fprotthetarball
Joined 13 years ago
Joined 13 years ago
Another problem I inadvertently dodged by using Jujutsu with Claude Code :)
I tend to send a lone "commit" message to Claude when I think I'm in a spot I may want to return to in the future, in case the current path doesn't work out. Then Claude commits it with a decent message. It knows how to use jj well enough for most things. Then it's really easy to jj new back to a previous change and try again.
This lets you work on things without having to worry about giving it a name. This turns out to be pretty helpful when you're experimenting — just "jj new <revision>" and start editing. If it turns out to be something you want to share, "jj bookmark create <name>" and then you can push it. (You can also push without giving it a name, in which case you'll get a git branch with a name based off of the change id.)
Change IDs stay constant with each change, so you use those as a type of branch name when switching between the features you're working on.
- axum: web application framework - https://github.com/tokio-rs/axum
- axum-htmx: axum extractors, responders, guards for htmx - https://github.com/robertwayne/axum-htmx
- rusqlite: SQLite bindings - https://github.com/rusqlite/rusqlite
- maud: HTML templating as a macro - https://maud.lambda.xyz
The way maud lets you compose markup works very nicely with htmx. The HX-Request header lets you know if the request is coming from htmx or if it is a regular request. You either call the top-level function if it's a regular request to get the entire page rendered, or call a subset of functions to get the appropriate partial rendered if it's an htmx request.
It's also nice to easily have tests for the rendered pages. My unit tests cover verification of the rendered HTML, too.
GitHub will call the webhook after a push to main and a successful test suite run. Snare runs a shell script on my server to git pull, build, deploy, and call a cronitor.io hook for monitoring deploy success.
I've been pretty happy with how relatively simple it is and how well it works.
If AGI is "a highly autonomous system that outperforms humans at most economically valuable work", I am Microsoft and have AGI, and other businesses do not, I am putting it charge of a Windows VM in Azure and offering it to companies to run aspects of their businesses. Why stop at "GPTs" if I can offer you specialized Clippys?
Put all your data in Microsoft 365, let Clippy do its thing, and you're saving a lot of money on not supporting people. Microsoft gets their cut, and you get to fire your employees. Win-win.
It takes 30-45 minutes to cool down enough to depressurize, but the lid is always clean so the food is likely staying in the pot.
After installing the application and running it, you run "ollama run <model name>" and it handles everything and drops you into a chat with the LLM. There are no dependencies for you to manage -- just one application.
Check out the README: https://github.com/jmorganca/ollama#readme
Joplin seems like the best at handling my mix of text notes, PDF files, and images at the moment. If it doesn't work out, though, at least I have my data in a more open form.