So you've built this awesome LLM-powered Q&A (RAG) application. Nice work!

Jupyter Notebook is a great tool for coding, prototyping, and experimentation, but as you might have noticed they're not very suitable for production or end-user use. If you want your application to be accessible to everyone, not just developers, you'll need to create a web app or frontend for it - and that's where Streamlit comes to the rescue! Streamlit is an open-source Python library that simplifies the creation and sharing of custom frontends for machine learning and data science apps with the world.

But how do you use Streamlit...? Well I've got good news from you! We have another ZTM course that will teach you exactly how to use Streamlit to create a frontend for an LLM-powered Q&A application.

Click here to start the "Developing LLM App Frontends with Streamlit" byte-sized course!