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.

import { OpenAI } from "langchain/llms/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?'}