Generate stories (with images) based on a prompt

Hacker News

Hi! I wanted to introduce a sideproject that I worked on over the holiday period. My daughter and I love reading stories at bedtime. When ChatGPT came out, I started to experiment with it and decided to create short stories that we could read at bedtime. Surprisingly, my daughter really enjoyed these stories, they were short, engaging and fun. So I thought what if there was a way to create a catalog of these stories that we could keep as part of our (digital) library. The idea of StoryPanda was born. With just a prompt + age group + art style, you can generate short stories that are great for kids. Looking for feedback on the quality of stories it generates and I am now working on adding more functionality in coming weeks. Here is a story that was created by StoryPanda - https://storypanda.ai/s/dc59910a-cbcd-467b-8c98-f3481036cfd3 Check it out at http://storypanda.ai

Visit product View on Hacker NewsJan 10, 2023

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3points

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Launch Intel predictions

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

84%84% 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 HuntUnlikely to reach the leaderboard · Strong signals: chatgpt · Missing: mac, agents, macos

43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

38%38% predicted probability of success on TrustMRR, 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

21%21% 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

15%15% 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, introduce · Missing: web3, crypto, cryptocurrency

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

Correct prediction on native model

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