Build on-device AI features in React Native and Expo apps with React Native ExecuTorch. Use when adding AI to a mobile app without cloud dependencies — chatbots and assistants, image classification, object detection, OCR, semantic or instance segmentation, style transfer, image generation, pose estimation, speech-to-text, text-to-speech, voice activity detection, semantic search with embeddings, tokenization, privacy filtering / PII redaction, or vision-language image understanding. Also use wh…
Build on-device AI features in React Native and Expo apps with React Native ExecuTorch.
Use when adding AI to a mobile app without cloud dependencies — chatbots and assistants, image classification, object detection, OCR, semantic or instance segmentation, style transfer, image generation, pose estimation, speech-to-text, text-to-speech, voice activity detection, semantic search with embeddings, tokenization, privacy filtering / PII redaction, or vision-language image understanding.
Also use when the user mentions offline AI, on-device ML, privacy-preserving AI, reducing cloud API cost or latency, running models locally on mobile, or downloading and managing ML models.
Covers initExecutorch, every public hook (useLLM, useClassification, useObjectDetection, useOCR, useVerticalOCR, useSemanticSegmentation, useInstanceSegmentation, useStyleTransfer, useTextToImage, useImageEmbeddings, usePoseEstimation, useSpeechToText, useTextToSpeech, useVAD, useTextEmbeddings, useTokenizer, usePrivacyFilter, useExecutorchModule), tool calling, structured output, VLMs, model loading via Expo or bare resource-fetcher adapters, and error handling.
Stronger alternatives
This repository is archived — consider an actively maintained alternative.
Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.
Claude CodeNot declared
CursorNot declared
CodexNot declared
GitHub CopilotNot declared
WindsurfNot declared
Gemini CLINot declared
ClineNot declared
OpenCodeNot declared
Repository health
Stars1.7K
LicenseLICENSE
Default branchmain
Open issues44
Status
Archived
Package contents
Files included with this skill beyond the listing page.
skill mdSKILL.md10,035 B
docsSUMMARY.md1,178 B
History
First seen on skills.sh
First recorded snapshot · 10 installs
SKILL.md
React Native ExecuTorch
Software Mansion's production patterns for on-device AI in React Native and Expo using React Native ExecuTorch.
Targets the current published API (v0.10.x). Load at most one reference file per question. For hook signatures, model constants, or config options not covered here, webfetch the matching page from docs.swmansion.com/react-native-executorch.
Decision Tree
What does the feature need?
│
├── Generate / chat with text?
│ └── useLLM → see llm.md
│ ├── Plain chat → standard useLLM
│ ├── Image + text input → useLLM with a VLM model (LFM2_VL_*)
│ ├── Tool / function calling → configure with toolsConfig
│ └── Structured JSON output → getStructuredOutputPrompt
│
├── Understand or transform images?
│ ├── What is in this image? → useClassification → see vision.md
│ ├── Where are the objects? → useObjectDetection → see vision.md
│ ├── Per-pixel class → useSemanticSegmentation → see vision.md
│ ├── Per-instance segmentation → useInstanceSegmentation → see vision.md
│ ├── Human pose keypoints → usePoseEstimation → see vision.md
│ ├── Read text from image → useOCR / useVerticalOCR → see vision.md
│ ├── Apply artistic style → useStyleTransfer → see vision.md
│ ├── Generate image from prompt → useTextToImage → see vision.md
│ └── Embed image as vector → useImageEmbeddings → see vision.md
│
├── Speech / audio?
│ ├── Transcribe speech → useSpeechToText → see speech.md
│ ├── Synthesize speech → useTextToSpeech → see speech.md
│ └── Detect speech segments → useVAD → see speech.md
│
├── Text utilities?
│ ├── Embed text as vector → useTextEmbeddings → see vision.md
│ ├── Count or inspect tokens → useTokenizer → see setup.md
│ └── Redact PII from text → usePrivacyFilter → see setup.md
│
├── Full RAG pipeline (retrieval + generation + vector store)?
│ └── react-native-rag (sibling library) → see setup.md
│
└── Custom `.pte` model not covered by a dedicated hook?
└── useExecutorchModule → see setup.md
Critical Rules
Call initExecutorch() at app entry, before any other API. The library does not bundle a network/file layer — you must register a resource-fetcher adapter (ExpoResourceFetcher for Expo, BareResourceFetcher for bare RN). Any hook called before initialization throws ResourceFetcherAdapterNotInitialized.
