Get started with the Gemini API using the Vertex AI in Firebase SDKs

This guide shows you how to get started making calls to the Vertex AI Gemini API directly from your app using the Vertex AI in Firebase SDK for your chosen platform.

Prerequisites

This guide assumes that you're familiar with developing apps with Flutter.

• Make sure that your development environment and Flutter app meet the following requirements:

  • Dart 3.2.0+

• (Optional) Check out the sample app.

  Download the sample app

  You can try out the SDK quickly, see a complete implementation of various use cases, or use the sample app if don't have your own Flutter app. To use the sample app, you'll need to connect it to a Firebase project.

Step 1: Set up a Firebase project and connect your app to Firebase

If you already have a Firebase project and an app connected to Firebase

1. In the Firebase console, go to the Build with Gemini page.

2. Click the Vertex AI in Firebase card to launch a workflow that helps you complete the following tasks:

   • Upgrade your project to use the pay-as-you-go Blaze pricing plan.

   • Enable the required APIs in your project (Vertex AI API and Vertex AI in Firebase API).

3. Continue to the next step in this guide to add the SDK to your app.

If you do not already have a Firebase project and an app connected to Firebase

Step 2: Add the SDK

With your Firebase project set up and your app connected to Firebase (see previous step), you can now add the Vertex AI in Firebase SDK to your app.

The Vertex AI in Firebase plugin for Flutter (firebase_vertexai) provides access to the Vertex AI Gemini API.

1. From your Flutter project directory, run the following command to install the core plugin:

   flutter pub add firebase_core
   

2. In your lib/main.dart file, import the Firebase core plugin and the configuration file you generated earlier:

   import 'package:firebase_core/firebase_core.dart';
   import 'firebase_options.dart';
   

3. Also in your lib/main.dart file, initialize Firebase using the DefaultFirebaseOptions object exported by the configuration file:

   await Firebase.initializeApp(
     options: DefaultFirebaseOptions.currentPlatform,
   );
   

4. Rebuild your Flutter application:

   flutter run
   

5. From your Flutter project directory, run the following command:

   flutter pub add firebase_vertexai

6. Once complete, rebuild your Flutter project:

   flutter run
   

Step 3: Initialize the Vertex AI service and the generative model

Before you can make any API calls, you need to initialize the Vertex AI service and the generative model.

import 'package:firebase_vertexai/firebase_vertexai.dart';
import 'package:firebase_core/firebase_core.dart';

// Initialize FirebaseApp
await Firebase.initializeApp();
// Initialize the Vertex AI service and the generative model
// Specify a model that supports your use case
// Gemini 1.5 models are versatile and can be used with all API capabilities
final model =
      FirebaseVertexAI.instance.generativeModel(model: 'gemini-1.5-flash');

When you've finished the getting started guide, learn how to choose a Gemini model and (optionally) a location appropriate for your use case and app.

Step 4: Call the Vertex AI Gemini API

Now that you've connected your app to Firebase, added the SDK, and initialized the Vertex AI service and the generative model, you're ready to call the Vertex AI Gemini API.

You can use generateContent() to generate text from a text-only prompt request:

import 'package:firebase_vertexai/firebase_vertexai.dart';
import 'package:firebase_core/firebase_core.dart';

await Firebase.initializeApp();
// Initialize the Vertex AI service and the generative model
// Specify a model that supports your use case
// Gemini 1.5 models are versatile and can be used with all API capabilities
final model =
      FirebaseVertexAI.instance.generativeModel(model: 'gemini-1.5-flash');

// Provide a prompt that contains text
final prompt = [Content.text('Write a story about a magic backpack.')];

// To generate text output, call generateContent with the text input
final response = await model.generateContent(prompt);
print(response.text);

What else can you do?

Learn more about the Gemini models

Try out other capabilities of the Gemini API

• Learn more about generating text from text-only prompts, including how to stream the response.
• Generate text from multimodal prompts (including text, images, PDFs, video, and audio).
• Build multi-turn conversations (chat).
• Generate structured output (like JSON) from both text and multimodal prompts.
• Use function calling to connect generative models to external systems and information.

Learn how to control content generation

• Understand prompt design, including best practices, strategies, and example prompts.
• Configure model parameters like temperature and maximum output tokens.
• Use safety settings to adjust the likelihood of getting responses that may be considered harmful.

Give feedback about your experience with Vertex AI in Firebase