DEV Community: Nakul Chaurasia

🌿 Plant Care Companion: An AI App That Gets You Off Your Screen & Into Your Garden 🌱

Nakul Chaurasia — Fri, 09 Oct 2026 17:23:27 +0000

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass

What I Built

Plant Care Companion — A free, AI-powered web app that gets people off their screens and into their gardens.

Instead of doomscrolling, users step outside, snap a photo of any plant (houseplant, garden flower, random leaf on a walk), and instantly get:

Plant identification with scientific names and fun facts
Health diagnosis detecting diseases, pests, overwatering, nutrient issues
3-step action plans to fix problems in plain, beginner-friendly language

It's built for anyone who wants to care for plants but lacks botanical knowledge — busy parents, apartment dwellers with struggling succulents, curious kids exploring parks, or hobby gardeners troubleshooting brown leaves.

The app encourages real-world interaction: you have to physically go outside, observe your plant closely, and take action based on the diagnosis. The screen is just the bridge, not the destination.

Demo

🌐 Live App: https://plant-care-ai-u9u8.vercel.app/

📸 How it works:

Upload a plant photo (drag & drop or click)
Choose "Identify this Plant" or "Check Health & Diseases"
Get instant, warm, human-like expert advice in seconds

![App Screenshot](

Code

CYBERtony786 / plant-care-ai

🌿 Plant Care Companion

Built for Hacktoberfest 2026 - Week 1: Touch Grass Challenge

A modern, AI-powered web application that helps people step away from their screens and connect with nature. Upload a photo of any plant, and get instant expert identification and health advice.

🌍 Problem Statement

In today's digital world, people spend countless hours staring at screens while their houseplants wither away or their gardens remain mysteries. Many want to care for plants but lack botanical knowledge. Commercial plant apps are expensive, require subscriptions, and often share your data.

Plant Care Companion solves this by:

Providing free, instant plant identification
Diagnosing plant health issues with actionable fixes
Encouraging people to go outside, observe nature, and engage with their plants
Keeping your data private and secure

✨ Features

🌱 Plant Identification

Upload a photo and instantly learn the common name, scientific name, and interesting facts about your plant.

🩺

…

View on GitHub

Key files:

app/page.tsx — Main UI with image upload and action buttons
app/api/analyze/route.ts — Serverless API that calls Gemini Vision AI
app/components/ImageUploader.tsx — Drag-and-drop component
.env.local — Secure API key storage (gitignored)

How I Built It

Open-Source AI at the Core

I used Google Gemini 3.8 Flash (vision-capable, open-weight model) via the @google/genai SDK. This model can analyze images and respond in natural language — perfect for identifying plants and diagnosing issues from photos.

Why Gemini?

Free tier with generous limits (no per-token costs during development)
Vision capabilities out of the box (processes photos directly)
Fast inference (~2-3 seconds per request)
Can be swapped for local models like LLaVA if I want to run this offline

Tech Stack

Frontend: Next.js 15 + React 19 + TypeScript
Styling: Tailwind CSS 4 with custom earthy green theme (not generic AI blue!)
Backend: Next.js API Routes (serverless functions)
Deployment: Vercel (free tier, auto-scaling)

Architecture

The app uses a simple client-server flow:

User uploads image → converted to base64 in browser
Frontend sends base64 + prompt to /api/analyze
Backend calls Gemini Vision API with custom prompts
AI response is formatted and returned to user

I crafted two distinct prompts:

Botanist mode: "You are a friendly expert botanist..." (warm, educational)
Gardener mode: "You are an experienced gardener..." (practical, troubleshooting)

This makes the AI sound human, not robotic.

Why Does Open Innovation Matter?

Privacy & Control

Using open-weight models means users could run this locally (with Ollama + LLaVA) without sending plant photos to third-party servers. For rare plant collectors or commercial growers, keeping image data private matters.

Cost & Accessibility

Closed APIs like GPT-4 Vision charge per-token. For a free gardening tool, that's unsustainable. Open models (Gemini free tier, or self-hosted Llama Vision) make this viable long-term.

Transparency & Customization

I can see exactly how the model works, fine-tune prompts, and even swap models if Google's API changes. With a closed API, I'm locked in. Open AI lets me adapt — for example, I could train a specialized model on plant diseases specific to my region.

Offline Access

In the future, I could package this as a Progressive Web App (PWA) with a local model for hikers and nature explorers with no internet connection. Open AI makes that possible.

