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Telnet lunatic.chat – A chat server for the terminal

Hacker News

Telnet lunatic.chat – A chat server for the terminal

Hi HN, I'm working on an Erlang inspired WebAssembly runtime for the backend[0]. Recently I added TCP support and was looking for apps I could build with it. I ended up building a telnet line chat app. It was a great dogfooding experience and has a nice retro feel to it. You can access the US server with > telnet lunatic.chat or the EU one with: > telnet eu.lunatic.chat You should pick the one closer to you as all the rendering is done on the backend and lower latency will mean better UX. The server is open source[1] and written in Rust. The Rust code is then compiled to WebAssembly and runs on top of Lunatic. Each connection runs in a separate (lightweight) process, has it's own state and sends just a diff of esc-sequences back to the terminal to bring it up to date with the current render buffer. Everything is deployed to an ARM Linux box. [0]: https://github.com/lunatic-solutions/lunatic [1]: https://github.com/lunatic-solutions/chat

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, code, open · Missing: mac, agents, macos
72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: open source, 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.
Indie HackersIH features products with proven revenue · Strong signals: para · Missing: supports, reddit linkedin, podcasting
45%45% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, para · Missing: mobile apps, ios, personal
35%35% 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
34%34% 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
13%13% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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