apple-foundation-models

On-device AI processes data locally using Apple's Foundation Models framework, ensuring privacy and offline functionality by leveraging SystemLanguageModel and LanguageModelSession without sending data off-device.

You can generate structured Swift types from prompts using the guided generation feature of Apple's Foundation Models, ensuring type-safe output directly within your iOS or macOS application.

Yes, Foundation Models support tool calling in macOS applications, allowing the on-device LLM to interact with custom tools and APIs to extend model functionality.

Yes, on-device AI with Apple's Foundation Models works offline by processing local LLM tasks directly on iOS and macOS devices, ensuring privacy and functionality without an internet connection.

On-device Foundation Models are limited by hardware capabilities and local memory, meaning complex natural language understanding tasks may perform slower than server-side LLMs, though they ensure privacy and offline functionality.

You manage transcripts and custom adapters within a LanguageModelSession using Apple's Foundation Models framework to handle dynamic conversations and customize on-device LLM behavior in iOS/macOS apps.