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didilili / shopkeeper-agent

📊 An intelligent AI agent for e-commerce data warehouse analytics, ideal for practical projects in system learning with LangGraph: based on LangGraph, FastAPI, Qdrant, Elasticsearch, MySQL, and React, it fully implements a metadata knowledge base, hybrid retrieval, natural language to SQL generation validation, SQL execution, and streaming query display. Complete frontend and backend code is ready for full-stack execution; deployment in Docker environment is possible with one-click, along with free tutorials from ai-agents-from-zero and chapter code branches. Suitable for system learning of large model applications, data analysis agents, and enterprise-level AI engineering implementation.

Repository stars
508All-time #61,196
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149
Last push
updated 24 days ago
Repository created
since 2026
Apps & systemsGeneralPythonMIT · Permissive
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Original · GitHub
📊 电商数仓智能问数 AI Agent,最适合用于系统学习 LangGraph 的实战项目:基于 LangGraph、FastAPI、Qdrant、Elasticsearch、MySQL 与 React,完整实现元数据知识库、混合检索、自然语言生成 NL2SQL 生成校验、SQL 执行与流式查询展示。前后端完整代码全栈可跑,Docker 环境一键部署,配套 ai-agents-from-zero 免费教程与章节代码分支。适合系统学习大模型应用、数据分析 Agent 和企业级 AI 工程落地。

Summarised by AI from the README; the original prevails

Author description: 📊 An intelligent AI agent for e-commerce data warehouse analytics, ideal for practical projects in system learning with LangGraph: based on LangGraph, FastAPI, Qdrant, Elasticsearch, MySQL, and React, it fully implements a metadata knowledge base, hybrid retrieval, natural language to SQL generation validation, SQL execution, and streaming query display. Complete frontend and backend code is ready for full-stack execution; deployment in Docker environment is possible with one-click, along with free tutorials from ai-agents-from-zero and chapter code branches. Suitable for system learning of large model applications, data analysis agents, and enterprise-level AI engineering implementation.

Basic listing based on official public information; functionality has not been independently evaluated.

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50850950911-06 · 50810-0810-1310-1810-2310-2811-0211-06

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