https://github.com/poloclub/mememo

A JavaScript library that brings vector search and RAG to your browser!
https://github.com/poloclub/mememo

browser document-search gen-ai image-search llm rag vector-database vector-search

Last synced: 3 months ago
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A JavaScript library that brings vector search and RAG to your browser!

• Host: GitHub
• URL: https://github.com/poloclub/mememo
• Owner: poloclub
• License: mit
• Created: 2024-01-28T20:21:53.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2024-08-15T19:13:37.000Z (5 months ago)
• Last Synced: 2024-08-31T08:24:31.869Z (5 months ago)
• Topics: browser, document-search, gen-ai, image-search, llm, rag, vector-database, vector-search
• Language: TypeScript
• Homepage: https://poloclub.github.io/mememo/
• Size: 66.7 MB
• Stars: 47
• Watchers: 2
• Forks: 6
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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• awesome - poloclub/mememo - A JavaScript library that brings vector search and RAG to your browser! (TypeScript)

README

        
# MeMemo 

[![build](https://github.com/poloclub/mememo/actions/workflows/build.yml/badge.svg)](https://github.com/poloclub/mememo/actions/workflows/build.yml)

[![npm](https://img.shields.io/npm/v/mememo?color=orange)](https://www.npmjs.com/package/mememo)

[![license](https://img.shields.io/badge/License-MIT-blue)](https://github.com/poloclub/mememo/blob/main/LICENSE)

[![arxiv badge](https://img.shields.io/badge/arXiv-2407.01972-red)](https://arxiv.org/abs/2407.01972)

[![DOI:10.1145/3543873.3587362](https://img.shields.io/badge/DOI-10.1145/3626772.3657662-blue)](https://doi.org/10.1145/3626772.3657662)

A JavaScript library that brings vector search and RAG to your browser!

  

    

  

  

  

     🤖 ML Paper Reviewer

     🌠 Prompt Enhancer

     🌱 Responsible AI Assistant

  

## What is MeMemo?

MeMemo is a JavaScript library that adapts the state-of-the-art approximate nearest neighbor search technique HNSW to browser environments.

Developed with modern and native Web technologies, such as IndexedDB and Web Workers, our toolkit leverages client-side hardware capabilities to enable researchers and developers to efficiently search through millions of high-dimensional vectors in browsers.

MeMemo enables exciting new design and research opportunities, such as private and personalized content creation and interactive prototyping, as demonstrated in our example application RAG Playground.✨

### Features

## Getting Started

### Installation

MeMemo supports both browser and Node.js environments. To install MeMemo, you can use `npm`:

```bash

npm install mememo

```

### Vector Search and Storage in Browsers

Then, you can create a vector index and do an approximate nearest neighbor search through two functions:

```typescript

// Import the HNSW class from the MeMemo module

import { HNSW } from 'mememo';

// Creating a new index

const index = new HNSW({ distanceFunction: 'cosine' });

// Inserting elements into our index in batches

let keys: string[];

let values: number[][];

await index.bulkInsert(keys, values);

// Find k-nearest neighbors

let query: number[];

const { keys, distances } = await index.query(query, k);

```

## Developing MeMemo

Clone or download this repository:

```bash

git clone [email protected]:poloclub/mememo.git

```

Install the dependencies:

```bash

npm install

```

Use Vitest for unit testing:

```

npm run test

```

## Developing the RAG Playground Examples

Clone or download this repository:

```bash

git clone [email protected]:poloclub/mememo.git

```

Navigate to the example folder:

```bash

cd ./examples/rag-playground

```

Install the dependencies:

```bash

npm install

```

Then run Loan Explainer:

```

npm run dev

```

Navigate to localhost:3000. You should see three Explainers running in your browser :)

## Credits

MeMemo is created by Jay Wang and Polo Chau.

## Citation

To learn more about MeMemo, check out our [research paper](https://arxiv.org/abs/2407.01972) published at SIGIR'24.

```bibtex

@inproceedings{wangMeMemoOndeviceRetrieval2024,

  title = {{{MeMemo}}: {{On-device Retrieval Augmentation}} for {{Private}} and {{Personalized Text Generation}}},

  booktitle = {Proceedings of the 47th {{International ACM SIGIR Conference}} on {{Research}} and {{Development}} in {{Information Retrieval}}},

  author = {Wang, Zijie J. and Chau, Duen Horng},

  year = {2024},

  urldate = {2024-06-26},

  langid = {english}

}

```

## License

The software is available under the [MIT License](https://github.com/poloclub/mememo/blob/main/LICENSE).

## Contact

If you have any questions, feel free to [open an issue](https://github.com/poloclub/mememo/issues/new) or contact [Jay Wang](https://zijie.wang).