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I've been using the JS version of langchain for a few months now, and despite there being a lot of valid criticism, (especially around the abstractions it provides) I'm still glad to be using it.

We get the benefits of a well used library, which means making certain changes is easy. For example, swapping our vector database was a one line change, as was swapping our cache provider. When OpenAI released GPT-4, we were able to change one parameter, and everything still just worked.

Sure, it's moving fast, and could use a lot better documentation. At this point, I've probably read the entire source code several times over. But when we start testing performance of different models, or decide that we need to add persistent replayability to chains of LLM calls, it should be pretty easy. These things matter to production applications.




> When OpenAI released GPT-4, we were able to change one parameter, and everything still just worked.

Wouldn't that be the same if you used the OAI js library directly? Basically swapping the model parameter?


It's not. The API is different, since GPT-4 is a chat based model, and davinci isn't. It's not a huge difference, but these little sort of things add up.


It is a very minor change (made the changes in minutes and didn't have to bring in a new framework for it).


Agreed. It's a trivial change, certainly not a justification for using langchain.


I see, thought you were using GPT-3.5 and moved to GPT-4.




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