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To enable vector search in a generic PostgreSQL database, LangChain.js supports using TypeORM with the pgvector Postgres extension.


To work with TypeORM, you need to install the typeorm and pg packages:

npm install typeorm
npm install pg
npm install @langchain/openai @langchain/community

Setup a pgvector self hosted instance with docker-compose

pgvector provides a prebuilt Docker image that can be used to quickly setup a self-hosted Postgres instance. Create a file below named docker-compose.yml:

export default {services:{db:{image:'ankane/pgvector',ports:['5432:5432'],volumes:['./data:/var/lib/postgresql/data'],environment:['POSTGRES_PASSWORD=ChangeMe','POSTGRES_USER=myuser','POSTGRES_DB=api']}}};

API Reference:

    And then in the same directory, run docker compose up to start the container.

    You can find more information on how to setup pgvector in the official repository.


    One complete example of using TypeORMVectorStore is the following:

    import { DataSourceOptions } from "typeorm";
    import { OpenAIEmbeddings } from "@langchain/openai";
    import { TypeORMVectorStore } from "@langchain/community/vectorstores/typeorm";

    // First, follow set-up instructions at

    export const run = async () => {
    const args = {
    postgresConnectionOptions: {
    type: "postgres",
    host: "localhost",
    port: 5432,
    username: "myuser",
    password: "ChangeMe",
    database: "api",
    } as DataSourceOptions,

    const typeormVectorStore = await TypeORMVectorStore.fromDataSource(
    new OpenAIEmbeddings(),

    await typeormVectorStore.ensureTableInDatabase();

    await typeormVectorStore.addDocuments([
    { pageContent: "what's this", metadata: { a: 2 } },
    { pageContent: "Cat drinks milk", metadata: { a: 1 } },

    const results = await typeormVectorStore.similaritySearch("hello", 2);


    API Reference:

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