If you're new to the Gemini API, the [Gemini Developer API](https://developer.android.com/ai/gemini/developer-api.md.txt) is the recommended [API provider](https://developer.android.com/ai/gemini.md.txt#api-providers) for Android Developers. However, if you have specific [data location requirements](https://firebase.google.com/docs/ai-logic/locations?api=vertex) or you're already embedded in the Google Cloud ecosystem, then you can use the Agent Platform Gemini API (formerly Vertex AI) with Firebase AI Logic to access Gemini Pro and Flash models. ![Illustration that shows an Android app using the Firebase Android SDK to send requests to the Firebase backend in the cloud. Requests are routed to the Agent Platform Gemini API, which can leverage both Gemini Pro and Flash models.](https://developer.android.com/static/ai/assets/images/firebase-ai-logic-agent-platform.svg) **Figure 1.** Firebase AI Logic integration architecture to access the Agent Platform Gemini API. ## Getting started Before you interact with the Agent Platform Gemini API directly from your app, you can experiment with prompts in [Agent Studio](https://docs.cloud.google.com/gemini-enterprise-agent-platform/agent-studio/quickstart). ### Set up a Firebase project and connect your app to Firebase Once you're ready to call the API from your app, follow the instructions in "Step 1" of the [Firebase AI Logic getting started guide](https://firebase.google.com/docs/ai-logic/get-started?api=vertex#set-up-firebase) to set up Firebase and enable required APIs and services. ### Add the Gradle dependencies Add the following Gradle dependencies to your app module: ### Kotlin ```groovy dependencies { // ... other androidx dependencies // Import the BoM for the Firebase platform implementation(platform("com.google.firebase:firebase-bom:35.1.0")) // Add the dependencies for the Firebase AI Logic and App Check libraries // When using the BoM, you don't specify versions in Firebase library dependencies implementation("com.google.firebase:firebase-ai") implementation("com.google.firebase:firebase-appcheck-debug") } ``` ### Java ```groovy dependencies { // Import the BoM for the Firebase platform implementation(platform("com.google.firebase:firebase-bom:35.1.0")) // Add the dependencies for the Firebase AI Logic and App Check libraries // When using the BoM, you don't specify versions in Firebase library dependencies implementation("com.google.firebase:firebase-ai") implementation("com.google.firebase:firebase-appcheck-debug") // Required for one-shot operations (to use `ListenableFuture` from Guava Android) implementation("com.google.guava:guava:31.0.1-android") // Required for streaming operations (to use `Publisher` from Reactive Streams) implementation("org.reactivestreams:reactive-streams:1.0.4") } ``` ### Configure the App Check debug provider for local development Starting early July 2026, as part of the guided setup workflow for AI Logic in the Firebase console, Firebase App Check is automatically enforced to protect the Gemini API. For local development, you need to configure the App Check *debug provider* to bypass attestation while still maintaining the enforcement of App Check. 1. In your debug build, configure App Check to use the debug provider factory: ### Kotlin ```kotlin Firebase.initialize(context = this) Firebase.appCheck.installAppCheckProviderFactory( DebugAppCheckProviderFactory.getInstance(), ) ``` ### Java ```java FirebaseApp.initializeApp(/*context=*/ this); FirebaseAppCheck firebaseAppCheck = FirebaseAppCheck.getInstance(); firebaseAppCheck.installAppCheckProviderFactory( DebugAppCheckProviderFactory.getInstance()); ``` 2. Obtain your debug token: 1. Run your app in the emulator or on your test device. 2. Look for the App Check debug token in your logs. For example: D DebugAppCheckProvider: Enter this debug secret into the allow list in the Firebase Console for your project: 123a4567-b89c-12d3-e456-789012345678 3. Copy the token (for example, `123a4567-b89c-12d3-e456-789012345678`). 3. Register your debug token with App Check: 1. In the Firebase console, go to the **Security** \> **App Check** \> [**Apps** tab](https://console.firebase.google.com/project/_/appcheck/apps/?useAutoProject=true). 2. Find your app, click the overflow menu (), and then select **Manage debug tokens**. 3. Follow the on-screen instructions to register your debug token. For details about the debug provider (including how to get a new debug token), check out the [official App Check docs](https://firebase.google.com/docs/app-check/android/debug-provider). > [!CAUTION] > **Here are some critical points about the > App Check debug provider:** > > - **Keep your debug token and debug build private.** Don't commit your debug token to a public repository, and don't ship your debug token or debug build in production builds of your app. > - **Register your app with a production attestation provider before > releasing to end users.** You'll need to [register your app with a production App Check attestation provider](https://firebase.google.com/docs/ai-logic/app-check) (for example, Play Integrity) so that your end-users can use your feature with App Check enforced. ### Initialize the generative model Start by instantiating a `GenerativeModel` and specifying the model name: ### Kotlin ```kotlin val model = Firebase.ai(backend = GenerativeBackend.agentPlatform()) .generativeModel("gemini-3.5-flash") ``` ### Java ```java GenerativeModel firebaseAI = FirebaseAI.getInstance(GenerativeBackend.agentPlatform()) .generativeModel("gemini-3.5-flash"); GenerativeModelFutures model = GenerativeModelFutures.from(firebaseAI); ```
In the Firebase documentation, you can learn more about the [available Gemini models](https://firebase.google.com/docs/ai-logic/models). You can also learn about [configuring model parameters](https://firebase.google.com/docs/ai-logic/model-parameters?api=vertex). > [!IMPORTANT] > **Important:** In mid-2026, "Vertex AI" rebranded to "Gemini Enterprise Agent Platform" (or "Agent Platform"). To accommodate this change, Firebase AI Logic SDKs added new "Agent Platform" initialization syntax, and the legacy "Vertex AI" syntax was *removed* in SDK v18.0.0 (Firebase BoM v35.0.0). > If you previously used the legacy "Vertex AI" syntax (`backend = GenerativeBackend.vertexAI()`), then migrate your app to use the new "Agent Platform" syntax (`backend = GenerativeBackend.agentPlatform()`). Learn more about [required changes](https://firebase.google.com/docs/ai-logic/faq-and-troubleshooting?api=vertex#changes-for-vertexai-rebrand-to-agent-platform). ### Generate text To generate a text response, call `generateContent()` with your prompt. ### Kotlin ```kotlin suspend fun generateText(model: GenerativeModel) { // Note: generateContent() is a suspend function, which integrates well // with existing Kotlin code. val response = model.generateContent("Write a story about a magic backpack.") // ... } ``` ### Java ```java Content prompt = new Content.Builder() .addText("Write a story about a magic backpack.") .build(); ListenableFuture response = model.generateContent(prompt); Futures.addCallback(response, new FutureCallback() { @Override public void onSuccess(GenerateContentResponse result) { String resultText = result.getText(); // ... } @Override public void onFailure(Throwable t) { t.printStackTrace(); } }, executor); ```
Similar to the Gemini Developer API, you can also pass images, audio, video, and files with your text prompt. For details, see [Interact with the Gemini Developer API from your app](https://developer.android.com/ai/gemini/developer-api.md.txt#interact-gemini). To learn more about Firebase AI Logic SDK, see the [Firebase documentation](https://firebase.google.com/docs/ai-logic/get-started?api=vertex).