AI Smart Student Assistant

Inspiration:

We wanted to create a single platform that helps students study smarter, organize learning materials, and get AI-powered assistance instead of searching through multiple resources.

What We Learned:

We learned how to integrate AI APIs, FastAPI, React, MySQL, document processing, embeddings, and authentication into one full-stack application.

How We Built It:

Frontend: React Backend: FastAPI Database: MySQL AI: Gemini API RAG: Documents are uploaded, divided into chunks, converted into embeddings, and stored for AI-based question answering. Features: Material upload, AI summarization, AI Q&A, quizzes, authentication, and study assistance.

Challenges:

The main challenges were API quota limits, authentication errors, connecting the frontend with FastAPI, document chunking, embeddings, and handling AI model changes. Solving these issues helped us understand how to build and debug a real-world AI application.