ai_providers 1.0.0

Professional Flutter AI SDK with unified API for multiple providers (OpenAI, Google AI, XAI). Advanced architecture showcasing enterprise patterns, caching, retry logic, and comprehensive monitoring.

🤖 AI Providers

Professional Flutter AI SDK - A unified, extensible architecture for integrating multiple AI providers (OpenAI, Google AI, XAI, Android Native) with advanced caching, retry logic, and comprehensive monitoring.

🎯 Professional Showcase

This package demonstrates advanced Flutter/Dart architecture patterns and AI integration expertise:

• 🏗️ Clean Architecture - Facade pattern with provider registry
• 🔧 Advanced DI - Dynamic provider resolution and capability-based routing
• ⚡ Performance - Intelligent caching, connection pooling, retry mechanisms
• 🧪 Quality Assurance - 32+ comprehensive tests, architectural protection
• 🔒 Enterprise Security - API key management, rate limiting, monitoring

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🚀 Quick Start

Installation

dependencies:
  ai_providers: ^1.0.0

Basic Usage

import 'package:ai_providers/ai_providers.dart';

// Initialize the AI system
await AI.initialize();

// Generate text with any available provider
final response = await AI.text(
  ['Hello, how are you?'], 
  'You are a helpful assistant'
);

// Generate images
final imageResponse = await AI.image('A beautiful sunset over mountains');

// Text-to-speech
final audioResponse = await AI.speak('Hello world');

// Speech-to-text  
final transcription = await AI.transcribe(audioBase64);

🏗️ Architecture Overview

Facade Pattern Implementation

// ✅ Clean API - Only this is exposed
AI.text()      // Text generation
AI.image()     // Image generation  
AI.speak()     // Audio generation
AI.transcribe() // Speech recognition
AI.generate()  // Universal method

// ❌ Internal complexity hidden
// OpenAIProvider, GoogleProvider, XAIProvider - not accessible
// ProviderRegistry, CacheService, RetryService - not accessible

Advanced Provider Registry

// Dynamic provider resolution based on capabilities
final providers = ProviderRegistry.instance.getProvidersForCapability(
  AICapability.textGeneration
);

// Automatic fallback and load balancing
final response = await AI.text(message, systemPrompt);
// → Tries OpenAI → Falls back to Google → Falls back to XAI

Enterprise-Grade Services

// Intelligent caching with TTL
final cached = await CacheService.get('text_generation_hash');

// Retry logic with exponential backoff  
final response = await RetryService.executeWithRetry(() async {
  return await provider.generateText(prompt);
});

// Connection pooling for optimal performance
final pool = HttpConnectionPool(maxPerHost: 10, maxTotal: 50);

🔧 Advanced Configuration

YAML-Based Provider Configuration

# assets/ai_providers_config.yaml
providers:
  openai:
    enabled: true
    priority: 1
    capabilities: [textGeneration, imageGeneration, audioGeneration]
    models:
      text: ["gpt-4", "gpt-3.5-turbo"]
      image: ["dall-e-3", "dall-e-2"]
    rate_limits:
      requests_per_minute: 60
      
  google:
    enabled: true
    priority: 2
    capabilities: [textGeneration, audioGeneration]
    models:
      text: ["gemini-pro", "gemini-pro-vision"]
    voices:
      default: "es-ES-Neural2-A"

Programmatic Configuration

final config = AIInitConfig(
  providers: {
    'openai': ProviderConfig(
      enabled: true,
      apiKey: 'your-api-key',
      models: ['gpt-4', 'gpt-3.5-turbo'],
      capabilities: [AICapability.textGeneration],
    ),
  },
  cacheConfig: CacheConfig(ttlMinutes: 60),
  retryConfig: RetryConfig(maxAttempts: 3),
);

await AI.initialize(config);

🎯 Capability-Based Architecture

Unified API with Multiple Capabilities

// Method 1: Specific capability methods
await AI.text(messages, systemPrompt);
await AI.image(prompt);
await AI.speak(text);

// Method 2: Universal method with explicit capability
await AI.generate(
  message: 'Generate something amazing',
  systemPrompt: systemPrompt,
  capability: AICapability.textGeneration,
);

Dynamic Provider Selection

// The system automatically selects the best provider based on:
// 1. Capability support
// 2. Provider priority  
// 3. Rate limits
// 4. Health status
// 5. Response time history

final response = await AI.text(messages, systemPrompt);
// → Internally routes to best available provider

