垂域大模型问答后台管理系统设计与实践

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中图分类号：TP315；TP182 文献标识码：A 文章编号：1006-8228（2025）11-55-06

Abstract：Withhewdespreadaplicationoflargelanguagemodelsinverticalfields，itiscrucialtobuildabackendplatforthat supportsmult-tyequestio-answeringandsystemmanagementInresponsetoheshortcomingsoftecurrntRetrieval-Augmeted Generatin（RAG）systemindatamanagement，dynamicupdates，andreusability，thispaperproposesabackendmanagement architecturesolutionbasedonRAGandLangChaintoachieveful-processmanagementfromknowledgeconstruction，service configuration，tofedbackcolection.Basedonthissolution，abackendmanagementsystemwasdevelopedtosupportthe automatedconstructionanddynamicupdateoftheknowledgebase，theestablishmentofinteligentagents，userdatacolection，and corpusconversion.ThispracticeshowsthatthesystemcanimproveQAaccuracyandeficiencyefectivelysupportingdivified question-answering services.

Keywords：LargeLanguageModels;Retrieval-AugmentedGeneration（RAG）;ManagementSystem;LangChain;DataManagement

0引言

近年来，基于大语言模型（LargeLanguageModel，LLM）的垂直领域智能问答系统，凭借其强大的语义理解能力与生成能力，推动了知识服务系统向智能化、个性化方向变革。（剩余7230字）