feat: migrate semantic search to pgvector + full-text search

Replace JSON-string embeddings with native pgvector(1536) storage and
add PostgreSQL full-text search (tsvector/GIN) with Reciprocal Rank Fusion
for hybrid keyword + semantic ranking.

Changes:
- NoteEmbedding.embedding: String → vector(1536) via pgvector
- NoteEmbedding: added updatedAt for reindex tracking
- Note: added tsv (tsvector) with auto-update trigger for FTS
- semantic-search.service: hybrid FTS + vector search with RRF fusion
- embedding.service: toVectorString() for pgvector SQL literals
- Removed JS-side cosine similarity loops (now DB-side via <=>)
- Added HNSW index on NoteEmbedding.embedding (cosine distance)
- Added GIN index on Note.tsv for FTS queries

Schema migration in: prisma/migrations/20260512120000_pgvector_and_fts_search/

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

memento-note/app/api/notes/reindex/route.ts

@@ -1,7 +1,7 @@
 import { NextRequest, NextResponse } from 'next/server'
 import { auth } from '@/auth'
 import { prisma } from '@/lib/prisma'
-import { EmbeddingService } from '@/lib/ai/services/embedding.service'
+import { semanticSearchService } from '@/lib/ai/services/semantic-search.service'
 
 export async function POST(req: NextRequest) {
   try {
@@ -12,41 +12,31 @@ export async function POST(req: NextRequest) {
 
     const userId = session.user.id
 
-    // Fetch all notes for the user
     const notes = await prisma.note.findMany({
       where: { userId, trashedAt: null },
-      select: { id: true, title: true, content: true }
+      select: { id: true }
     })
 
-    const embeddingService = new EmbeddingService()
     let processedCount = 0
+    let failedCount = 0
+    const BATCH_SIZE = 20
 
-    // Process in small batches to avoid timeouts if possible
-    // Note: In a real production app, this should be a background job
-    for (const note of notes) {
-      try {
-        const textToEmbed = `${note.title || ''}\n${note.content}`
-        if (textToEmbed.trim()) {
-          const embedding = await embeddingService.generateEmbedding(textToEmbed)
-          
-          await prisma.noteEmbedding.upsert({
-            where: { noteId: note.id },
-            update: { embedding: JSON.stringify(embedding) },
-            create: {
-              noteId: note.id,
-              embedding: JSON.stringify(embedding)
-            }
-          })
-          processedCount++
-        }
-      } catch (err) {
-        console.error(`Failed to reindex note ${note.id}:`, err)
+    for (let i = 0; i < notes.length; i += BATCH_SIZE) {
+      const batch = notes.slice(i, i + BATCH_SIZE)
+      const results = await Promise.allSettled(
+        batch.map(note => semanticSearchService.indexNote(note.id))
+      )
+
+      for (const r of results) {
+        if (r.status === 'fulfilled') processedCount++
+        else failedCount++
       }
     }
 
     return NextResponse.json({
       success: true,
       count: processedCount,
+      failed: failedCount,
       total: notes.length
     })
   } catch (error) {