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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.

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Web AI Toolkit

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.

Installation

To install the Web AI Toolkit, run:

npm install web-ai-toolkit

Available Functions

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"

Technical Details

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.

Usage

Here are examples of how to use each function:

Transcribe Audio File

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);

Text to Speech

import { textToSpeech } from 'web-ai-toolkit';

const text = "Hello, world!";
const audio = await textToSpeech(text);
console.log(audio);

Summarize Text

import { summarize } from 'web-ai-toolkit';

const text = "Long text to be summarized...";
const summary = await summarize(text);
console.log(summary);

Optical Character Recognition (OCR)

import { ocr } from 'web-ai-toolkit';

const image = ...; // Your image Blob
const text = await ocr(image);
console.log(text);

Image Classification

import { classifyImage } from 'web-ai-toolkit';

const image = ...; // Your image Blob
const text = await classifyImage(image);
console.log(text);

Contribution

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.

License

The Web AI Toolkit is licensed under the MIT License. See the LICENSE file for more details.

Contact

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.

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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.

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