Conversation buffer window memory

ConversationBufferWindowMemory keeps a list of the interactions of the conversation over time. It only uses the last K interactions. This can be useful for keeping a sliding window of the most recent interactions, so the buffer does not get too large

Let's first explore the basic functionality of this type of memory.

tip

See this section for general instructions on installing integration packages.

npm

npm install @langchain/openai

Yarn

yarn add @langchain/openai

pnpm

pnpm add @langchain/openai

import { OpenAI } from "@langchain/openai";
import { BufferWindowMemory } from "langchain/memory";
import { ConversationChain } from "langchain/chains";

const model = new OpenAI({});
const memory = new BufferWindowMemory({ k: 1 });
const chain = new ConversationChain({ llm: model, memory: memory });
const res1 = await chain.call({ 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 chain.call({ 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?'}