Multiple Choice Quizzes using Langchain and Gemini LLM
K Sudhakar,
Sannidhi Venkata Sai Revanth,
Nayab Sama Sulthana,
V Purushotham Reddy,
S Sindhuja,
K Vannur Swamy
The research study investigates the use of cutting- edge technologies like Langchain and Gemini AI for
the automated creation and assessment of multiplechoice questions (MCQs). Although producing multiple- choice questions (MCQs) has traditionally
been done by hand and required a lot of work, advances in artificial intelligence (AI) and natural
language processing (NLP) have opened up new possibilities. The creation and implementation of an
MCQ generator—which uses Gemini AI to generate MCQs and Langchain for rapid engineering are
covered in this paper. Customizing prompts for prompt engineering, chaining prompts with the Gemini
AI model, and utilizing OpenAI's GPT-3.5 and multiple Language Learning Models (LLMs) to assess
the created MCQs are the steps in the process. The study intends to assess these models' efficiency in
handling intricate queries,producing appropriate answers, and examining the caliber of the MCQs that
are produced.
