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Open Artifacts - Crop and Talk to edit your Artifacts

Hacker News

Open Artifacts - Crop and Talk to edit your Artifacts

App: https://openartifacts.vercel.app Code: https://github.com/13point5/open-artifacts Open Artifacts allows you to create Artifacts like Claude with your API keys and OpenAI LLMs too. I'm building this to explore new UXs to interact with LLMs. Interesting Feature - Crop and Talk You can iterate editing Artifacts by visually cropping areas of the artifact and you can also speak if you have an OpenAI API key. Please use it and share your thoughts and any issues!

Visit productView on Hacker NewsJul 23, 2024
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, new, visual · Missing: mac, agents, macos
93%93% 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.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
41%41% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.
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
7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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