.Varshney VS Searx

Source: https://github.com/Bhupesh-V/.Varshney/blob/master/scripts/aws/get-aws-token

The source is available here if you want to reference or hack anything. I took the liberty to beautify the output from our script. Here is how the finalized version looks like:

If you are still interested, here is the script to hack around.

The complete and up to date script is available here

The script is available on my github

Since I'm bored I sent you a little PR to follow the xdg basedir spec a little more closely. :)

Below is an example of a Jekyll Post header from my dotfiles

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.