firebase-ai

name	firebase-ai
description	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.
metadata	{"author":"evanca"}

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:

Platform	Support
iOS	Full
Android	Full
Web	Full
macOS / other Apple	Beta
Windows	Not supported

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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.

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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.

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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.

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References

• Firebase AI Logic Flutter documentation

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