react-native-nitro-sqlite-vec

Opt-in sqlite-vec support for react-native-nitro-sqlite. sqlite-vec is statically linked into the core package's SQLite build, so it does not load an extension at runtime.

Installation

Install both this package and react-native-nitro-sqlite, then enable the native build flag.

npm install react-native-nitro-sqlite react-native-nitro-sqlite-vec

• Apple platforms (iOS, macOS, visionOS):

  NITRO_SQLITE_VEC=1 npx pod-install

  For React Native macOS, run NITRO_SQLITE_VEC=1 pod install from macos/.
• Android: add this to android/gradle.properties and rebuild:

  nitroSqliteVec=true

isVecAvailable() returns false when the native flag was not enabled.

API

import { open } from 'react-native-nitro-sqlite'
import {
  createVectorTable,
  isVecAvailable,
  knnSearch,
  vecVersion,
} from 'react-native-nitro-sqlite-vec'

const db = open({ name: 'vectors.sqlite' })

if (!isVecAvailable(db)) {
  throw new Error('Enable sqlite-vec in the native build first')
}

console.log(vecVersion(db))
createVectorTable(db, 'embeddings', {
  dimensions: 3,
  type: 'float', // 'float' (default), 'int8', or 'bit'
  distanceMetric: 'L2', // 'L2' (default), 'cosine', or 'L1'
  column: 'embedding', // default
})

db.execute('INSERT INTO embeddings (rowid, embedding) VALUES (?, ?)', [
  1,
  '[0.1, 0.2, 0.3]',
])

const matches = knnSearch(db, 'embeddings', [0.1, 0.2, 0.25], 10)
// [{ rowid: 1, distance: 0.05... }]

knnSearch() accepts a JSON vector string or a number[] and returns rows containing rowid, distance, and any selected columns. createVectorTable() and knnSearch() interpolate table and column identifiers into SQL, so only pass trusted identifiers.

For the core SQLite API, see the repository README.