With Spring AI on the classpath, calling a chat model comes down to three things: add the right starter, set an API key or base URL in config, and inject ChatClient. The same Java code then works whether you’re hitting OpenAI in the cloud or a local Ollama model on your laptop — you swap the dependency and the config, not the logic. This is Part 2 of the Spring AI series. ...
Running LLMs locally with Ollama means an open-weight model lives on your machine — no API keys, no per-token billing, no sending your data to someone else’s servers. You install Ollama, pull a model with one command, and chat from the terminal or hit a local API. For prototyping, privacy-sensitive work, or just learning how these models behave without a credit card attached, it’s the simplest on-ramp there is. Install and run a model Installation is straightforward: grab the Ollama binary for macOS, Linux, or Windows from the project site and run it. Then, from the command line: ...