user.js VS Searx

I don't know about Chrome based browsers but if you are using Firefox you can try user.js from arkenfox [link] or from pyllyukko [link] (I personally recommend the first one because they have a great wiki), you just put the script to your Firefox profile directory and it will spoof your screen resolution, link referrer, user agent, etc. (Remember to manually edit the file to suit your preferences, otherwise it may delete your history and cookies!). Also you can try User-Agent Switcher and Manager [Chrome] [Firefox] it is open source and lets you change your user agent to whatever you want. You can view your browser information on this website: https://deviceinfo.me, IMO this is a great website for identifying your browser's privacy issues.

I don't know how this one compares to Arkenfox, but from my limited understanding, it seems it's more/less of an out-of-the-box Arkenfox experience.

I recommend pyllyukko's hardened user.js https://github.com/pyllyukko/user.js/

I've been using the user.js script based on https://github.com/pyllyukko/user.js/tree/relaxed for a few years now, but today I noticed that it hasn't been updated for quite a while.

If you're that worried about privacy you should probably change your Firefox to one of these templates.

Already tried it. Pretty nice but I prefer hardening Firefox on my own (which just means copying and pasting this user.js accordingly and applying some extensions )

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.