duckduckgo-help-pages VS Searx

It restored: https://github.com/duckduckgo/duckduckgo-help-pages/commit/82c121b9a8ffa8b4ae635d4f50e26ebf4a16140b

Link: duckduckgo / duckduckgo-help-pages

There is also a (related, I assume) PR to remove the search syntax page from being published entirely[1]. It's dated December, so it may be fair to assume this has all just been documentation-publishing that hasn't been done yet, as others have posited.

[1] https://github.com/duckduckgo/duckduckgo-help-pages/pull/152

When I tried just now again on a different machine, it no longer seems to work. I also found this commit on the help page which I think is where references to the other operators were removed and it's dated for march 3rd, so I think it might be that either the search site was cached somehow or it was not yet updated, which could explain why there was inconsistent behavior between users.

That's a bit of a stretch. One instance of a tracker being enabled contractually, and has been openly communicated on their website since February 2020. That's hardly their "business" now. The fact people choose not to read the information available to them and then complain when they find out later isn't DDG's problem.

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.