CapSlap – Local caption generation using Whisper

Hacker News

Built this for a friend who needed to add captions to videos without uploading to third-party services. uses whisper models locally or Openai's api as a fallback. Features: - Runs entirely on your machine (privacy-first) - Supports local whisper models - Openai api integration optional - Free and open source Technical notes: - Macos only (haven't tested on windows) - Built with Rust, ffmpeg 8, Electron - You'll need to either run from source or allow the app in system settings (no apple developer cert, so gatekeeper will complain). Pretty straightforward if you're comfortable with terminal or adjusting security settings Figured the HN community might find it useful or have suggestions for improvement. Github: https://github.com/riseandignite/capslap Happy to answer questions or take feedback.

Visit product View on Hacker NewsOct 29, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, model · Missing: agents, agent, cursor

88%88% 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 · Strong signals: supports · Missing: reddit linkedin, podcasting, created

83%83% 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

55%55% 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 · Missing: plus, platform, intuitive

41%41% 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

38%38% 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

14%14% 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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