DEV Community: Ramya Sai Challa

🎁 GiftGuide AI — Personalized Gift Ideas with Gemma

Ramya Sai Challa — Sun, 18 Oct 2026 15:05:00 +0000

🎁 What I Built

I built GiftGuide AI, an AI-powered gift recommendation tool that helps people find thoughtful gift ideas based on:

Recipient
Occasion
Interests
Budget
Relationship

The user enters these details, and Gemma generates four personalized gift recommendations with the gift name, why it fits, and an estimated price.

💡 Why I Built It

Choosing a good gift can be surprisingly difficult, especially when you know someone's interests but don't know what would actually suit them.

I wanted to build a simple tool that turns a few details about a person into practical gift suggestions.

I also wanted to explore how open-source AI can be turned into something that could potentially become a small side hustle.

🤖 How Gemma Is Used

Gemma is at the core of the application.

The user's information is included in a prompt containing:

Recipient
Occasion
Interests
Budget
Relationship

Gemma then generates exactly four personalized recommendations.

Each recommendation includes:

Gift Name

Why it fits

Estimated price

✨ Features

🎁 Personalized gift recommendations
🤖 Gemma-powered AI suggestions
💝 Interest-based recommendations
💰 Budget-aware suggestions
🎉 Occasion-based recommendations
💻 Simple web interface

💼 Who Would Pay for This?

This could potentially be useful for:

Gift shops
Personalized gift businesses
Event and wedding planners
Small businesses offering gift recommendations
People who frequently need personalized gift ideas

A future version could be offered as an AI recommendation service for businesses that want to help customers choose gifts.

🛠️ How I Built It

Frontend

HTML
CSS
JavaScript

Backend

Python
Flask

Gemma
Google GenAI SDK

The application sends the user's preferences to the Gemma model and displays the generated recommendations in the browser.

📸 Screenshots

🌱 Why Open Innovation Matters

Open AI models make it easier for students, developers, and small creators to experiment with AI and build useful applications without having to train an AI model from scratch.

This project helped me explore how an accessible AI model like Gemma can be used as the core of a practical application.

🔗 Project

GitHub:

https://github.com/Ramyasaichalla/GiftGuide-AI

🚀 Future Improvements

Some ideas for future versions:

Gift shopping links
More detailed price filtering
Better recommendation formatting
Occasion-specific recommendations
Public deployment
Business-focused features

Built for the Hacktoberfest 2026 Week 2 — Side Hustle Challenge.

devchallenge #hf26challenge #gemma

🚶 WalkQuest AI — Turning Screen Time Into Outdoor Time with Gemma

Ramya Sai Challa — Thu, 08 Oct 2026 13:21:07 +0000

🌿 What I Built

For the Hacktoberfest Open-Source AI Challenge — Week 1, I built WalkQuest AI, a simple AI-powered outdoor activity planner.

The idea is simple:

Instead of spending another session entirely in front of a screen, WalkQuest AI creates a personalized outdoor movement session based on:

🎯 Your goal
⏱️ Available time
🚶 Fitness level

The AI generates a complete WalkQuest with a warm-up, main exercise, outdoor challenge, cool-down, and a goal for the session.

🎯 Why I Built It

Getting enough movement into our daily routine can be difficult when so much of our time is spent studying, working, coding, or using our phones.

I wanted to build something that doesn't just give another productivity task on a screen.

The goal is to use AI to help people step away from the screen.

🤖 How AI Is Used

WalkQuest AI uses the Gemma open-weight model to generate the activity plan.

The user provides:

Goal
↓
Available Time
↓
Fitness Level
↓
Gemma
↓
Personalized WalkQuest

For example, the generated plan can include:

🌿 Warm-up
🚶 Main exercise
🌳 Outdoor quest
🌿 Cool-down
🎯 Today's goal

The outdoor quest makes the experience more interactive. Instead of simply saying "go for a walk", the AI can give the user something to observe or accomplish while outside.

✨ Features
🤖 AI-generated outdoor activity plans
🚶 Personalized walking sessions
⏱️ Custom exercise timer
⏸️ Pause / Resume
🛑 Stop session
🌳 Outdoor observation challenges
🎉 Session completion notification
⚠️ Beginner-friendly safety reminder
🛠️ How I Built It

The project uses:

Python
Flask
HTML
CSS
JavaScript
Gemma open-weight AI model
Google Gen AI SDK

The Flask backend sends the user's goal, available time, and fitness level to Gemma and returns the generated WalkQuest.

JavaScript handles the interactive interface and exercise timer.

📸 Demo

Create a WalkQuest

The user enters their goal, available time, and fitness level.

AI-generated WalkQuest

Gemma generates a personalized outdoor activity plan.

