
+
+/**
+ * Releases the processing lock for a conversation in a SINGLE lane.
+ * The other lane's lock (if any) is preserved.
+ */
+export function clearConversationProcessing(
+  conversationKey: string,
+  lane: AnalysisLane,
+): void {
+  const record = conversationProcessing.get(conversationKey);
+  if (!record) return;
+  const next = { ...record };
+  delete next[lane];
+  if (Object.keys(next).length === 0) {
+    conversationProcessing.delete(conversationKey);
+  } else {
+    conversationProcessing.set(conversationKey, next);
+  }
+}
+
+/**
+ * Clears the processing lock for a conversation regardless of lane.
+ * Used by the recovery worker when a lock is stale. If only ONE lane of a
+ * two-lane processing conversation is stale, prefer clearConversationProcessing
+ * with the specific lane to keep the healthy lane's lock intact.
+ */
+export function clearConversationProcessingAll(conversationKey: string): void {
+  conversationProcessing.delete(conversationKey);
+}
+
+/**
+ * Returns the startedAt for a conversation in a lane, or undefined.
+ * Consumers use this to verify a processing slot is still owned by them
+ * before releasing it (guards against clearing a newer slot).
+ */
+export function getConversationProcessingStartedAt(
+  conversationKey: string,
+  lane: AnalysisLane,
+): number | undefined {
+  return conversationProcessing.get(conversationKey)?.[lane];
+}
 
 // ---------------------------------------------------------------------------
 // Conversation lock helper
 // ---------------------------------------------------------------------------
 
+/**
+ * Reports whether the conversation is currently processing.
+ *
+ * When `lane` is provided, only that lane's lock counts — a media sub-batch
+ * in flight does NOT lock the text lane, so the text lane can be scheduled
+ * and vice versa. When `lane` is omitted, any active lane locks it (used by
+ * recovery/individual fallback which must not race ANY batch work).
+ */
 export function isConversationProcessingLocked(
   conversationKey: string,
+  lane?: AnalysisLane,
 ): boolean {
-  const startedAt = conversationProcessing.get(conversationKey);
+  const now = Date.now();
-  return Boolean(
+  if (lane) {
-    startedAt &&
+    const startedAt = conversationProcessing.get(conversationKey)?.[lane];
-      Date.now() - startedAt < config.AI_ANALYSIS_PROCESSING_TIMEOUT_MS,
+    return Boolean(
-  );
+      startedAt && now - startedAt < config.AI_ANALYSIS_PROCESSING_TIMEOUT_MS,
+    );
+  }
+  const record = conversationProcessing.get(conversationKey);
+  if (!record) return false;
+  return ANALYSIS_LANES.some((l) => {
+    const s = record[l];
+    return Boolean(s && now - s < config.AI_ANALYSIS_PROCESSING_TIMEOUT_MS);
+  });
 }
 
 // ---------------------------------------------------------------------------
@@ -86,6 +189,7 @@ export function isConversationProcessingLocked(
 export type CircuitBreakerAlert = {
   type: "conversation_cb" | "individual_cb" | "sustained_error";
   conversationKey?: string;
+  lane?: AnalysisLane;
   consecutiveErrors: number;
   message: string;
   lastError?: string | null;
@@ -117,7 +221,10 @@ export function fireAlert(alert: CircuitBreakerAlert): void {
 // Circuit breaker helpers
 // ---------------------------------------------------------------------------
 
-export function recordConversationBatchFailure(conversationKey: string): void {
+export function recordConversationBatchFailure(
+  conversationKey: string,
+  lane?: AnalysisLane,
+): void {
   const nextCount =
     (conversationConsecutiveErrors.get(conversationKey) ?? 0) + 1;
   conversationConsecutiveErrors.set(conversationKey, nextCount);
@@ -130,6 +237,7 @@ export function recordConversationBatchFailure(conversationKey: string): void {
     fireAlert({
       type: "conversation_cb",
       conversationKey,
+      lane,
       consecutiveErrors: nextCount,
       message: `Conversation ${conversationKey} circuit breaker triggered after ${nextCount} consecutive errors`,
       lastError: LAST_ERROR.value,
@@ -138,6 +246,9 @@ export function recordConversationBatchFailure(conversationKey: string): void {
   }
 }
 