Check isReady before calling forward / generate / transcribe. All hooks load asynchronously. Inference before the model is ready throws ModuleNotLoaded.
Interrupt LLM generation before unmounting. Unmounting while isGenerating is true crashes. Call llm.interrupt() and wait for isGenerating === false before navigating away.
Use quantized model variants on mobile. Full-precision variants exceed device memory on most phones. Every supported model ships a _QUANTIZED variant — prefer it unless you've measured otherwise.
Audio for speech-to-text and VAD must be 16 kHz mono. Mismatched sample rates produce silently garbled transcriptions. Decode with new AudioContext({ sampleRate: 16000 }).
Audio from text-to-speech is 24 kHz. Create the playback context with new AudioContext({ sampleRate: 24000 }).
The New Architecture (Fabric) is required. Old architecture is unsupported. Expo Go is unsupported — use a custom dev build (npx expo prebuild). iOS release builds need a real device (the simulator lacks the Metal APIs ExecuTorch relies on).
Minimal Setup
// App.tsx (Expo)
import { initExecutorch } from 'react-native-executorch';
import { ExpoResourceFetcher } from 'react-native-executorch-expo-resource-fetcher';
initExecutorch({ resourceFetcher: ExpoResourceFetcher });
Full setup, Metro config for bundled .pte files, custom adapters, model-loading strategies, and error handling: see [setup.md](./references/setup.md).
Hook Quick Reference
Hook
Purpose
Reference
useLLM
Text generation, chat, tool calling, VLM
[llm.md](./references/llm.md)
useClassification
Image categorisation
[vision.md](./references/vision.md)
useObjectDetection
Bounding-box detection (YOLO26, RF-DETR, SSDLite)
[vision.md](./references/vision.md)
useSemanticSegmentation
Per-pixel class segmentation
[vision.md](./references/vision.md)
useInstanceSegmentation
Per-instance segmentation
[vision.md](./references/vision.md)
usePoseEstimation
COCO 17-keypoint human pose
[vision.md](./references/vision.md)
useStyleTransfer
Artistic image filters
[vision.md](./references/vision.md)
useTextToImage
Stable Diffusion image generation
[vision.md](./references/vision.md)
useImageEmbeddings
CLIP image embeddings
[vision.md](./references/vision.md)
useOCR
Horizontal text OCR
[vision.md](./references/vision.md)
useVerticalOCR
Vertical text OCR (experimental, CJK)
[vision.md](./references/vision.md)
useTextEmbeddings
Sentence embeddings for similarity / RAG
[vision.md](./references/vision.md)
useSpeechToText
Whisper transcription (batch + streaming)
[speech.md](./references/speech.md)
useTextToSpeech
Kokoro TTS (batch + streaming, phoneme input)
[speech.md](./references/speech.md)
useVAD
FSMN voice activity detection
[speech.md](./references/speech.md)
useTokenizer
HuggingFace-compatible tokenization
[setup.md](./references/setup.md)
usePrivacyFilter
On-device PII / privacy redaction
[setup.md](./references/setup.md)
useExecutorchModule
Custom .pte model inference
[setup.md](./references/setup.md)
Every hook also has a non-React Module counterpart (e.g. LLMModule.fromModelName(...), ClassificationModule.fromModelName(...)) for use outside React components.
Common Pitfalls
Symptom
Likely cause
Fix
ResourceFetcherAdapterNotInitialized
initExecutorch not called
Call it at app entry with an adapter
ModuleNotLoaded
Inference before model finished loading
Gate calls on isReady
MemoryAllocationFailed on launch
Model too large for device
Switch to _QUANTIZED variant or smaller parameter count
App crashes on screen navigation
Unmount during active generation
llm.interrupt() and await isGenerating === false
Whisper produces garbled text
Wrong sample rate
Decode audio at 16 kHz mono
TTS output sounds chipmunked
Playback context at wrong rate
Create AudioContext({ sampleRate: 24000 })
Build fails on iOS simulator (release)
Simulator lacks Metal APIs
Build release on real device
Full error code list and recovery patterns: [setup.md](./references/setup.md).
initExecutorch, Expo / bare resource-fetcher adapters, model loading strategies, Metro config, error codes and recovery, useExecutorchModule for custom .pte models, useTokenizer, usePrivacyFilter, full model catalogue