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PGVector

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

Setup​

To work with PGVector, you need to install the pg package:

npm install pg

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:

services:
  db:
    image: ankane/pgvector
    ports:
      - 5433:5432
    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.

    Usage​

    One complete example of using PGVectorStore is the following:

    import { OpenAIEmbeddings } from "langchain/embeddings/openai";
    import { PGVectorStore } from "langchain/vectorstores/pgvector";
    import { PoolConfig } from "pg";

    // First, follow set-up instructions at
    // https://js.langchain.com/docs/modules/indexes/vector_stores/integrations/pgvector

    const config = {
      postgresConnectionOptions: {
        type: "postgres",
        host: "127.0.0.1",
        port: 5433,
        user: "myuser",
        password: "ChangeMe",
        database: "api",
      } as PoolConfig,
      tableName: "testlangchain",
      columns: {
        idColumnName: "id",
        vectorColumnName: "vector",
        contentColumnName: "content",
        metadataColumnName: "metadata",
      },
    };

    const pgvectorStore = await PGVectorStore.initialize(
      new OpenAIEmbeddings(),
      config
    );

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

    const results = await pgvectorStore.similaritySearch("water", 1);

    console.log(results);

    /*
      [ Document { pageContent: 'Cat drinks milk', metadata: { a: 1 } } ]
    */

    await pgvectorStore.end();

    API Reference: