ChatGPT Highlight – A KOReader Plugin Powered by OpenAI

Hacker News

I just released AskGPT, a plugin for KOReader that allows users to ask questions about highlighted text in their eBooks. The plugin generates a response using OpenAI's ChatGPT, offering instant answers and insights to improve the reading experience. I know this is super niche, but I found out recently I could jailbreak my Kindle and it led to this project! Key features: Simple integration with KOReader Utilizes OpenAI's ChatGPT for response generation Get insights and answers instantly while reading Check out the video demonstration here: https://www.youtube.com/watch?v=lu8oq_hKpac I'd appreciate any feedback and suggestions. You can download the plugin here: https://github.com/drewbaumann/AskGPT

Visit product View on Hacker NewsMar 28, 2023

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4points

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, chatgpt, openai · Missing: mac, agents, macos

65%65% 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

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: video, answers, users · Missing: mobile apps, ios, personal

62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

Hacker NewsMay not resonate with HN audience · Strong signals: just released, ide, io · Missing: https docs, excited, exist

37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

12%12% 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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