sqlite_vector 0.9.70

SQLite Vector extension for Flutter/Dart. Provides vector search with SIMD-optimized distance functions (L2, cosine, dot product) for Float32, Float16, Int8, 1Bit vectors.

sqlite_vector

SQLite Vector extension for Flutter/Dart. Provides vector search with SIMD-optimized distance functions (L2, cosine, dot product) for Float32, Float16, Int8, and 1Bit vectors.

Installation

dart pub add sqlite_vector

Requires Dart 3.10+ / Flutter 3.38+.

Usage

With sqlite3

import 'package:sqlite3/sqlite3.dart';
import 'package:sqlite_vector/sqlite_vector.dart';

void main() {
  // Load once at startup.
  sqlite3.loadSqliteVectorExtension();

  final db = sqlite3.openInMemory();

  // Create a regular table with a BLOB column for vectors.
  db.execute('CREATE TABLE items (id INTEGER PRIMARY KEY, embedding BLOB)');

  // Insert vectors.
  final stmt = db.prepare('INSERT INTO items (embedding) VALUES (vector_as_f32(?))');
  stmt.execute(['[1.0, 2.0, 3.0, 4.0]']);
  stmt.dispose();

  // Initialize the vector index.
  db.execute("SELECT vector_init('items', 'embedding', 'type=FLOAT32,dimension=4')");

  // Find the 2 nearest neighbors.
  final results = db.select('''
    SELECT e.id, v.distance FROM items AS e
    JOIN vector_full_scan('items', 'embedding', vector_as_f32('[1.0, 2.0, 3.0, 4.0]'), 2) AS v
    ON e.id = v.rowid
  ''');

  db.dispose();
}

With drift

import 'package:sqlite3/sqlite3.dart';
import 'package:sqlite_vector/sqlite_vector.dart';
import 'package:drift/native.dart';

Sqlite3 loadExtensions() {
  sqlite3.loadSqliteVectorExtension();
  return sqlite3;
}

// Use when creating the database:
NativeDatabase.createInBackground(
  File(path),
  sqlite3: loadExtensions,
);

Supported platforms

Platform	Architectures
Android	arm64, arm, x64
iOS	arm64 (device + simulator)
macOS	arm64, x64
Linux	arm64, x64
Windows	x64

API

See the full sqlite-vector API documentation.

License

See LICENSE.