
learn-agent
A collection of notes on building coding agents, derived from the production development of the desktop agent Reina, with each mechanism simplified into a zero-dependency, single-file Node.js demo.

TripStar is a multi-agent travel planning system built on Spring Boot 4 and Spring AI Alibaba, combining XiaoHongShu (Little Red Book) content, Amap POI/weather/hotel data, and a StateGraph workflow to generate complete itineraries with maps, budgets, and knowledge graphs.
48
No data
10
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GPL-2.0
2026-07-20
It demonstrates a practical multi-agent architecture with observable workflows, real data integration from Chinese platforms (XiaoHongShu and Amap), and supports two distinct planning modes—autonomous and note-following—making it a rare open-source example of Spring AI Alibaba's StateGraph in action.
TripStar 基于 Spring Boot 4 与 Spring AI Alibaba 的多智能体旅行规划系统
TripStar 是一个前后端分离的 AI 旅行规划项目。系统使用多 Agent 协作理解用户需求,读取小红书旅行内容,查询高德 POI、天气、酒店与餐饮,并生成包含每日路线、地图、景点图片、预算和知识图谱的完整攻略。
行程概览
每日行程
景点地图与真实路线
预算明细
输入目的地、日期、交通方式、住宿偏好和自然语言要求,系统按以下顺序执行:
用户可以输入一个或多个小红书长链接、短链、App 分享内容,或者直接粘贴攻略正文。系统会:
StateGraph 控制自主规划研究阶段的执行顺序和条件边。ReactAgent 负责阶段内的工具调用与参数决策。BeanOutputConverter 将模型 JSON 转换为 Java Record。service、tool、both 三种运行模式。flowchart LR
WEB[TripStar Frontend] --> API[Spring Boot API]
API --> TASK[TripTaskService]
TASK --> AUTO[自主规划 Workflow]
TASK --> NOTE[指定笔记 Workflow]
AUTO --> XHS[XHS Search / Detail Agents]
XHS --> GRAPH[Spring AI Alibaba StateGraph]
GRAPH --> AMAP[AMap POI / Weather / Hotel Agents]
NOTE --> READER[Note Reader + Image Downloader]
READER --> VISION[Multimodal Understanding Agent]
VISION --> POI[POI Enrichment Service]
POI --> SUPPLEMENT[Weather + Conditional Hotel/Food Agents]
AMAP --> PLANNER[Planner Agent]
SUPPLEMENT --> PLANNER
PLANNER --> REVIEW[Review Agent]
REVIEW --> RESULT[Trip
TripStar Java 实现版:基于 Spring Boot 4 + Spring AI Alibaba ReactAgent 的 AI 旅行规划后端,支持高德 Tool、小红书内容接入和 Structured Output。
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