Generate text from text-only prompts using the Gemini API

When calling the Gemini API from your app using a Vertex AI in Firebase SDK, you can prompt the Gemini model to generate text based on a text-only input.

Before you begin

If you haven't already, complete the getting started guide for the Vertex AI in Firebase SDKs. Make sure that you've done all of the following:

1. Set up a new or existing Firebase project, including using the Blaze pricing plan and enabling the required APIs.

2. Connect your app to Firebase, including registering your app and adding your Firebase config to your app.

3. Add the SDK and initialize the Vertex AI service and the generative model in your app.

After 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 Gemini API.

Generate text from text-only input

You can call the Gemini API with input that includes only text. For these calls, you need to use a model that supports text-only prompts (like Gemini 1.5 Pro).

Choose whether you want to stream the response (generateContentStream) or wait for the response until the entire result is generated (generateContent).

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

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

// 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 stream generated text output, call generateContentStream with the text input
final response = model.generateContentStream(prompt);
await for (final chunk in response) {
  print(chunk.text);
}

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

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

// 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);

Learn how to choose a Gemini model and optionally a location appropriate for your use case and app.

What else can you do?

• Learn how to count tokens before sending long prompts to the model.
• Start thinking about preparing for production, including setting up Firebase App Check to protect the Gemini API from abuse by unauthorized clients.

Try out other capabilities of the Gemini API

• Build multi-turn conversations (chat).
• Generate text from multimodal prompts (including text, images, PDFs, video, and audio).
• 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.

Learn more about the Gemini models

Give feedback about your experience with Vertex AI in Firebase