This repository is a curated list of resources for developers building generative AI applications with Spring AI, a project that simplifies LLM integration into the Spring ecosystem. It targets Java developers seeking a familiar Spring-style experience for AI development, offering consistent abstractions, prompt engineering capabilities, and robust integrations.

How It Works

Spring AI provides a unified interface for interacting with various LLM providers, abstracting away differences in APIs and functionalities. It emphasizes a Spring Boot-native approach, allowing developers to leverage familiar Spring patterns for AI application development, including features like prompt templating, caching, and integration with vector databases.

Quick Start & Requirements

• Install: Typically via Maven or Gradle dependency management within a Spring Boot project.
• Prerequisites: Java Development Kit (JDK), Maven or Gradle. Specific LLM providers may require API keys or local model setups (e.g., Ollama).
• Resources: Official Documentation: https://docs.spring.io/spring-ai/reference/

Highlighted Details

• Extensive collection of code examples and comprehensive sample repositories covering various AI models, RAG, and Spring AI features.
• Detailed resources on the Model Context Protocol (MCP) for extending LLMs with external tools and services.
• Numerous blog posts, articles, online courses, and talks covering Spring AI from beginner to advanced topics, including specific provider integrations (OpenAI, Ollama, Groq, NVIDIA, etc.).
• UI client examples using HTMX and Vaadin, and CLI application examples demonstrating RAG and local LLM usage.

Maintenance & Community

• Active community with a dedicated community repository for sharing knowledge and examples.
• Key contributors and speakers include Josh Long, Christian Tzolov, and Craig Walls.
• Links to community resources like Discord/Slack are not explicitly provided in the README.

Licensing & Compatibility

• The repository itself is a curated list, not a software project with a specific license. The underlying Spring AI project is Apache 2.0 licensed, allowing for commercial use and closed-source linking.

Limitations & Caveats

• Some linked resources, such as specific workshops, may be outdated.
• While extensive, the community section lacks direct links to active communication channels like Discord or Slack.