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:

  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

Learn about the models available for various use cases and their quotas and pricing.

Try out other capabilities of the Gemini API

Learn how to control content generation

You can also experiment with prompts and model configurations using Vertex AI Studio.


Give feedback about your experience with Vertex AI in Firebase