firebase-ai

name	firebase-ai
description	Integrate Firebase AI Logic into Flutter apps using the Gemini Developer API. Use when setting up the firebase_ai plugin, generating text or chat responses with Gemini models, streaming AI output, implementing multimodal prompts, handling AI service errors, or applying security and privacy considerations for AI features.

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.
• Generating text content or chat responses with Gemini models.
• Implementing streaming AI responses for real-time UI updates.
• Sending multimodal prompts (text + images) to Gemini.
• Handling errors, offline scenarios, and rate limits 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
final model =
    FirebaseAI.googleAI().generativeModel(model: 'gemini-2.5-flash');

• Ensure the Firebase project is 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).
• Implement App Check to prevent abuse of Firebase AI endpoints.

Platform support:

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

---

2. Generating Content

Single-turn text generation

final response = await model.generateContent([
  Content.text('Summarize the benefits of Flutter for mobile development'),
]);
final text = response.text; // The generated summary string

Multi-turn chat

final chat = model.startChat();
final response = await chat.sendMessage(
  Content.text('What is the difference between StatelessWidget and StatefulWidget?'),
);
print(response.text);

// Follow-up in the same conversation
final followUp = await chat.sendMessage(
  Content.text('When should I use StatefulWidget?'),
);
print(followUp.text);

Streaming responses

Use streaming to display partial results as they arrive:

final stream = model.generateContentStream([
  Content.text('Write a step-by-step guide to implementing dark mode in Flutter'),
]);

await for (final chunk in stream) {
  // Append chunk.text to the UI progressively
  setState(() => _output += chunk.text ?? '');
}

Multimodal prompts (text + image)

final imageBytes = await File('photo.jpg').readAsBytes();
final response = await model.generateContent([
  Content.multi([
    TextPart('Describe what you see in this image'),
    InlineDataPart('image/jpeg', imageBytes),
  ]),
]);

---

3. Error Handling

Wrap AI calls in structured error handling:

try {
  final response = await model.generateContent([Content.text(prompt)]);
  return response.text;
} on FirebaseAIException catch (e) {
  if (e.message?.contains('quota') ?? false) {
    // Handle rate limiting — show retry message or queue the request
    return 'Service is busy. Please try again shortly.';
  }
  return 'AI service error: ${e.message}';
} catch (e) {
  return 'Unexpected error: $e';
}

• Provide meaningful error messages to users when AI operations fail.
• Handle offline scenarios with appropriate fallback behavior (e.g., cached responses).
• Implement exponential backoff for rate-limited or transient errors.

---

4. Security and Privacy

• Follow Firebase Security Rules best practices when using AI services alongside other Firebase products.
• Ensure proper authentication and authorization for AI feature access.
• Sanitize user input before sending it to the model to prevent prompt injection.
• Be mindful of data privacy requirements when processing user content with AI services.
• Implement appropriate content filtering and moderation using safety settings:

final model = FirebaseAI.googleAI().generativeModel(
  model: 'gemini-2.5-flash',
  safetySettings: [
    SafetySetting(HarmCategory.harassment, HarmBlockThreshold.medium),
    SafetySetting(HarmCategory.dangerousContent, HarmBlockThreshold.high),
  ],
);

---

References

• Firebase AI Logic Flutter documentation