PredictEd: A free and open source predictive text editor for windows

Hacker News

Video intro: https://www.youtube.com/watch?v=RZPQNAE9kYs Download link: https://github.com/oormicreations/PredictEd/releases It suggests words for auto completion as you start typing. It suggests the next probable words when you finish typing a word, and when you press the space bar, or when you auto complete the word, and press space bar. It presents five such words and three phrases below your cursor. Pressing the tab key selects the next word or phrase in the list. PredictEd learns, as you type in real time, and creates a knowledge base unique to your style of writing, and your subject matter. You get the most relevant suggestions as it builds up its knowledge from the words and phrases you type. Gradually it becomes your personal typing assistant. You can also feed it your own writings in the form of text files, and instantly get the same result. It also has some more smart features like formatting as you type. It also capitalizes the words, inserts spaces after periods and inserts paragraph breaks after new lines. It saves the file after each paragraph automatically. Source code: https://github.com/oormicreations/PredictEd

Visit product View on Hacker NewsAug 11, 2018

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3points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, new, code · 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.

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.

Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting

53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

51%51% 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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: real time, smart · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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