Developers Build AI Medicine Assistant Using YOLOv10 and RAG to Detect Drug Interactions

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A tutorial published on DEV Community outlines how to build a Smart Home Medicine Assistant that identifies medication packaging using YOLOv10, a real-time object detection model. The system scans images or video of medicine blister packs and cross-references detected drugs against validated medical databases to flag potential Drug-Drug Interaction (DDI) risks. Redis is used to maintain a session-based medication history, while OpenAI Function Calling connects the vision model to the DrugBank API to retrieve accurate interaction data instead of relying on AI-generated guesses. The backend is built with FastAPI, and the pipeline is designed to run on edge devices such as smart mirrors or mobile applications. The project aims to offer a more reliable alternative to searching the internet for medication safety information.

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