A P2P Web App for Chat, File Transfer, and Video Calls

Hacker News

I’d like to share a open source project I’ve been working on: Weblink, a pure web-based file transfer and chat application built on WebRTC. No downloads or installations are needed—everything works directly in your browser. Key features include: - Works seamlessly as a PWA for sharing files/text through the system - File synchronization and resuming interrupted transfers - Video calling - Clipboard and folder transfer (folders are auto-compressed) Weblink uses a serverless P2P architecture, supporting multiple backends like Firebase and self-hosted WebSocket, and ensures signaling privacy with end-to-end encryption. It’s deployed on Vercel and using Firebase can be accessed here: https://web1ink.vercel.app . Another example of using websocket can be found at https://webl.ink Would love your thoughts and feedback!

Visit product View on Hacker NewsNov 30, 2024

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

82%82% 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

61%61% 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

59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

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

45%45% 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

18%18% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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