java-ai

A lightweight, modular Java application framework for web and CLI development, designed for AI integration and plugin-based architecture. Enabling developers to create robust solutions with ease for building efficient and scalable applications.

One API, any AI

Open-Source Omnichannel CRM with Premium Autodialer Description: bring all features together—voice, SMS, WhatsApp, email, and chat—inside a single agent desktop with automations, analytics, and integrations.

Spring AI vs LangChain4j vs SAA 三框架同台对比（配套篇2）

Java spring boot boilerplate with a JWT authentication & Postgre database

A Java Spring Boot application that uses DL4J (Deeplearning4j) to build and train an AI model for predicting player suitability. It supports CRUD operations with MySQL and automatically replaces the trained model whenever performance data is updated.

Java LLM memory framework: lightweight, efficient conversation context & long-term memory management for Agent/RAG.

Kontext4J is a chaotic yet powerful Java wrapper for BFL/Flux Kontext APIs. Edit, fill, generate, or expand images with one slick file—no 200 lines of boilerplate, no ritual sacrifices. Handles paths, URLs, base64, polls until ready, and downloads results. The nano-banana of Java AI libs.

Spring AI Alibaba + Graph 企业级 Multi-Agent 实战：4 Agent 协同 + 状态快照 + Nacos/Sentinel（配套篇6）

Building a simulation of a RoboCup Soccer competition using an artificial intelligence project written in a Java Jade environment.

A flexible, multithreaded neural network library in Java

AI 可观测与 FinOps 实战：OTel 链路 + Token 指标 + 语义缓存 + 三级成本封顶 + Grafana 看板（配套篇8）

AI 应用安全四层防御实战：提示注入检测 + 语义隔离 + 工具参数校验 + 输出审计（配套篇9）

An AI database agent for the terminal, built on the tinystruct Java framework. You ask questions in plain English, such as "show me the ten newest orders" or "how many users signed up this week?". The agent works out the SQL, runs it against your database, and shows the results.

Spring AI MCP Server 实战：@McpTool/@McpResource/@McpPrompt + 权限/限流/审计（配套篇5）

A laboratory for Java AI applications and agentic architectures. Focused on stateful multi-agent orchestration,LangChain4j, LangGraph4j workflows, and Spring Boot integrations. Practical, local-first LLM patterns using Ollama, and the Model Context Protocol (MCP).

多模型路由与故障转移实战：ModelRouter 路由层 + 按模型维度熔断 + Higress AI 网关（配套篇7）