RAG Integration with Nvidia NIM and LlamaIndex - Building Document Query Applications

RAG Integration with Nvidia NIM and LlamaIndex - Building Document Query Applications

Learn to build a Retrieval-Augmented Generation (RAG) application for querying private documents in this 20-minute tutorial that demonstrates the integration between LlamaIndex and Nvidia NIM microservices. Explore practical implementation using two leading Large Language Models - LLama 3.2 3B Instruct and Phi3 3.5 Small 128k Instruct. Follow along with hands-on examples and access the complete implementation through the provided Jupyter notebook to develop your own document interrogation system using machine learning and data science techniques.