feat(phase1): on-device semantic recall — embeddings, vector search, hybrid ranking

Exam-time search over your own lectures, 100% on-device (vectors never leave it):
- EmbeddingEngine (transformers.js feature-extraction via the CDN loader,
  multilingual-e5-small 384-dim, e5 query/passage prefixes); native stub.
- Vector store in StorageRepo (Dexie v3 + native v3 segvecs): upsertVectors,
  brute-force cosine searchVectors (course-scoped), clearVectors, unembeddedIds.
  Cascades: re-embed on segment edit, reassign updates vector courseId, deletes cascade.
- Hybrid search: semantic candidates + lexical rank fused via reciprocal-rank-fusion
  (pure, tested); searchLectures() returns segment hits tagged semantic/lexical/both.
- embeddingStore: build-index/backfill with progress + embed-on-save (fire-and-forget).
- Search screen: query -> segment hits (snippet · course · time) -> tap jumps the
  transcript to that timestamp (seek + scroll-into-view). Per-course stats on Courses.

25 repo tests (incl. cosine ranking + course scoping), 13 search tests, 170 total green.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

src/app/index.tsx

@@ -72,6 +72,11 @@ export default function LibraryScreen() {
             </ThemedText>
           </View>
           <View style={styles.headerLinks}>
+            <Link href="/search" asChild>
+              <Pressable hitSlop={8}>
+                <ThemedText type="link" themeColor="textSecondary">Search</ThemedText>
+              </Pressable>
+            </Link>
             <Link href="/courses" asChild>
               <Pressable hitSlop={8}>
                 <ThemedText type="link" themeColor="textSecondary">Courses</ThemedText>