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One wrapper cuts API churn, but it also widens the supply-chain blast radius you own.
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I think almost everyone supports the openai api anyway (even Gemini). Not entirely sure why there needs to be a wrapper.
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Msot do, but Anthropic indicates that theirs is "is not considered a long-term or production-ready solution for most use cases" [0]; in any case, where the OpenAI-compatible API isn't the native API, both for cloud vendors other than OpenAI and for self-hosting software, the OpenAI-compatible API is often limited, both because the native API offers features that don't map to the OpenAI API (which a wrapper that presents an OpenAI-compatible API is not going to solve) and because the vendor often lags in implementing support for features in the OpenAI-compatible API—including things like new OpenAI endpoints that may support features that the native API already supports (e.g., adding support for chat completions when completions were the norm, or responses when chat completions were.) A wrapper that used the native API and did its own mapping to OpenAI could, in principle, address that.

[0] https://platform.claude.com/docs/en/api/openai-sdk

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>Programming for different LLM APIs is a hassle

That's what they pay us for

I'd get it if it were a hassle that could be avoided, but it feels like you are trying to avoid the very work you are being paid for, like if a MCD employee tried to pay a kid with Happy Meal toys to work the burger stand.

Another red flag, although a bit more arguable, is that by 'abstracting' the api into a more generic one, you achieving vendor neutrality, yes, but you also integrate much more loosely with your vendors, possibly loose unique features (or can only access them with even more 'hassle' custom options, and strategically, your end product will veer into commodity territory, which is not a place you usually want to be.

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There's only two different LLM APIs in practice (Anthropic and everyone else), and the differences are cosmetic.

This is like a couple hours of work even without vibe coding tools.

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> There's only two different LLM APIs in practice (Anthropic and everyone else), and the differences are cosmetic.

There's more than that (even if most other systems also provide a OpenAI compatible API which may or may not expose either all features of the platform or all features of the OpenAI API), and the differences are not cosmetic, but since LiteLLM itself just presents an OpenAI-compatible API, it can't be providing acccess to other vendor features that don't map cleanly to that API, and I don't think its likely to be using the native API for each and being more complete in its OpenAI-compatible implementation of even the features that map naturally than the first-party OpenAI-compatibility APIs.)

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