feat: integrate vectordb for note embeddings

- Added `vectordb` as a dependency in `package.json`.
- Implemented `embedText` function in `src/main/ai/embeddings.ts` to handle text embeddings using GitHub Copilot OAuth token or OpenAI token.
- Created `vectordb.ts` for managing LanceDB connection and embedding notes with upsert strategy.
- Updated `index.ts` to initialize vector database and migrate existing notes on app ready.
- Modified `router/index.ts` to fire-and-forget embedding calls on note creation and updates.
- Enhanced `progress.txt` with detailed implementation notes and learnings regarding the integration.

src/main/db/vectordb.ts

@@ -0,0 +1,113 @@
+import * as lancedb from 'vectordb';
+import { app } from 'electron';
+import path from 'node:path';
+import { getDb } from './index';
+import { notes } from './schema';
+import { embedText } from '../ai/embeddings';
+
+interface NoteRecord {
+  id: string;
+  /** Empty string when the note has no project (Arrow string fields don't cleanly handle null) */
+  projectId: string;
+  content: string;
+  vector: number[];
+}
+
+let conn: lancedb.Connection | null = null;
+
+/**
+ * Initialize the LanceDB connection. Must be called before any other
+ * function in this module. Vector data is stored at userData/vectors/.
+ */
+export async function initVectorDb(): Promise<void> {
+  const vectorPath = path.join(app.getPath('userData'), 'vectors');
+  conn = await lancedb.connect(vectorPath);
+  console.log('[VectorDB] Connected at:', vectorPath);
+}
+
+function getConn(): lancedb.Connection {
+  if (!conn) throw new Error('[VectorDB] Not initialized. Call initVectorDb() first.');
+  return conn;
+}
+
+/**
+ * Embed note content and upsert the record into the LanceDB 'notes' table.
+ *
+ * Upsert strategy: delete-then-add.
+ * table.delete(where) is a no-op when no rows match, so this is safe for
+ * both first-time inserts and subsequent updates.
+ *
+ * On the very first call when the table does not yet exist, createTable
+ * infers the Arrow schema from the initial record.
+ *
+ * Throws on error — callers fire-and-forget via .catch().
+ */
+export async function upsertNoteEmbedding(
+  noteId: string,
+  projectId: string | null,
+  content: string,
+): Promise<void> {
+  const c = getConn();
+  const vector = await embedText(content);
+
+  const record: NoteRecord = {
+    id: noteId,
+    projectId: projectId ?? '',
+    content,
+    vector,
+  };
+
+  const tableNames = await c.tableNames();
+
+  if (!tableNames.includes('notes')) {
+    // First embedding: createTable infers the Arrow schema from this record.
+    // The vector dimension (1536 for text-embedding-3-small) is baked in here.
+    await c.createTable('notes', [record]);
+    console.log('[VectorDB] Created notes table');
+    return;
+  }
+
+  const table = await c.openTable<NoteRecord>('notes');
+  // Note IDs are UUID v4 — only [0-9a-f-] chars, no SQL injection risk.
+  await table.delete(`id = '${noteId}'`);
+  await table.add([record]);
+}
+
+/**
+ * On first startup, check if the LanceDB 'notes' table exists.
+ * If not, embed all existing SQLite notes and populate LanceDB.
+ *
+ * Per-note errors are caught and logged; a single failure does not
+ * abort the remaining notes.
+ */
+export async function migrateNotesIfNeeded(): Promise<void> {
+  const c = getConn();
+  const tableNames = await c.tableNames();
+
+  if (tableNames.includes('notes')) {
+    console.log('[VectorDB] Notes table exists, skipping migration');
+    return;
+  }
+
+  const allNotes = getDb().select().from(notes).all();
+
+  if (allNotes.length === 0) {
+    console.log('[VectorDB] No existing notes to migrate');
+    return;
+  }
+
+  console.log(`[VectorDB] Migrating ${allNotes.length} notes...`);
+  let successCount = 0;
+
+  for (const note of allNotes) {
+    try {
+      const embeddingText = `${note.title}\n\n${note.content}`;
+      await upsertNoteEmbedding(note.id, note.projectId ?? null, embeddingText);
+      successCount++;
+    } catch (err) {
+      console.error(`[VectorDB] Failed to embed note ${note.id} during migration:`, err);
+    }
+  }
+
+  console.log(`[VectorDB] Migration complete: ${successCount}/${allNotes.length} notes embedded`);
+}