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Most Retrieval-Augmented Generation (RAG) tutorials start with a framework like LangChain - but what if you could build leaner, faster apps using just Python?
In this online session, we’ll show you the fundamentals and how to simplify the complexity of traditional AI toolchains. You’ll learn how to build production-ready RAG applications using only Python, SurrealDB, and Streamlit - no framework required.
In this session, we’ll walk through:
You’ll leave with a clearer mental model for building RAG apps - and a fully working example you can adapt for your own use cases.
Senior Product Marketing Manager at SurrealDB
The benefits of learning RAG fundamentals in pure Python before jumping into frameworks
Managing multi-model data effectively with SurrealDB
Creating interactive frontends for RAG applications using Streamlit