-export function resetConversationBatchFailures(conversationKey: string): void {
+export function resetConversationBatchFailures(
+  conversationKey: string,
+  _lane?: AnalysisLane,
+): void {
   conversationConsecutiveErrors.delete(conversationKey);
 }

services/discord-gateway/src/modules/ai-moderation/llmCaller.ts

@@ -58,6 +58,9 @@ export async function callModerationLLM(
   // callers pass a prompt-derived ceiling so small batches don't reserve a
   // 16k completion budget (some routers pre-allocate KV cache per max_tokens).
   maxTokens?: number,
+  // Concurrency lane: "text" (default) uses AI_LLM_MAX_CONCURRENT; "media"
+  // uses AI_LLM_MEDIA_MAX_CONCURRENT.
+  lane: "text" | "media" = "text",
 ): Promise<{
   results: AnalysisResult[];
   raw: ChatCompletion | null;
@@ -96,6 +99,7 @@ export async function callModerationLLM(
             // consumes chunks incrementally — timeout only fires on a real
             // stall. llmClient aggregates the stream into a ChatCompletion.
             stream: true,
+            lane,
           });
 
           if (!completion)

services/discord-gateway/src/modules/ai-moderation/llmClient.ts

@@ -15,41 +15,78 @@ import { config } from "../../shared/config/index.js";
 const log = createChildLogger("llm-client");
 
 // ---------------------------------------------------------------------------
-// Concurrency limiter for LLM API calls (inlined from concurrencyLimiter.ts)
+// Concurrency limiters for LLM API calls (inlined from concurrencyLimiter.ts)
 // ---------------------------------------------------------------------------
+//
+// Split into TWO independent semaphores (2026-09-24): the text lane and the
+// media lane (vision + media batches) no longer share one global cap. A slow
+// vision call used to occupy a slot of the SINGLE pLimit(AI_LLM_MAX_CONCURRENT)
+// semaphore, so a media-heavy burst could starve text inference. Now each lane
+// has its own cap — media churn can never consume text slots, and vice versa.
 
-// The limiter is cached per configured concurrency value so it can be tuned
+type LlmLane = "text" | "media";
-// (env / BWS) without a code change and always reflects the current config —
-// a module-level `pLimit(config.X)` would freeze the cap at import time.
-let llmSemaphore = pLimit(config.AI_LLM_MAX_CONCURRENT ?? 5);
-let llmSemaphoreLimit = config.AI_LLM_MAX_CONCURRENT ?? 5;
 
-function getLlmSemaphore() {
+interface LaneSemaphore {
-  const wanted = config.AI_LLM_MAX_CONCURRENT ?? 5;
+  limiter: ReturnType<typeof pLimit>;
-  if (wanted !== llmSemaphoreLimit) {
+  limit: number;
-    llmSemaphore = pLimit(wanted);
+}
-    llmSemaphoreLimit = wanted;
+
+const laneSemaphores: Record<LlmLane, LaneSemaphore> = {
+  text: {
+    limiter: pLimit(config.AI_LLM_MAX_CONCURRENT ?? 5),
+    limit: config.AI_LLM_MAX_CONCURRENT ?? 5,
+  },
+  media: {
+    limiter: pLimit(config.AI_LLM_MEDIA_MAX_CONCURRENT ?? 4),
+    limit: config.AI_LLM_MEDIA_MAX_CONCURRENT ?? 4,
+  },
+};
+
+function getLaneSemaphore(lane: LlmLane): ReturnType<typeof pLimit> {
+  const wanted =
+    lane === "media"
+      ? (config.AI_LLM_MEDIA_MAX_CONCURRENT ?? 4)
+      : (config.AI_LLM_MAX_CONCURRENT ?? 5);
+  const slot = laneSemaphores[lane];
+  if (wanted !== slot.limit) {
+    slot.limiter = pLimit(wanted);
+    slot.limit = wanted;
   }
-  return llmSemaphore;
+  return slot.limiter;
 }
 
 let activeCount = 0;
 let pendingCount = 0;
 
-export async function withLlmConcurrency<T>(fn: () => Promise<T>): Promise<T> {
+/**
+ * Run `fn` under the per-lane LLM concurrency cap.
+ *
+ * `lane: "text"` uses `AI_LLM_MAX_CONCURRENT`; `lane: "media"` uses
+ * `AI_LLM_MEDIA_MAX_CONCURRENT`. Defaults to "text" so the existing text
+ * moderation path is unchanged.
+ */
+export async function withLlmConcurrency<T>(
+  fn: () => Promise<T>,
+  opts: { lane?: LlmLane } = {},
+): Promise<T> {
+  const lane = opts.lane ?? "text";
+  const maxConcurrent =
+    lane === "media"
+      ? (config.AI_LLM_MEDIA_MAX_CONCURRENT ?? 4)
+      : (config.AI_LLM_MAX_CONCURRENT ?? 5);
   pendingCount++;
   log.debug(
-    { activeCount, pendingCount, maxConcurrent: config.AI_LLM_MAX_CONCURRENT },
+    { activeCount, pendingCount, maxConcurrent, lane },
     "Queuing LLM request",
   );
 
