ayshrivlabs/mastering-spring-ai

Mastering Spring AI is a learning repository for Java developers who want to build applications that use artificial intelligence. It covers the Spring AI framework, a toolkit that makes it easier to add AI capabilities to Java and Spring Boot applications, going from beginner to advanced levels with real-world projects and production-ready examples. The repository covers a range of AI techniques. RAG, or Retrieval-Augmented Generation, is a method where an AI system looks up relevant information from a database before answering a question, making responses more accurate and grounded in real data. Vector Databases are specialized databases that store information in a way that makes it easy to find semantically similar content, which is useful for search and AI memory. The repository also touches on AI Agents, meaning programs that can take actions automatically on a user's behalf, Prompt Engineering, which means crafting better instructions to get better AI responses, and Multimodal AI applications, which work with more than just text. The tech stack listed in the README includes Java 21, Spring Boot, Spring AI, PostgreSQL with pgvector, OpenAI, Gemini AI, Ollama, Docker, Maven, Redis, Kafka, and AWS. This points to a project aimed at a Java backend developer who wants to move beyond basic tutorials and understand how to integrate AI into enterprise-grade applications rather than toy scripts. Whether someone is just starting out or already comfortable with Java backends, the repository is structured to guide them through progressively more complex AI concepts, moving from basic integrations up to scalable production architectures. The README itself is a short overview and does not go into the specifics of individual example projects.