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How I added LLM fallback to my OpenAI app in 10 minutes

DEV Community·Jay·30 days ago
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How I added LLM fallback to my OpenAI app in 10 minutes You're running a production app on OpenAI. One Tuesday morning it goes down. Your app returns 500s. You spend an hour refreshing status.openai.com. There's a better setup. Here's how to add provider fallback to any OpenAI-SDK app without rewriting anything. The problem with single-provider setups When you call OpenAI directly, you have one point of failure: from openai import OpenAI client = OpenAI ( api_key = " sk-... " ) resp = client . chat . completions . create ( model = " gpt-4o-mini " , messages = [{ " role " : " user " , " content " : " Summarise this text... " }], ) Enter fullscreen mode Exit fullscreen mode If OpenAI returns a 500 or a 429, your user sees an error. You have no fallback, no visibility into what failed, and no easy way to route to a cheaper provider when you don't need GPT-4 quality. The fix: two lines and a gateway InferBridge is an OpenAI-compatible API gateway. You point the OpenAI SDK at it instead of OpenAI directly.…

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