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How to Build a Fully Offline AI Finance Assistant Using LiteRT and Gemma 4

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A developer guide published on DEV Community outlines how to build a privacy-first personal finance assistant that runs entirely within a web browser without any internet connection. The application uses Google's LiteRT LM Web API and the Gemma 4 E2B small language model, caching roughly 2GB of model weights in the browser's Cache Storage for offline use. Transaction data is stored locally via IndexedDB, ensuring sensitive financial information never leaves the user's device. To reduce AI hallucinations on numerical data, the system pre-computes expense totals by day, month, and category before passing them to the model as verified ground truth. The tech stack includes Angular 22, TailwindCSS, and Node 24, with conversation memory managed carefully to stay within on-device token limits.

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