wjs018
Piefed contributor and part of the piefed.social admin team.
- 1 Post
- 5 Comments
wjs018@piefed.socialto
Programming@programming.dev•AI’s Unpaid Debt: How LLM Scrapers Destroy the Social Contract of Open SourceEnglish
3·7 months agoMbin 1.9 just came out and lets users basically set a custom image to go with the link. However, the way it federates is kind of messing up lemmy and piefed, where they just think it is a link to the image only.
wjs018@piefed.socialto
Programming@programming.dev•AI’s Unpaid Debt: How LLM Scrapers Destroy the Social Contract of Open SourceEnglish
5·7 months agoLooks like it since it came from fedia. I would need to take a peek at the AP json to be sure when I get a chance. The picture and the link come as two attachments, and PieFed just pulls the first one, the picture.
wjs018@piefed.socialto
Mlem for Lemmy@lemmy.ml•[ TestFlight Update ] Mlem TestFlight Patch Notes 2025-12-13English
3·8 months agoThat makes sense! Thanks for the explanation.
wjs018@piefed.socialto
Mlem for Lemmy@lemmy.ml•[ TestFlight Update ] Mlem TestFlight Patch Notes 2025-12-13English
4·8 months agooption to filter comment search by instance
Does this mean to search only for comments from users of a specific instance? Or does it mean comments made in communities local to a specific instance? I wasn’t even aware this was in lemmy’s api.

@blaze@piefed.zip has been asking for this feature for ages and @Skavau@piefed.social made an issue for it on the codeberg already. The reason this isn’t in the api yet is because it isn’t anywhere in piefed yet. AFAIK, the read/unread status of comments isn’t currently tracked anywhere within piefed. Additionally, for this feature, I don’t believe we track the timestamp at which you do interact with a post…so doing something like calculating the number of new comments that have occurred since you last opened that post isn’t possible…yet.
I don’t have a great idea of how to do this in a db-efficient way. Keeping track of when every user opens each post sounds like db-query hell. However, there might be clever caching tricks to make it a bit less computationally intense. @rimu@piefed.social would likely have a better idea of how to do this.