Flutter UI Agent

Control your Flutter app with natural language. Let AI agents understand and interact with your UI.

What is Flutter UI Agent?

Flutter UI Agent lets users control your app using natural language instead of traditional UI interactions. Wrap your widgets with AiActionWidget and they become AI-controllable.

Example Commands:

"Change my bio to 'Flutter Developer'"
"Find red products and add them to cart"
"Navigate to settings and enable dark mode"
"Increment the counter 5 times"

AI Agent controlling a Flutter app with natural language commands

✨ Features

🧠 LLM-Agnostic - Works with Gemini, HuggingFace, OpenAI, Claude, or any LLM
🎯 Dynamic Actions - Wrap any widget to make it AI-controllable
🧭 Enhanced Smart Navigation - Automatic page tracking with intelligent continuation after navigation for complex commands
⚡ Async Support - Handle navigation and async operations seamlessly
🔄 Multi-Step Commands - Execute complex action sequences
📊 Analytics - Track action usage and performance
🎨 Customizable - Flexible configuration and logging

🚀 Quick Start

1. Installation

dependencies:
  flutter_ui_agent: ^1.1.0

2. Create an LLM Provider

Implement the LlmProvider interface for your chosen LLM:

import 'package:flutter_ui_agent/flutter_ui_agent.dart';

class GeminiProvider implements LlmProvider {
  late String apiKey;
  late String modelName;
  
  @override
  Future<void> configure({required String apiKey, String? modelName}) async {
    this.apiKey = apiKey;
    this.modelName = modelName ?? 'gemini-2.0-flash-exp';
  }

  @override
  Future<LlmResponse> send({
    required String systemPrompt,
    required String userMessage,
    required List<Map<String, dynamic>> tools,
    required List<ConversationMessage> history,
  }) async {
    // Call your LLM API here with your chosen SDK
    // Return LlmResponse with functionCalls or text response
  }
}

LlmProvider Interface

The LlmProvider is an abstract interface that allows Flutter UI Agent to work with any LLM. It has two main methods:

configure({required String apiKey, String? modelName}): Optional setup method for providers that need API keys or model configuration. Called once during initialization.
send(...): The core method that sends messages to your LLM. It receives:
- systemPrompt: System-level instructions for the AI
- userMessage: The composed user message with context and available actions
- tools: List of function/tool definitions in JSON schema format
- history: Recent conversation messages for context
Returns an LlmResponse containing either:
- text: Plain text response (for conversational replies)
- functionCalls: List of LlmFunctionCall objects representing actions to execute

See the example implementations for Gemini and HuggingFace providers.

3. Setup AgentService

void main() async {
  final agentService = AgentService();
  final llmProvider = GeminiProvider();
  
  await llmProvider.configure(
    apiKey: 'YOUR_API_KEY',
    modelName: 'gemini-2.0-flash-exp',
  );
  
  agentService.setLlmProvider(
    llmProvider,
    config: const AgentConfig(
      logLevel: AgentLogLevel.info,
      enableAnalytics: true,
      debugMode: true,
    ),
  );

  runApp(
    AgentHost(
      agentService: agentService,
      child: MyApp(),
    ),
  );
}

4. Make Widgets AI-Controllable

AiActionWidget(
  actionId: 'increment_counter',
  description: 'Increment the counter by 1',
  onExecute: () {
    setState(() => counter++);
  },
  child: ElevatedButton(
    onPressed: () => setState(() => counter++),
    child: Text('Increment'),
  ),
)

5. Add Navigation Tracking

MaterialApp(
  navigatorObservers: [
    AgentNavigatorObserver(agentService),
  ],
  // ...
)

6. Process User Commands

await agentService.processUserMessage('Increment the counter 5 times');

🎯 Example Prompts

Try these natural language commands in your app:

Simple Actions:

"Increment counter 5 times"
"Set counter to 100"
"Reset counter"

Navigation + Actions:

"Go to settings and enable dark mode"
"Navigate to profile and change my bio to 'Flutter Developer'"
"Open shopping page and search for shoes"

Multi-Step:

"Set counter to 50, increment 10 times, then go to profile"
"Go to settings, enable dark mode, then go to shopping"

Natural Language:

"Can you increase the counter by 7?"
"I want to see my profile"
"Turn off notifications and update my status"

See the example app for a complete demo with shopping, profile, and settings pages.

⚠️ Important: Safety & Limitations

This package is experimental and should be used with caution in production environments.

Safety Guidelines

🚫 DO NOT use for sensitive operations without user confirmation:

Payment processing (NO automatic payments)
Financial transactions
Data deletion
Security-critical actions

✅ SAFE use cases:

Generate summaries for user review
Create draft content for approval
Assist with form filling (with confirmation)
Navigate and display information
Filter and search data

Best Practice: For sensitive operations, use AI to prepare the action (e.g., calculate total, create order summary), then require explicit user confirmation before execution.

