on-device-ai
Best practices for building on-device AI features in React Native using React Native ExecuTorch. Use when the user wants to add AI to a mobile app without cloud dependencies: AI chatbots and assistants, image classification, object detection, text recognition and document parsing (OCR), style transfer, image generation, speech-to-text transcription, text-to-speech synthesis, voice activity detection, semantic search with embeddings, real-time camera AI with VisionCamera, or vision-language image understanding. Also use when the user mentions offline AI, on-device ML, privacy-preserving AI, reducing cloud API costs or latency, running models locally on mobile, or downloading and managing ML models. Covers react-native-executorch hooks (useLLM, useClassification, useObjectDetection, useOCR, useSemanticSegmentation, useInstanceSegmentation, useStyleTransfer, useTextToImage, useImageEmbeddings, useSpeechToText, useTextToSpeech, useVAD, useTextEmbeddings, useExecutorchModule), tool calling, structured output, VLMs
Installation and usage
Best practices for building on-device AI features in React Native using React Native ExecuTorch. Use when the user wants to add AI to a mobile app without cloud dependencies: AI chatbots and assistants, image classification, object detection, text recognition and document parsing (OCR), style transfer, image generation, speech-to-text transcription, text-to-speech synthesis, voice activity detection, semantic search with embeddings, real-time camera AI with VisionCamera, or vision-language image understanding. Also use when the user mentions offline AI, on-device ML, privacy-preserving AI, reducing cloud API costs or latency, running models locally on mobile, or downloading and managing ML models. Covers react-native-executorch hooks (useLLM, useClassification, useObjectDetection, useOCR, useSemanticSegmentation, useInstanceSegmentation, useStyleTransfer, useTextToImage, useImageEmbeddings, useSpeechToText, useTextToSpeech, useVAD, useTextEmbeddings, useExecutorchModule), tool calling, structured output, VLMs
Après l'installation, vous pouvez utiliser ce skill en exécutant la commande suivante dans votre terminal :
skills use on-device-ai