AI Studdy Buddy

Inspiration

As B.Tech Data Science students, we constantly struggled with finding concise, personalized answers from huge PDFs and class notes. The idea sparked from our real need — what if we could upload our study material and talk to an AI tutor like it’s a friend?

What it does

AI Study Buddy lets students:

• 📄 Upload study material (like PDFs, notes)
• ❓ Ask questions directly
• 💬 Get smart, context-aware answers
• 🔊 Listen to voice responses via ElevenLabs

It's like having your own AI-powered tutor — available 24/7, in your voice and pace.

How we built it

• 🔗 Used Together AI's Meta-LLaMA 3.1 model for high-quality, free and open-source chat completion
• 🔉 Integrated ElevenLabs Text-to-Speech API to turn answers into clear, natural voice
• ⚙️ Developed with React + TypeScript for the frontend
• 🧠 Backend in Node.js with Vite + Express
• ☁️ Hosted using Netlify, voice streamed through ElevenLabs
• 🧪 Used Bolt’s AI tools to rapidly prototype the app UI/UX

Challenges we ran into

• Managing limited API quotas (OpenAI/Gemini)
• Getting file upload → extraction → chunking → prompt routing to work smoothly
• Adapting large language models to focus only on the uploaded context
• Making the UI simple for users, but powerful behind the scenes

What we learned

• How to work with multiple AI providers efficiently (Together AI, ElevenLabs)
• Handling prompt engineering to get precise educational answers
• Deploying fast MVPs using Bolt’s visual interface
• Turning user feedback into real-time UI improvements

What's next

• Add support for more file formats (PPT, DOCX)
• Bookmark answers / Add to Flashcards
• Voice input (Speech-to-Text)
• Multilingual voice output for regional accessibility

Built With

• bolt
• echowave.io
• elevenlabs.ai
• netlify
• node.js
• react
• taliwindcss
• togetherai
• typescript
• vite