A vector store stores embedded data and performs similarity search.

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Install dependencies

npm i @langchain/openai

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Add environment variables

OPENAI_API_KEY=your-api-key

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Instantiate the model

import { OpenAIEmbeddings } from "@langchain/openai";

const embeddings = new OpenAIEmbeddings({
  model: "text-embedding-3-large"
});

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Install dependencies

npm i langchain

import { MemoryVectorStore } from "langchain/vectorstores/memory";

const vectorStore = new MemoryVectorStore(embeddings);
LangChain.js integrates with a variety of vector stores. You can check out a full list below:

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All vector stores

AnalyticDB

Astra DB

Azion EdgeSQL

Azure AI Search

Azure Cosmos DB for MongoDB vCore

Azure Cosmos DB for NoSQL

Cassandra

Chroma

ClickHouse

CloseVector

Cloudflare Vectorize

Convex

Couchbase

Elasticsearch

Faiss

Google Cloud SQL for PostgreSQL

Google Vertex AI Matching Engine

SAP HANA Cloud Vector Engine

HNSWLib

LanceDB

libSQL

MariaDB

In-memory

Milvus

Momento Vector Index (MVI)

MongoDB Atlas

MyScale

Neo4j Vector Index

Neon Postgres

OpenSearch

PGVector

Pinecone

Prisma

Qdrant

Redis

Rockset

SingleStore

Supabase

Tigris

Turbopuffer

TypeORM

Typesense

Upstash Vector

USearch

Vectara

Vercel Postgres

Voy

Weaviate

Xata

Zep Open Source

Zep Cloud