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Hands-On LangChain for LLM Applications Development: Prompt Templates
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Hands-On LangChain for LLM Applications Development: Prompt Templates

Last Updated on February 27, 2024 by Editorial Team

Author(s): Youssef Hosni

Originally published on Towards AI.

By prompting an LLM or large language model, it is possible to develop complex AI applications much faster than ever before. However, an application can require prompting an LLM multiple times and parsing its output, so a lot of glue code must be written.

LangChain makes this development process much easier by using an easy set of abstractions to do this type of operation and by providing prompt templates.

In this article, we will cover prompt templates, why it is important, and how to use them effectively, explained with practical examples.

Setting Up Working Environment & Getting StartedPrompt Template using LangChainWhy do We Need LangChain Prompt Templates?

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