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The LLM ecosystem has seen an explosion of frameworks, particularly in JavaScript and Python. While popular, these frameworks often serve two purposes: they either hide language limitations around concurrency or task orchestration, or they abstract "common" LLM operations. But do we really need this abstraction? Usually we would be better off building simple, bespoke solutions.
I've found, and from what I've seen the general consensus online as well is, that a lot of these frameworks work well enough for a POC but as the project grows and needs for custom behaviours arise, it's failing to meet the challenge.
langchain isn't a library, it's a collection of demos held together by duct tape, fstrings and prayers. It doesn't provide building blocks, it provides someone's fantasy of one line of code is all you need. And it mainly breaks apart if you're using anything but openai.
Disastrous_Elk_6375 on reddit
I'd only use it to quickly validate some ideas, PoC style to test the waters, but for sanity and production you need to pick alternatives or write your own stack.
continue reading on goto-code.com
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