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: chatbots and assistants, image classification, object detection, OCR and document parsing, style transfer, image generation, speech-to-text, text-to-speech, 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, model loading, and resource management.