Example - Safe Payment Flow:

// ✅ GOOD: AI prepares, user confirms
AiActionWidget(
  actionId: 'prepare_checkout',
  description: 'Prepare checkout summary for user review',
  onExecuteWithParams: (params) {
    // AI calculates total, applies discounts, etc.
    showCheckoutSummary(); // User must tap "Confirm Payment" button
  },
)

// ❌ BAD: Direct payment automation
AiActionWidget(
  actionId: 'process_payment',  // NEVER DO THIS
  description: 'Process payment immediately',
  onExecute: () => processPayment(), // Dangerous!
)

📖 Core Concepts

AiActionWidget

Wraps any widget to make it AI-controllable:

// Simple action
AiActionWidget(
  actionId: 'like_post',
  description: 'Like the post',
  onExecute: () => likePost(),
  child: IconButton(icon: Icon(Icons.favorite)),
)

// Action with parameters
AiActionWidget(
  actionId: 'update_bio',
  description: 'Update user bio text',
  parameters: const [
    AgentActionParameter.string(
      name: 'bio_text',
      description: 'New bio value to save',
    ),
  ],
  onExecuteWithParams: (params) {
    final bio = params['bio_text'] as String;
    updateBio(bio);
  },
  child: TextField(),
)

// Action that can run multiple times per request (count parameter exposed)
AiActionWidget(
  actionId: 'tap_increment',
  description: 'Tap increment button',
  allowRepeats: true,
  onExecute: increment,
  child: IconButton(icon: Icon(Icons.exposure_plus_1)),
)

// Async action
AiActionWidget(
  actionId: 'navigate_settings',
  description: 'Navigate to settings page',
  onExecuteAsync: () async {
    Navigator.pushNamed(context, '/settings');
    await Future.delayed(Duration(milliseconds: 100));
  },
  child: ListTile(title: Text('Settings')),
)

AgentService

Central service managing AI actions:

// Process commands
await agentService.processUserMessage('your command');

// Cancel in-progress requests
agentService.cancelCurrentRequest();

// Access statistics
final stats = agentService.statistics;
print('API Calls: ${stats['apiCalls']}');
print('Success Rate: ${stats['successRate']}%');

// Get current page
print('Current page: ${agentService.currentPage}');

// Clear conversation history
agentService.clearHistory();

Navigation Tracking

Track page changes automatically:

MaterialApp(
  navigatorObservers: [
    AgentNavigatorObserver(agentService),
  ],
  onGenerateRoute: (settings) {
    // Your routing logic
  },
)

⚙️ Configuration

AgentConfig Options

AgentConfig(
  // Logging
  logLevel: AgentLogLevel.info,  // none, error, warning, info, verbose, debug
  useEmojis: true,
  logPrefix: '[FlutterUIAgent]',
  
  // Behavior
  enableRetry: true,
  maxRetries: 3,
  retryBackoffStrategy: RetryBackoffStrategy.exponential,
  retryBaseDelayMs: 1000,
  
  // History & Analytics
  enableHistory: true,
  maxHistoryLength: 10,
  enableAnalytics: true,
  onActionExecuted: (actionId, duration) {
    print('$actionId took ${duration.inMilliseconds}ms');
  },
  
  // Development
  debugMode: true,
  fallbackToMock: false,
)

Log Levels

Level	Use Case	Output
`none`	Production (silent)	No logs
`error`	Production (errors only)	Errors only
`warning`	Production (important)	Errors + warnings
`info`	Default	Errors + warnings + info
`verbose`	Development	All above + verbose details
`debug`	Debugging	Everything including debug info

🎯 Example App

Check out the example/ folder for a complete demo featuring:

Counter Page - Simple increment/decrement actions
Profile Page - Bio and status updates
Data Browser - Search and filtering
Shopping Page - Product browsing and cart management
Settings Page - Theme and configuration changes
Floating Chat UI - Natural language command interface

Run the example:

cd example
cp lib/app/config/app_config.dart.example lib/app/config/app_config.dart
# Add your API key to app_config.dart
flutter run

Try these commands in the example:

"Increment counter 3 times"
"Change my bio to 'Flutter enthusiast'"
"Find red products"
"Navigate to settings and enable dark mode"
"Add running shoes to cart"

🤖 Tested AI Models

These models have been tested and work well with Flutter UI Agent:

Gemini (Google)

modelName: 'gemini-2.0-flash-exp'  // Fast, reliable

HuggingFace

modelName: 'Qwen/Qwen3-235B-A22B-Instruct-2507'  // High quality, open-source

Bring Your Own

Implement LlmProvider for any LLM with function calling support (OpenAI GPT-4, Claude, etc.)

