Creating RAG-Based Question-and-Answer LLM Workflows at NVIDIA

NVIDIA has developed a new system architecture for question-and-answer workflows using retrieval-augmented generation (RAG). They found that users want more than just RAG-driven tasks, appreciating features like web search and summarization. By integrating Perplexity's search API, LlamaIndex, NVIDIA NIM microservices, and Chainlit, they created a versatile chat application. The post provides detailed instructions on setting up and deploying this system, highlighting the ease of development with NVIDIA's tools.