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*   [](/v0.1/)
*   [Components](/v0.1/docs/integrations/components/)
*   [Chat Memory](/v0.1/docs/integrations/chat_memory/)
*   PlanetScale Chat Memory

PlanetScale Chat Memory
=======================

Because PlanetScale works via a REST API, 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 other Serverless environments.

For longer-term persistence across chat sessions, you can swap out the default in-memory `chatHistory` that backs chat memory classes like `BufferMemory` for an PlanetScale [Database](https://planetscale.com/) instance.

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

You will need to install [@planetscale/database](https://github.com/planetscale/database-js) in your project:

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 @planetscale/database @langchain/community

    yarn add @langchain/openai @planetscale/database @langchain/community

    pnpm add @langchain/openai @planetscale/database @langchain/community

You will also need an PlanetScale Account and a database to connect to. See instructions on [PlanetScale Docs](https://planetscale.com/docs) on how to create a HTTP client.

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

Each chat history session stored in PlanetScale database must have a unique id. The `config` parameter is passed directly into the `new Client()` constructor of [@planetscale/database](https://planetscale.com/docs/tutorials/planetscale-serverless-driver), and takes all the same arguments.

    import { BufferMemory } from "langchain/memory";import { PlanetScaleChatMessageHistory } from "@langchain/community/stores/message/planetscale";import { ChatOpenAI } from "@langchain/openai";import { ConversationChain } from "langchain/chains";const memory = new BufferMemory({  chatHistory: new PlanetScaleChatMessageHistory({    tableName: "stored_message",    sessionId: "lc-example",    config: {      url: "ADD_YOURS_HERE", // Override with your own database instance's URL    },  }),});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`
*   [PlanetScaleChatMessageHistory](https://api.js.langchain.com/classes/langchain_community_stores_message_planetscale.PlanetScaleChatMessageHistory.html) from `@langchain/community/stores/message/planetscale`
*   [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`

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

You can also directly pass in a previously created [@planetscale/database](https://planetscale.com/docs/tutorials/planetscale-serverless-driver) client instance:

    import { BufferMemory } from "langchain/memory";import { PlanetScaleChatMessageHistory } from "@langchain/community/stores/message/planetscale";import { ChatOpenAI } from "@langchain/openai";import { ConversationChain } from "langchain/chains";import { Client } from "@planetscale/database";// Create your own Planetscale database clientconst client = new Client({  url: "ADD_YOURS_HERE", // Override with your own database instance's URL});const memory = new BufferMemory({  chatHistory: new PlanetScaleChatMessageHistory({    tableName: "stored_message",    sessionId: "lc-example",    client, // You can reuse your existing database client  }),});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`
*   [PlanetScaleChatMessageHistory](https://api.js.langchain.com/classes/langchain_community_stores_message_planetscale.PlanetScaleChatMessageHistory.html) from `@langchain/community/stores/message/planetscale`
*   [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`

* * *

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