Smart Academic and Placement Assistant using Graph-RAG

The increasing volume of academic and placement-related information creates challenges for students in efficiently finding relevant and contextual resources. This research addresses this gap by proposing a Smart Academic and Placement Assistant using Graph-RAG, which combines graph-based knowledge representation with Retrieval-Augmented Generation for intelligent information retrieval. The proposed system provides a web-based platform for accessing academic notes, question papers, placement resources, and AI-based assistance. The system uses a Python and FastAPI-based backend with a React and TypeScript frontend, while relevant academic content is processed and retrieved to generate context-aware responses using a large language model. The approach improves the organization and accessibility of academic information while supporting students in learning and placement preparation. The proposed system demonstrates the potential of Graph-RAG-based retrieval for providing relevant and efficient academic assistance through a unified platform.