Build Firebase AI Logic Application with Antigravity CLI

A developer used Antigravity CLI to build an image analysis demo with Angular, Firebase Hybrid & On-device Inference Web SDK, and Gemini models. The demo analyzes uploaded images to generate alternative text, tags, recommendations, and CSS tips. On Chrome 148+, it uses the on-device Gemini Nano model with zero token usage; on other browsers, it falls back to Cloud AI (Gemini 3.5 Flash).

Note: Google Cloud credits are provided for this project. In this blog post, I want to demonstrate how I use Antigravity CLI to build an image analysis demo using Angular, Firebase Hybrid & On-device Inference Web SDK, and Gemini models. Users upload an image and use a Gemini model to analyze it to generate a few alternative texts, tags, recommendations, and CSS tips to enhance the image quality. When the demo is running on Chrome 148+, the Hybrid & On-device SDK leverages the Prompt API of the on-device Gemini Nano model to perform the image-to-text tasks, and the token usage is 0. When other browsers such as Safari or Firefox executes the same tasks on the demo, the SDK falls back to Cloud AI Gemini 3.5 Flash model , and the token usage is greater than 0. Next, I will describe how I installed the skills in my Angular project, and registered the Stitch MCP server in the Antigravity CLI to develop the infrastructure, services, and UI design of my demo. I installed grill-with-docs , angular , and firebase skills in my project for the following reasons: