Vanilla Cookbook – a deceptively simple recipe manager

Hacker News

Vanilla Cookbook is a self hosted recipe manager built with Svelte(kit). It is designed with complexity under the hood, keeping the user experience as uncluttered, simply vanilla as possible. A brief feature list: - Recipe Scraping - via script with optional OpenAI API backup, old school bookmarklet - Smart unit conversion, volumetric ingredient matching (cups to grams via an ingredient lookup table), temperature parsing in instructions - Complex ingredient parsing for quantity, units, ranges, fractions, extras - Multiple language support - User management - Data control: Paprika format import/export - Shopping list - Cooking logs - Docker deployment - PWA - Local storage: images + SQLite Constructive feedback, GitHub issues/contributions/stars(!) are all very welcome.

Visit product View on Hacker NewsMar 23, 2025

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

82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

44%44% 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 · Missing: mobile apps, ios, personal

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive

36%36% 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: smart · Missing: web3, chat, crypto

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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