feat: support binary vector and IVF_FLAT in TypeScript (#2221)

resolve #2218

---------

Signed-off-by: BubbleCal <bubble-cal@outlook.com>

nodejs/examples/search.test.ts

@@ -4,9 +4,12 @@ import { expect, test } from "@jest/globals";
 // --8<-- [start:import]
 import * as lancedb from "@lancedb/lancedb";
 // --8<-- [end:import]
+// --8<-- [start:import_bin_util]
+import { Field, FixedSizeList, Int32, Schema, Uint8 } from "apache-arrow";
+// --8<-- [end:import_bin_util]
 import { withTempDirectory } from "./util.ts";
 
-test("full text search", async () => {
+test("vector search", async () => {
   await withTempDirectory(async (databaseDir) => {
     {
       const db = await lancedb.connect(databaseDir);
@@ -14,8 +17,6 @@ test("full text search", async () => {
       const data = Array.from({ length: 10_000 }, (_, i) => ({
         vector: Array(128).fill(i),
         id: `${i}`,
-        content: "",
-        longId: `${i}`,
       }));
 
       await db.createTable("my_vectors", data);
@@ -52,5 +53,41 @@ test("full text search", async () => {
       expect(r.distance).toBeGreaterThanOrEqual(0.1);
       expect(r.distance).toBeLessThan(0.2);
     }
+
+    {
+      // --8<-- [start:ingest_binary_data]
+      const schema = new Schema([
+        new Field("id", new Int32(), true),
+        new Field("vec", new FixedSizeList(32, new Field("item", new Uint8()))),
+      ]);
+      const data = lancedb.makeArrowTable(
+        Array(1_000)
+          .fill(0)
+          .map((_, i) => ({
+            // the 256 bits would be store in 32 bytes,
+            // if your data is already in this format, you can skip the packBits step
+            id: i,
+            vec: lancedb.packBits(Array(256).fill(i % 2)),
+          })),
+        { schema: schema },
+      );
+
+      const tbl = await db.createTable("binary_table", data);
+      await tbl.createIndex("vec", {
+        config: lancedb.Index.ivfFlat({
+          numPartitions: 10,
+          distanceType: "hamming",
+        }),
+      });
+      // --8<-- [end:ingest_binary_data]
+
+      // --8<-- [start:search_binary_data]
+      const query = Array(32)
+        .fill(1)
+        .map(() => Math.floor(Math.random() * 255));
+      const results = await tbl.query().nearestTo(query).limit(10).toArrow();
+      // --8<-- [end:search_binary_data
+      expect(results.numRows).toBe(10);
+    }
   });
 });