Handling LLM API rate limits and downtime in production usually means adding retry logic with backoff, queuing requests during traffic spikes, and, for critical paths, having a fallback such as a secondary model provider or a cached response. Monitoring actual usage against the provider's published limits ahead of time avoids most rate-limit failures before they reach users.
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