fix(gateway): image vision analysis + media cache lock failures

Two root causes behind 'all image analysis failing':

1. imageResizer still emitted lossless PNG for vision input. A 1024px
   Facebook photo balloons to multi-MB PNG base64 that the vision model
   silently rejects ('Vision API null response'). Switch to JPEG q85
   (no upscaling) — same photo drops to ~100-400KB, model processes fine.
   Re-encodes even already-small images so raw originals never bloat the
   data URL. Added tests/imageResizer.test.ts covering both cases.

2. acquireMediaAnalysisLock INSERT aborted with 'index row requires N
   bytes, maximum size is 8191'. text_analysis_cache.text is the PK in a
   B-tree index (8191-byte/row cap); callers pass the raw image URL as the
   key, and base64 data URLs / very long URLs blow past the limit, so the
   lock INSERT fails and every media analysis is skipped. Hash the URL in
   makeImageCacheKey (image:<sha256[:32]>) — fixed-length, deterministic,
   well under the limit. All store/get/lock/delete callers already route
   through this function so lookup stays consistent.

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

@@ -77,14 +77,16 @@ export function makeCustomEmojiCacheKey(emojiId: string): string {
  * (different URLs) never collide.
  */
 export function makeImageCacheKey(imageUrl: string): string {
-  try {
-    const u = new URL(imageUrl);
-    u.search = "";
-    u.hash = "";
-    return `image:${u.toString()}`;
-  } catch {
-    return `image:${imageUrl}`;
-  }
+  // Hash the URL to a fixed-length key. The raw Discord CDN URL is short,
+  // but callers sometimes pass base64 data URLs (can be multi-MB) or very
+  // long signed/external URLs. text_analysis_cache.text is the PK and lives
+  // in a B-tree index with an 8191-byte per-row limit — inserting a long URL
+  // as the key aborts the whole INSERT ("index row requires N bytes, maximum
+  // size is 8191"), which fails acquireMediaAnalysisLock and silently skips
+  // every media analysis. A 32-char sha256 keeps the key well under the limit
+  // and is still deterministic (same attachment → same key).
+  const hash = createHash("sha256").update(imageUrl).digest("hex").slice(0, 32);
+  return `image:${hash}`;
 }
 
 /**

services/discord-gateway/src/modules/attachment-upload/imageResizer.ts

@@ -4,10 +4,17 @@ import { createChildLogger } from "@/shared/logger/index";
 const log = createChildLogger("imageResizer");
 
 /**
- * Prepare an image buffer for optimal vision LLM analysis.
+ * Prepare an image buffer for vision LLM analysis.
  *
- * - Resizes to maxDim x maxDim maintaining aspect ratio (only if larger)
- * - Converts to PNG (lossless) to preserve full image detail
+ * - Resizes to maxDim x maxDim maintaining aspect ratio WITHOUT upscaling
+ *   (small images such as stickers/emojis are passed through at original size,
+ *   just re-encoded)
+ * - Encodes as JPEG (lossy, quality ~85). Photos compress VERY poorly in
+ *   lossless PNG — a 1024px Facebook photo balloons to multi-MB PNG base64 that
+ *   the vision model silently rejects (empty response → "Vision API null").
+ *   JPEG keeps the same photo at ~100–400KB, which the model processes fine and
+ *   stays well below request/token size limits.
+
  * - Falls back to original buffer if sharp fails
  *
  * @param buf - Raw image buffer
@@ -20,35 +27,28 @@ export async function resizeImageForVision(
 ): Promise<{ data: Buffer; mimeType: string }> {
   try {
     const metadata = await sharp(buf).metadata();
-    const inputFormat = metadata.format ?? "jpeg";
 
-    // Skip resize entirely if already within max dimension
-    if ((metadata.width ?? 0) <= maxDim && (metadata.height ?? 0) <= maxDim) {
-      return { data: buf, mimeType: `image/${inputFormat}` };
-    }
-
-    // Resize dimension only — convert to PNG lossless to preserve detail
+    // Always (re-)encode to JPEG and fit inside maxDim without upscaling.
+    // Skipping the encode for already-small images left raw originals in
+    // their native (often lossless PNG or full-quality) form, which could
+    // still bloat data URLs and trip the vision model's size limit.
     const resized = await sharp(buf)
-      .resize(maxDim, maxDim, {
-        fit: "inside",
-        withoutEnlargement: true,
-      })
-      .png()
+      .resize(maxDim, maxDim, { fit: "inside", withoutEnlargement: true })
+      .jpeg({ quality: 85 })
       .toBuffer();
 
+    const inputFormat = metadata.format ?? "jpeg";
     log.debug(
       {
         originalSize: buf.length,
         originalFormat: inputFormat,
         resizedSize: resized.length,
-        reductionPct: Math.round(
-          ((buf.length - resized.length) / buf.length) * 100,
-        ),
+        reductionPct: Math.round(((buf.length - resized.length) / buf.length) * 100),
       },
-      "Image resized for vision analysis (lossless PNG)",
+      "Image resized for vision analysis (JPEG)",
     );
 
-    return { data: resized, mimeType: "image/png" };
+    return { data: resized, mimeType: "image/jpeg" };
   } catch (error) {
     log.warn(
       { error: error instanceof Error ? error.message : String(error) },