AI-Driven Development: Enhancing Java with the Latest AI Innovations

Welcome! This repo is a companion for the workshop "AI-Driven Development: Enhancing Java with the Latest AI Innovations." To ensure a smooth and productive session, please refer to the workshop prerequisites before beginning.

Workshop Structure

This workshop is divided into three main parts:

Part 1: Enhancing Spring Applications with Spring AI

Learn how to integrate AI capabilities into Spring Boot applications using Spring AI and Azure OpenAI:

• Setting up Spring AI with Azure OpenAI Service
• Implementing basic AI integration ("Hello World")
• Creating parameterized prompts
• Working with structured AI outputs
• Building a Retrieval Augmented Generation (RAG) system

Part 2: Java Development Using GitHub Copilot

Leverage GitHub Copilot to accelerate your Java development workflow:

• Installing and configuring GitHub Copilot in VS Code
• Redeeming GitHub Pro (if needed)
• Using effective prompts to generate Spring code
• Creating controllers, tests, and documentation with AI assistance
• Implementing new features in existing codebases

Part 3: Building Intelligent Java Applications with LangChain4j

Create advanced AI-powered Java applications using LangChain4j:

• Setting up the development environment with Docker
• Working with GitHub-hosted AI models
• Building a RAG system with Qdrant vector database
• Optional local LLM deployment
• Extending applications with custom document sources
• Integrating with Azure AI services

Getting Started

1. Review the prerequisites document
2. Clone this repository
3. Follow the instructions in each part sequentially
4. Refer to the workshop materials for detailed step-by-step guidance

Additional Resources

• Spring AI Documentation
• Azure OpenAI Service Documentation
• GitHub Copilot Documentation
• LangChain4j Documentation