Build a Visual Novel with AI

Hacker News

Hey HN, I built a simple visual novel creator using a combination of tools such as Flux, LLM APIs and three.js. You can describe your game concept ("I am a knight sitting in a bar with a mysterious witch who only speaks in riddles") and mangobox will generate the characters, plot, environment, etc. Current solutions to build VNs such as Ren'Py involve using a python library and distributing an executable. It requires a decent amount of technical knowledge which makes building VNs difficult unless you are a programmer. While my MVP doesn't cover even a small fraction of what Ren'Py does, my hope is to slowly achieve feature parity. After an early access launch, my average session time across all users is ~1 hour. Hope you enjoy!

Visit product View on Hacker NewsJan 29, 2025

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, visual, using · Missing: mac, agents, macos

76%76% 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

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive

51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% 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.

Incorrect prediction on native model

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