Start the outdoor session

The built-in timer helps the user stay on track during the session.

🌱 Why Open Innovation Matters

Open-weight AI models make it easier for students and independent developers to experiment with AI and build useful applications.

With Gemma, I was able to take a simple idea and turn it into a working application that combines AI with a real-world activity.

I especially liked the idea of using AI for something that encourages people to leave the screen rather than spend more time on it.

🔗 Code

The complete project is available on GitHub:
https://github.com/Ramyasaichalla/WalkQuest-AI.git

WalkQuest AI — GitHub Repository

🚀 Future Improvements

Some things I would like to add in the future:

🌦️ Weather-aware activity suggestions
🗺️ Outdoor route suggestions
📊 Walking progress tracking
📝 Activity history
📴 Offline AI support
🏆 Prize Category

Best Use of Gemma

WalkQuest AI uses the Gemma open-weight model as the core of its personalized outdoor activity generation.

⚠️ Note

WalkQuest AI provides general activity suggestions and is not a medical or fitness prescription.

Built for Hacktoberfest 2026 💚

devchallenge #hf26challenge #gemma #ai

🔒 FocusLock AI — An AI-Powered Study Focus Planner

Ramya Sai Challa — Sun, 04 Oct 2026 06:27:58 +0000

What I built

I built FocusLock AI, a simple AI-powered study productivity tool designed to help students stay focused while studying or coding.

👩‍💻 Who I built it for

I built FocusLock AI for a friend who often gets distracted while studying and coding.

They wanted a simple way to decide what to work on, stay focused for a specific amount of time, and avoid common distractions without needing a complicated productivity system.

So I built FocusLock AI around that problem: give it a goal and a time limit, get an AI-generated focus plan, and then work through the session using the built-in timer.

The idea came from a common problem: while working on an important task, it is very easy to get distracted by social media, messaging platforms, and unrelated websites.

FocusLock AI combines an open-weight Gemma model with a focus timer to create a simple structured study session.

🤖 How AI is used

FocusLock AI uses the Gemma open-weight AI model to generate a personalized focus plan.

The user provides:

A study or coding goal
The amount of available time

Gemma then generates:

A practical study approach
Specific tasks to complete
Useful learning resources

For example, a user can enter:

Learn Python Lists and solve coding problems

and receive an AI-generated plan containing specific Python practice tasks and useful learning resources.

✨ Features

🤖 AI-generated study plans
⏱️ Custom focus timer
⏸️ Pause and resume
🛑 Stop session
🔒 Focus environment
📚 Allowed study resources
🚫 Common distractions
🎉 Session completion notification

🛠️ Technologies

Python
Flask
HTML
CSS
JavaScript
Gemma
Google Gen AI SDK

🔄 How it works

Study Goal + Duration
        ↓
     Gemma AI
        ↓
    Focus Plan
        ↓
   Start Session
        ↓
    Focus Timer
        ↓
 Session Completed

📸 Demo

Here is FocusLock AI running with an AI-generated focus plan and focus timer.

🌱 Why open innovation matters

Open-weight AI models make it possible for students and independent developers to experiment with AI and build useful applications without having to train an AI model from scratch.

For me, this project was an opportunity to learn how an open-weight AI model can be connected to a real web application and used to solve a simple everyday problem.

I also wanted to keep the project accessible and understandable rather than making it unnecessarily complex.

🔗 Project

GitHub: https://github.com/Ramyasaichalla/FocusLock-AI

🚀 Future improvements

Some ideas I may explore in the future include:

Browser-based distraction blocking
Study progress tracking
Personalized study history
More AI-generated study strategies
Local AI inference

🙌 What I learned

While building FocusLock AI, I learned how to:

Build a Flask web application
Connect an AI model to a web application
Send user input to an AI model
Display AI-generated results in the frontend
Build a JavaScript focus timer
Use Git and GitHub to manage and publish a project
Keep API credentials secure using environment variables

Prize Categories

Best Use of Gemma

Built for Hacktoberfest 2026 💙

hf26challenge

My Journey Into Open Source 🚀

Ramya Sai Challa — Fri, 02 Oct 2026 07:12:57 +0000

My First Step into Open Source 🚀

Hi everyone! 👋

I'm Ramya, a 3rd-year engineering student currently learning Python, DSA, web development, and AI.

I recently joined the DEV Community and I'm excited to start my open-source journey with Hacktoberfest 2026.

I'm looking forward to:

Learning how open-source projects work
Making my first contributions
Improving my coding skills
Connecting with other developers
Learning from the developer community

This is just the beginning of my open-source journey, and I'm excited to see where it takes me! 🌱

If you're also a beginner in open source, feel free to say hi! 👋

beginners #opensource #hacktoberfest #python #learning