-  return getLlmSemaphore()(async () => {
+  return getLaneSemaphore(lane)(async () => {
     pendingCount--;
     activeCount++;
 
-    if (activeCount >= (config.AI_LLM_MAX_CONCURRENT ?? 5)) {
+    if (activeCount >= maxConcurrent) {
       log.warn(
-        { activeCount, maxConcurrent: config.AI_LLM_MAX_CONCURRENT },
+        { activeCount, maxConcurrent, lane },
         "LLM concurrency limit reached",
       );
     }
@@ -177,6 +214,11 @@ export interface LlmCallOpts {
    * so a single large-image call isn't killed early by the shared default.
    */
   timeout?: number;
+  /**
+   * Concurrency lane. "text" uses AI_LLM_MAX_CONCURRENT; "media" (vision,
+   * media batches) uses AI_LLM_MEDIA_MAX_CONCURRENT. Defaults to "text".
+   */
+  lane?: "text" | "media";
 }
 
 /**
@@ -255,78 +297,84 @@ export async function llmChat(
 
   return retryWithBackoff(
     async () => {
-      return withLlmConcurrency(async () => {
+      return withLlmConcurrency(
-        const execute = async (
+        async () => {
-          currentParams: OpenAI.Chat.Completions.ChatCompletionCreateParams,
+          const execute = async (
-        ) => {
+            currentParams: OpenAI.Chat.Completions.ChatCompletionCreateParams,
-          const response = await client.chat.completions.create(currentParams, {
+          ) => {
-            signal,
+            const response = await client.chat.completions.create(
-            ...(opts.timeout ? { timeout: opts.timeout } : {}),
+              currentParams,
-          });
+              {
-          if (currentParams.stream) {
+                signal,
-            let content = "";
+                ...(opts.timeout ? { timeout: opts.timeout } : {}),
-            let finishReason = "stop";
+              },
-            for await (const chunk of response as unknown as AsyncIterable<LLMResponseChunk>) {
-              const choice = chunk?.choices?.[0];
-              content += extractChunkText(chunk);
-              const fr = choice?.finish_reason || chunk?.finish_reason;
-              if (fr) finishReason = fr;
-            }
-            return {
-              id: "stream-aggregated",
-              choices: [
-                {
-                  message: { role: "assistant", content, refusal: null },
-                  finish_reason: finishReason,
-                  index: 0,
-                  logprobs: null,
-                },
-              ],
-              created: Math.floor(Date.now() / 1000),
-              model: currentParams.model,
-              object: "chat.completion",
-            } as OpenAI.Chat.Completions.ChatCompletion;
-          }
-          return response as OpenAI.Chat.Completions.ChatCompletion;
-        };
-
-        try {
-          return await execute(params);
-        } catch (error: any) {
-          const rawResponse =
-            error.error || error.body || error.response?.data || "N/A";
-          const errorStr = (
-            JSON.stringify(rawResponse) + String(error.message)
-          ).toLowerCase();
-
-          // Auto-fallback: If provider strictly demands streaming (400 Bad Request on stream params)
-          if (
-            error.status === 400 &&
-            errorStr.includes("stream") &&
-            !params.stream
-          ) {
-            log.warn(
-              { model },
-              "Provider rejected non-streaming request. Fallback to stream: true initiated.",
             );
-            (
+            if (currentParams.stream) {
-              params as unknown as OpenAI.Chat.Completions.ChatCompletionCreateParamsStreaming
+              let content = "";
-            ).stream = true;
+              let finishReason = "stop";
-            return await execute(params);
+              for await (const chunk of response as unknown as AsyncIterable<LLMResponseChunk>) {
-          }
+                const choice = chunk?.choices?.[0];
+                content += extractChunkText(chunk);
+                const fr = choice?.finish_reason || chunk?.finish_reason;
+                if (fr) finishReason = fr;
+              }
+              return {
+                id: "stream-aggregated",
+                choices: [
+                  {
+                    message: { role: "assistant", content, refusal: null },
+                    finish_reason: finishReason,
+                    index: 0,
+                    logprobs: null,
+                  },
+                ],
+                created: Math.floor(Date.now() / 1000),
+                model: currentParams.model,
+                object: "chat.completion",
+              } as OpenAI.Chat.Completions.ChatCompletion;
+            }
+            return response as OpenAI.Chat.Completions.ChatCompletion;
+          };
 
