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*   [Providers](/v0.1/docs/integrations/platforms/)
    
    *   [Providers](/v0.1/docs/integrations/platforms/)
    *   [Anthropic](/v0.1/docs/integrations/platforms/anthropic/)
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*   [Components](/v0.1/docs/integrations/components/)
    
    *   [LLMs](/v0.1/docs/integrations/llms/)
        
    *   [Chat models](/v0.1/docs/integrations/chat/)
        
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        *   [Astra DB Chat Memory](/v0.1/docs/integrations/chat_memory/astradb/)
        *   [Cassandra Chat Memory](/v0.1/docs/integrations/chat_memory/cassandra/)
        *   [Cloudflare D1-Backed Chat Memory](/v0.1/docs/integrations/chat_memory/cloudflare_d1/)
        *   [Convex Chat Memory](/v0.1/docs/integrations/chat_memory/convex/)
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        *   [Xata Chat Memory](/v0.1/docs/integrations/chat_memory/xata/)
        *   [Zep Memory](/v0.1/docs/integrations/chat_memory/zep_memory/)
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*   [Components](/v0.1/docs/integrations/components/)
*   [Chat Memory](/v0.1/docs/integrations/chat_memory/)
*   Xata Chat Memory

On this page

Xata Chat Memory
================

[Xata](https://xata.io) is a serverless data platform, based on PostgreSQL. It provides a type-safe TypeScript/JavaScript SDK for interacting with your database, and a UI for managing your data.

With the `XataChatMessageHistory` class, you can use Xata databases for longer-term persistence of chat sessions.

Because Xata works via a REST API and has a pure TypeScript SDK, you can use this with [Vercel Edge](https://vercel.com/docs/concepts/functions/edge-functions/edge-runtime), [Cloudflare Workers](https://developers.cloudflare.com/workers/) and any other Serverless environment.

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

### Install the Xata CLI[​](#install-the-xata-cli "Direct link to Install the Xata CLI")

    npm install @xata.io/cli -g

### Create a database to be used as a vector store[​](#create-a-database-to-be-used-as-a-vector-store "Direct link to Create a database to be used as a vector store")

In the [Xata UI](https://app.xata.io) create a new database. You can name it whatever you want, but for this example we'll use `langchain`.

When executed for the first time, the Xata LangChain integration will create the table used for storing the chat messages. If a table with that name already exists, it will be left untouched.

### Initialize the project[​](#initialize-the-project "Direct link to Initialize the project")

In your project, run:

    xata init

and then choose the database you created above. This will also generate a `xata.ts` or `xata.js` file that defines the client you can use to interact with the database. See the [Xata getting started docs](https://xata.io/docs/getting-started/installation) for more details on using the Xata JavaScript/TypeScript SDK.

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

Each chat history session stored in Xata database must have a unique id.

In this example, the `getXataClient()` function is used to create a new Xata client based on the environment variables. However, we recommend using the code generated by the `xata init` command, in which case you only need to import the `getXataClient()` function from the generated `xata.ts` file.

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/openai @langchain/community

    yarn add @langchain/openai @langchain/community

    pnpm add @langchain/openai @langchain/community

    import { BufferMemory } from "langchain/memory";import { ChatOpenAI } from "@langchain/openai";import { ConversationChain } from "langchain/chains";import { XataChatMessageHistory } from "@langchain/community/stores/message/xata";import { BaseClient } from "@xata.io/client";// if you use the generated client, you don't need this function.// Just import getXataClient from the generated xata.ts instead.const getXataClient = () => {  if (!process.env.XATA_API_KEY) {    throw new Error("XATA_API_KEY not set");  }  if (!process.env.XATA_DB_URL) {    throw new Error("XATA_DB_URL not set");  }  const xata = new BaseClient({    databaseURL: process.env.XATA_DB_URL,    apiKey: process.env.XATA_API_KEY,    branch: process.env.XATA_BRANCH || "main",  });  return xata;};const memory = new BufferMemory({  chatHistory: new XataChatMessageHistory({    table: "messages",    sessionId: new Date().toISOString(), // Or some other unique identifier for the conversation    client: getXataClient(),    apiKey: process.env.XATA_API_KEY, // The API key is needed for creating the table.  }),});const model = new ChatOpenAI();const chain = new ConversationChain({ llm: model, memory });const res1 = await chain.invoke({ input: "Hi! I'm Jim." });console.log({ res1 });/*{  res1: {    text: "Hello Jim! It's nice to meet you. My name is AI. How may I assist you today?"  }}*/const res2 = await chain.invoke({ input: "What did I just say my name was?" });console.log({ res2 });/*{  res1: {    text: "You said your name was Jim."  }}*/

