A few months ago I was building a personal project that needed to generate structured data from natural language. I started with OpenAI's GPT-4 because, well, everyone does. The code worked, the responses were great, and I thought I was done. Then Anthropic released Claude 3, and the benchmarks looked promising. I wanted to try it—just swap one model for another to compare quality and cost.
That turned into an entire weekend of refactoring.
Different SDKs. Different authentication. Different response objects. Even the way you handle streaming (or don't) changed completely. By the end I had a messy pile of if provider == "openai": ... elif provider == "anthropic": ... blocks that made me feel like I'd written JavaScript in 2014.
I knew I couldn't be the only one dealing with this. Every week there's a new model or a new API. The idea of being locked into one provider felt both brittle and inefficient. So I set out to build a thin abstraction that would let me swap AI providers without rewriting my entire codebase.
What I tried first (and why it didn't work)
