A simple Flutter application that demonstrates the power of on-device, offline, multimodal AI using the flutter_gemma package. This app can translate a Japanese menu from an image, even without an internet connection.

This project was built as a proof-of-concept for my Medium article, which details the entire journey and implementation. Using Gemma for Flutter apps: First steps with on-device AI in Flutter using flutter_gemma package

• Offline First: The entire AI interaction happens on-device, with no internet connection required.
• Multimodal Input: Understands both images and text prompts in a single query.
• Powered by Gemma 3N: Utilizes Google's lightweight and powerful Gemma 3 Nano model.
• Simple, Single-Screen UI: A minimal, easy-to-understand chat interface.

To run this project locally, follow these steps:

Add Your Hugging Face Token: You will need a Hugging Face access token to download the Gemma model. Open lib/data/gemma_downloader_datasource.dart and replace the placeholder with your own token:

const String accessToken = 'YOUR_HUGGING_FACE_TOKEN_HERE';

Flutter: The UI toolkit for building the application.

• flutter_gemma: The core package for running Gemma models on-device.
• image_picker: For selecting images from the camera or gallery.

Any contributions is welcomed! 🙏