What Is Streamlit?—An Intro for Beginners
Explore how Streamlit allows AI engineers to quickly build interactive web applications using Python, without needing HTML or JavaScript. Learn to create a simple app, understand Streamlit's rerun logic, session state, and how it integrates with LangChain to build user-friendly frontends for retrieval-augmented generation systems.
Streamlit is a tool that makes building web apps incredibly straightforward, especially for AI engineers. Imagine we have all these complex retrievers and generators that we want to share with the world, but we don’t want to get bogged down in the nitty-gritty of web development. That's where Streamlit comes in.
Here's how it works, in plain terms. We write a Python script just like we would for any other project. However, instead of writing code that just runs and gives us an output in the terminal, we write code that generates an interactive web app. Streamlit watches our script and automatically creates the web app as we write it. We don’t need to know HTML, CSS, or JavaScript. We don’t need to set up a server or worry about the frontend. Streamlit takes care of all that for us.
Streamlit also makes iterating in RAG systems effortless. When we modify our script and save it, the app updates automatically. This quick feedback loop is perfect for experimenting with different retrievers and generators and fine-tuning our models. Moreover, since it’s all in Python, we can continue using familiar libraries like LangChain, NumPy, and pandas.
At the end, we end up with this minimalistic, interactive app that can display graphs, maps, text, and even interactive widgets like sliders and buttons, all generated from our Python code. It’s like magic! We just write our code, add a few Streamlit commands to display our results, and boom, we’ve got a web app.