We are pleased to announce that a tutorial on the RAG system based on the arXiv paper is now available! This tutorial provides a complete guide to building a RAG system, covering every step from data acquisition to model deployment, aiming to help developers quickly get started and build their own RAG system. The tutorial explains in detail how to use the Unstructured library to process PDF documents, how to use ChromaDB to create a vector database, and how to integrate the LangChain framework to build an efficient RAG application. All steps are clear and easy to understand, with code examples for easy learning and practice. Visit the tutorial link now to start your RAG system building journey!
RAG system tutorial released! The system is based on arXiv papers as contextual sources, providing links to source papers used when generating answers. Tutorial link: https://colab.research.google.com/drive/1Lc8eq8P87JjzUhbYb33_c7h7njsWb-hn#scrollTo=eCSBhP4FxOg3. The tutorial shows in detail the process of implementing the RAG system, including obtaining the paper text, using Unstructured to preprocess and chunk the PDF document, creating a ChromaDB retriever, setting up RAG and LangChain, and defining the response link function.
I hope this tutorial can help you better understand and apply the RAG system. By studying this tutorial, you will be able to build a powerful question answering system based on arXiv papers and easily trace the source of the answers. Come learn and experience building your own RAG system!