Google AI Studio Adds Import from GitHub to Build a Deployable App

Google AI Studio Adds Import from GitHub to Build a Deployable App">

Google AI Studio is rolling out an ‘import from GitHub’ feature inside its Build mode. It takes a repo and transforms it into a runtime-compatible format. You can then keep iterating on it, deploy it, and more. The update was shared by the Google AI Studio account and by Logan Kilpatrick, who leads the product.

bringing your code from @github into ai studio build is as easy as clicking 'import from github' pic.twitter.com/lIyZ1lnpQQ

Today we are rolling out "import from GitHub" in @GoogleAIStudio Build!! We will automagically take the repo and transform it into a format that is compatible with our runtime and then let you keep iterating on it in AI Studio, deploy it, and more. pic.twitter.com/F63MjsJQjf

Build mode is Google AI Studio’s ‘vibe coding’ surface. You describe an app in a prompt. Gemini generates a full-stack app with a live preview. You then refine it through chat or annotation mode.

The new feature adds a starting point. Instead of a blank prompt, you point Build at a GitHub repository. AI Studio then transforms the repo into a format compatible with its runtime.

Google has not published the internal steps. In plain terms, the importer reads the repo, fits it to the runtime, then opens it in Build. The interactive walkthrough embedded below is a concept simulation, not the real backend.

One documented behavior matters when moving code in. For apps that use the Gemini API, AI Studio configures your GEMINI_API_KEY as a server-side secret. Keys are never included in client-side code.

So plan for the server-side pattern if your repo calls the Gemini API from the browser. The example below shows both sides for contrast.

The endpoint and header above match the Gemini REST API. The point is placement: keep the key on the server.

The table shows the shape of the change. Import adds the inbound path that was missing.

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