mememo

MeMemo

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

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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

mememo-demo.mp4

Getting Started

Installation

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

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:

// 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:

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

Install the dependencies:

npm install

Use Vitest for unit testing:

npm run test

Developing the RAG Playground Examples

Clone or download this repository:

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

Navigate to the example folder:

cd ./examples/rag-playground

Install the dependencies:

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 published at SIGIR'24.

@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.

Contact

If you have any questions, feel free to open an issue or contact Jay Wang.