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Explore the power of Retrieval-Augmented Generation (RAG) in this comprehensive tutorial on building an AI-powered document inquiry web application. Learn how to create a personal chat system that accurately answers questions about selected documents using open-source tools. Dive into the fundamentals of RAG, understand its role in enhancing Large Language Models (LLMs), and gain hands-on experience with Ragna, a user-friendly Python and REST API. Compare the effectiveness of different LLMs and vector databases while developing a web application using Panel, a powerful Python application development framework. By the end of this 2-hour 40-minute session, acquire the knowledge and skills to build your own RAG-based applications, making institutional knowledge more accessible and transforming how organizations handle document interrogation.
