This whole exploration into Python async driven by LLM coding has been really interesting. I wanted to understand this better as I couldn’t really grok it. My mental model is still treating an async for loop as just a regular for loop but there are differences!

I was trying out various tutorials to learn AI, specifically Google’s ADK and a course on Gradio at Deeplearning.ai; both courses featured code in notebooks that sourced from APIs and both seemed like they did streaming. But I wanted a deeper understanding of how this mechanism worked. Cuz I’m old and I’ve been out of the coding game for quite some time so have little to no experience with streaming.

So I actually vibe coded a site and put it into production. It wasn’t a terribly sophisticated site. It was a single page application on a Typescript/React stack with no database. Really pretty simple.

But it was a passion project and I needed it up and running in a very quick timeframe. It was a lot of fun because basically everything was new to me. I used Cursor for this development and made more use of GitHub than I ever have previously.

Privacy with Email

Today I was playing with the hugging face API when I was following the gradio course on deep learning.ai ; in that course they use the python request API to make calls out to hugging face’s inference API;

You’ll find this post in your _posts directory. Go ahead and edit it and re-build the site to see your changes. You can rebuild the site in many different ways, but the most common way is to run jekyll serve, which launches a web server and auto-regenerates your site when a file is updated.

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