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*   Vercel Postgres

On this page

Vercel Postgres
===============

LangChain.js supports using the [`@vercel/postgres`](https://www.npmjs.com/package/@vercel/postgres) package to use generic Postgres databases as vector stores, provided they support the [`pgvector`](https://github.com/pgvector/pgvector) Postgres extension.

This integration is particularly useful from web environments like Edge functions.

Setup[​](#setup "Direct link to Setup")
---------------------------------------

To work with Vercel Postgres, you need to install the `@vercel/postgres` package:

*   npm
*   Yarn
*   pnpm

    npm install @vercel/postgres

    yarn add @vercel/postgres

    pnpm add @vercel/postgres

tip

See [this section for general instructions on installing integration packages](/v0.1/docs/get_started/installation/#installing-integration-packages).

*   npm
*   Yarn
*   pnpm

    npm install @langchain/community

    yarn add @langchain/community

    pnpm add @langchain/community

This integration automatically connects using the connection string set under `process.env.POSTGRES_URL`. You can also pass a connection string manually like this:

    const vectorstore = await VercelPostgres.initialize(new OpenAIEmbeddings(), {  postgresConnectionOptions: {    connectionString:      "postgres://<username>:<password>@<hostname>:<port>/<dbname>",  },});

### Connecting to Vercel Postgres[​](#connecting-to-vercel-postgres "Direct link to Connecting to Vercel Postgres")

A simple way to get started is to create a serverless [Vercel Postgres instance](https://vercel.com/docs/storage/vercel-postgres/quickstart). If you're deploying to a Vercel project with an associated Vercel Postgres instance, the required `POSTGRES_URL` environment variable will already be populated in hosted environments.

### Connecting to other databases[​](#connecting-to-other-databases "Direct link to Connecting to other databases")

If you prefer to host your own Postgres instance, you can use a similar flow to LangChain's [PGVector](/v0.1/docs/integrations/vectorstores/pgvector/) vectorstore integration and set the connection string either as an environment variable or as shown above.

Usage[​](#usage "Direct link to Usage")
---------------------------------------

    import { CohereEmbeddings } from "@langchain/cohere";import { VercelPostgres } from "@langchain/community/vectorstores/vercel_postgres";// Config is only required if you want to override default values.const config = {  // tableName: "testvercelvectorstorelangchain",  // postgresConnectionOptions: {  //   connectionString: "postgres://<username>:<password>@<hostname>:<port>/<dbname>",  // },  // columns: {  //   idColumnName: "id",  //   vectorColumnName: "vector",  //   contentColumnName: "content",  //   metadataColumnName: "metadata",  // },};const vercelPostgresStore = await VercelPostgres.initialize(  new CohereEmbeddings(),  config);const docHello = {  pageContent: "hello",  metadata: { topic: "nonsense" },};const docHi = { pageContent: "hi", metadata: { topic: "nonsense" } };const docMitochondria = {  pageContent: "Mitochondria is the powerhouse of the cell",  metadata: { topic: "science" },};const ids = await vercelPostgresStore.addDocuments([  docHello,  docHi,  docMitochondria,]);const results = await vercelPostgresStore.similaritySearch("hello", 2);console.log(results);/*  [    Document { pageContent: 'hello', metadata: { topic: 'nonsense' } },    Document { pageContent: 'hi', metadata: { topic: 'nonsense' } }  ]*/// Metadata filteringconst results2 = await vercelPostgresStore.similaritySearch(  "Irrelevant query, metadata filtering",  2,  {    topic: "science",  });console.log(results2);/*  [    Document {      pageContent: 'Mitochondria is the powerhouse of the cell',      metadata: { topic: 'science' }    }  ]*/// Metadata filtering with IN-filters works as wellconst results3 = await vercelPostgresStore.similaritySearch(  "Irrelevant query, metadata filtering",  3,  {    topic: { in: ["science", "nonsense"] },  });console.log(results3);/*  [    Document {      pageContent: 'hello',      metadata: { topic: 'nonsense' }    },    Document {      pageContent: 'hi',      metadata: { topic: 'nonsense' }    },    Document {      pageContent: 'Mitochondria is the powerhouse of the cell',      metadata: { topic: 'science' }    }  ]*/// Upserting is supported as wellawait vercelPostgresStore.addDocuments(  [    {      pageContent: "ATP is the powerhouse of the cell",      metadata: { topic: "science" },    },  ],  { ids: [ids[2]] });const results4 = await vercelPostgresStore.similaritySearch(  "What is the powerhouse of the cell?",  1);console.log(results4);/*  [    Document {      pageContent: 'ATP is the powerhouse of the cell',      metadata: { topic: 'science' }    }  ]*/await vercelPostgresStore.delete({ ids: [ids[2]] });const results5 = await vercelPostgresStore.similaritySearch(  "No more metadata",  2,  {    topic: "science",  });console.log(results5);/*  []*/// Remember to call .end() to close the connection!await vercelPostgresStore.end();

#### API Reference:

*   [CohereEmbeddings](https://api.js.langchain.com/classes/langchain_cohere.CohereEmbeddings.html) from `@langchain/cohere`
*   [VercelPostgres](https://api.js.langchain.com/classes/langchain_community_vectorstores_vercel_postgres.VercelPostgres.html) from `@langchain/community/vectorstores/vercel_postgres`

* * *

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*   [Setup](#setup)
    *   [Connecting to Vercel Postgres](#connecting-to-vercel-postgres)
    *   [Connecting to other databases](#connecting-to-other-databases)
*   [Usage](#usage)

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