Own your AI. The native macOS harness for AI agents -- any model, persistent memory, autonomous execution, cryptographic identity. Built in Swift. Fully offline. Open source.
A practical lab for building, testing, and evaluating apps with Apple's Foundation Models framework.
React Native Apple LLM plugin using Foundation Models
'afm' command cli: macOS server and single prompt mode that exposes Apple's Foundation and MLX Models and other APIs running on your Mac through a single aggregated OpenAI-compatible API endpoint. Supports Apple Vision and single command (non-server) inference with piping as well . Now with Web Browser and local AI API aggregator
Document chat app for macOS / iOS. Upload files, ask questions. Everything runs locally on your Mac / iPhone.
A Swift command-line interface tool for interacting with macOS Apple Intelligence foundation models.
TypeScript/Node.js bindings for Apple's on-device Foundation Models (macOS 26+ only)
Production-ready architectural patterns and implementation skills for building modern iOS apps with Swift, SwiftUI, and Tuist — designed as context for AI coding agents.
A collection of Agent Skills for building iOS/macOS applications with Apple's Foundation Models framework (Apple Intelligence). These skills are designed for zero-friction AI-assisted development with on-device models.
apfelclaw is an AI agent for tasks with macOS using Apple's Foundation model via apfel.
iOS app that turns Ray-Ban Meta smart glasses into a hands-free study tool. Scan documents, extract text with OCR, generate AI summaries with Apple Foundation Models (Apple's On-Device AI) or online LLM models and organize content into decks with flashcards and quizzes. Built with SwiftUI, SwiftData, Vision, PDFKit, and Meta Wearables SDK.
A collection of examples using Apple’s FoundationModels framework
Make Apple's Foundation Models accessible over web APIs
Apple Foundation Models server with OpenAI-like API.
Access Apple’s on-device Foundation Models in React Native
Crystal bindings for Apple's FoundationModels.framework
Fully offline iPhone meeting memory. Zero network calls, no Wi Fi required. Records, transcribes, summarises, and answers questions entirely on device. Audio, transcripts, summaries, embeddings, and chat never leave the phone.
Structured output generation for Swift. Define types that language models can generate with compile-time schema validation.
Run free on-device AI on your Mac with apfel, a Swift app that works without Xcode and keeps all inference local