Study Buddy

Study Buddy: AI-Powered Study Companion

Inspiration

As AI students drowning in deadlines and exam stress, we knew there had to be a better way. We watched our peers struggle with focus, mood swings, and scattered study materials. The solution? Combine productivity tools with AI intelligence in one calming, aesthetic space. The equation was simple: Student Struggles + AI = Ultimate Study Companion

What it does

Study Buddy is your academic best friend:

Pomodoro Timer - Focus sessions with strategic breaks
AI Mood Tracker - Get personalized study plans based on your emotions
Smart Flashcards - AI-generated revision cards for any topic
To-Do List - Organize tasks with deadlines and priorities
Sticky Notes - Drag-and-drop quick reminders
Daily Affirmations - Motivational boosts when you need them
Mini AI Chatbot - Chat with an assistant that remembers your notes (LangChain + FAISS)

How we built it

Our tech stack blended vibes and innovation:

• Frontend: HTML + CSS + JavaScript

• Backend: Node.js + Express

• AI: Gemini API (mood plans + flashcards)

• Chatbot: LangChain + FAISS VectorStore

• Design: Girly, pastel aesthetic with custom CSS animations

• Version Control: GitHub

Challenges we ran into

API Key Security: GitHub blocked our pushes → learned .gitignore & config management
Time Pressure: Building 7 features in hackathon hours → late-night coding and ruthless prioritization
Multi-API Integration: Coordinating Gemini, and LangChain with different formats and rate limits
State Persistence: Keeping user flows smooth
Cross-Feature Integration: Making 7 tools work seamlessly together

Accomplishments we're proud of

• Created a fully functional 7-feature dashboard in hackathon timeframe • Designed calming, student-friendly UI with custom animations • Integrated 2 different AI services (Gemini, LangChain) • Built responsive UI working on all devices • Implemented smart mood tracking with AI-generated study plans

What we learned

✓ Backend API architecture

✓ Secure API key management

✓ AI integration techniques

✓ Git collaboration workflow

✓ Time management under pressure

What's next

Study Groups: Collaborative features for peer study sessions
Progress Analytics: Visual dashboards tracking study time & productivity
Spaced Repetition: Smart flashcard algorithm for better retention
Calendar Integration: Sync with Google Calendar for exam dates
Custom Themes: Let users personalize their aesthetic

Built With

css
express.js
faiss
gemini-api
html
javascript
jquery
langchain
node.js
tailwindcss

Submitted to

CS Girlies November Hackathon - Make Learning Cool Again!

Created by

As the UI & Frontend Lead, I designed and built the entire visual experience of Study Buddy — from the layout and color palette to the interactive components that make the dashboard feel smooth, cute, and intuitive. I developed all major frontend features including the Pomodoro timer, mood tracker, flashcards, sticky notes, and to-do list, ensuring each one matched our pastel aesthetic and worked seamlessly across devices.

I also took charge of all the documentation, organizing the project structure, writing the full README, and maintaining clarity across team tasks.
Overall, I loved the experience.

Eman Butt
I was the Frontend Functionality Lead, and I wrote all the JavaScript to make the dashboard interactive. I built the logic for all the non-AI features, including the Pomodoro timer, the to-do list, and the sticky notes. I also implemented the mood tracker's history system and the rotating affirmations using localStorage.

Noor Fatima
My main contribution was the backend. It was my first time building a Node.js server from scratch and connecting it to a live service like the Google Gemini API. I built the API routes that generate flashcards and create personalized study plans. I ran into a really frustrating 404 error, but I learned a lot about persistence and problem-solving, finally figuring out that the Google Cloud project's "Vertex AI API" needed to be enabled.

Mubbara Majid
I worked as an AI chatbot developer . And added the functionality of chatbot where you can upload your document or url and ask the questions related to it . And even can ask your queries in text. So the students can take help from it regarding their studies.
Tech stack used: Python, Vector DB(faiss), langchain

Attia Inayat