Programming Tutorials

  You check your OpenAI dashboard. Your billing status is green. You have $50 in available credits. Yet, your application logs are flooded with   429: Too Many Requests   errors. This is the single most common source of frustration for developers integrating Large Language Models (LLMs). The confusion stems from a fundamental misunderstanding of how OpenAI separates  Billing Quotas  from  Rate Limits . Having money in your account does not grant you unlimited throughput. This article dissects the specific mechanics of Token Per Minute (TPM) and Request Per Minute (RPM) limits and provides a production-grade TypeScript implementation for handling them via Exponential Backoff. The Root Cause: Quota vs. Rate Limits To fix the error, you must understand precisely why the API is rejecting your request. OpenAI enforces limits on two distinct axes. 1. Usage Quota (The "Wallet") This is a hard cap on the total dollars you can spend in a month. If you hit this, you ...