Learning the Ropes for Your Next LangChain Project

Large language models entered the mainstream last year as tools for fun—and occasionally downright silly—experimentation. Who among us hasn’t challenged ChatGPT to invent a new knock-knock joke or compose a Shakespearean sonnet about puppies?

As the power of LLMs became increasingly apparent, so did their limitations. Machine learning practitioners and app builders quickly realized that there’s only so much you can do with models that can’t obtain up-to-date information and remain hermetically shut off from each other.

Luckily, we already …

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