OpenSearch-Dashboards VS Searx

I hate OpenSearch with a passion, an absolutely horrid lagging project that can't get basic autocomplete working (https://github.com/opensearch-project/OpenSearch-Dashboards/...)

but still manages to suck the air out of the room when you want Elasticsearch because AWS already has the company's billing details and no one wants to figure out paying another provider.

Time to look at the data in OpenSearch with the help of OpenSearch Dashboards!

Create dashboards to show and graph whatever you want. - https://opensearch.org/docs/latest/dashboards/index/

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.