Flashcard

Flashcard is an educational web application designed to enhance the learning experience for students by leveraging the power of Retrieval Augmented Generation (RAG). The RAG framework enables the application to pull relevant information from a pre-populated vector store and combine it with a generative model to provide precise, contextually accurate answers or explanations. This tool is specifically designed to assist students in generating dynamic flashcards and educational materials from a large corpus of educational content, improving learning efficiency and retention.

React: Used for building the front-end interface, providing students with an intuitive, responsive platform to interact with and generate flashcards.

Flask: Handled back-end logic, managing the connection between the educational content, the machine learning models, and the front-end interface.

Supabase: Used as the database management solution, ensuring fast retrieval and secure storage of educational content and user-generated flashcards.

Machine Learning Engineering: Integrated the RAG model, combining information retrieval techniques with a generative AI model to provide highly relevant and accurate content for the flashcards.

Full-Stack Development: Led the entire development process, from designing a user-friendly interface in React to implementing the server-side logic using Flask and Supabase for seamless data handling.

RAG Model Integration: Integrated the RAG framework to allow the system to retrieve relevant data from a large knowledge base (in this case, Pinecone) and generate context-aware flashcards for students based on their queries.

Content Management & Retrieval: Set up a robust content retrieval system using Supabase, allowing the application to store and access educational content efficiently, ensuring students receive accurate and useful information.

Testing & Optimization: Conducted performance testing to ensure quick response times, especially during data retrieval and flashcard generation, optimizing both the back-end and machine learning models for a smooth user experience.

Flashcard successfully delivered an innovative, AI-powered educational tool that enhanced the study process for students. The RAG-based system allowed students to generate custom flashcards and summaries in real-time, helping them better retain and understand key concepts. The seamless integration of machine learning models and user-friendly front-end design created a smooth, engaging learning experience.