pgvector support for Node.js
Supports Sequelize, node-postgres, pg-promise, Prisma, Postgres.js, and Drizzle ORM
Run:
npm install pgvectorAnd follow the instructions for your database library:
- Sequelize
- node-postgres
- pg-promise
- Prisma
- Postgres.js
- Drizzle ORM (experimental, unreleased)
Register the type
import { Sequelize } from 'sequelize';
import pgvector from 'pgvector/sequelize';
pgvector.registerType(Sequelize);Add a vector field
Item.init({
embedding: {
type: DataTypes.VECTOR(3)
}
}, ...);Insert a vector
await Item.create({embedding: [1, 2, 3]});Get the nearest neighbors to a vector
const items = await Item.findAll({
order: [sequelize.literal(`embedding <-> '[1, 2, 3]'`)],
limit: 5
});Register the type for a client
import pgvector from 'pgvector/pg';
await pgvector.registerType(client);or a pool
pool.on('connect', async function (client) {
await pgvector.registerType(client);
});Insert a vector
const embedding = [1, 2, 3];
await client.query('INSERT INTO items (embedding) VALUES ($1)', [pgvector.toSql(embedding)]);Get the nearest neighbors to a vector
const result = await client.query('SELECT * FROM items ORDER BY embedding <-> $1 LIMIT 5', [pgvector.toSql(embedding)]);Register the type
import pgpromise from 'pg-promise';
import pgvector from 'pgvector/pg';
const initOptions = {
async connect(e) {
await pgvector.registerType(e.client);
}
};
const pgp = pgpromise(initOptions);Insert a vector
const embedding = [1, 2, 3];
await db.none('INSERT INTO items (embedding) VALUES ($1)', [pgvector.toSql(embedding)]);Get the nearest neighbors to a vector
const result = await db.any('SELECT * FROM items ORDER BY embedding <-> $1 LIMIT 5', [pgvector.toSql(embedding)]);Import the library
import pgvector from 'pgvector/utils';Add the extension to the schema
generator client {
provider = "prisma-client-js"
previewFeatures = ["postgresqlExtensions"]
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
extensions = [vector]
}Add a vector column to the schema
model Item {
id Int @id @default(autoincrement())
embedding Unsupported("vector(3)")?
}Insert a vector
const embedding = pgvector.toSql([1, 1, 1])
await prisma.$executeRaw`INSERT INTO items (embedding) VALUES (${embedding}::vector)`Get the nearest neighbors to a vector
const embedding = pgvector.toSql([1, 1, 1])
const items = await prisma.$queryRaw`SELECT id, embedding::text FROM items ORDER BY embedding <-> ${embedding}::vector LIMIT 5`Import the library
import pgvector from 'pgvector/utils';Insert vectors
const items = [
{embedding: pgvector.toSql([1, 2, 3])},
{embedding: pgvector.toSql([4, 5, 6])}
];
await sql`INSERT INTO items ${ sql(items, 'embedding') }`;Get the nearest neighbors to a vector
const embedding = pgvector.toSql([1, 2, 3]);
const items = await sql`SELECT * FROM items ORDER BY embedding <-> ${ embedding } LIMIT 5`;Note: This is currently experimental and does not work with Drizzle Kit
Add a vector field
import { vector } from 'pgvector/drizzle-orm';
const items = pgTable('items', {
id: serial('id').primaryKey(),
embedding: vector('embedding', {dimensions: 3})
});Insert vectors
const newItems = [
{embedding: [1, 2, 3]},
{embedding: [4, 5, 6]}
];
await db.insert(items).values(newItems);Get the nearest neighbors to a vector
import { l2Distance } from 'pgvector/drizzle-orm';
const embedding = [1, 2, 3];
const allItems = await db.select().from(items).orderBy(l2Distance(items.embedding, embedding)).limit(5);Also supports maxInnerProduct and cosineDistance
View the changelog
Everyone is encouraged to help improve this project. Here are a few ways you can help:
- Report bugs
- Fix bugs and submit pull requests
- Write, clarify, or fix documentation
- Suggest or add new features
To get started with development:
git clone https://github.com/pgvector/pgvector-node.git
cd pgvector-node
npm install
createdb pgvector_node_test
npx prisma migrate dev
npm test