Build your AI assistant with Ollama, LLM and Spring

AI models are evolving rapidly, and as developers, we need to adapt to this new era where AI can enhance our applications in ways we never imagined. With modern APIs, we can offload computations and decision-making to powerful language models, making our applications smarter, more responsive, and highly personalized. Imagine building a smarter smart home—where an AI decides which devices should turn on or off based on real-time scenarios. Or creating a health assistant that analyzes a user’s medication list, flags potential interactions, and even considers allergies and medical history. How about a nutrition tracker that not only logs meals but also offers real-time dietary advice based on the user's body metrics? The possibilities are endless. In this hands-on lab, you’ll build a REST API application that takes user data, generates dynamic AI-powered responses, and processes the results logically. We'll be running a local LLM using Ollama API and integrating it into a Spring application, creating a seamless AI-powered assistant.

⚠ Note: This will be a more advanced session, requiring some prior experience with backend development. Make sure to also bring a beefier laptop with 16 GB of RAM as minimum.