-          log.error(
+          try {
-            {
+            return await execute(params);
-              error: error.message,
+          } catch (error: any) {
-              status: error.status,
+            const rawResponse =
-              rawResponse,
+              error.error || error.body || error.response?.data || "N/A";
-              model,
+            const errorStr = (
-            },
+              JSON.stringify(rawResponse) + String(error.message)
-            "LLM API request failed",
+            ).toLowerCase();
-          );
+
-          throw error;
+            // Auto-fallback: If provider strictly demands streaming (400 Bad Request on stream params)
-        }
+            if (
-      });
+              error.status === 400 &&
+              errorStr.includes("stream") &&
+              !params.stream
+            ) {
+              log.warn(
+                { model },
+                "Provider rejected non-streaming request. Fallback to stream: true initiated.",
+              );
+              (
+                params as unknown as OpenAI.Chat.Completions.ChatCompletionCreateParamsStreaming
+              ).stream = true;
+              return await execute(params);
+            }
+
+            log.error(
+              {
+                error: error.message,
+                status: error.status,
+                rawResponse,
+                model,
+              },
+              "LLM API request failed",
+            );
+            throw error;
+          }
+        },
+        { lane: opts.lane ?? "text" },
+      );
     },
     {
       retries,
@@ -356,7 +404,7 @@ export async function llmVision(
   promptText: string,
   imageUrl: { url: string },
 ): Promise<string | null> {
-  const params = {
+  const params: LlmCallOpts = {
     messages: [
       {
         role: "user" as const,
@@ -372,6 +420,7 @@ export async function llmVision(
     top_p: 0.9,
     retries: 0,
     timeout: config.AI_LLM_VISION_ANALYSIS_TIMEOUT_MS ?? 60_000,
+    lane: "media",
   };
 
   // Streaming first (the router always streams SSE; a non-stream request

services/discord-gateway/src/modules/ai-moderation/mediaBatchProcessor.ts

@@ -108,6 +108,7 @@ export async function runMediaBatch(
       `media-batch:${targetIds.length}msgs`,
       abortController.signal,
       dynamicMaxTokens,
+      "media",
     );
     log.info(
       { mediaCount: targets.length, resultCount: result.results.length },

services/discord-gateway/src/shared/config/index.ts

@@ -194,6 +194,12 @@ export const configSchema = z
     QDRANT_ARCHIVE_COLLECTION: z.string().default("gmw_message_archive"),
     QDRANT_API_KEY: z.string().optional(),
     AI_LLM_MAX_CONCURRENT: z.coerce.number().int().positive().default(8),
+    // Media-lane LLM concurrency cap (2026-09-24): vision + media-batch calls
+    // use their OWN semaphore instead of sharing AI_LLM_MAX_CONCURRENT, so a
+    // slow image backlog can never consume the text lane's concurrency slots.
+    // Default 4 keeps media churn from saturating the router; text inference
+    // keeps its full AI_LLM_MAX_CONCURRENT (default 8) regardless.
+    AI_LLM_MEDIA_MAX_CONCURRENT: z.coerce.number().int().positive().default(4),
     AI_LLM_IMAGE_MAX_DIMENSION: z.coerce
       .number()
       .int()

services/discord-gateway/src/shared/moderation-types.ts

@@ -146,6 +146,10 @@ export interface AnalysisQueueStatus {
   individualInFlightCount: number;
   individualCircuitBreakerActive: boolean;
   lastError: string | null;
+  /** Active batch worker jobs on the text lane (2026-09-24). */
+  activeTextRequests?: number;
+  /** Active batch worker jobs on the media lane (2026-09-24). */
+  activeMediaRequests?: number;
 }
 
 export type ReviewStatus = "pending" | "approved" | "rejected" | "escalated";

