Main Functionality

The main function serves as the entry point, orchestrating user inputs, category selection, level determination, word generation, and hint retrieval. It encapsulates the core logic of the integration, offering a cohesive and interactive user experience.

void main() async {
  // Initialize the generative model
  dynamic generativeModel = initializeGenerativeModel("YOUR_API_KEY");

  final categories = ["animals", "body parts", "objects", "countries", "flowers", "fruits", "cities"];

  // Display available categories to the user
  print("Available categories:");
  categories.asMap().forEach((index, category) {
    print("${index + 1}. $category");
  });

  // Prompt user to select a category
  print("Select a category (1-${categories.length}): ");
  final int categoryIndex = int.parse(stdin.readLineSync()!) - 1;
  final String selectedCategory = categories[categoryIndex];

  // Prompt user to select a difficulty level
  print("Select a difficulty level (1-7): ");
  final int selectedLevel = int.parse(stdin.readLineSync()!) - 1;

  // Generate word counts based on the selected difficulty level
  Map<String, dynamic> wordCounts = generateWordCounts(selectedLevel);
  int totalWords = wordCounts['totalWords'];
  int wordLength = wordCounts['wordLength'];
  int easyWords = wordCounts['wordCounts']['easy'];
  int hardWords = wordCounts['wordCounts']['hard']!;
  int difficultWords = wordCounts['wordCounts']['difficult'];

  // Generate words based on the selected category and counts
  List<String> words = await generateWordsByCategory(
    model: generativeModel,
    category: selectedCategory,
    numWords: totalWords,
    numberOfEasyWords: easyWords,
    numberOfHardWords: hardWords,
    numberOfDifficultWords: difficultWords,
    wordLength: wordLength,
  );

  // Display generated words to the user
  print("Words:");
  for (int i = 0; i < words.length; i++) {
    if (words[i].length <= wordLength) {
      print("${i + 1}. ${words[i]}");
    } else {
      print("Error!");
      print("${i + 1}. ${words[i]}"); // Print the word even if it exceeds length for clarity
    }
  }

  // Prompt user to select a word index to get hints
  print("Select a word index to get hints for (1-${words.length}): ");
  final int wordIndex = int.parse(stdin.readLineSync()!) - 1;

  // Generate hints for the selected word
  List<String> hints = await generateHints(words[wordIndex], 3, generativeModel);

  // Display hints to the user
  print("Hints:");
  for (final hint in hints) {
    print("- $hint");
  }
}

Conclusion

In this blog post, we embarked on a captivating exploration of integrating the Gemini model with Dart, unlocking a plethora of possibilities for content generation, gamification, and user engagement. By harnessing the power of AI within the Dart ecosystem, developers can create immersive experiences that captivate and inspire audiences worldwide.

Stay tuned for more insights, tutorials, and innovations at the intersection of AI and programming languages. Together, let’s push the boundaries of creativity and technology, shaping a future where the possibilities are limitless.

For more information on Dart and Gemini, explore the following resources:

• Dart Programming Language
• Google Generative AI
• Gemini Model Documentation

Feel free to experiment with the code snippet provided and embark on your own journey of AI integration with Dart. The possibilities await!

Stay inspired, stay innovative, and happy coding!