feat: support IVF_FLAT, binary vectors and hamming distance (#1955)

binary vectors and hamming distance can work on only IVF_FLAT, so
introduce them all in this PR.

---------

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

python/python/tests/docs/test_binary_vector.py

@@ -0,0 +1,44 @@
+import shutil
+
+# --8<-- [start:imports]
+import lancedb
+import numpy as np
+import pytest
+# --8<-- [end:imports]
+
+shutil.rmtree("data/binary_lancedb", ignore_errors=True)
+
+
+def test_binary_vector():
+    # --8<-- [start:sync_binary_vector]
+    db = lancedb.connect("data/binary_lancedb")
+    data = [
+        {
+            "id": i,
+            "vector": np.random.randint(0, 256, size=16),
+        }
+        for i in range(1024)
+    ]
+    tbl = db.create_table("my_binary_vectors", data=data)
+    query = np.random.randint(0, 256, size=16)
+    tbl.search(query).to_arrow()
+    # --8<-- [end:sync_binary_vector]
+    db.drop_table("my_binary_vectors")
+
+
+@pytest.mark.asyncio
+async def test_binary_vector_async():
+    # --8<-- [start:async_binary_vector]
+    db = await lancedb.connect_async("data/binary_lancedb")
+    data = [
+        {
+            "id": i,
+            "vector": np.random.randint(0, 256, size=16),
+        }
+        for i in range(1024)
+    ]
+    tbl = await db.create_table("my_binary_vectors", data=data)
+    query = np.random.randint(0, 256, size=16)
+    await tbl.query().nearest_to(query).to_arrow()
+    # --8<-- [end:async_binary_vector]
+    await db.drop_table("my_binary_vectors")