Token Limits / Rate Limiting

AI providers enforce two types of limits: rate limits (requests per minute, tokens per minute) and token limits (maximum context window per request). OpenAI's free tier allows ~3 RPM (requests per minute) while paid tiers allow thousands. These limits protect provider infrastructure and prevent abuse. Rate limiting affects your application architecture. You need to: (1) implement retry logic with exponential backoff for 429 (rate limit) errors, (2) queue requests when approaching limits, (3) potentially use multiple API keys or providers for high-traffic apps, and (4) monitor usage to avoid unexpected outages. For production apps, rate limiting is a design constraint from day one. Solutions include: request queuing (buffer requests and process within limits), tiered processing (prioritize paying users), caching (avoid re-processing identical requests), and provider diversification (split traffic across OpenAI, Anthropic, and Google). Always implement graceful degradation: when limits are hit, show users a friendly message rather than an error.