JeecgBoot is an enterprise-grade low-code development platform that accelerates application delivery through AI-powered code generation, online form/report builders, and workflow integration. The backend is built on Spring Boot 3 with MyBatis-Plus, Shiro, and JWT, supporting both monolithic and microservice architectures (Spring Cloud, Nacos, Sentinel, XXL-Job). The frontend uses Vue 3 + TypeScript + Ant Design Vue with a rich component library including JVxeTable for editable grids and schema-driven forms. The platform provides comprehensive RBAC, multi-tenancy, dynamic data sources, data dictionaries, and third-party integrations (DingTalk, WeChat, Feishu). A dedicated AI module (airag) offers RAG knowledge bases, LLM chat, voice/image generation, and MCP plugin support. The codebase is actively maintained with frequent commits and a large community, though it contains some commented-out legacy code and hardcoded security values that represent minor technical debt.
This repository is a Spring Boot training/courseware package rather than a production service. It consists of five independent, runnable Spring Boot applications under com.kousenit (demo, restclient, persistence, shopping, springai), accompanied by lab workbooks (labs.md, advanced-labs.md), course slides (slides.md), and CI workflows. The code demonstrates current-generation Spring and Spring Boot patterns: MVC and REST controllers, Java records for DTOs, RestClient and HTTP interfaces, JdbcClient and JPA data access, AOP aspects, RFC 7807 exception handling, and Spring AI chat clients. Although the dominant character is application code, it is educational example code, not a deployed system.
This repository is a comprehensive multi-module Maven project that serves as a learning and demonstration resource for the Java ecosystem, specifically focusing on Spring Boot, microservices, middleware, and AI integration. It contains over 20 independent modules, each showcasing a specific technology or pattern: from core Spring features (AOP, events, lifecycle) to advanced distributed systems (Dubbo, gRPC, Netty, RocketMQ, Kafka, Redis, Elasticsearch, ShardingSphere, Sentinel, Nacos, Curator) and modern AI capabilities (LangChain4j-based RAG, agentic workflows, guardrails, MCP client, image generation, TTS). The architecture is a modular monolith where each module is independently runnable via its own Spring Boot application class, sharing a common utility library (whatsmars-common) for serialization, caching, consistent hashing, encryption, and logging. The AI module is particularly notable for implementing advanced patterns such as query compression, smart routing, re-ranking, structured output, and configurable agentic workflows (sequential, parallel, conditional, loop, supervisor). While the repository is not a single deployable product, it provides high-quality, well-documented examples that demonstrate non-obvious craftsmanship in areas like custom gRPC load balancing, consistent hashing with virtual nodes, and programmatic logger creation. The codebase is professionally written with good separation of concerns, though testing coverage is limited to utility classes. Overall, it is a valuable reference for Java developers exploring modern frameworks and AI integration patterns.