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Generate 100 recipes with images using Tablepilot

Hacker News

Generate 100 recipes with images using Tablepilot

Hey HN, I’m the creator of Tablepilot ( https://github.com/Yiling-J/tablepilot ), an open-source tool that lets you effortlessly generate or autofill content for tables using AI. Tablepilot comes with both a CLI and WebUI interface, and it allows you to easily switch between different models. To give you an idea of how it works, I’ve created this 100 AI Generated Recipes example, which includes detailed information and images. The recipes are generated using `gemini-2.0-flash-001` and `gemini-2.0-flash-exp-image-generation`. To ensure diversity in the results, I use three columns as context to guide the LLM: Cuisine, Must Have Ingredient, and Meal. You can check out the results on this Notion site: https://tabulator-ai.notion.site/1df2066c65b580e9ad76dbd12ae... . The gallery view showcases the images nicely, and you can switch to table view to explore the details of each recipe. Why Tablepilot? I've always been interested in spreadsheets, AI, and workflow automation, and Tablepilot is my attempt to combine all these together into one tool. To my knowledge, there isn't an open-source tool quite like this. While you might be able to achieve something similar using platforms like Airtable or Notion, they are not open-source and may come with costs. On the other hand, tools like Dify or LangChain are powerful but often feel overengineered for simple table content generation case. Tablepilot, however, is designed to be simple yet powerful, making it perfect for generating table based data with ease.

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, gemini · Missing: supports, reddit linkedin, podcasting
90%90% 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: model, models, context · Missing: mac, agents, macos
83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: platform, interface · Missing: plus, intuitive, reviews
53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
52%52% 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: way · Missing: mobile apps, ios, personal
50%50% 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
9%9% 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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