[tobyjsullivan]

I’m only looking at it for the first time but it looks like a framework to me. And that promises all the usual benefits (and drawbacks) of any framework.

- learning the framework is a one-time cost that pays dividends over multiple projects. Subsequent products can be built by only implementing the domain-specific stuff above the framework.

- presumably the stuff solved by the framework is non-trivial. It might be “obvious” (in hindsight) but chances are the framework designer has thought about it much more than we want to.

- (theoretical) the framework will outlive any single generation of LLM. This is a fast-moving space and learning a new API or model every few months isn’t going to be fun. Hopefully the framework will adapt and adopters can transition to new models using one framework they already know.

Only the third really applies to an existing project adopting the framework. Is that applicable in your case?

[killthebuddha]

Ironically, LangChain is basically DOA with OpenAI's plugins release. LangChain would still be useful for multi-model applications, but every other sufficiently powerful model will probably just build the same thing.

[satvikpendem]

It would still work for more open LLMs like LLaMA and Alpaca, no? Because I don't think OpenAI's plugins are open source nor would they work outside of their GPT.