MED VQA

Users can upload medical imagery (such as X-rays, MRIs, or histology slides), and the system uses a Vision-Language Model (VLM) combined with a Vector Database to identify physical anomalies, retrieve relevant medical literature, and generate a cited diagnostic summary. To demonstrate cloud infrastructure and MLOps competency, the entire application will be decoupled into microservices and containerized using Docker.