Ollama

TL;DR It is advisable to go from adolesence to senility, bypassing maturity, at least for humans, for language models that can cause timeouts. fastapi cloud works like a charm. Mixing local and remote models with ollama (cloud) easy peasy - good usage limits currently (did all my processing with ollama cloud) of 90+ pdfs. The objective I always enjoy looking through Tom Lehrer songs, almost as much as I like to listen to them. But it plagued me that I had to do a click, actually choose a song, and then click again. I’m sure you can relate. To alleviate this I wanted to create a new website. Which just shoves one different song per day down your something. ...

This blog post is for you if you’ve heard of the model context protocol (MCP) and are curious how you could implement something in Python such that you can try it with your local models that are capable of tool use, e.g. via Ollama. Maybe you even looked at the documentation but felt there still was something missing for you to get started? At least that’s how I felt. The “easiest” / Stdio server verison worked immediately but when I wanted to use a HTTP server I was sort of stranded. It was unclear to me how to actually run the server and what the client needs where so it can successfully talk to the server. Don’t get me wrong, the MCP and PydanticAI documentation is pretty good, but things could always be easier, could they not? :-P Maybe I’ll save you some time with this post. ...