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DynamoDB-Backed Chat Memory
===========================

For longer-term persistence across chat sessions, you can swap out the default in-memory `chatHistory` that backs chat memory classes like `BufferMemory` for a DynamoDB instance.

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

First, install the AWS DynamoDB client in your project:

*   npm
*   Yarn
*   pnpm

    npm install @aws-sdk/client-dynamodb

    yarn add @aws-sdk/client-dynamodb

    pnpm add @aws-sdk/client-dynamodb

tip

See [this section for general instructions on installing integration packages](/v0.2/docs/how_to/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

Next, sign into your AWS account and create a DynamoDB table. Name the table `langchain`, and name your partition key `id`. Make sure your partition key is a string. You can leave sort key and the other settings alone.

You'll also need to retrieve an AWS access key and secret key for a role or user that has access to the table and add them to your environment variables.

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

    import { BufferMemory } from "langchain/memory/index";import { DynamoDBChatMessageHistory } from "@langchain/community/stores/message/dynamodb";import { ChatOpenAI } from "@langchain/openai";import { ConversationChain } from "langchain/chains";const memory = new BufferMemory({  chatHistory: new DynamoDBChatMessageHistory({    tableName: "langchain",    partitionKey: "id",    sessionId: new Date().toISOString(), // Or some other unique identifier for the conversation    config: {      region: "us-east-2",      credentials: {        accessKeyId: "<your AWS access key id>",        secretAccessKey: "<your AWS secret access key>",      },    },  }),});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 from `langchain/memory/index`
*   [DynamoDBChatMessageHistory](https://v02.api.js.langchain.com/classes/langchain_community_stores_message_dynamodb.DynamoDBChatMessageHistory.html) from `@langchain/community/stores/message/dynamodb`
*   [ChatOpenAI](https://v02.api.js.langchain.com/classes/langchain_openai.ChatOpenAI.html) from `@langchain/openai`
*   [ConversationChain](https://v02.api.js.langchain.com/classes/langchain_chains.ConversationChain.html) from `langchain/chains`

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