#### API Reference:

*   [BufferMemory](https://api.js.langchain.com/classes/langchain_memory.BufferMemory.html) from `langchain/memory`
*   [ChatOpenAI](https://api.js.langchain.com/classes/langchain_openai.ChatOpenAI.html) from `@langchain/openai`
*   [ConversationChain](https://api.js.langchain.com/classes/langchain_chains.ConversationChain.html) from `langchain/chains`
*   [XataChatMessageHistory](https://api.js.langchain.com/classes/langchain_community_stores_message_xata.XataChatMessageHistory.html) from `@langchain/community/stores/message/xata`

### With pre-created table[​](#with-pre-created-table "Direct link to With pre-created table")

If you don't want the code to always check if the table exists, you can create the table manually in the Xata UI and pass `createTable: false` to the constructor. The table must have the following columns:

*   `sessionId` of type `String`
*   `type` of type `String`
*   `role` of type `String`
*   `content` of type `Text`
*   `name` of type `String`
*   `additionalKwargs` of type `Text`

    import { BufferMemory } from "langchain/memory";import { ChatOpenAI } from "@langchain/openai";import { ConversationChain } from "langchain/chains";import { XataChatMessageHistory } from "@langchain/community/stores/message/xata";import { BaseClient } from "@xata.io/client";// Before running this example, see the docs at// https://js.langchain.com/docs/modules/memory/integrations/xata// if you use the generated client, you don't need this function.// Just import getXataClient from the generated xata.ts instead.const getXataClient = () => {  if (!process.env.XATA_API_KEY) {    throw new Error("XATA_API_KEY not set");  }  if (!process.env.XATA_DB_URL) {    throw new Error("XATA_DB_URL not set");  }  const xata = new BaseClient({    databaseURL: process.env.XATA_DB_URL,    apiKey: process.env.XATA_API_KEY,    branch: process.env.XATA_BRANCH || "main",  });  return xata;};const memory = new BufferMemory({  chatHistory: new XataChatMessageHistory({    table: "messages",    sessionId: new Date().toISOString(), // Or some other unique identifier for the conversation    client: getXataClient(),    createTable: false, // Explicitly set to false if the table is already created  }),});const model = new ChatOpenAI();const chain = new ConversationChain({ llm: model, memory });const res1 = await chain.invoke({ input: "Hi! I'm Jim." });console.log({ res1 });/*{  res1: {    text: "Hello Jim! It's nice to meet you. My name is AI. How may I assist you today?"  }}*/const res2 = await chain.invoke({ input: "What did I just say my name was?" });console.log({ res2 });/*{  res1: {    text: "You said your name was Jim."  }}*/

#### API Reference:

*   [BufferMemory](https://api.js.langchain.com/classes/langchain_memory.BufferMemory.html) from `langchain/memory`
*   [ChatOpenAI](https://api.js.langchain.com/classes/langchain_openai.ChatOpenAI.html) from `@langchain/openai`
*   [ConversationChain](https://api.js.langchain.com/classes/langchain_chains.ConversationChain.html) from `langchain/chains`
*   [XataChatMessageHistory](https://api.js.langchain.com/classes/langchain_community_stores_message_xata.XataChatMessageHistory.html) from `@langchain/community/stores/message/xata`

* * *

#### Help us out by providing feedback on this documentation page:

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Upstash Redis-Backed Chat Memory

](/v0.1/docs/integrations/chat_memory/upstash_redis/)[

Next

Zep Memory

](/v0.1/docs/integrations/chat_memory/zep_memory/)

*   [Setup](#setup)
    *   [Install the Xata CLI](#install-the-xata-cli)
    *   [Create a database to be used as a vector store](#create-a-database-to-be-used-as-a-vector-store)
    *   [Initialize the project](#initialize-the-project)
*   [Usage](#usage)
    *   [With pre-created table](#with-pre-created-table)

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