Skip to main content

In Memory Store

This example demonstrates how to setup chat history storage using the InMemoryStore KV store integration.


The InMemoryStore allows for a generic type to be assigned to the values in the store. We'll assign type BaseMessage as the type of our values, keeping with the theme of a chat history store.

import { InMemoryStore } from "@langchain/core/stores";
import { AIMessage, BaseMessage, HumanMessage } from "@langchain/core/messages";

// Instantiate the store using the `fromPath` method.
const store = new InMemoryStore<BaseMessage>();
* Here you would define your LLM and chat chain, call
* the LLM and eventually get a list of messages.
* For this example, we'll assume we already have a list.
const messages = Array.from({ length: 5 }).map((_, index) => {
if (index % 2 === 0) {
return new AIMessage("ai stuff...");
return new HumanMessage("human stuff...");
// Set your messages in the store
// The key will be prefixed with `message:id:` and end
// with the index.
await store.mset(, index) => [`message:id:${index}`, message])
// Now you can get your messages from the store
const retrievedMessages = await store.mget(["message:id:0", "message:id:1"]);
console.log( => v));
AIMessage {
lc_kwargs: { content: 'ai stuff...', additional_kwargs: {} },
content: 'ai stuff...',
HumanMessage {
lc_kwargs: { content: 'human stuff...', additional_kwargs: {} },
content: 'human stuff...',
// Or, if you want to get back all the keys you can call
// the `yieldKeys` method.
// Optionally, you can pass a key prefix to only get back
// keys which match that prefix.
const yieldedKeys = [];
for await (const key of store.yieldKeys("message:id:")) {
// The keys are not encoded, so no decoding is necessary
// Finally, let's delete the keys from the store
await store.mdelete(yieldedKeys);

API Reference:

Was this page helpful?

You can also leave detailed feedback on GitHub.