This project explores the development of an AI-based quiz generation system using GPT-3.5 and Vectara to foster personalized and adaptive learning experience. Our methodology involved sourcing relevant structured dataset, data pre-processing, embeddings generation, vector database storage, hybrid-search retrieval, LLM feed, prompt engineering, and context-based response. The primary challenge addressed is the insufficient customization in quiz generation and overcoming the challenge of generating precise and contextually relevant quiz questions that minimize the risk of LLM generating incorrect or misleading information (hallucinations). We also have included an option for the user to upload their preferred document and let the app generate quiz. As the users answer the questions, the LLM will generate further questions adapting the difficulty level. The hallucination levels are found to be really low as per Vectara in-built evaluations. This is designed for interactive AI based user learning and is scalable to different arenas like education, online learning, and employee trainings.
Category tags:"excellent work. excellent application of technology. you need to work more on the idea to make it unique and to standout of competition. "
Walaa Nasr Elghitany
Lablab Head Judge
"Great job! Impressive utilization of technology"
Theodoros Ampas
Technical Mentor
"Well done on creating a scalable solution for personalized and adaptive learning experiences!"
Jay Rodge
LLM Developer Advocate