🧪 Quality Assurance

Comprehensive Test Suite

• 32+ Unit Tests - Complete coverage of all components
• Architectural Tests - Ensures facade pattern integrity
• Integration Tests - Real provider interaction validation
• Security Tests - API key protection and bypass prevention

flutter test
# → All tests pass with architectural protection

Anti-Bypass Protection

// ✅ This compiles and works
final response = await AI.text(messages, systemPrompt);

// ❌ This won't compile - internal access blocked
final provider = OpenAIProvider(); // Compilation error
final manager = AIProviderManager.instance; // Not exported

📊 Performance Features

Intelligent Caching

// Automatic response caching with configurable TTL
final response1 = await AI.text(['Hello'], 'Assistant'); // API call
final response2 = await AI.text(['Hello'], 'Assistant'); // Cached response

Connection Pooling

// Optimized HTTP connections
HttpConnectionPoolConfig(
  maxPerHost: 10,
  maxTotal: 50,
  keepAliveTimeout: Duration(seconds: 15),
)

Retry Logic with Circuit Breaker

// Exponential backoff with circuit breaker pattern
RetryConfig(
  maxAttempts: 3,
  circuitBreakerThreshold: 5,
  backoffMultiplier: 2.0,
)

🔒 Security & Monitoring

API Key Management

// Secure API key storage with rotation support
ApiKeyManager.instance.setApiKey('openai', 'primary-key');
ApiKeyManager.instance.addFallbackKey('openai', 'backup-key');

Comprehensive Monitoring

// Real-time performance monitoring
final metrics = MonitoringService.instance.getMetrics();
print('Success rate: ${metrics.successRate}%');
print('Average response time: ${metrics.avgResponseTime}ms');

Rate Limiting

// Built-in rate limiting per provider
RateLimitConfig(
  requestsPerMinute: 60,
  burstLimit: 10,
  adaptiveThrottling: true,
)

🛠️ Extensibility

Adding Custom Providers

class CustomAIProvider extends BaseProvider {
  @override
  List<AICapability> get supportedCapabilities => [
    AICapability.textGeneration,
  ];
  
  @override
  Future<ProviderResponse> generateText(String prompt) async {
    // Custom implementation
  }
}

// Register in provider registry
ProviderRegistry.instance.registerProvider('custom', CustomAIProvider);

Custom Capabilities

enum CustomCapability implements AICapability {
  documentAnalysis,
  codeGeneration,
  realtimeConversation;
}

📈 Performance Benchmarks

Feature	Performance	Memory Usage
Cold start	~200ms	15MB
Cached response	~5ms	+2MB
Provider switching	~50ms	+1MB
Concurrent requests	50/sec	Linear scaling

🎯 Use Cases

Chatbot Applications

final conversation = AI.createConversation();
await conversation.addMessage('Hello', Role.user);
final response = await conversation.generateResponse();

Content Generation

final article = await AI.text(
  ['Write an article about Flutter'],
  'You are a technical writer'
);

Multimodal AI

final description = await AI.generate(
  message: 'Describe this image',
  imageBase64: imageData,
  capability: AICapability.imageAnalysis,
);

🏆 Why This Architecture?

Professional Software Engineering Principles

1. Separation of Concerns - Each component has a single responsibility
2. Dependency Inversion - High-level modules don't depend on low-level details
3. Open/Closed Principle - Open for extension, closed for modification
4. Interface Segregation - Clients don't depend on unused interfaces
5. Single Responsibility - Each class has one reason to change

Enterprise Patterns

• Facade Pattern - Simplified interface to complex subsystem
• Strategy Pattern - Interchangeable provider algorithms
• Registry Pattern - Dynamic service discovery and registration
• Circuit Breaker - Fault tolerance and resilience
• Observer Pattern - Event-driven monitoring and alerts

📝 License

This project is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

⚖️ License Summary:

• ✅ Personal Use - Use for learning, personal projects
• ✅ Attribution - Credit must be given to the author
• ❌ Commercial Use - No commercial use without permission
• ❌ Derivatives - No modifications or derivative works
• ❌ Forking - Repository forks are not permitted

🤝 Feedback Welcome

While forks and pull requests are not accepted, issues and discussions are encouraged for:

• Bug reports
• Feature suggestions
• Architecture feedback
• Professional opportunities

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👨‍💻 About the Developer

This package showcases advanced Flutter and AI integration skills as part of a professional portfolio.

Technical Expertise Demonstrated:

• Advanced Dart/Flutter architecture patterns
• AI/ML integration and prompt engineering
• Enterprise software design patterns
• Comprehensive testing strategies
• Performance optimization techniques
• Security best practices

Contact for Professional Opportunities:

• GitHub: @albertooishii
• Open to Flutter/AI development roles

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🚀 Built with Flutter & Dart for Professional Excellence

Demonstrating modern software architecture and AI integration expertise