Fo

Forte, an open-source self-hosted music platform with lots of features

Hacker News

Forte, an open-source self-hosted music platform with lots of features

Hey everyone, I've made a project to make your own music archive streamable and turn it into a complete music platform. The reason I've been working on this project for a while was to stream the CD's I've had at home without any cost and also make a nice looking system to manage and listen to these albums. You can host your own server and use the web player to connect. Also, it is possible to create users and give them access to your own server. Some features of the current release are group sessions, endless listening with radio, fuzzy searches, showing lyrics and specialized context menus. This was the first biggest project I've made using Vue.js and I am open to any suggestions. Feel free to leave a comment. I really appreciate your support! GitHub Repo: https://github.com/kaangiray26/forte Web Player: https://forte.buzl.uk/

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Actual performance

6points
1comments
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, context, using · Missing: mac, agents, macos
81%81% 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
72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: platform, host, users · Missing: plus, intuitive, reviews
58%58% 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
57%57% 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
42%42% 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
9%9% 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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