Emoji This – A tool to decorate your texts with emojis

Hacker News

Hi HN! I have created a website (and app) where you can send a text, and it will decorate it with relevant emojis: https://emojithis.com I noticed that I often use ChatGPT to add emojis to my messages, so I created a super simple one-API-call thing. I ended up using it a lot, and after a 5-minute search, I noticed that something like this didn’t exist! So, I asked ChatGPT for a website design (please don't judge me :) ), made the tool more robust, and showed it to some friends. Naturally, they asked for more features, such as a list of relevant emojis, which proved to be very popular. They also asked for an app, which gave me the opportunity to check React Native (pretty OK for small projects like this!). Other things: I tried to run LLaMA locally on my server, but it could not handle more than two requests concurrently. Hallucinations and 'jailbreaking' are hopefully taken care of. There are some AI API costs, and I may shut it down if they get out of hand (unlikely). I thought about adding a small ad to compensate for the costs, but Google did not approve the site. I added some content and reapplied. The mobile apps have ads. That's my get-rich-quick scheme (joke).

Visit product View on Hacker NewsJan 22, 2025

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3points

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: google, apps, chatgpt · Missing: mac, agents, macos

82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: exist, llama, io · Missing: https docs, excited, just released

59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: mobile apps, apps, google · Missing: ios, personal, entrepreneurs

54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

48%48% 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

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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