Improved Web Search with Local LLM, SearxNG and Deno 2.0
Many are raising that Google search (with ~90% market share) has lowered in quality and that is much harder to find accurate information. Some are finding alternatives in more privacy oriented (as in less tracking and ad targeting) search engines like DuckDuckGo, Brave, Qwant, Startpage… with each of them having potential downsides of their own.
On the other hand GenAI solutions came with ability to give a lot of information about any topic, but questionably accurate. Those LLM models only have the knowledge until the date of the data they were trained upon which is normally quite outdated. To combat this limitation companies have built functionality to get data from online sources and then let LLM answer the original queries based on what it found in that data. This is better known as Retrival— Augmented Generation or RAG in short— see more and can be seen in search engines these days which are also providing a summary of search results.
This should provide the best results as we can get the relevant new web content which LLM can then ‘reason’ on.
And this is exactly what we are going to do, but instead of using fully closed solutions, we are going to build one ourselves so we can decide what we think is most accurate and relevant for us, while also keeping our data as private as possible.
