There is a basic concern I have that some eventual bug/poor coding may lead to an infinite loop of GPT API calls that will blow a hole in my finance and I may not realize it until it is too late. So I was curious how people prevent this scenario.
I know in AWS you can set up a monthly cost/budget, where it will alert you if you hit [x%] of budget. But of course, I run the risk of missing the alert or it could be too late by the time I see the alert. So I was wondering how people deal with this potential scenario?
(to be clear - I am not talking about cost optimization. I just want some way to prevent cost from ‘blowing up’ due to an infinite loop or something of that nature)
I was wondering if there are some type of cost safeguards I could put in place.
This is an understandable concern. You can set both budget alerts and monthly hard limits for spend at https://platform.openai.com/settings/organization/limits . I’m not aware if you can get more granular than that though (ie, limits per project/api key), but the global limit can prevent the worse bugs.
The org-level hard limit + budget alert DNGros mentioned is the right first line of defense, but worth knowing its limits for the “infinite loop” scenario specifically: the built-in budget alert is a single email once you cross the threshold, with no earlier warning tier, and it’s org-wide rather than something you’d notice mid-incident unless you’re actively watching your inbox.
If you want graduated warnings instead of one alert at the limit (free tier emails once you hit 100%; a paid tier adds earlier 50%/80% warnings), I built a small tool for exactly this after hitting the same worry myself — it’s called Fusebox, it polls the usage/costs API on a schedule and emails you before you’re already at the limit. Search “Fusebox” on Gumroad if you want to try it. It can’t stop a runaway loop by itself (nothing short of the org hard limit truly can), but it buys earlier warning than a single alert.