Creating Large Language Model Applications Utilizing LangChain: A Primer on Developing LLM Apps Fast


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Authors

  • Oguzhan Topsakal Florida Polytechnic University
  • Tahir Cetin Akinci University of California at Riverside

DOI:

https://doi.org/10.59287/icaens.1127

Keywords:

Large Language Models, LangChain, Concepts, Application, ChatGPT, NLP, GPT

Abstract

This study focuses on the utilization of Large Language Models (LLMs) for the rapid development of applications, with a spotlight on LangChain, an open-source software library. LLMs have been rapidly adopted due to their capabilities in a range of tasks, including essay composition, code writing, explanation, and debugging, with OpenAI’s ChatGPT popularizing their usage among millions of users. The crux of the study centers around LangChain, designed to expedite the development of bespoke AI applications using LLMs. LangChain has been widely recognized in the AI community for its ability to seamlessly interact with various data sources and applications. The paper provides an examination of LangChain's core features, including its components and chains, acting as modular abstractions and customizable, use-case-specific pipelines, respectively. Through a series of practical examples, the study elucidates the potential of this framework in fostering the swift development of LLM-based applications.

Author Biographies

Oguzhan Topsakal, Florida Polytechnic University

Computer Science Department, FL, USA

Tahir Cetin Akinci, University of California at Riverside

WCGEC,  CA, USA

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Published

2023-07-22

How to Cite

Topsakal, O., & Akinci, T. C. (2023). Creating Large Language Model Applications Utilizing LangChain: A Primer on Developing LLM Apps Fast. International Conference on Applied Engineering and Natural Sciences, 1(1), 1050–1056. https://doi.org/10.59287/icaens.1127