acharya

📖 About the Project

🎯 Inspiration

During exam seasons, we noticed how students often feel overwhelmed by scattered notes, lack of structure, and the pressure to cover vast syllabi. Traditional study methods weren’t enough, and many lacked access to quality personalized guidance. That’s when the idea of Acharya was born — an AI-powered platform to make exam prep smarter, faster, and more efficient.

🧠 What We Learned

• How to build scalable, responsive apps using Next.js
  
• Integrating AI/ML features like summarization, quiz generation, and chatbots
  
• Real-world use of PDF parsing, Firebase integration, and user experience optimization
  
• Understanding how different exams require different prep strategies

🛠️ How We Built It

• Frontend: Developed using Next.js and Tailwind CSS for modern UI/UX
  
• Backend: Node.js with Firebase/MongoDB for real-time data sync and storage
  
• AI Features: Integrated OpenAI API to process PDFs, generate MCQs, and support chatbot queries
  
• PDF Handling: Custom logic to parse and analyze uploaded PDFs for content extraction
  
• Timetable Logic: Algorithm that calculates topic priority and builds daily plans
  

⚠️ Challenges Faced

• Converting diverse and unstructured PDF formats into meaningful summaries and MCQs
  
• Ensuring the chatbot gave relevant, exam-specific answers
  
• Balancing personalization with performance in real-time study plan generation
  
• Designing for students of varying grades, goals, and learning paces

Acharya isn’t just a project — it’s a mission to make quality education support accessible through smart technology. 💡

Built With

• and-chatbot-functionality-**firebase**-?-authentication
• api
• firebase
• mcq-generation
• next.js
• node.js
• openai
• real-time-database
• responsive-ui-**openai-api**-?-for-summarization
• scalable-web-apps-**tailwind-css**-?-utility-first-css-for-sleek
• talwind