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You can easily add AI capabilities to your web applications without the need for complex server-side infrastructure or third-party APIs.\n\nFeatures:\n\n- Easy to use. Create a model with one line of code, get the result with another one.\n- Powered by [ONNX runtime](https://onnxruntime.ai/). Web AI runs the models using ONNX Runtime, which has rich support for of all kinds of operators. It means that any model will work just fine.\n- Built-in caching. When using in the browser, Web AI stores the downloaded models in IndexedDB using [localforage](https://github.com/localForage/localForage). You can configure the size of the cache dynamically.\n- Web worker support. All heavy operations - model creation and inference - are offloaded to a separate thread so the UI does not freeze.\n\nMore information about how to use the library can be found in the [wiki](https://github.com/visheratin/web-ai/wiki).\n\n## How to install\n\nThe library can be installed via `npm`.\n\nBrowser version:\n\n```bash\nnpm install @visheratin/web-ai\n```\n\nNode.js version:\n\n```bash\nnpm install @visheratin/web-ai-node\n```\n\n## Status\n\nThe library is under active development. If something does not work correctly, please file an issue on GitHub. Contributions are very welcome.\n\n## Sponsors\n\n- Continuing work on this project is sponsored by [Reflect](https://reflect.app/home) - awesome app for taking notes.\n- Thanks to AlgoveraAI for the grant under their AI project financing [program](https://docs.algovera.ai/docs/Handbook/Grants/Introduction).\n","readmeFilename":"README.md"}