Not sure if I agree here. Langchain's LLMChains while initially popular, is not what people have been using. With function calling and agent+tools, both langchain and chatgpt do quite a lot of the same things that semantic kernel does.
You've mentioned a few things that langchain doesn't offer and I'm not sure how true that is. Langchain has a typescript offering which is easier to interweave with traditional coding, and if you're even the tiniest bit serious about your ML system then you'll likely use python anyway.
Langchain is a bunch of thin abstractions that can quickly scale up with the pace of growth in the LLM world. All the features you mention are now mature features within langchain too.
I'm genuinely interested in semantic kernel, and langchain has obvious pitfalls. But I am yet to find another solution that moves as quickly, integrates broadly, has a large community and still ends up being an acceptable product from a quality standpoint.
You've mentioned a few things that langchain doesn't offer and I'm not sure how true that is. Langchain has a typescript offering which is easier to interweave with traditional coding, and if you're even the tiniest bit serious about your ML system then you'll likely use python anyway.
Langchain is a bunch of thin abstractions that can quickly scale up with the pace of growth in the LLM world. All the features you mention are now mature features within langchain too.
I'm genuinely interested in semantic kernel, and langchain has obvious pitfalls. But I am yet to find another solution that moves as quickly, integrates broadly, has a large community and still ends up being an acceptable product from a quality standpoint.