SQLite Vector

Creator
Creator
Seonglae Cho
Created
Created
2022 Aug 25 16:49
Editor
Edited
Edited
2025 Mar 24 11:43
Use sqlite-vec when you need a lightweight, embedded solution for vector similarity search. It is ideal for applications that require vector data handling on-device or at the edge, such as mobile apps, IoT devices, or local AI model inference.
pip install sqlite-vec import sqlite3 import sqlite_vec from sqlite_vec import serialize_float32 db = sqlite3.connect(":memory:") db.enable_load_extension(True) sqlite_vec.load(db) db.enable_load_extension(False) embedding = [0.1, 0.2, 0.3, 0.4] result = db.execute('SELECT vec_length(?)', [serialize_float32(embedding)]) print(result.fetchone()[0]) # Outputs: 4
For NumPy arrays, cast to 32-bit floats with .astype(np.float32)
 
 
 
 
 
 
 

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