Building a Resilient Multi-Model AI Router in Python

When building AI-powered applications, it's easy to get started with a single large language model (LLM) provider. A quick pip install openai and you're off to the races. But what happens when that single provider experiences an outage? Or suddenly doubles its prices? Or when a competitor releases a model that's significantly better for a specific task or much cheaper? Relying on a single AI model is a single point of failure. It's an AI monoculture that leaves your application vulnerable to outages, performance degradation, and unexpected cost increases.