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*   [Get started](/v0.1/docs/get_started/)
    
    *   [Introduction](/v0.1/docs/get_started/introduction/)
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    *   [Get started](/v0.1/docs/expression_language/get_started/)
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*   [Modules](/v0.1/docs/modules/)
    
    *   [Model I/O](/v0.1/docs/modules/model_io/)
        
    *   [Retrieval](/v0.1/docs/modules/data_connection/)
        
    *   [Chains](/v0.1/docs/modules/chains/)
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    *   [More](/v0.1/docs/modules/memory/)
        
        *   [Memory](/v0.1/docs/modules/memory/)
            
            *   [\[Beta\] Memory](/v0.1/docs/modules/memory/)
            *   [Chat Message History](/v0.1/docs/modules/memory/chat_messages/)
                
            *   [Memory types](/v0.1/docs/modules/memory/types/)
                
                *   [Conversation buffer memory](/v0.1/docs/modules/memory/types/buffer/)
                *   [Using Buffer Memory with Chat Models](/v0.1/docs/modules/memory/types/buffer_memory_chat/)
                *   [Conversation buffer window memory](/v0.1/docs/modules/memory/types/buffer_window/)
                *   [Entity memory](/v0.1/docs/modules/memory/types/entity_summary_memory/)
                *   [Combined memory](/v0.1/docs/modules/memory/types/multiple_memory/)
                *   [Conversation summary memory](/v0.1/docs/modules/memory/types/summary/)
                *   [Conversation summary buffer memory](/v0.1/docs/modules/memory/types/summary_buffer/)
                *   [Vector store-backed memory](/v0.1/docs/modules/memory/types/vectorstore_retriever_memory/)
        *   [Callbacks](/v0.1/docs/modules/callbacks/)
            
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*   [Memory](/v0.1/docs/modules/memory/)
*   [Memory types](/v0.1/docs/modules/memory/types/)
*   Combined memory

Combined memory
===============

It is also possible to use multiple memory classes in the same chain. To combine multiple memory classes, we can initialize the `CombinedMemory` class, and then use that.

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

    yarn add @langchain/openai

    pnpm add @langchain/openai

    import { ChatOpenAI } from "@langchain/openai";import {  BufferMemory,  CombinedMemory,  ConversationSummaryMemory,} from "langchain/memory";import { ConversationChain } from "langchain/chains";import { PromptTemplate } from "@langchain/core/prompts";// buffer memoryconst bufferMemory = new BufferMemory({  memoryKey: "chat_history_lines",  inputKey: "input",});// summary memoryconst summaryMemory = new ConversationSummaryMemory({  llm: new ChatOpenAI({ model: "gpt-3.5-turbo", temperature: 0 }),  inputKey: "input",  memoryKey: "conversation_summary",});//const memory = new CombinedMemory({  memories: [bufferMemory, summaryMemory],});const _DEFAULT_TEMPLATE = `The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.Summary of conversation:{conversation_summary}Current conversation:{chat_history_lines}Human: {input}AI:`;const PROMPT = new PromptTemplate({  inputVariables: ["input", "conversation_summary", "chat_history_lines"],  template: _DEFAULT_TEMPLATE,});const model = new ChatOpenAI({ temperature: 0.9, verbose: true });const chain = new ConversationChain({ llm: model, memory, prompt: PROMPT });const res1 = await chain.invoke({ input: "Hi! I'm Jim." });console.log({ res1 });/*  {    res1: {      response: "Hello Jim! It's nice to meet you. How can I assist you today?"    }  }*/const res2 = await chain.invoke({ input: "Can you tell me a joke?" });console.log({ res2 });/*  {    res2: {      response: 'Why did the scarecrow win an award? Because he was outstanding in his field!'    }  }*/const res3 = await chain.invoke({  input: "What's my name and what joke did you just tell?",});console.log({ res3 });/*  {    res3: {      response: 'Your name is Jim. The joke I just told was about a scarecrow winning an award because he was outstanding in his field.'    }  }*/

#### API Reference:

*   [ChatOpenAI](https://api.js.langchain.com/classes/langchain_openai.ChatOpenAI.html) from `@langchain/openai`
*   [BufferMemory](https://api.js.langchain.com/classes/langchain_memory.BufferMemory.html) from `langchain/memory`
*   [CombinedMemory](https://api.js.langchain.com/classes/langchain_memory.CombinedMemory.html) from `langchain/memory`
*   [ConversationSummaryMemory](https://api.js.langchain.com/classes/langchain_memory.ConversationSummaryMemory.html) from `langchain/memory`
*   [ConversationChain](https://api.js.langchain.com/classes/langchain_chains.ConversationChain.html) from `langchain/chains`
*   [PromptTemplate](https://api.js.langchain.com/classes/langchain_core_prompts.PromptTemplate.html) from `@langchain/core/prompts`

* * *

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

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