Efficient Large Language Model Application Development: A Case Study of Knowledge Base, API, and Deep Web Search Integration  

作　　者：Xiangyu Wang Yan Tan Tao Yang Meng Yuan Shaohan Wang Min Chen Feiyang Ren Zijian Zhang Yuqi Shao Xiangyu Wang;Yan Tan;Tao Yang;Meng Yuan;Shaohan Wang;Min Chen;Feiyang Ren;Zijian Zhang;Yuqi Shao(COSCO SHIPPING Technology Co., Ltd., Shanghai, China;COSCO SHIPPING Specialized Carriers Co., Ltd., Guangzhou, China)

机构地区：[1]COSCO SHIPPING Technology Co., Ltd., Shanghai, China [2]COSCO SHIPPING Specialized Carriers Co., Ltd., Guangzhou, China

出　　处：《Journal of Computer and Communications》2024年第12期171-200,共30页电脑和通信(英文)

摘　　要：This paper presents a reference methodology for process orchestration that accelerates the development of Large Language Model (LLM) applications by integrating knowledge bases, API access, and deep web retrieval. By incorporating structured knowledge, the methodology enhances LLMs’ reasoning abilities, enabling more accurate and efficient handling of complex tasks. Integration with open APIs allows LLMs to access external services and real-time data, expanding their functionality and application range. Through real-world case studies, we demonstrate that this approach significantly improves the efficiency and adaptability of LLM-based applications, especially for time-sensitive tasks. Our methodology provides practical guidelines for developers to rapidly create robust and adaptable LLM applications capable of navigating dynamic information environments and performing effectively across diverse tasks.This paper presents a reference methodology for process orchestration that accelerates the development of Large Language Model (LLM) applications by integrating knowledge bases, API access, and deep web retrieval. By incorporating structured knowledge, the methodology enhances LLMs’ reasoning abilities, enabling more accurate and efficient handling of complex tasks. Integration with open APIs allows LLMs to access external services and real-time data, expanding their functionality and application range. Through real-world case studies, we demonstrate that this approach significantly improves the efficiency and adaptability of LLM-based applications, especially for time-sensitive tasks. Our methodology provides practical guidelines for developers to rapidly create robust and adaptable LLM applications capable of navigating dynamic information environments and performing effectively across diverse tasks.

关 键 词：Large Language Model Knowledge Base API Integration Web Retrieval Application Development 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]