My Agent Session

This entire project was built using "Vibe Coding" with an AI agent (Antigravity). I wrote zero lines of code by hand — just described what I wanted in plain language, and the agent:

Scaffolded the full Next.js project structure
Wrote TypeScript components with drag-and-drop file upload
Integrated Gemini Vision API with error handling
Created a professional README for GitHub
Fixed API versioning issues when Google updated model names

(Optional: If you saved your session with DevRelay, embed it here using the agent_session tag)

Prize Categories

I'm entering:

Best Overall Project (Core challenge)
Best Use of Open-Source AI (Uses open-weight Gemini model)
Most Impactful "Touch Grass" Project (Gets people outdoors and gardening)

Built with ❤️ and open-source AI for Hacktoberfest 2026.

Get outside. Touch grass. Care for your plants. 🌱

Study Buddy

Nakul Chaurasia — Sat, 03 Oct 2026 15:32:11 +0000

This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend

What I Built

I built StudyBuddy—an all-in-one, distraction-free study companion web app designed to help learners conquer exam fatigue, stay in deep focus, and retain knowledge effectively.

The Friend I Built It For

I built this for my friend who has been preparing for demanding tech certification exams and software engineering interviews. Like many students and self-learners, they found themselves constantly context-switching between 4 different tools:

A noisy Pomodoro timer app filled with ads.
A clunky online flashcard app that required an account and monthly subscription.
Random quiz websites that didn't allow customizing questions.
A white noise app that drained laptop battery in the background. This fragmentation caused friction and mental exhaustion before the actual studying even started. ### The Solution: StudyBuddy StudyBuddy unites all these tools into a single, cohesive, zero-friction experience:
⏱️ Customizable Pomodoro Clock: Choose or customize your Focus, Short Break, and Long Break durations, track session rounds, watch a smooth SVG progress dial, and hear a calming 3-note audio chime upon completion.
🎧 Built-In Focus Ambience: Synthesized soundscapes (Rain, White Noise, Ocean Waves) built directly with the Web Audio API—no heavy streaming or external audio files required.
🗂️ Interactive 3D Flashcards: Realistic flip animations, card recall grading ("Mastered" vs. "Needs Review"), deck switcher, and full card editing/shuffling with keyboard shortcuts (Space, ◀, ▶).
📝 Quiz Master (with 1-Click Flashcard-to-Quiz Conversion): Test recall with instant feedback and explanations. Learners can build custom multiple-choice quizzes or auto-generate a quiz directly from their active flashcards!
🤖 Pixel the Virtual Study Buddy: An animated, expressive companion mascot that shares contextual encouragement, tracks daily focus time, and celebrates high quiz scores with confetti.

- 🔒 100% Private & Offline-Ready: Operates completely in the browser with `localStorage` persistence, dark/light mode toggle, and full JSON data export/import capabilities.

Demo

Live Demo Link: https://cybertony786.github.io/studybuddy/
Repository Preview:



 ┌─────────────────────────────────────────────────────────────┐
 │  StudyBuddy 🎓           [Pomodoro] [Flashcards] [Quiz] [⚙]  │
 ├───────────────────────────────┬─────────────────────────────┤
 │                               │   🤖 Pixel (Study Buddy)    │
 │            25:00              │   "You've got this! Let's   │
 │        [Stay focused]         │    conquer your goals!"     │
 │          Round 1/4            │                             │
 │                               │   🎯 Goal: Master Closures  │
 │     [Start]  [Reset]  [Skip]  │   ⏱ 50m Focus Today        │

INTRO

Nakul Chaurasia — Thu, 01 Oct 2026 17:07:09 +0000

I am new to the community,happy to be the part of dev.

DEV Community: Nakul Chaurasia

🌿 Plant Care Companion: An AI App That Gets You Off Your Screen & Into Your Garden 🌱

What I Built

Demo

Code

CYBERtony786 / plant-care-ai

🌿 Plant Care Companion

🌍 Problem Statement

✨ Features

🌱 Plant Identification

🩺

How I Built It

Open-Source AI at the Core

Tech Stack

Architecture

Why Does Open Innovation Matter?

Privacy & Control

Cost & Accessibility

Transparency & Customization

Offline Access

My Agent Session

Prize Categories

Study Buddy

What I Built

The Friend I Built It For

- 🔒 100% Private & Offline-Ready: Operates completely in the browser with localStorage persistence, dark/light mode toggle, and full JSON data export/import capabilities.

Demo

INTRO

- 🔒 100% Private & Offline-Ready: Operates completely in the browser with `localStorage` persistence, dark/light mode toggle, and full JSON data export/import capabilities.