Canvas LMS VS Searx

I did not realize that Canvas is open source. That's an LMS most people like. You have hosting space and server-side savvy, you could set that up: https://github.com/instructure/canvas-lms

Canvas go brrrrrrrr

Also look at Canvas.

github.com/instructure/canvas-lms (745k lines): A popular LMS (learning management system).

No it's not. From a practical standpoint, I'm not even sure how that could work. You would have to require all browsers to be open source AGPL in order to load a web page served by it. By way of analogy it seems the equivalent of requiring the mouse and keyboard firmware to be licensed the same as the operating system.

A real life example is Instructure, which makes Canvas (which is agpl) but has other proprietary services that interact heavily with it. It's never been a problem

1: https://github.com/instructure/canvas-lms

Look into Canvas LMS, I would recommend using 8GB RAM and at least 4 vCores. I have used it in the past (`2 years ago) and only had issues with cloning class/course templates.

If you're planning on doing this as business though, bear in mind this is a pretty crowded market. There's already at least one Rails-based LMSes out there (https://github.com/instructure/canvas-lms), and dozens in PHP-land.

There is also Canvas.

I think searx was largely built by a single person.

https://github.com/searx/searx

I use Recoll to index all of it. Recoll WebUI exposes an API, which I plugged into Searx.

The quality of Google search results has been awful for many years now, but if you still want to use it, the only usable way is via a frontend like Searx[1]. Using any of Google's frontends for any of their services is an exercise in frustration from dodging ads and fighting their hostile UI.

[1]: https://github.com/searx/searx

RSS-Bridge has a Google search adapter. You can also fake it with Searx (which offers RSS feeds of search results).

I've recently wondered how effective local models were at chaining together thoughts as proposed in https://ofir.io/self-ask.pdf. Turns out they are indeed capable of doing so while also creating reasonable chains of thoughts that are easily as good as OpenAI's models. To make it completely free to run I used SearX running inside a Docker container with a second model curating the search results for the main model to get answers from the web.