Nano PDF – A CLI Tool to Edit PDFs with Gemini's Nano Banana

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The new Gemini 3 Pro Image model (aka Nano Banana) is incredible at generating slides, so I thought it would be fun to build a CLI tool that lets you edit PDF presentations using plain English. The tool converts the page you want to edit into an image, sends it to the model API together with your prompt to generate an edited image, then converts the updated image back and stitches into the original document. Examples: - `nano-pdf edit deck.pdf 5 "Update the revenue chart to show Q3 at $2.5M"` - `nano-pdf add deck.pdf 15 "Create an executive summary slide with 5 bullet points"` Features: - Edit multiple pages in parallel - Add entirely new slides that match your deck's style - Google Search enabled by default so the model can look up current data - Preserves text layer for copy/paste and search It can work with any kind of PDF but I expect it would be most useful for a quick edit to a deck or something similar. GitHub: https://github.com/gavrielc/Nano-PDF

Visit product View on Hacker NewsNov 29, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, google, new · Missing: mac, agents, macos

83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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TrustMRRLess likely to generate early MRR · Strong signals: google, para · Missing: mobile apps, ios, personal

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

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

18%18% 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 · Strong signals: revenue · Missing: arr, mrr, profit

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2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

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