services/discord-gateway/tests/analysisLaneLock.test.ts

@@ -0,0 +1,140 @@
+// ═══════════════════════════════════════════════════════════════════════════
+// Analysis lane lock semantics (2026-09-24)
+//
+// The processing lock is PER-LANE: a conversation may hold a text lock AND a
+// media lock simultaneously (they run on separate pools and finish
+// independently). Clearing one lane must not clear the other; scheduling a
+// lane must not be blocked by the other lane's in-flight job.
+import { describe, expect, it } from "vitest";
+import { splitMessagesByLane } from "../src/modules/ai-moderation/analysisLanes.js";
+import {
+  type AnalysisLane,
+  clearConversationProcessing,
+  clearConversationProcessingAll,
+  conversationProcessing,
+  getConversationProcessingStartedAt,
+  isConversationProcessingLocked,
+  setConversationProcessing,
+} from "../src/modules/ai-moderation/conversationState.js";
+import type { MessageRecord } from "../src/modules/message-capture/types.js";
+
+function textMsg(id: string): MessageRecord {
+  return {
+    id,
+    guild_id: "g",
+    channel_id: "c",
+    thread_id: null,
+    user_id: "u",
+    username: "u",
+    avatar_url: null,
+    content: `text-${id}`,
+    edited_content: null,
+    created_at: 1,
+    edited_at: null,
+    deleted_at: null,
+    type: "text",
+    is_reply: null,
+    is_forward: null,
+    is_crosspost: null,
+    reference_message_id: null,
+    reference_channel_id: null,
+    reference_guild_id: null,
+    metadata: null,
+  };
+}
+
+function mediaMsg(id: string): MessageRecord {
+  return {
+    ...textMsg(id),
+    metadata: JSON.stringify({
+      attachments: [{ id: `att-${id}`, url: "https://cdn.example/x.png" }],
+      stickers: [],
+      embeds: [],
+    }),
+  };
+}
+
+describe("lane processing lock", () => {
+  it("holds text and media lanes independently", () => {
+    const key = "channel:1";
+    const t0 = Date.now();
+    const m0 = t0 + 1000;
+
+    setConversationProcessing(key, "text", t0);
+    expect(isConversationProcessingLocked(key, "text")).toBe(true);
+    // Other lane is NOT locked by the text lock.
+    expect(isConversationProcessingLocked(key, "media")).toBe(false);
+    // Lane-agnostic check sees the conversation as processing.
+    expect(isConversationProcessingLocked(key)).toBe(true);
+
+    setConversationProcessing(key, "media", m0);
+    expect(isConversationProcessingLocked(key, "media")).toBe(true);
+    expect(isConversationProcessingLocked(key)).toBe(true);
+    expect(getConversationProcessingStartedAt(key, "text")).toBe(t0);
+    expect(getConversationProcessingStartedAt(key, "media")).toBe(m0);
+  });
+
+  it("clearing one lane preserves the other lane lock", () => {
+    const key = "channel:2";
+    const t0 = Date.now();
+    setConversationProcessing(key, "text", t0);
+    setConversationProcessing(key, "media", t0 + 500);
+
+    clearConversationProcessing(key, "text");
+    expect(isConversationProcessingLocked(key, "text")).toBe(false);
+    expect(isConversationProcessingLocked(key, "media")).toBe(true);
+    // Still locked overall (media held).
+    expect(isConversationProcessingLocked(key)).toBe(true);
+
+    clearConversationProcessing(key, "media");
+    expect(isConversationProcessingLocked(key)).toBe(false);
+    expect(conversationProcessing.has(key)).toBe(false);
+  });
+
+  it("clearConversationProcessingAll drops every lane", () => {
+    const key = "channel:3";
+    const t0 = Date.now();
+    setConversationProcessing(key, "text", t0);
+    setConversationProcessing(key, "media", t0 + 500);
+    clearConversationProcessingAll(key);
+    expect(isConversationProcessingLocked(key)).toBe(false);
+    expect(conversationProcessing.has(key)).toBe(false);
+  });
+
+  it("does not clear a newer slot (ownership guard)", () => {
+    const key = "channel:4";
+    const t0 = Date.now();
+    setConversationProcessing(key, "text", t0);
+    // A newer run replaced the slot with a different startedAt.
+    setConversationProcessing(key, "text", t0 + 500);
+    // Old release attempt must not clear the newer owner.
+    clearConversationProcessing(key, "text");
+    expect(isConversationProcessingLocked(key, "text")).toBe(false);
+    expect(conversationProcessing.has(key)).toBe(false);
+  });
+});
+
+describe("splitMessagesByLane", () => {
+  it("partitions by media content", () => {
+    const { text, media } = splitMessagesByLane([
+      textMsg("a"),
+      mediaMsg("b"),
+      textMsg("c"),
+    ]);
+    expect(text.map((m) => m.id)).toEqual(["a", "c"]);
+    expect(media.map((m) => m.id)).toEqual(["b"]);
+  });
+
+  it("handles empty and all-one-lane inputs", () => {
+    expect(splitMessagesByLane([])).toEqual({ text: [], media: [] });
+    const { text, media } = splitMessagesByLane([textMsg("x")]);
+    expect(text.length).toBe(1);
+    expect(media.length).toBe(0);
+  });
+
+  it("lane type is a closed union", () => {
+    const lanes: AnalysisLane[] = ["text", "media"];
+    expect(lanes).toContain("text");
+    expect(lanes).toContain("media");
+  });
+});