I feel the same! Just look at all the separate classes for different model providers for tackling minor input/output differences.

As for the alternatives, I think there are 3 things to think about: 1. LLM call itself 2. Orchestration of calls & monitoring/input/output 3. Integrations with external services

For #1, if we were to limit the discussion to model providers with REST APIs (OpenAI, Anthropic, Google, Cohere, Groq, Together, ElevenLabs all have them), I think it would be much simpler to build a simple wrapper directly on top of fetch or equivalent APIs and even skip the SDKs.

For #2, don't think LangChain is a better solution than alternatives like state charts.

#3 is where LangChain might offer some value, but it's pretty thin.