How to rate limit AI features and avoid surprise costs

As AI-powered chat applications become increasingly prevalent, managing costs and preventing abuse through effective rate limiting is crucial, particularly for cloud-based language model (LLM) providers like OpenAI and Anthropic, where a single session can trigger numerous costly inference requests. This guide explores the implementation of rate limiting on Netlify to control the number of requests a client can make within a given timeframe, thereby safeguarding resources and preventing unexpected expenses. Unlike traditional web endpoints, AI endpoints incur costs based on token consumption, making usage forecasting challenging. Netlify offers code-based and UI-based rate limiting options, allowing users to set request limits, block excessive requests, or redirect to custom error pages, ensuring smoother operations and preventing malicious activity. This document provides a comprehensive tutorial on building a rate-limited AI chat endpoint using Netlify's serverless functions, including setting up the project, configuring rate limits, handling responses, and monitoring usage to fine-tune limits for optimal performance and cost management.

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