• 6 Posts
  • 119 Comments
Joined 1 year ago
cake
Cake day: June 15th, 2023

help-circle
  • Not necessarily. While of course in many many cases, open source is a volunteer effort, there’s usually some implicit transaction going on. Whether that’s improving the software for yourself and passing that on to others, being a business and improving a library or something you use that helps your project generate revenue, or even a straight up commercial transaction.

    But in all these cases, the open source project can be taken by you (or others) and you can do whatever you want with it. In the case of Winamp here, you cannot do any of that. It would be different if they were paying for contributions. But they’re not, so.



















  • A vector search converts your query into magic numbers, and then searches the database for other magic numbers that are “similar” (closet to it in the vector space, which is basically an N-dimensional graph of points and directions). These results are then returned as snippets to the LLM and it does stuff from that point.

    The effectiveness of the vector search depends on how Open WebUI breaks up the documents into smaller sections, and how good the embeddings are.

    I’m not exactly sure what you want to achieve, but you might have success in using an LLM to summarize the documents beforehand, using a specific prompt to extract the info you want, then feed that into the vector DB. This would require some scripting, of course.

    The easiest thing to do is try it. See if Open WebUI’s vector search is able to handle it. Make sure to use a good embedding model like nomic-embed-text (can be found on ollama.com). You can change the vector search settings in the documents settings from the workspace on OpenWebUI.

    Edit: https://ollama.com/library/nomic-embed-text