firebase-ai

Integrates Firebase AI Logic into Flutter apps. Use when setting up the firebase_ai plugin, calling Gemini models, handling AI service errors, or applying security and privacy considerations for AI features.

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Install skill "firebase-ai" with this command: npx skills add evanca/flutter-ai-rules/evanca-flutter-ai-rules-firebase-ai

Firebase AI Skill

This skill defines how to correctly use Firebase AI Logic in Flutter applications.

When to Use

Use this skill when:

  • Setting up and configuring Firebase AI in a Flutter project.
  • Implementing AI features on supported platforms.
  • Handling errors and offline scenarios for AI operations.
  • Applying security and privacy considerations for AI features.

1. Setup and Configuration

flutter pub add firebase_ai
import 'package:firebase_ai/firebase_ai.dart';
import 'package:firebase_core/firebase_core.dart';
import 'firebase_options.dart';

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

// Initialize the Gemini Developer API backend service
// Create a GenerativeModel instance with a model that supports your use case
final model =
    FirebaseAI.googleAI().generativeModel(model: 'gemini-2.5-flash');
  • Ensure your Firebase project is properly configured for AI services (via the Firebase AI Logic page in the Firebase Console).
  • Initialize Firebase before using any Firebase AI features.
  • Use FirebaseAI.googleAI() for the Gemini Developer API backend (recommended starting point).
  • Consider implementing App Check to prevent abuse of your Firebase AI endpoints.

Platform support:

PlatformSupport
iOSFull
AndroidFull
WebFull
macOS / other AppleBeta
WindowsNot supported

2. Best Practices

  • Be aware of rate limits and quotas when implementing AI features — monitor usage and costs in the Firebase Console.
  • Handle AI service errors gracefully with appropriate fallback mechanisms.
  • Consider user privacy when implementing AI features that process user data.
  • Test AI functionality across all supported platforms during development.

3. Error Handling

  • Implement proper error handling for AI service failures.
  • Provide meaningful error messages to users when AI operations fail.
  • Handle offline scenarios and implement appropriate fallback behavior.
  • Handle rate limiting and quota exceeded errors appropriately.

4. Security

  • Follow Firebase Security Rules best practices when using AI services alongside other Firebase products.
  • Ensure proper authentication and authorization for AI feature access.
  • Be mindful of data privacy requirements when processing user content with AI services.
  • Implement appropriate content filtering and moderation as needed.

References

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