62 lines
3.4 KiB
Markdown
62 lines
3.4 KiB
Markdown
---
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name: foundation-models
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description: Use when implementing on-device AI with Apple's Foundation Models framework (iOS 26+), building summarization/extraction/classification features, or using @Generable for type-safe structured output.
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---
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# Foundation Models
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Apple's on-device AI framework providing access to a 3B parameter language model for summarization, extraction, classification, and content generation. Runs entirely on-device with no network required.
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## Overview
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Foundation Models enable intelligent text processing directly on device without server round-trips, user data sharing, or network dependencies. The core principle: leverage on-device AI for specific, contained tasks (not for general knowledge).
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## Reference Loading Guide
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**ALWAYS load reference files if there is even a small chance the content may be required.** It's better to have the context than to miss a pattern or make a mistake.
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| Reference | Load When |
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|-----------|-----------|
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| **[Getting Started](references/getting-started.md)** | Setting up LanguageModelSession, checking availability, basic prompts |
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| **[Structured Output](references/structured-output.md)** | Using `@Generable` for type-safe responses, `@Guide` constraints |
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| **[Tool Calling](references/tool-calling.md)** | Integrating external data (weather, contacts, MapKit) via Tool protocol |
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| **[Streaming](references/streaming.md)** | AsyncSequence for progressive UI updates, PartiallyGenerated types |
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| **[Troubleshooting](references/troubleshooting.md)** | Context overflow, guardrails, errors, anti-patterns |
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## Core Workflow
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1. Check availability with `SystemLanguageModel.default.availability`
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2. Create `LanguageModelSession` with optional instructions
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3. Choose output type: plain String or @Generable struct
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4. Use streaming for long generations (>1 second)
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5. Handle errors: context overflow, guardrails, unsupported language
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## Model Capabilities
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| Use Case | Foundation Models? | Alternative |
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|----------|-------------------|-------------|
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| Summarization | Yes | - |
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| Extraction (key info) | Yes | - |
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| Classification | Yes | - |
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| Content tagging | Yes (built-in adapter) | - |
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| World knowledge | No | ChatGPT, Claude, Gemini |
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| Complex reasoning | No | Server LLMs |
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## Platform Requirements
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- iOS 26+, macOS 26+, iPadOS 26+, visionOS 26+
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- Apple Intelligence-enabled device (iPhone 15 Pro+, M1+ iPad/Mac)
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- User opted into Apple Intelligence
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## Common Mistakes
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1. **Using Foundation Models for world knowledge** — The 3B model is trained for on-device tasks only. It won't know current events, specific facts, or "who is X". Use ChatGPT/Claude for that. Keep prompts to: summarizing user's own content, extracting info, classifying text.
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2. **Blocking the main thread** — LanguageModelSession calls must run on a background thread or async context. Blocking the main thread locks UI. Always use `Task { }` or background queue.
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3. **Ignoring context overflow** — The model has finite context. If the user pastes a 50KB document, it will fail silently or truncate. Check input length and trim/truncate proactively.
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4. **Forgetting to check availability** — Not all devices support Foundation Models. Check `SystemLanguageModel.default.availability` before using. Graceful degradation is required.
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5. **Ignoring guardrails** — The model won't answer harmful queries. Instead of fighting it, design prompts that respect safety guidelines. Rephrasing requests usually works.
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