AppleFoundationModels

What problem does it solve?

Developers want to integrate powerful AI capabilities into their Apple applications while ensuring user privacy, offline functionality, and structured, reliable outputs. This Skill provides a comprehensive guide to leveraging Apple's on-device Foundation Models framework for natural language understanding, guided generation, and tool invocation.

Core Features & Use Cases

• On-Device AI: Utilizes Apple's ~3 billion-parameter LLM running entirely on-device, ensuring privacy and offline access without data leaving the device.
• Structured Output: Employs @Generable and @Guide macros to guarantee model responses conform to specific Swift types, eliminating unreliable string parsing.
• Tool Invocation: Extends model capabilities by allowing it to autonomously call custom app functions (tools) to fetch real-time data or perform actions beyond its built-in knowledge.
• Use Case: An app developer wants to add a feature that summarizes user notes and extracts key action items. This Skill guides them to use the Foundation Models framework for NLU and structured output, ensuring the extracted data is always in a usable format and user data remains private.

Quick Start

Help me integrate Apple's Foundation Models into my iOS app to extract structured data from user text, ensuring the output is always a valid Swift struct.