HI ,
As we continue to integrate OpenAI’s models into our production workflows, it becomes essential to discuss and determine the most effective strategies for managing rate limits, both at the token and request levels. This topic aims to explore the nuanced approaches to handling rate limits and dives into two primary considerations: managing rate limits through custom headers (utilizing information such as remaining requests and tokens) versus relying on OpenAI’s default retry mechanisms.
I’d love to hear some thoughts on this, any strategies
Cheers