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    <title>DEV Community: Mira Kumar</title>
    <description>The latest articles on DEV Community by Mira Kumar (@mira_kumar).</description>
    <link>https://dev.to/mira_kumar</link>
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      <title>DEV Community: Mira Kumar</title>
      <link>https://dev.to/mira_kumar</link>
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    <item>
      <title>Roast your dog</title>
      <dc:creator>Mira Kumar</dc:creator>
      <pubDate>Mon, 17 Aug 2026 01:20:47 +0000</pubDate>
      <link>https://dev.to/mira_kumar/roast-your-dog-31bf</link>
      <guid>https://dev.to/mira_kumar/roast-your-dog-31bf</guid>
      <description>&lt;p&gt;&lt;em&gt;This is a submission for &lt;a href="https://dev.to/challenges/weekend-2026-08-13"&gt;Weekend Challenge: Dog Days Edition&lt;/a&gt;&lt;/em&gt;&lt;/p&gt;

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

&lt;p&gt;I built Dog Roaster - a small web app deployed on vercel. You can upload an image of your dog (format - jpg, png, max size - 8MB), and the Gemini AI (model: 3.6-flash) would generate a roast line.&lt;/p&gt;

&lt;p&gt;The idea is simple on purpose: one upload, one API call, one roast. No sign-up, no clutter. Just upload, or drag and drop, get humbled.&lt;/p&gt;

&lt;p&gt;&lt;a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fpkt6ijeiji8pfzfmvzj4.png" class="article-body-image-wrapper"&gt;&lt;img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fpkt6ijeiji8pfzfmvzj4.png" alt=" " width="800" height="790"&gt;&lt;/a&gt;&lt;/p&gt;

&lt;h2&gt;
  
  
  Demo
&lt;/h2&gt;

&lt;p&gt;Link: &lt;a href="https://dog-roast.vercel.app/" rel="noopener noreferrer"&gt;https://dog-roast.vercel.app/&lt;/a&gt; &lt;/p&gt;

&lt;p&gt;&lt;a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fxyxsnvbvp3mqs5tbl3gg.png" class="article-body-image-wrapper"&gt;&lt;img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fxyxsnvbvp3mqs5tbl3gg.png" alt=" " width="800" height="726"&gt;&lt;/a&gt;&lt;/p&gt;

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

&lt;p&gt;Github link: &lt;a href="https://github.com/MIRA-KUMAR/dog-roast" rel="noopener noreferrer"&gt;https://github.com/MIRA-KUMAR/dog-roast&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;&lt;a href="https://github.com/MIRA-KUMAR/dog-roast/blob/main/README.md" rel="noopener noreferrer"&gt;README.md&lt;/a&gt; has instructions to run to locally and modify the model and prompt accordingly.&lt;/p&gt;

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

&lt;p&gt;The app is a lightweight frontend + serverless backend, deployed on Vercel:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;&lt;p&gt;Image upload — users upload a dog photo directly from the browser (jpg/png, capped at 8MB to keep things fast and within API limits).&lt;/p&gt;&lt;/li&gt;
&lt;li&gt;&lt;p&gt;Gemini Vision — the image is sent to Google's @google/genai SDK using gemini-3.6-flash, prompted to look at the photo and generate a short, punchy roast rather than a neutral description.&lt;/p&gt;&lt;/li&gt;
&lt;li&gt;&lt;p&gt;Retry handling — API calls are wrapped in a retry function to gracefully handle transient 503 errors from the model.&lt;/p&gt;&lt;/li&gt;
&lt;li&gt;&lt;p&gt;Serverless deployment — the whole thing runs on Vercel.&lt;/p&gt;&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;The trickiest part was actually picking the right model. I started with &lt;code&gt;gemini-3.7-flash&lt;/code&gt; since it's the newest, but it kept throwing 503s under high traffic. Switching to &lt;code&gt;gemini-3.6-flash&lt;/code&gt; fixed it immediately: still fast, still sharp on the roasts.&lt;/p&gt;

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

&lt;p&gt;Submitting to Best Use of Google AI — Gemini, using the image upload directly as model input and outputting text.&lt;/p&gt;

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      <category>weekendchallenge</category>
      <category>dogroast</category>
      <category>gemini</category>
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