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I built a bot that lets you generate AI art without leaving Twitter

Hacker News

I built a bot that lets you generate AI art without leaving Twitter

Hey HN I've been building Super Prompts [1]. It's a place for AI artists to share and organise their work. I noticed that lots of artists post their work primarily on Twitter and there's no easy way to see all their work in one place. Whenever I'd ask to see all their work they'd either sheepishly point me to their Twitter "Media" tab or I'd have to comb through 5 different NFT platforms and aggregate it myself. I built a little tool called "/publish" that lets you create a gallery for your AI art without leaving Twitter. You just reply to a tweet containing your artwork with "/publish @superprompts" and we add it to your gallery. Now I've built a fun little tool that lets you generate AI art with Stable Diffusion without leaving Twitter. You can tweet "/generate @superprompts" followed by your prompt, and we'll generate the art, publish it to Super Prompts, and reply to your tweet with your creation. It's completely free but it does require you to sign up on Super Prompts and verify your Twitter first. I'm using Google Cloud Functions to check for new Twitter mentions every minute and handle accordingly. To generate the art I'm using Replicate [2]. They provide an API to run machine learning models in the cloud. Would love to know what you think. [1] https://superprompts.com [2] https://replicate.com

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, model, google · Missing: agents, macos, agent
87%87% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google, way · Missing: mobile apps, ios, personal
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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