Sequoia declined to comment, and LangChain did not respond to a request for comment.
LangChain was originally launched last October as an open-source project by Harrison Chase while working as an engineer at machine-learning startup Robust Intelligence. The project quickly caught on within the developer community, spawning lively online forums across Twitter, GitHub, and Discord, offline meetups from San Francisco to London, and crowd-sourced changes from hundreds of contributors, Madrona partner Jon Turow told Insider.
The startup aims to help developers build more complex AI applications by combining the power of large language models likewith other sources of computation and knowledge. It achieves this by providing users with the ability to split up complex tasks into easy-to-digest components called"chains" that can then be connected together.
For instance, summarizing large swathes of text can be a surprisingly difficult task for LLMs. With LangChain, a developer is able to first create a chain to split up the text into smaller sections based on similarity of meaning and then connect this action to a subsequent chain that summarizes the meaning of each section.
As an open-source project, LangChain is especially known for its strong community — one that Chase is personally involved in. When Untapped Capital general partner Yohei Nakajima created a
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