Add specifications for gamification, generation, and R42 chat services

- Introduced gamification service spec detailing responsibilities, API surface, XP calculation, levels, streaks, badges, milestone cards, and heatmap data.
- Added generation service spec outlining the process for generating micro learning content, including API endpoints, AI call configuration, prompt strategies, and error handling.
- Created R42 chat service spec covering chatbot interactions, retrieval pipeline, prompt construction, response generation, and stateless design principles.

app/services/ingestion/src/pipeline/embed.ts

@@ -26,11 +26,16 @@ export async function embedAndStore(
   writtenTopics: WrittenTopic[],
   onProgress: (embedded: number) => void,
 ): Promise<void> {
-  // Build chunk → topic mapping
+  // Build chunk → topic mapping.
+  // The AI labels chunks as [CHUNK-<uuid>] so sourceChunkIds may carry that prefix;
+  // strip it so lookups match the bare UUID used as the Qdrant point ID.
+  const normalise = (id: string): string => id.replace(/^CHUNK-/i, '');
+
   const chunkTopicMap = new Map<string, string>();
   const chunkThemeMap = new Map<string, string>();
   for (const topic of writtenTopics) {
-    for (const chunkId of topic.sourceChunkIds) {
+    for (const rawId of topic.sourceChunkIds) {
+      const chunkId = normalise(rawId);
       chunkTopicMap.set(chunkId, topic.id);
       chunkThemeMap.set(chunkId, topic.themeId);
     }
@@ -94,7 +99,9 @@ export async function embedAndStore(
   // Update topics.qdrant_chunk_ids in PocketBase
   // -------------------------------------------------------------------------
   for (const topic of writtenTopics) {
-    const qdrantIds = topic.sourceChunkIds.filter(id => chunkTopicMap.get(id) === topic.id);
+    const qdrantIds = topic.sourceChunkIds
+      .map(id => normalise(id))
+      .filter(id => chunkTopicMap.get(id) === topic.id);
     if (qdrantIds.length > 0) {
       await updateTopicQdrantIds(topic.id, qdrantIds);
     }