Generative AI and its applications are no longer just a prerogative of data scientists using Python, but with Java and SpringBoot skills it could be approached through "Spring AI" API.
We will see step-by-step how we can implement a Spring Boot application based on Retrieval Augmented Generation (RAG) with: cloud, hybrid or on-premises LLM models, using a knowledge base stored in a VectorDB, showing tips&trics in ingestion, choosing the LLMs models and prompt engineering. The transition phase to production, through a Backend platform, will not be overlooked.