Aeru: Enhanced Apple Intelligence

An intelligent iOS application that combines Retrieval-Augmented Generation (RAG) and Web Search functions to provide contextually aware AI responses.

Aeru is a powerful iOS app that leverages Apple’s FoundationModels framework to deliver intelligent responses by searching both local knowledge bases and real-time web content. Built with SwiftUI and optimized for iOS, it provides a seamless chat interface for enhanced AI interactions.

👨🏽‍💻 Demo Video

📱 TestFlight Download

• Must use an Apple Intelligence activated device
• Latest version of iOS 26 Beta (Dev Beta 5, Public Beta 2)

💬 Discord Community

✨ Features

🧠 Dual Intelligence Sources

• RAG System: Search through local vector databases for relevant context
• Web Search: Real-time web scraping via DuckDuckGo for up-to-date information

🚀 Advanced AI Capabilities

• Apple FoundationModels: Native integration with Apple’s language models
• Vector Embeddings: Semantic search using NaturalLanguage framework
• Streaming Responses: Real-time response generation with live updates
• Context Awareness: Maintains conversation history for coherent interactions

💻 Native iOS Experience

• SwiftUI Interface: Modern, responsive design optimized for iOS
• Chat Sidebar: Organized conversation management
• Keyboard Shortcuts: Efficient navigation and interaction
• Document Processing: Support for various file formats in the knowledge base

🔧 Technical Excellence

• Vector Database: SVDB integration for efficient similarity search
• Web Scraping: SwiftSoup for clean content extraction
• Rate Limiting: Respectful web scraping with built-in delays
• Error Handling: Robust error management and graceful degradation

🛠 Installation

Prerequisites

• iPhone 15 Pro or higher end model REQUIRED
• iOS 26.0 DEV 5/PUBLIC BETA 2 REQUIRED+
• Xcode 16.0+
• Swift 6+

Setup Instructions

Clone the Repository

git clone https://github.com/yourusername/aeru.git
cd aeru

Open in Xcode

open ../Aeru.xcodeproj

Install Dependencies Dependencies are automatically managed through Xcode’s built-in Swift Package Manager integration. The following packages will be resolved automatically:

• SVDB: Vector database operations
• SwiftSoup: HTML parsing and content extraction
• FoundationModels: Apple’s language model framework
• NaturalLanguage: Text embeddings and processing
• Accelerate: High-performance vector operations

Build and Run

• Press Cmd+R or click the play button in Xcode
• The app will launch with the main chat interface

🚦 Usage

Basic Chat Interface

1. Start a Conversation: Type your question in the input field
2. Choose Search Mode:

• Use RAG for queries about your local knowledge base
• Use web search for current events and real-time information

1. View Responses: Watch as responses stream in real-time
2. Manage Conversations: Use the sidebar to organize multiple chat sessions

RAG (Local Knowledge Base)

• Add Documents: Process documents into the vector database
• Semantic Search: Find relevant content using natural language queries
• Context Integration: Retrieved content enhances AI responses

Web Search

• Real-time Results: Get current information from the web
• Smart Scraping: Clean content extraction from top search results
• Source Attribution: Responses include source information

🏗 Architecture

Core Components

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│  AeruView.swift │    │    LLM.swift    │    │  RAGModel.swift │
│   (UI Layer)    │◄──►│ (Orchestrator)  │◄──►│ (Vector DB)     │
└─────────────────┘    └─────────────────┘    └─────────────────┘
│
▼
┌─────────────────┐
│WebSearchService │
│ (Web Scraping)  │
└─────────────────┘

Data Flow

1. User Input → AeruView captures user queries
2. Query Processing → LLM class determines search strategy
3. Context Retrieval → RAGModel searches vector database OR WebSearchService scrapes web
4. AI Generation → FoundationModels generates contextual responses
5. UI Updates → Streaming responses update the interface in real-time

Key Technologies

• SwiftUI: Reactive UI framework
• Combine: Reactive programming for data flow
• FoundationModels: Apple’s ML framework
• Vector Embeddings: NaturalLanguage + Accelerate
• Web Scraping: URLSession + SwiftSoup

🤝 Contributing

We welcome contributions! Here’s how you can help:

Development Setup

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Make your changes and test thoroughly
4. Commit with clear messages: git commit -m 'Add amazing feature'
5. Push to your branch: git push origin feature/amazing-feature
6. Open a Pull Request

Code Standards

• Follow Swift API Design Guidelines
• Use SwiftUI best practices
• Include unit tests for new functionality
• Maintain documentation for public APIs
• Ensure Xcode builds without warnings

Areas for Contribution

• 🐛 Bug Fixes: Help improve stability
• ✨ Features: Add new capabilities
• 📚 Documentation: Improve guides and examples
• 🧪 Testing: Expand test coverage
• 🎨 UI/UX: Enhance user experience

Wishlist Updates

• 🤖 MCP Server Support: Create curated list of MCP Servers to connect and use on-device
• 🎤 Voice Mode: Enable voice mode to interact with the AI hands free

📄 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

🙏 Acknowledgments

• Apple: For FoundationModels and NaturalLanguage frameworks
• SVDB: Vector database library
• SwiftSoup: HTML parsing capabilities
• Open Source Community: For inspiration and support

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Built with ❤️ for the iOS community