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Conversation buffer memory

This notebook shows how to use BufferMemory. This memory allows for storing of messages, then later formats the messages into a prompt input variable.

We can first extract it as a string.

npm install @langchain/openai
import { OpenAI } from "@langchain/openai";
import { BufferMemory } from "langchain/memory";
import { ConversationChain } from "langchain/chains";

const model = new OpenAI({});
const memory = new BufferMemory();
const chain = new ConversationChain({ llm: model, memory: memory });
const res1 = await{ input: "Hi! I'm Jim." });
console.log({ res1 });
{response: " Hi Jim! It's nice to meet you. My name is AI. What would you like to talk about?"}
const res2 = await{ input: "What's my name?" });
console.log({ res2 });
{response: ' You said your name is Jim. Is there anything else you would like to talk about?'}

You can also load messages into a BufferMemory instance by creating and passing in a ChatHistory object. This lets you easily pick up state from past conversations:

import { BufferMemory, ChatMessageHistory } from "langchain/memory";
import { HumanMessage, AIMessage } from "langchain/schema";

const pastMessages = [
new HumanMessage("My name's Jonas"),
new AIMessage("Nice to meet you, Jonas!"),

const memory = new BufferMemory({
chatHistory: new ChatMessageHistory(pastMessages),

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