fix: include vectors in backup and fix Float32Array serialization

index.ts

@@ -2555,16 +2555,28 @@ const memoryLanceDBProPlugin = {
         );
         await mkdir(backupDir, { recursive: true });
 
-        const allMemories = await store.list(undefined, undefined, 10000, 0);
+        // Include vectors so backup can be restored without re-embedding
+        const allMemories = await store.list(undefined, undefined, 10000, 0, true);
         if (allMemories.length === 0) return;
 
         const dateStr = new Date().toISOString().split("T")[0];
         const backupFile = join(backupDir, `memory-backup-${dateStr}.jsonl`);
 
-        const lines = allMemories.map((m) =>
+        // First line: metadata header for restore compatibility
+        const embeddingModel = config.embedding.model || "text-embedding-3-small";
+        const metaLine = JSON.stringify({
+          _meta: true,
+          version: "1.1",
+          model: embeddingModel,
+          dimensions: vectorDim,
+          timestamp: new Date().toISOString(),
+        });
+
+        const dataLines = allMemories.map((m) =>
           JSON.stringify({
             id: m.id,
             text: m.text,
+            vector: m.vector,
             category: m.category,
             scope: m.scope,
             importance: m.importance,
@@ -2573,7 +2585,7 @@ const memoryLanceDBProPlugin = {
           }),
         );
 
-        await writeFile(backupFile, lines.join("\n") + "\n");
+        await writeFile(backupFile, metaLine + "\n" + dataLines.join("\n") + "\n");
 
         // Keep only last 7 backups
         const files = (await readdir(backupDir))

src/store.ts

@@ -592,6 +592,7 @@ export class MemoryStore {
     category?: string,
     limit = 20,
     offset = 0,
+    includeVectors = false,
   ): Promise<MemoryEntry[]> {
     await this.ensureInitialized();
 
@@ -615,25 +616,33 @@ export class MemoryStore {
       query = query.where(conditions.join(" AND "));
     }
 
+    // Select columns - optionally include the vector column for backup/export
+    const selectCols = [
+      "id",
+      "text",
+      "category",
+      "scope",
+      "importance",
+      "timestamp",
+      "metadata",
+    ];
+    if (includeVectors) {
+      selectCols.push("vector");
+    }
+
     // Fetch all matching rows (no pre-limit) so app-layer sort is correct across full dataset
     const results = await query
-      .select([
-        "id",
-        "text",
-        "category",
-        "scope",
-        "importance",
-        "timestamp",
-        "metadata",
-      ])
+      .select(selectCols)
       .toArray();
 
     return results
       .map(
         (row): MemoryEntry => ({
           id: row.id as string,
           text: row.text as string,
-          vector: [], // Don't include vectors in list results for performance
+          vector: includeVectors && row.vector
+            ? Array.from(row.vector as Iterable<number>)
+            : [],
           category: row.category as MemoryEntry["category"],
           scope: (row.scope as string | undefined) ?? "global",
           importance: Number(row.importance),