Programming Tutorials

  Your application is scaling. Users are engaging with your AI features. Then, suddenly, your logs are flooded with red text, and your support tickets spike. The culprit:   openai.RateLimitError . Handling API rate limits is the difference between a prototype and a production-grade system. When relying on third-party dependencies like OpenAI, network flakiness and strict quotas are inevitable constraints, not unexpected errors. This guide provides a rigorous, drop-in solution to handle  429 Too Many Requests  errors using Python and the  tenacity  library. We will move beyond simple  try/except  blocks to implement industry-standard exponential backoff with jitter. The Root Cause: Why 429 Errors Occur Before implementing the fix, it is crucial to understand the mechanics of the error. A  429  status code indicates that you have exceeded the quota assigned to your API key. OpenAI enforces limits on three dimensions: RPM (Requests Per Minu...