🛠️ Advanced Usage

Custom System Prompts

agentService.setSystemPrompt('''
You are a helpful assistant for a shopping app.
Focus on helping users find and purchase products.
Be concise and action-oriented.
''');

Mock Mode (Testing)

Test without API keys:

// Don't call setLlmProvider()
// AgentService will use keyword-based matching
await agentService.processUserMessage('increment counter');

Error Handling

try {
  await agentService.processUserMessage('your command');
} catch (e) {
  print('Command failed: $e');
  // Handle error
}

Dynamic Action Registration

// Actions are automatically registered when AiActionWidget builds
// Access all registered actions:
final actions = agentService.actions;
print('Available actions: ${actions.keys}');

📊 Analytics & Monitoring

Track Performance

AgentConfig(
  enableAnalytics: true,
  onActionExecuted: (actionId, duration) {
    analytics.logEvent(
      name: 'ai_action',
      parameters: {
        'action_id': actionId,
        'duration_ms': duration.inMilliseconds,
      },
    );
  },
)

View Statistics

final stats = agentService.statistics;
print('Total API calls: ${stats['apiCalls']}');
print('Failed calls: ${stats['failures']}');
print('Success rate: ${stats['successRate']}%');

🔒 Security Best Practices

1. Never Commit API Keys

// ✅ Good: Use environment variables or secure storage
apiKey: Platform.environment['GEMINI_API_KEY']

// ❌ Bad: Hardcoded in source
apiKey: 'actual-api-key-here'

2. Use `.gitignore`

**/app_config.dart
**/*.env

3. Validate AI Actions

Always validate and sanitize parameters before executing actions:

AiActionWidget(
  actionId: 'update_profile',
  parameters: const [
    AgentActionParameter.string(
      name: 'bio',
      description: 'New profile bio text',
    ),
  ],
  onExecuteWithParams: (params) {
    final bio = params['bio'] as String;
    
    // ✅ Validate input
    if (bio.length > 500) {
      throw Exception('Bio too long');
    }
    if (_containsProfanity(bio)) {
      throw Exception('Invalid content');
    }
    
    updateBio(bio);
  },
)

4. Require Confirmation for Sensitive Actions

Never allow AI to directly execute:

Payments or purchases
Account deletion
Password changes
Data exports
Sharing private information

Instead, use a confirmation flow:

// AI prepares the action
AiActionWidget(
  actionId: 'prepare_delete_account',
  description: 'Show account deletion confirmation dialog',
  onExecute: () {
    showDialog(
      context: context,
      builder: (context) => AlertDialog(
        title: Text('Delete Account?'),
        content: Text('This action cannot be undone.'),
        actions: [
          TextButton(
            onPressed: () => Navigator.pop(context),
            child: Text('Cancel'),
          ),
          TextButton(
            onPressed: () {
              _actuallyDeleteAccount(); // User explicitly confirmed
              Navigator.pop(context);
            },
            child: Text('Delete'),
          ),
        ],
      ),
    );
  },
)

5. Rate Limiting

Implement rate limiting to prevent abuse:

// Limit AI requests per user/session
class RateLimiter {
  final _timestamps = <DateTime>[];
  final maxRequests = 10;
  final timeWindow = Duration(minutes: 1);
  
  bool allowRequest() {
    final now = DateTime.now();
    _timestamps.removeWhere(
      (t) => now.difference(t) > timeWindow,
    );
    
    if (_timestamps.length >= maxRequests) {
      return false; // Rate limit exceeded
    }
    
    _timestamps.add(now);
    return true;
  }
}

6. Log and Monitor

Track all AI actions for security auditing:

AgentConfig(
  enableAnalytics: true,
  onActionExecuted: (actionId, duration) {
    securityLog.record(
      action: actionId,
      timestamp: DateTime.now(),
      userId: currentUser.id,
      duration: duration,
    );
  },
)

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Fork the repository
Create your feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🔗 Links

💬 Support

Issues: GitHub Issues
Discussions: GitHub Discussions

Made with ❤️ for the Flutter community

Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
assets		assets
example		example
lib		lib
test		test
.gitignore		.gitignore
.metadata		.metadata
CHANGELOG.md		CHANGELOG.md
LICENSE		LICENSE
README.md		README.md
analysis_options.yaml		analysis_options.yaml
devtools_options.yaml		devtools_options.yaml
pubspec.yaml		pubspec.yaml

License

MAUstaoglu/flutter_ui_agent

Folders and files

Latest commit

History

Repository files navigation