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I made a local web-based notes app in the spirit of "One Big Text File"

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I made a local web-based notes app in the spirit of "One Big Text File"

Textpod is a simple UI on top of a single notes.md file + a few features I always wanted: - add + in front of a link to fetch a local copy of the page (downloaded in the background using monolith[1]) - search is integrated into the note input, just start typing with / - attach images and other files (stored in 'attachments' directory) I made a 1-minute demo video (no sound) [2]. When you start the binary, the data is served from the current directory: the notes file and the attachments directory are created automatically. Run multiple instances from different directories, if needed (I do that to separate work and personal notes). It's a very rough initial version thrown together on a Sunday evening. I hope to add nicer error messages and some customizations later. [1] https://crates.io/crates/monolith [2] https://www.youtube.com/watch?v=VAqJJxaJNVM

Visit productView on Hacker NewsOct 28, 2024
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: single, using, notes · Missing: mac, agents, macos
67%67% 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: created, para · Missing: supports, reddit linkedin, podcasting
67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: personal, video, way · Missing: mobile apps, ios, entrepreneurs
48%48% 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
43%43% 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
17%17% 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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