基于DeepSeek和RAGFlow的智能项目推荐客服系统部署实践

打开文本图片集

中图分类号：TP311.1；TP18 文献标识码：A文章编号：2096-4706（2025）18-0110-05

Abstract： This paper focuses onhow to realize the transformation of naturallanguage to SQL statement based on Large Language Model by means of lowcode，soas to help users automaticall obtain project data that mets the requirements and improve workeciencyandserviceeffciency.FirstlyDeepSeekiseployedlocallyasthebasic model，andtheAgentproess ofnaturallanguage to SQLisbuilt with thehelpofopensourcetoolRAGFlow.Thesystemcanaccuratelyanalyzethenatural language inputbytheuser，transformitintotecoespondingSQLstatements，andfinallyetu theproject iformationquired bytheuser tothedialogue windowbyperforming thequeryoperationin thedatabase.Theresearchelaborates on thekey steps intheconstructionandimplementationofthesystemarchitecture.Experimentalverificationshowsthatthesystemperforms wel intheaccuracyofnaturallanguage toSQLandtheeficiencyof data query.Itprovides enterprises with moreconvenientdata utilization and service solutions， and helps enterprises to develop digital transformation.

Keywords：DeepSeek;RAGFlow; natural language to SQL;Large Language Model

0 引言

1系统流程部署

在人工智能蓬勃发展的当下，各大语言模型展现出对自然语言良好的深度理解与处理能力，然而在结构化数据的查询和统计方面效果不佳，且常出现“幻觉”现象[1-3]。（剩余5682字）