The Web AI Toolkit simplifies the integration of AI features, such as OCR, speech-to-text, text summarization and more into your application. It ensures data privacy and offline capability by running all AI workloads locally, leveraging WebNN when available, with a fallback to WebGPU.
To install the Web AI Toolkit, run:
npm install web-ai-toolkit
Note: Supported hardware is listed in priority of device selection. For example, for transcribing an audio file, the code will attempt to choose the GPU first and then the CPU otherwise.
Function Name | Parameter | Type | Default Value | Supported Hardware |
---|---|---|---|---|
transcribeAudioFile | audioFile | Blob | - | GPU / CPU |
model | string | "Xenova/whisper-tiny" | ||
timestamps | boolean | false | ||
language | string | "en-US" | ||
textToSpeech | text | string | - | GPU / CPU |
model | string | "Xenova/mms-tts-eng" | ||
summarize | text | string | - | GPU / CPU |
model | string | "Xenova/distilbart-cnn-6-6" | ||
ocr | image | Blob | - | GPU / CPU |
model | string | "Xenova/trocr-small-printed" | ||
classifyImage | image | Blob | - | NPU / GPU / CPU |
model | string | "Xenova/resnet-50" |
The Web AI Toolkit utilizes the transformers.js project to run AI workloads. All AI processing is performed locally on the device, ensuring data privacy and reducing latency. AI workloads are run using the WebNN API when available, otherwise falling back to the WebGPU API, or even to the CPU with WebAssembly. Choosing the correct hardware to target is handled by the library.
Here are examples of how to use each function:
import { transcribeAudioFile } from 'web-ai-toolkit';
const audioFile = ...; // Your audio file Blob
const transcription = await transcribeAudioFile(audioFile, "Xenova/whisper-tiny", true, "en-US");
console.log(transcription);
import { textToSpeech } from 'web-ai-toolkit';
const text = "Hello, world!";
const audio = await textToSpeech(text);
console.log(audio);
import { summarize } from 'web-ai-toolkit';
const text = "Long text to be summarized...";
const summary = await summarize(text);
console.log(summary);
import { ocr } from 'web-ai-toolkit';
const image = ...; // Your image Blob
const text = await ocr(image);
console.log(text);
import { classifyImage } from 'web-ai-toolkit';
const image = ...; // Your image Blob
const text = await classifyImage(image);
console.log(text);
We welcome contributions to the Web AI Toolkit. Please fork the repository and submit a pull request with your changes. For major changes, please open an issue first to discuss what you would like to change.
The Web AI Toolkit is licensed under the MIT License. See the LICENSE file for more details.
For questions or support, please open an issue here on GitHub
Thank you for using the Web AI Toolkit! We hope it makes integrating AI into your applications easier and more efficient.