llm-rate-limiting

To prevent LLM API quota exhaustion, implement rate limiting strategies like token bucket or sliding window algorithms to control request flow and stay within allowed limits. This ensures continuous API access without unexpected interruptions.

The best way to handle rate limit errors and manage burst traffic is by applying exponential backoff strategies and parsing API-specific rate limit headers. This approach automatically pauses and retries requests, preventing failed responses.

You manage concurrent requests to an LLM API by implementing concurrency limiting algorithms. These algorithms control the number of simultaneous requests, ensuring fair usage policies and preventing server overload during high traffic periods.

A token bucket rate limiter works by maintaining a capacity of tokens that refill at a set rate, such as 1000 tokens per minute. Each API request consumes tokens, allowing controlled burst traffic while enforcing a steady average rate.

You need concurrency limiting to prevent hitting API rate limits because it restricts the number of simultaneous in-flight requests. Combined with quota management, it ensures your application respects both per-minute requests and daily token limits.