feat(db): extraction des embeddings + mode WAL + config DB provider-agnostic

- Ajout de la table de relation 1-1 NoteEmbedding pour alléger Model Note
- Refactor complet des actions IA sémantique et Memory Echo pour utiliser la jointure
- Migration propre des 85 embeddings locaux existants
- Ajout PRAGMA journal_mode=WAL pour la concurrence au sein de lib/prisma
- Ajout npm run db:switch pour configuration auto SQLite / PostgreSQL
- Fix du compilateur Turbopack et Next-PWA

keep-notes/lib/ai/services/semantic-search.service.ts

@@ -177,12 +177,12 @@ export class SemanticSearchService {
       const notes = await prisma.note.findMany({
         where: {
           ...(userId ? { userId } : {}),
-          ...(notebookId !== undefined ? { notebookId } : {}), // NEW: Notebook filter
-          embedding: { not: null }
+          ...(notebookId !== undefined ? { notebookId } : {}),
+          noteEmbedding: { isNot: null }
         },
         select: {
           id: true,
-          embedding: true
+          noteEmbedding: true
         }
       })
 
@@ -192,7 +192,7 @@ export class SemanticSearchService {
 
       // Calculate similarities for all notes
       const similarities = notes.map(note => {
-        const noteEmbedding = note.embedding ? JSON.parse(note.embedding) as number[] : []
+        const noteEmbedding = note.noteEmbedding?.embedding ? JSON.parse(note.noteEmbedding.embedding) as number[] : []
         const similarity = embeddingService.calculateCosineSimilarity(
           queryEmbedding,
           noteEmbedding
@@ -273,7 +273,7 @@ export class SemanticSearchService {
     try {
       const note = await prisma.note.findUnique({
         where: { id: noteId },
-        select: { content: true, embedding: true, lastAiAnalysis: true }
+        select: { content: true, noteEmbedding: true, lastAiAnalysis: true }
       })
 
       if (!note) {
@@ -283,7 +283,7 @@ export class SemanticSearchService {
       // Check if embedding needs regeneration
       const shouldRegenerate = embeddingService.shouldRegenerateEmbedding(
         note.content,
-        note.embedding as any,
+        note.noteEmbedding?.embedding as any,
         note.lastAiAnalysis
       )
 
@@ -295,10 +295,14 @@ export class SemanticSearchService {
       const { embedding } = await embeddingService.generateEmbedding(note.content)
 
       // Save to database
+      await prisma.noteEmbedding.upsert({
+        where: { noteId: noteId },
+        create: { noteId: noteId, embedding: embeddingService.serialize(embedding) as any },
+        update: { embedding: embeddingService.serialize(embedding) as any }
+      })
       await prisma.note.update({
         where: { id: noteId },
         data: {
-          embedding: embeddingService.serialize(embedding) as any,
           lastAiAnalysis: new Date()
         }
       })