Leveraging LLM As Backend Service

Author(s)	R Niranjan, J Pavan Prasad, S Nivetha
Country	India
Abstract	Large Language Models (LLMs) are revolutionizing dynamic web applications backend architectures by facilitating user centric, intelligent, and responsive interactions. In order to produce JSON replies for use cases including creating job descriptions, calculating candidate job matching scores, and suggesting chess moves, this article investigates the integration of LLM powered APIs. For scalable and effective application workflows, these responses are either stored in databases or seamlessly mapped to frontends. We go over the system design, performance indicators, and scalability issues. We also suggest ways to enhance response times for LLM powered backends, such as utilizing the Groq API, the fastest inference engine on the market. A thorough analysis demonstrates this method's potential in contemporary web development.
Keywords	Large Language Models, LLM, backend integration, Dynamic web applications, API inference, Groq API, JSON response generation
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 1, January-February 2025
Published On	2025-01-30
Cite This	Leveraging LLM As Backend Service - R Niranjan, J Pavan Prasad, S Nivetha - IJFMR Volume 7, Issue 1, January-February 2025.

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