When you build a machine learning (ML) project, one of the most common questions is:
How do I show this to others without writing a full web app from scratch?
Two of the most popular tools for this are Gradio and Streamlit. Both let you create interactive web apps with just Python — no HTML, CSS, or JavaScript needed. But they are designed with slightly different goals in mind.
In this article, we'll compare Gradio and Streamlit, highlight their strengths, and help you decide which one is right for your application.
What is Gradio?
Gradio is a Python library designed for quickly building demos for ML models.
Just a few lines of code can create an interface where users can enter text, upload images, record audio, or interact with a chatbot.
It is especially popular in the Hugging Face ecosystem, where most demo apps use Gradio.
What is Streamlit?
Streamlit is a more general-purpose tool for building interactive data apps and dashboards.
It offers rich UI components like sliders, dropdowns, charts, maps, and tables.
You can combine ML models with visualizations, data exploration, or even multi-page apps.
Example
Gradio
import gradio as gr
def chatbot(message):
return f"You said: {message}"
demo = gr.Interface(fn=chatbot, inputs="text", outputs="text")
demo.launch()Steamlit
import streamlit as st
st.title("Simple Chatbot")
user_input = st.text_input("Type a message:")
if user_input:
st.write(f"You said: {user_input}")Now, go to the command prompt of the Virtual Environment and enter
Steamlit run <filename.py>
Streamlit automatically starts a local development web server and binds it to port 8501 by default.
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