Build a RAG App with Spring Boot, Spring AI, Ollama & Svelte | Full Tutorial (Java + Maven)

Want to build an AI-powered Retrieval-Augmented Generation (RAG) app with Spring Boot & Spring AI? This step-by-step tutorial covers everything—from setting up Spring AI ETL Pipelines, integrating Chroma Vector Store & Ollama, and creating RAG inference endpoints to connecting a Svelte 5 frontend!

🔗 Resources & Links:

👉 cURL Command to call the RAG inference endpoint: curl localhost:8080/inference -H"Content-type: application/json" \ -d '{"query": "tell me a cuban volunteers?", "sessionId": "dummy-session-id-01", "messages": []}'

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Chapters:
0:00 - Introduction: How to build a RAG app using Spring AI
0:10 - What is RAG?
0:22 - Demo Application Overview
0:41 - Understanding Spring AI
1:22 - Building a Spring Boot RAG Application
2:54 - Opening the Spring Boot App in IntelliJ IDEA
4:06 - Coding the RAG Application
5:31 - Spring AI ETL Pipeline Explained
6:07 - Constructing the ETL RAG Pipeline
9:43 - Creating Chroma Vector Store, Ollama Chat Model, Ollama Embedding Model, and Chat Client
14:01 - REST Endpoint for RAG Inferencing
14:49 - Setting Up Document Storage for ETL
15:03 - Running the Spring AI RAG Application
15:34 - Indexing Documents in the ETL Pipeline
16:35 - Calling the RAG Inference Endpoint Using Curl
16:57 - Integrating Svelte 5 Frontend with Spring AI RAG Backend
18:49 - Outro