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    <title>DEV Community: Isha Gautam</title>
    <description>The latest articles on DEV Community by Isha Gautam (@ishagautam504).</description>
    <link>https://dev.to/ishagautam504</link>
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      <title>DEV Community: Isha Gautam</title>
      <link>https://dev.to/ishagautam504</link>
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      <title>PLATEWISE</title>
      <dc:creator>Isha Gautam</dc:creator>
      <pubDate>Mon, 05 Oct 2026 00:26:28 +0000</pubDate>
      <link>https://dev.to/ishagautam504/platewise-20gm</link>
      <guid>https://dev.to/ishagautam504/platewise-20gm</guid>
      <description>&lt;p&gt;PlateWise — Your Plate. Your Rules.&lt;/p&gt;

&lt;p&gt;This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend&lt;/p&gt;

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

&lt;p&gt;I built PlateWise, a simple AI-powered personalized meal planner.&lt;/p&gt;

&lt;p&gt;I originally built it for a friend who wanted an easier way to plan meals while keeping personal preferences and food allergies in mind. I wanted to make something that could take a few basic details about a person and turn them into a meal plan that actually fits them.&lt;/p&gt;

&lt;p&gt;With PlateWise, users can enter their dietary preference, fitness goal, allergies, foods they don't like, number of meals they want per day, and optionally their daily calorie target.&lt;/p&gt;

&lt;p&gt;The app then uses this information to generate a personalized meal plan.&lt;/p&gt;

&lt;p&gt;One thing I really wanted to get right was allergies. Instead of completely trusting the AI's response, I added a separate backend allergy checker that checks the ingredients generated by the AI against the user's listed allergies before showing the meal plan.&lt;/p&gt;

&lt;p&gt;The basic idea was:&lt;/p&gt;

&lt;p&gt;Let AI generate. Let the backend verify.&lt;/p&gt;

&lt;p&gt;Code&lt;/p&gt;

&lt;p&gt;GitHub Repository:&lt;br&gt;
&lt;a href="https://github.com/shiriei/PLATEWISE" rel="noopener noreferrer"&gt;https://github.com/shiriei/PLATEWISE&lt;/a&gt; &lt;/p&gt;

&lt;p&gt;The project is built as a small full-stack application using React, FastAPI, SQLite, and Gemini.&lt;/p&gt;

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

&lt;p&gt;The frontend is built with React, Vite, and TypeScript, while the backend uses Python and FastAPI. SQLite is used to store the user's preferences and profile information.&lt;/p&gt;

&lt;p&gt;For the AI part, I used the Gemini API to generate the meal plans based on the information provided by the user.&lt;/p&gt;

&lt;p&gt;I also built a simple rule-based allergy checker in the backend. After Gemini generates the meal plan, the backend checks the ingredients against the user's allergies before returning the result.&lt;/p&gt;

&lt;p&gt;The basic flow is:&lt;/p&gt;

&lt;p&gt;User Profile&lt;br&gt;
↓&lt;br&gt;
FastAPI&lt;br&gt;
↓&lt;br&gt;
Gemini&lt;br&gt;
↓&lt;br&gt;
Meal Plan&lt;br&gt;
↓&lt;br&gt;
Allergy Checker&lt;br&gt;
↓&lt;br&gt;
Final Meal Plan&lt;/p&gt;

&lt;p&gt;I wanted to keep the project simple rather than adding a lot of unnecessary features. The main focus was to make something useful, easy to understand, and safe enough to handle one of the most important pieces of information in a meal planner: the user's allergies.&lt;/p&gt;

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      <category>weekendchallenge</category>
      <category>hf26challenge</category>
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