Integrate Generative AI into a Flutter Application

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Understanding how to integrate generative AI into Flutter can unlock significant opportunities to create smarter and more interactive applications. Check out our explanation below to learn more.

Recently, developing mobile applications using Flutter is no longer just about creating basic interfaces and features. With the advent of Generative AI, applications can become smarter and better to understand user needs. Not only they can provide recommendations or automate tasks, but Generative AI can also generate various new types of content, such as text, images, and audio, tailored to the context or needs of the user.

How to Integrate Generative AI into Flutter Application

In general, we need to communicate with the API from AI service providers such as Google, OpenAI, and Claude. Before integrating, we need to register on each platform to obtain an API KEY, which will later be used for communication. Below are examples of simple integration in Flutter using several Generative AI service platforms.

1. Integrate AI: Google Gemini AI

To integrate generative AI into a Flutter app with Google’s Gemini AI, we can use an API. Here is an example of integration using the google_generative_ai package:

import 'package:google_generative_ai/google_generative_ai.dart';

const apiKey = 'API_KEY';

void main() async {
  final model = GenerativeModel(
      model: 'gemini-1.5-flash-latest',
      apiKey: apiKey,
  );

  final prompt = 'Write a story about a magic backpack.';
  final content = [Content.text(prompt)];
  final response = await model.generateContent(content);

  print(response.text);
};

In this code, we use the gemini-1.5-flash-latest model with a prompt to create a story about a magic backpack.

2. Integrate AI: Open AI (ChatGPT)

Similarly, we can use OpenAI’s API. Here is an example of integration using the openai_dart package:

import 'package:openai_dart/openai_dart.dart';

const apiKey = 'API_KEY';

void main() async {
  final client = OpenAIClient(apiKey: apiKey);
  final res = await client.createChatCompletion(
    request: CreateChatCompletionRequest(
      model: ChatCompletionModel.modelId('gpt-4o'),
      messages: [
        ChatCompletionMessage.system(
          content: 'You are a novelist.',
        ),
        ChatCompletionMessage.user(
          content: ChatCompletionUserMessageContent.string('Write a story about a magic backpack.!'),
        ),
      ],
      temperature: 0,
    ),
  );
  print(res.choices.first.message.content);
};

In this code, we use the gpt-4o model with two types of prompts: the first is a system prompt that sets the AI’s role as a novelist, and the second is a user prompt to create a story about a magic backpack.

3. Integrate AI: Claude AI

Claude AI is an LLM from Anthropic that can be integrated via API. Here is an example of integration using the anthropic_sdk_dart package:

import 'package:anthropic_sdk_dart/anthropic_sdk_dart.dart';

const apiKey = 'API_KEY';

void main() async {
  final client = AnthropicClient(apiKey: apiKey);
  final res = await client.createMessage(
    request: CreateMessageRequest(
      model: Model.model(Models.claude35Sonnet20241022),
      maxTokens: 1024,
      messages: [
        Message(
          role: MessageRole.user,
          content: MessageContent.text('Write a story about a magic backpack.!'),
        ),
      ],
    ),
  );
  print(res.content.text);
}

In this code, we use the claude-sonnet3.5 model with a user prompt to create a story about a magic backpack.

Things to Consider When Integrating Generative AI into a Flutter App

When integrating generative AI into a Flutter application, there are several important things to consider.
First, it is crucial to prepare the application for situations where the internet connection is lost, ensuring the app remains functional even offline or if there are issues with the AI API.

Second, user data confidentiality must be well-maintained. Ensure compliance with privacy regulations to protect sensitive information. Additionally, ensure secure communication with the AI server, especially in safeguarding the API key from exposure.

Third, carefully calculate the costs of using the API, as excessive or uncontrolled usage can lead to significantly high bills.

Conclusion

Integrating generative AI into Flutter applications opens up many possibilities for creating more advanced, creative, and personalized apps that can deeply understand user needs. However, it is also important to recognize that AI has limitations, such as dependence on internet connectivity and potential biases in AI models.

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