GPU-accelerated Retrieval-Augmented Generation for Academic Documents
LectureNotes RAG System is a high-performance question-answering system designed specifically for academic documents and lecture notes. Built with GPU acceleration in mind, it leverages NVIDIA's RTX 5090 to deliver lightning-fast semantic search across thousands of documents.
The system implements a complete RAG pipeline: from multi-format document ingestion (PDF, DOCX, TXT, MD) to intelligent text chunking, high-dimensional embedding generation, and efficient vector search using FAISS. It integrates seamlessly with LM Studio for local, private LLM inference, ensuring data privacy while providing intelligent responses.