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Understanding LangChain Chains for Large Language Model Application Development
Data Science   Latest   Machine Learning

Understanding LangChain Chains for Large Language Model Application Development

Last Updated on April 8, 2024 by Editorial Team

Author(s): Youssef Hosni

Originally published on Towards AI.

Hands-On LangChain for LLMs App Development: Chains

One of the fundamental pillars of LangChain, as implied by its name, is the concept of β€œchains.” These chains typically integrate a large language model (LLM) with a prompt.

Through these chain structures, you have the ability to assemble multiple building blocks, enabling the execution of a series of operations on your text or other data.

This article will delve into the significance of these chains, ranging from basic forms like the Simple Sequential Chain to more sophisticated variations such as the Router Chain, elucidated with practical illustrations.

Setting Up Working Environment & Getting StartedLLM ChainSequential Chains3.1. Simple Sequential Chain3.2. Complex Sequential ChainRouter Chain

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