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    <title>DEV Community: Kesava Mohan Ganesh Anirudh Chunduru</title>
    <description>The latest articles on DEV Community by Kesava Mohan Ganesh Anirudh Chunduru (@anirudh645).</description>
    <link>https://dev.to/anirudh645</link>
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      <title>DEV Community: Kesava Mohan Ganesh Anirudh Chunduru</title>
      <link>https://dev.to/anirudh645</link>
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      <title>TouchGrass Duck: A Desktop Companion That Pulls You Away From the Screen Using Local AI Roasts &amp; ActivityWatch</title>
      <dc:creator>Kesava Mohan Ganesh Anirudh Chunduru</dc:creator>
      <pubDate>Sat, 10 Oct 2026 15:35:47 +0000</pubDate>
      <link>https://dev.to/anirudh645/touchgrass-duck-a-desktop-companion-that-pulls-you-away-from-the-screen-using-local-ai-roasts--epe</link>
      <guid>https://dev.to/anirudh645/touchgrass-duck-a-desktop-companion-that-pulls-you-away-from-the-screen-using-local-ai-roasts--epe</guid>
      <description>&lt;p&gt;&lt;em&gt;This is a submission for the &lt;a href="https://dev.to/challenges/hacktoberfest-week1-2026-10-05"&gt;Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass&lt;/a&gt;&lt;/em&gt;&lt;/p&gt;

&lt;h2&gt;
  
  
  What I Built
&lt;/h2&gt;

&lt;p&gt;Meet TouchGrass Duck (aw-touchgrass)—a desktop system tray utility designed for developers and power users who spend way too many hours glued to their monitors. Here is a small video showing how it works: &lt;a href="https://youtu.be/TVNW_Ak5oq8" rel="noopener noreferrer"&gt;Youtube Link&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;It works by combining your actual screen-time telemetry from ActivityWatch with local, lightweight open-weight models running via Ollama. When you’ve been deep in a coding rabbit hole for too long, the app triggers animated Tkinter overlays featuring an unforgiving, witty digital duck that delivers personalized, highly contextual local AI roasts to forcefully remind you to step away, touch grass, and reset.&lt;/p&gt;

&lt;h2&gt;
  
  
  Code
&lt;/h2&gt;

&lt;p&gt;You can check out the source code directly on GitHub:&lt;br&gt;
&lt;a href="https://github.com/A11-Code/aw-touchgrass" rel="noopener noreferrer"&gt;GitHub Repo.&lt;/a&gt;&lt;/p&gt;

&lt;h2&gt;
  
  
  How I Built It
&lt;/h2&gt;

&lt;p&gt;The application is built as a lightweight Python desktop app packaged cleanly via PyInstaller:&lt;/p&gt;

&lt;p&gt;Telemetry Layer: Integrates with ActivityWatch to pull live window and activity data, detecting long, uninterrupted screen sessions.&lt;/p&gt;

&lt;p&gt;AI Engine: Leverages local LLMs via Ollama (utilizing models like Qwen or Gemma) to dynamically generate savage, customized roasts based on how long you've been sitting down.&lt;/p&gt;

&lt;p&gt;UI &amp;amp; Overlay: Built using Tkinter to render cute, lightweight animated overlays directly on the Windows system tray and desktop without hogging system memory.&lt;/p&gt;

&lt;h2&gt;
  
  
  Why Does Open Innovation Matter?
&lt;/h2&gt;

&lt;p&gt;Building an app like TouchGrass Duck relies heavily on complete local control and privacy. Because it reads live screen telemetry and system activity, routing user behavior data through a closed third-party cloud API would be a massive privacy nightmare.&lt;/p&gt;

&lt;p&gt;Open-weight models and local inference via Ollama make it possible to run custom intelligence directly on the user's local machine. It ensures total data privacy while enabling zero-cost, offline-first agentic behavior without API rate limits or recurring subscription fees.&lt;/p&gt;

&lt;h2&gt;
  
  
  Prize Categories
&lt;/h2&gt;

&lt;p&gt;Open-Source AI (Local Inference &amp;amp; Ollama Integration)&lt;/p&gt;

&lt;p&gt;Productivity &amp;amp; Desktop Utilities&lt;/p&gt;

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      <category>devchallenge</category>
      <category>hf26challenge</category>
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