标签：#appbuilder

If you need a free AI app builder with backend to get a FastAPI microservice running today, you can do it with a handful of platforms that bundle hosting, a database, and auth for zero cost. The catch is that the free tiers have hard limits, and they expose the same failure modes you’ll hit in production if you’re not careful. Below I walk through the exact steps, show the code that works, compare the popular builders, and explain how to transition to a production-grade stack when the free tier starts to choke. What free AI app builder platforms include backend services? The short answer is: Cursor , Bolt , and Lovable all ship with a “one-click deploy” that creates a container, wires up a PostgreSQL instance, and adds optional OAuth. They are marketed as “no-code AI app builders,” but you can drop in any Dockerfile – including one that runs FastAPI – and they’ll handle the rest. Platform Backend offering Free tier limits Auth support Cursor Managed container + Postgres 13 500 MB RAM, 1 CPU, 100 k requests/mo Google, GitHub, email Bolt Container + SQLite (upgrade to Postgres) 256 MB RAM, 0.5 CPU, 50 k requests/mo Magic link, JWT Lovable Container + MySQL 5.7 300 MB RAM, 1 CPU, 75 k requests/mo Email/password, OAuth All three let you push a Git repo and they rebuild automatically. That’s the “free AI app builder with backend” you’re after – you get a place to run your FastAPI code without paying for a VM. How do I build a FastAPI AI microservice and deploy it with a free builder? The first thing most builders break on is the cold-start latency of a Python container that pulls a large model at import time. I’ve been bitten by this on Cursor: the first request took 30 seconds, then timed out because the free tier caps request time at 15 seconds. The fix is to load the model lazily or move it to a separate worker. Below is a minimal FastAPI app that calls Claude via the anthropic SDK. The code fits in a 30-line file and works on any of the three platforms. # main.py fro