🚀 RAGify Flutter #

Intelligent Context Orchestration Framework for Flutter - Smart Context for LLM-Powered Applications

A Flutter package that combines data from multiple sources (documents, APIs, databases, real-time) and resolves conflicts intelligently. Built specifically for LLM-powered Flutter applications that need accurate, current information.

🎯 Why RAGify Flutter? #

Building AI-powered Flutter apps is challenging because:

• Multiple data sources need to be combined intelligently
• Conflicting information between sources must be resolved
• Real-time updates require efficient context management
• Privacy and security need to be built-in, not bolted-on
• Performance must be optimized for mobile and web

RAGify Flutter solves these problems with a unified, production-ready framework.

🌟 What You Get #

Core Capabilities #

• Multi-Source Context Fusion - Combine data from documents, APIs, databases, and real-time sources
• Intelligent Conflict Resolution - Detect and resolve contradictions using source authority and freshness
• Privacy Management - 4-tier privacy levels (Public, Private, Enterprise, Restricted)
• Concurrent Processing - Process multiple sources simultaneously for better performance
• Relevance Scoring - Multi-factor assessment of context relevance

Flutter-Specific Features #

• Cross-Platform Support - Works on iOS, Android, Web, and Desktop
• Async/Await Support - Full async support for non-blocking operations
• State Management Integration - Works with Provider, Bloc, Riverpod, and other state management solutions
• Performance Optimized - Efficient memory usage and processing

🚀 Quick Start #

1. Add Dependency #

dependencies:
  ragify_flutter: ^0.1.0

2. Import Package #

import 'package:ragify_flutter/ragify_flutter.dart';

3. Basic Usage #

// Create RAGify instance
final ragify = RAGify();

// Initialize
await ragify.initialize();

// Add data sources
ragify.addDataSource(DocumentSource(
  name: 'docs',
  documentPath: './documents',
));

// Get context
final context = await ragify.getContext(
  query: 'What are the latest features?',
  maxChunks: 10,
  minRelevance: 0.7,
);

// Use the context
for (final chunk in context.chunks) {
  print('${chunk.content} (Score: ${chunk.relevanceScore?.score})');
}

🏗️ Architecture #

Core Components #

┌─────────────────────────────────────────────────────────────────┐
│                Flutter Application                            │
├─────────────────────────────────────────────────────────────────┤
│                    RAGify Flutter                             │
├─────────────────────────────────────────────────────────────────┤
│  ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│  │   Fusion    │ │   Scoring   │ │   Storage   │ │   Updates   │ │
│  │  Engine     │ │  Engine     │ │  Engine     │ │  Engine     │ │
│  │ (Conflicts) │ │ (Relevance) │ │ (Save)      │ │ (Live)      │ │
│  └─────────────┘ └─────────────┘ └─────────────┘ └─────────────┘ │
├─────────────────────────────────────────────────────────────────┤
│  ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│  │   Vector    │ │   Cache     │ │   Privacy   │ │   Monitor   │ │
│  │     DB      │ │  Manager    │ │  Manager    │ │  Engine     │ │
│  │(Local/Cloud)│ │(Memory/Redis)│ │ (Encrypt)   │ │(Performance)│ │
│  └─────────────┘ └─────────────┘ └─────────────┘ └─────────────┘ │
├─────────────────────────────────────────────────────────────────┤
│                    Data Sources                                 │
│  ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│  │  Documents  │ │    APIs     │ │  Databases  │ │ Real-time   │ │
│  │ (PDF, DOCX, │ │ (REST,      │ │ (SQL,       │ │   Data      │ │
│  │ TXT, MD)    │ │ GraphQL)    │ │ NoSQL)      │ │(WebSocket,  │ │
│  │             │ │             │ │             │ │ MQTT, Kafka)│ │
│  └─────────────┘ └─────────────┘ └─────────────┘ └─────────────┘ │
└─────────────────────────────────────────────────────────────────┘

📱 Examples #

The package includes complete example applications:

• Basic Usage - Simple context retrieval
• Advanced Features - Complex integration patterns
• Full Integration - Complete application examples

Run examples:

cd example/basic_usage
flutter run

🔧 Configuration #

final config = RagifyConfig(
  privacyLevel: PrivacyLevel.enterprise,
  maxContextSize: 50000,
  defaultRelevanceThreshold: 0.7,
  enableCaching: true,
  cacheTtl: 7200,
  conflictDetectionThreshold: 0.8,
  sourceTimeout: 60.0,
  maxConcurrentSources: 20,
);

final ragify = RAGify(config: config);

🧪 Testing #

# Run all tests
flutter test

# Run with coverage
flutter test --coverage

# Current coverage: 40.92%

🔒 Privacy & Security #

• 4 Privacy Levels: Public, Private, Enterprise, Restricted
• Encryption: AES-256, RSA-2048, ChaCha20 support
• Access Control: Role-based permissions (Guest to Superuser)
• Audit Logging: Complete operation tracking
• Compliance: GDPR, HIPAA, SOX ready

🚀 Performance #

• Response Time: Optimized for <200ms typical queries
• Concurrent Processing: Multi-isolate parallel processing
• Memory Efficient: Intelligent caching and chunking
• Cross-Platform: Platform-specific optimizations

🔌 Data Sources #

• Documents: PDF, DOCX, TXT, Markdown
• APIs: REST, GraphQL with rate limiting
• Databases: PostgreSQL, MySQL, MongoDB, SQLite
• Real-time: WebSocket, MQTT, Redis, Kafka

🤝 Contributing #

We welcome contributions! See Contributing Guide for details.

# Development setup
git clone https://github.com/sumitnemade/ragify_flutter.git
cd ragify_flutter
flutter pub get
flutter test

📄 License #

BSD 3-Clause License - see LICENSE file for details.

🔗 Related Projects #

• Python Version: RAGify Python - The original

🆘 Support #

• Issues: GitHub Issues
• Discussions: GitHub Discussions

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