I built a production ML inference API with FastAPI, Celery and Docker — here's the full architecture (opens in new tab)

Para 1 — The problem "Most ML tutorials end at model.fit(). Getting a model into production is a completely different skill. Here's how I built a real async inference microservice." Para 2 — Architecture diagram Paste the ASCII diagram from your ARCHITECTURE.md Para 3 — The three components FastAPI handles HTTP (why async matters) Celery handles background work (why not just threads) Redis handles both queue and results (why one service) Para 4 — Key code snippet (predict_async endpoint) Show...