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react-native-ai-skills

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Provides integration recipes for the React Native AI @react-native-ai packages that wrap the Llama.rn (Llama.cpp), MLC-LLM, Apple Foundation backends. Use when integrating local on-device AI in React Native, setting up providers, model management.

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Source SKILL.md: https://github.com/callstackincubator/ai/blob/HEAD/skills/react-native-ai/SKILL.md

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React Native AI Skills

Overview

Example workflow for integrating on-device AI in React Native apps using the @react-native-ai ecosystem. Available provider tracks (can be combined):

  • Apple – Apple Intelligence (iOS 26+)
  • Llama – GGUF models via llama.rn
  • MLC – MLC-LLM models
  • NCNN – Low-level NCNN inference wrapper (vision, custom models)

Path Selection Gate (Must Run First)

Before selecting any reference file, classify the user request:

  1. Select Apple:
    • if you intend to build with: apple, Apple Intelligence, Apple Foundation Models
    • if you want features: transcription, speech synthesis, embeddings on Apple devices
    • optionally with capabilities: tool calling
  2. Select Llama:
    • if you intend to use the following technologies: llama, GGUF, llama.rn, HuggingFace, SmolLM
    • if you want to perform the following operations: embedding model, rerank, speech model
  3. Select MLC:
    • if you intend to use a library that allows for custom models and involves build-time model optimizations
  4. Select NCNN:
    • if you need to use run low-level inference on bare metal tensors
    • if you intend to run inference of custom models such as convolutional networks, multi-layer perceptrons, low-level inference, etc.
    • DO NOT select NCNN if the prompt mentions LLMs only, this use case is better solved by other providers

Skill Format

Each reference file follows a strict execution format:

  • Quick Command
  • When to Use
  • Prerequisites
  • Step-by-Step Instructions
  • Common Pitfalls
  • Related Skills

Use the checklists exactly as written before moving to the next phase.

When to Apply

Reference this package when:

  • Integrating on-device AI in React Native apps
  • Installing and configuring @react-native-ai providers
  • Managing model downloads (llama, mlc)
  • Wiring providers with Vercel AI SDK (generateText, streamText)
  • Implementing SetupAdapter pattern for multi-provider apps
  • Debugging native module or Expo plugin issues

Priority-Ordered Guidelines

PriorityCategoryImpactStart File
1Path selection and baselineN/Aquick-start
2Apple providerN/Aapple-provider
3Llama providerN/Allama-provider
4MLC-LLM providerN/Amlc-provider
5NCNN providerN/Ancnn-provider

Quick Reference

npm install

# Provider-specific install
npm add @react-native-ai/apple
npm add @react-native-ai/llama llama.rn
npm add @react-native-ai/mlc
npm add @react-native-ai/ncnn-wrapper

Route by path:

References

FileImpactDescription
quick-startN/AShared preflight
apple-providerN/AApple Intelligence setup and integration
llama-providerN/AGGUF models, llama.rn, model management
mlc-providerN/AMLC models, download, prepare, Expo plugin
ncnn-providerN/ANCNN wrapper, loadModel, runInference

Problem → Skill Mapping

ProblemStart With
Need path decision firstquick-start
Integrate Apple Intelligenceapple-provider
Run GGUF models from HuggingFacellama-provider
Run MLC-LLM models (Llama, Phi, Qwen)mlc-provider
Use NCNN for custom inferencencnn-provider
Multi-provider app with SetupAdapterquick-start → provider-specific
Expo + native module setupProvider-specific (each has Expo notes)