Building RAG Applications with PDFs Using LlamaIndex - Comparing Gemini Pro and Nvidia NIM Llama 3.2

Building RAG Applications with PDFs Using LlamaIndex - Comparing Gemini Pro and Nvidia NIM Llama 3.2

Learn to build a RAG (Retrieval-Augmented Generation) agent for PDF document interaction in this comprehensive video tutorial. Explore the implementation of PymuPDF for text and image extraction, while comparing two powerful model variants: the Gemini SDK and NVIDIA NIM SDK with NVIDIA embeddings paired with LLama 3.2 3B language model. Follow along with practical demonstrations and access the complete implementation through the provided GitHub notebook to develop your own PDF-based conversational AI system using LlamaIndex framework.