@Vertex is now easier to use, and it's free!
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Replies (16)
this decision was inspired by conversations with @Vladimir KrstiΔ, @franzap and @calle. So thanks guys, keep the feedback coming π«
Jellyfish also uses Vertex for spam protection.
Amazing! π€
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damn you are right, let me add it to the blog post!
just added
I approve of this message
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Who pays for the public relays ? There is nothing free, someone pays in the end
Sold me at free!
Time to check it out :)
Main / docs page needs a link to the actual product / utility. I was briefly mentioning Vertex recently and both times I tried to find the actual tool, I just ended up frantically navigating docs and giving up. If it's there maybe I'm retarded but I don't think there's a link from this site
well, the product is the services.
It's not for end users to interact.
Services
Supercharge your app with Web of Trust in minutes, reducing spam and increasing signal Nostr Relay Free Verify Reputation Recommend Follows Rank Pr...
TLDR;
Every reputable Nostr pubkey (+100K) receives 100 free @Vertex credits every day.
In your app, users sign job requests with their own key and send them to our relay. It's that simple!
No need to manage secrets, no need for backends.
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Right.. npub world is what I was looking for, I found it this time. I had conflated the two
I see some similarities with work we did using Neo4j to track follows/unfollows for push notifications. Since the graph was already there, we added a PageRank API too:
π https://followers.nos.social/api/v1/trusted/89ef92b9ebe6dc1e4ea398f6477f227e95429627b0a33dc89b640e137b256be5
Itβs only HTTP for now, but Iβm considering exposing it on Nostr with the same custom kinds you use for PageRank data π€
Code: 
cc @rabble
GitHub
GitHub - planetary-social/nos-followers: Server for Nostr follows and unfollows
Server for Nostr follows and unfollows. Contribute to planetary-social/nos-followers development by creating an account on GitHub.
yes, it's similar. I've looked into neo4j and memgraph and I wasn't happy with the performance, so I've built my own graph database on top of Redis.
The result is that, instead of computing Pagerank every hour, storing the values and reading them, I can compute Pagerank every time a new follow list has been published.
So it's a dynamic Pagerank based on monte Carlo.
Also, it allows for personalized pagerank.
This is a clever approach, build trust on trust
Since this announcement, lots more people have been using @Vertex.
The best part is that I don't even know who they are, I just see the number of requests going up.
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