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Abstract
In particular, LangChain, an open-source software library, and LlaMA3, Meta's most recent AI model that is comparable to proprietary models now on the market, are the subjects of this study's examination of the usage of Large Language Models (LLMs) for the quick development of applications. Thanks to their widespread adoption in jobs like writing essays, creating code, explaining things, and debugging-openAI's ChatGPT, Google's Gemini, and other products have made LLMs popular among millions of people. This paper focuses on how LangChain can help speed up the creation of unique AI applications with LLMs. LangChain is well-known in the AI world for its ability to work fluidly with a variety of applications and data sources. The fundamental characteristics of Lang Chain are examined in this study, including its chains and modular components that function as adaptable, use-case-specific pipelines. The paper shows how this framework may be used to quickly create LLM-based applications through a practical example, especially when combined with LLaMA3 and LangChain.
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Details
1 Assistant Professor, Department of MCA Dayananda Sagar College of Engineering(VTU), Bangalore, India
2 Professor, Department of MCA Dayananda Sagar College of Engineering(VTU), Bangalore, India
3 PG Scholar, Department of MCA Dayananda Sagar College of Engineering(VTU) Bangalore, India
4 PG Scholar, Department of MCA Dayananda Sagar College of Engineering(VTU) Bengaluru, India