Introduction to Syft.js

Of course, PySyft has the ability to run in its own environment. But if you would like to train federated learning models in the browser, you must resort to using some ML framework like TensorFlow.js.
Syft.js is a microlibrary built on top of TensorFlow.js, allowing for a socket connection with any running PySyft instance.
PySyft acts as the parent node, instructing child nodes (Syft.js instances running in a website on users' browsers) of what tensors to add to a list, remove from a list, and operate against.


If you're using a package manage like NPM:
npm install --save syft.js
Or if Yarn is your cup of tea:
yarn add syft.js
When using a package manager, TensorFlow.js will be automatically installed.
If you're not using a package manager, you can also include Syft.js within a <script> tag:
<script src=""></script>
<script src="[email protected]/lib/index.js"></script>
For integration into your client-side application, please check out our guide.
For further API documentation, please check that out here.

Local Development

  1. 1.
    Clone or fork
  2. 2.
    Run npm install or yarn install
  3. 3.
    Run npm start or yarn start


We're accepting PR's for testing at the moment to improve our overall code coverage. In terms of core functionality, we're considering the current version of Syft.js feature complete until a further roadmap is designated.
Last modified 4yr ago