🚀 RAGify Flutter

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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 provides intelligent context management. Built specifically for LLM-powered Flutter applications that need to retrieve and manage contextual information from various data sources.

🎯 Why RAGify Flutter?

Building AI-powered Flutter apps is challenging because:

• Multiple data sources need to be combined intelligently
• Context management requires efficient data retrieval and processing
• Cross-platform compatibility needs to work on all Flutter platforms
• Performance must be optimized for mobile and web
• Easy integration with existing Flutter applications

RAGify Flutter provides a unified framework for context management and data source integration.

🌟 What You Get

Core Capabilities

• Multi-Source Data Integration - Connect to documents, APIs, databases, and real-time sources
• Context Management - Organize and retrieve contextual information efficiently
• Privacy Management - Configurable privacy levels for different data sources
• Concurrent Processing - Process multiple sources simultaneously for better performance
• Relevance Scoring - Basic relevance assessment for context chunks

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: ^0.0.5

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 a comprehensive example application:

• Basic Usage - Complete example with all data source types (API, Document, Database)
• Database Testing - SQLite, PostgreSQL, MySQL, and MongoDB integration examples
• Real-time Features - WebSocket and real-time data source examples

Run the example:

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

🔒 Privacy & Security

• Privacy Levels: Configurable privacy levels for different data sources
• Basic Encryption: Support for data encryption (implementation in progress)
• Access Control: Basic access control mechanisms
• Logging: Comprehensive logging for debugging and monitoring
• Data Protection: Basic data protection features

🚀 Performance

• Response Time: Optimized for reasonable query response times
• Concurrent Processing: Async processing for better performance
• Memory Efficient: Basic caching and chunking mechanisms
• Cross-Platform: Works across all Flutter platforms

🔌 Data Sources

• Documents: PDF, DOCX, TXT, HTML, CSV, JSON, YAML, XML, INI, DOC
• APIs: REST APIs with GET/POST support and query inclusion
• Databases: SQLite, PostgreSQL, MySQL, MongoDB
• Real-time: WebSocket support (basic implementation)

🤝 Contributing

We welcome contributions! This is an active project with ongoing development.

# 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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