---
title: HNSWLib
---

[HNSWLib](https://github.com/nmslib/hnswlib) is an high performance in-memory vectorstore.
It is great for testing since you do not need access to the file system or a cloud service.

## Install HNSWLib addon

```bash
npm install @llm-tools/embedjs-hnswlib
```

## Usage
<CodeGroup>
```ts Example
import { RAGApplicationBuilder } from '@llm-tools/embedjs';
import { OpenAiEmbeddings } from '@llm-tools/embedjs-openai';
import { HNSWDb } from '@llm-tools/embedjs-hnswlib';
import { WebLoader } from '@llm-tools/embedjs-loader-web';

// set OPENAI_API_KEY in your env
process.env.OPENAI_API_KEY = "sk-xxx";

const app = await new RAGApplicationBuilder()
.setEmbeddingModel(new OpenAiEmbeddings())
.setModel(SIMPLE_MODELS.OPENAI_GPT4_O)
.setVectorDatabase(new HNSWDb())
.build();

//add data source and start query it
await app.addLoader(new WebLoader({ urlOrContent: 'https://www.forbes.com/profile/elon-musk' }));
await app.query('Tell me about Elon Musk');
```
</CodeGroup>

<Snippet file="missing-vector-db-tip.mdx" />
