cross-posted from: https://lemmy.world/post/16102424
Hi all,
Quiblr now has personalized post feeds for Lemmy!
I haven’t seen a “recommended feed” feature anywhere else in the fediverse but I thought I would take a crack at building it!
My goal was to make a privacy-focused recommendation engine that tailors your experience based on the content you interact with. None of the data leaves your device. You don’t even need to log in for it to work
- You can turn it off or tune your feed in the settings
- Each post now also includes a show me more/less button
I would LOVE feedback from folks if you get a chance to try it out!
This was really fun to build so let me know if there are any questions!
PS: Let me know if someone else has built this feature for the fediverse - then I will change the title to not claim “the first” lol
So it’s fully local right? That’s a really awesome system then. I’d probably recommend encrypting the data but that’s not really necessary
Yup, 100% completely local to your device alone
I don’t understand why nobody did it in the past. It makes the experience so much better for normal users. I hope this becomes mainstream. Btw does it have any automatic analytics cache cleaning or something like that (so it doesn’t grow 20 gigs of it in a year)? If so, make sure it cleans it periodically and not immediately when a piece of data becomes unneeded. On low end devices frequent write/delete cycles can be an issue
I can’t go into too much detail, I was working for a recognisable company who was dabbling in the Fediverse with a heavy lean towards empowering the users.
This was high on my list of demands. Along with fine grain controls for what metrics you opt into and what notifications you receive.
Project got gutted early this year.
Hmm that sounded a bit sus to me. I would highly suggest you not to work for unethical companies, mister/miss
I appreciate the kind words. And yes, I included a mechanism to constantly refresh and clean up recommendations so that it doesn’t use too much memory
How do you pay for costs? Will there be donations or a premium feature?
I use Kofi for donations (button in the top bar). I build and pay for everything myself so support is appreciated!
Apologies for the late comment. So this is a full-fledged frontend like photon or alexandrite, but with this recommendation engine built in? On first glance, it looks so much more responsive and lightweight! I’m really wondering what you’ve done that other big frontends haven’t lol, no broken images or anything! If you do end up going open source, I might consider actually contributing to something for once. I’d love to help build out some features.
Edit: After using it for a few minutes, wtf, it’s snappier than lemmy itself. And the community search, wow! Maybe a pretty ui does something to perception, I dunno. I am assuming you have barrels of cache lol.
I appreciate all the kind words! You are correct that it is a frontend with recommendation engine built in. And the speed likely comes from being a progressive web app.
There are tradeoffs, but it definitely makes thinks “snappier” :)
Can you elaborate how and what actions will affect my feed? I don’t quite understand how this works without any login as I can’t vote or write comments. Also how do my subscriptions affect it if I’m logged in to an instance?
I do like it and would wish something like that as an app.
Better late then never, thanks!
Wow this is such a clean and snappy Lemmy client, may become my new daily driver!
The “For You” feed looks like it has a similar focus as the one I have on Agora, which is a webapp for following people across the “extended Fediverse” as I call it (Mastodon, Bluesky, Threads, Nostr).
The For You feed on Agora utilizes a fork of the open source FediAlgo library to create a feed that combines interesting posts from people you follow, as well as friends of friends, and it learns your preferences based on whose content you like/boost.
Agora: https://agorasocial.app
Source code: https://github.com/ghobs91/agora
How does it work? I was planning on importing a recommendation algorithm I made in the past for MAL for an upcoming fediverse summer project I was thinking of making that was also pretty much privacy-friendly. I’d like to know how you do the on device recommendation though. Since it’s content based, do you download thousands of posts or something?
Do you mean it downloads all the posts whether you read them or not? Is that basically running your own instance?
No. Posts are not downloaded and Quiblr is purely a frontend (you can choose which instance you want to use). The algorithm basically crafts the relevant API calls to populate the For You feed with content that matches your usage preferences. Those preferences and metadata are all stored on your device
🚩 Anti-libre software bans us from proving it’s claims. This is worse, service as a software substitute.
