Documentation

SvelteML

Work in Progress

Hi! Svelte JS tries to remove some of the complexity of large reactive JS apps to the compiler, producing tree-shaken small app footprints in the meantime, all without a Virtual DOM.

This library is combined with Tensorflow JS to add Machine learning features to any Svelte app. The aim is make it as simple as possible to integrate ML into your app.

Text Toxicity

Ideal for things like customer reviews or somewhere you need to review what user writes before it gets sent. A pre-check before your server has to do the work.

 <TextToxicity  {samples} verbose={true} on:prediction={yourHandlerFunction}  
	 let:modelsLoaded
	 let:predictions
	 let:labels>
          <!-- Your reactive code here -->
 </TextToxicity>

* samples is required

Parameter	Type	Description
samples	array of objects	The sentences to evaluate are in the 'text' field. E.g. [{text: 'text to check'}]
on:prediction	event	triggered when a prediction comes in from Tensorflow.
modelsLoaded	boolean	tells you when the TF models etc are downloaded and ready to use. In the meantime, show a loading spinner in your reactive code
predictions	array	tells your reactive code when the predictions for the given samples are ready.
labels	array	is a list of prediction labels that appear in the predictions array response. Available after models are loaded
verbose	boolean	enabled console logging for debugging purposes.

on:prediction: Allows processing in the caller component's <script> not in the markup, which is mostly useful for rendering state.