react-native-ai-skills

name	react-native-ai-skills
description	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.
license	MIT
metadata	{"author":"Callstack","tags":"react-native, ai, llama, apple, mlc, ncnn, vercel-ai-sdk, on-device"}

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

Priority	Category	Impact	Start File
1	Path selection and baseline	N/A	quick-start
2	Apple provider	N/A	apple-provider
3	Llama provider	N/A	llama-provider
4	MLC-LLM provider	N/A	mlc-provider
5	NCNN provider	N/A	ncnn-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:

• Apple: apple-provider
• Llama: llama-provider
• MLC: mlc-provider
• NCNN: ncnn-provider

References

File	Impact	Description
quick-start	N/A	Shared preflight
apple-provider	N/A	Apple Intelligence setup and integration
llama-provider	N/A	GGUF models, llama.rn, model management
mlc-provider	N/A	MLC models, download, prepare, Expo plugin
ncnn-provider	N/A	NCNN wrapper, loadModel, runInference

Problem → Skill Mapping

Problem	Start With
Need path decision first	quick-start
Integrate Apple Intelligence	apple-provider
Run GGUF models from HuggingFace	llama-provider
Run MLC-LLM models (Llama, Phi, Qwen)	mlc-provider
Use NCNN for custom inference	ncnn-provider
Multi-provider app with SetupAdapter	quick-start → provider-specific
Expo + native module setup	Provider-specific (each has Expo notes)

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Source: callstackincubator/ai — distributed by TomeVault.