try out static blobs feature behind SQLITE_VEC_ENABLE_EXPERIMENTAL

tmp-static.py

@@ -0,0 +1,55 @@
+import sqlite3
+import numpy as np
+
+db = sqlite3.connect(":memory:")
+
+db.enable_load_extension(True)
+db.load_extension("./dist/vec0")
+db.enable_load_extension(False)
+
+x = np.array([[0.1, 0.2, 0.3, 0.4], [0.9, 0.8, 0.7, 0.6]], dtype=np.float32)
+y = np.array([[0.2, 0.3], [0.9, 0.8], [0.6, 0.5]], dtype=np.float32)
+z = np.array(
+    [
+        [0.1, 0.1, 0.1, 0.1],
+        [0.2, 0.2, 0.2, 0.2],
+        [0.3, 0.3, 0.3, 0.3],
+        [0.4, 0.4, 0.4, 0.4],
+        [0.5, 0.5, 0.5, 0.5],
+    ],
+    dtype=np.float32,
+)
+
+
+def register_np(array, name):
+    ptr = array.__array_interface__["data"][0]
+    nvectors, dimensions = array.__array_interface__["shape"]
+    element_type = array.__array_interface__["typestr"]
+
+    assert element_type == "<f4"
+
+    name_escaped = db.execute("select printf('%w', ?)", [name]).fetchone()[0]
+
+    db.execute(
+        "insert into temp.vec_static_blobs(name, data) select ?, vec_static_blob_from_raw(?, ?, ?, ?)",
+        [name, ptr, element_type, dimensions, nvectors],
+    )
+
+    db.execute(
+        f'create virtual table "{name_escaped}" using vec_static_blob_entries({name_escaped})'
+    )
+
+
+register_np(x, "x")
+register_np(y, "y")
+register_np(z, "z")
+print(db.execute("select *, dimensions, count from temp.vec_static_blobs;").fetchall())
+
+print(db.execute("select vec_to_json(vector) from x;").fetchall())
+print(db.execute("select (vector) from y limit 2;").fetchall())
+print(
+    db.execute(
+        "select (vector) from z where vector match ? and k = 2 order by distance;",
+        [np.array([0.3, 0.3, 0.3, 0.3], dtype=np.float32)],
+    ).fetchall()
+)