Build AI Apps with Spring AI, OpenAI, Ollama & SpringBoot

Learn chat with LLMs, Retrieval-Augmented Generation, tool calling, and multimodal AI using Spring AI.

What you'll learn
- Learn to integrate Large Language Models (LLMs) with Spring AI to build interactive chat applications using Java and Spring Boot.
- Understand and implement Retrieval-Augmented Generation (RAG) to enhance LLM responses using custom and external knowledge sources.
- Master tool calling with Spring AI to enable your LLM apps to take real-world actions like querying APIs or performing tasks.
- Build multimodal applications that work with text, images, and audio by leveraging the latest OpenAI capabilities in Spring AI.
- Learn how to configure and work with Spring AI clients, including prompt templates, message history, and streaming responses.
- Build and deploy multiple real-world projects that cover chatbots, search assistants, and AI-powered tools using Spring AI.

Requirements
- Basic knowledge of Java and Spring Boot will help, but the course covers concepts from scratch for new learners.
- No prior experience with AI, OpenAI, or LLMs is required—everything is explained in a simple, hands-on way.
- Familiarity with REST APIs and JSON can be helpful, but not mandatory to follow along with the projects.
- Curiosity and willingness to experiment with code are the most important things you’ll need for this course.

Description
Course Description

Unlock the power of Generative AI within your Java applications usingSpring AI,OpenAI, andOllama!In this hands-on course, you’ll learn how to build intelligent, scalable AI-driven applications using the robust Spring Boot ecosystem. From crafting prompts to building full RAG-based systems, you’ll gain practical skills to integrate LLMs into real-world projects.

Here’s a breakdown of what you’ll learn in each section:

Course Introduction & Setup

Understand the course structure, prerequisites, and how to set up your Java and Spring AI environment.

Introduction to Large Language Models (LLMs), OpenAI & ChatGPT

Learn the basics of LLMs, their evolution, applications, and how OpenAI’s ChatGPT fits into modern AI workflows.

Getting Started with Spring AI and OpenAI API

Configure your project and IDE, create your first chat-based app using ChatClient, and understand prompts, tokens, and OpenAI request parameters.

Working with Chat Models and OpenAIChatModel

Customize LLM responses using ChatOptions, enable streaming, and build responsive AI chat applications.

Prompt Engineering with Spring AI

Master prompt engineering techniques like zero-shot, few-shot, chain-of-thought, and multi-step prompting to guide AI outputs effectively.

Generating Structured Data with Spring AI

Learn to create structured outputs using prompt templates and Spring’s converters, including lists, maps, and entity objects.

Tool Calling (Function Calling) with Spring AI

Integrate external systems into your AI apps with OpenAI’s tool calling—fetch live data like weather, currency rates, and more.

Building RAG Applications (Retrieval-Augmented Generation)

Build an end-to-end RAG-powered Q&A system using PgVector, document chunking, indexing, and semantic retrieval.

Document Ingestion Strategies

Explore how to ingest and chunk various document types including PDFs, Word files, and plain text using different readers and splitters.

Exploring Multimodality: Vision Capabilities

Leverage OpenAI’s image models to generate, analyze, and process images including real-world examples like invoice parsing.

Exploring Multimodality: Audio Capabilities

Convert text to realistic voice using TTS, and transcribe or translate speech to text using the Whisper API.

Building Local AI Apps with Spring AI and Ollama

Run LLMs locally using Ollama, integrate it with Spring AI, and build applications without relying on external APIs.

By the end of this course, you’ll be equipped to build full-stack AI-powered applications using Java and Spring Boot, with integrations that span cloud-based models, local deployments, vision, audio, and retrieval-augmented techniques.

You’ll walk away with the confidence and experience to bring Generative AI into production-ready Java applications.

Who this course is for:
- Java developers curious about building AI-powered apps using Spring AI and modern generative AI techniques.
- Beginners looking to get started with Spring AI, LLMs, and practical generative AI use cases without needing prior AI experience.
- Backend engineers and full-stack developers wanting to integrate OpenAI’s LLMs into real-world Spring Boot applications.
- Tech enthusiasts and students eager to explore hands-on projects involving chatbots, RAG, tool calling, and multimodality.
- Professionals interested in learning how to build production-ready AI applications with Spring Boot and OpenAI.
- Anyone looking to future-proof their Java skills by diving into the world of generative AI and building practical AI tools.
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