feat(discord-gateway): use Discord CDN for image analysis, uploader archive-only

- mediaDownloader: flip URL candidate order so discord_url is tried
  before uploaded_url (uploaded_url is archive-only fallback)
- ai-analysis-worker: remove upload-pending race guard that blocked
  analysis until Tele upload completed; analysis now runs immediately
  on the Discord CDN URL
- batchProcessor: remove upload-pending defer/poll-backoff logic
- individualFallbackProcessor: remove upload_pending requeue loop
- batchOutcomeClassifier/fallbackResultClassifier: drop upload_pending
  classification (no longer needed)
- tests: update batchOutcomeClassifier + fallbackResultClassifier tests
  to reflect removed upload_pending signal

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

@@ -1,15 +1,7 @@
 /**
  * batchOutcomeClassifier.ts
  *
- * Pure partitioner of the batch worker response (2026-08-25).
- *
- * Bug history: the batch race guard returned `{ok:true, rows:[]}` when every
- * target's attachment upload was still in-flight. The processor classified all
- * of them as "incomplete" and fanned out to the individual queue, where the
- * guard there requeued + rescheduled at the 250ms debounce — a hot ~300ms loop
- * for the entire upload duration (~10 cycles in 3s in prod logs). Root fix:
- * the worker now reports `uploadPendingIds` explicitly and this pure function
- * partitions the outcome so upload-pending targets NEVER enter the fanout.
+ * Pure partitioner of the batch worker response.
  */
 
 export interface BatchRowLike {
@@ -21,15 +13,12 @@ export interface BatchRowLike {
 export interface BatchWorkerResponseLike {
   ok?: boolean;
   rows?: BatchRowLike[];
-  /** Explicit race-guard signal from the worker (2026-08-25). */
-  uploadPendingIds?: string[];
   error?: string;
 }
 
 /** One target's per-message disposition after a batch attempt. */
 export type BatchTargetKind =
   | "completed"
-  | "upload_pending"
   | "incomplete"
   | "parse_failed"
   | "api_failed";
@@ -40,7 +29,7 @@ function flagsOf(row: { ai_moderation_flags?: string | null }): string[] {
     const parsed = JSON.parse(row.ai_moderation_flags) as unknown;
     return Array.isArray(parsed) ? (parsed as string[]) : [];
   } catch {
-    return [] as string[];
+    return [];
   }
 }
 
@@ -48,14 +37,13 @@ function flagsOf(row: { ai_moderation_flags?: string | null }): string[] {
  * Partition the input message ids into per-message dispositions for one batch
  * worker response. Pure: no DB/Piscina/logger — unit-testable directly.
  *
- * Priority per id: explicit uploadPendingIds → completed row → flag-based
- * failure kinds → unexplained missing (treated like incomplete).
+ * Priority per id: completed row → flag-based failure kinds → unexplained
+ * missing (treated like incomplete).
  */
 export function partitionBatchOutcome(
   messages: ReadonlyArray<{ id: string }>,
   response: BatchWorkerResponseLike,
 ): Map<string, BatchTargetKind> {
-  const pendingSet = new Set(response.uploadPendingIds ?? []);
   const rowsById = new Map(
     (response.rows ?? [])
       .filter((r): r is BatchRowLike & { id: string } => Boolean(r?.id))
@@ -64,10 +52,6 @@ export function partitionBatchOutcome(
 
   const out = new Map<string, BatchTargetKind>();
   for (const msg of messages) {
-    if (pendingSet.has(msg.id)) {
-      out.set(msg.id, "upload_pending");
-      continue;
-    }
     const row = rowsById.get(msg.id);
     if (!row) {
       // Unexplained drop: LLM silently omitted it. Same retryable bucket as
@@ -92,17 +76,3 @@ export function partitionBatchOutcome(
   }
   return out;
 }
-
-/**
- * Linear backoff ramp for consecutive upload-pending polls:
- * poll N (1-based) waits min(base × N, cap). Keeps latency low for fast
- * uploads while bounding total polling cost for long uploads.
- */
-export function computeUploadPollDelayMs(
-  consecutivePolls: number,
-  baseMs: number,
-  capMs: number,
-): number {
-  const n = Math.max(1, Math.floor(consecutivePolls));
-  return Math.min(Math.round(baseMs * n), Math.round(capMs));
-}