Next Beats – A Modern, Customizable, Open Source Lofi Music Player

Hacker News

Hey everyone, I've always wanted to build my own lofi player, and I recently added it to one of my projects, You-TLDR. I decided to open-source it so more people can play around with it and make it their own. NextBeats is a modern, customizable lofi music player built with Next.js and TypeScript. It features a retro TV-style interface, YouTube integration for endless lofi streams, sound effect mixing (rain, cafe, etc.), and theme customization. Perfect for coding, studying, or relaxing, it lets you add custom channels, control music and effect volumes independently, and save settings locally. Open-source and mobile-friendly. Appreciate any feedback!

Visit product View on Hacker NewsNov 17, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: coding, open · 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

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

69%69% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: friendly, interface · Missing: plus, platform, intuitive

44%44% 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

41%41% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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