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Building the Frontend of Python Web Applications with Streamlit

Building the Streamlit UI

Explore how to build a user interface in Streamlit for an audio transcription web app. Understand how to use Streamlit components like file uploaders, progress bars, spinners, and text display to create an interactive experience. This lesson guides you through implementing upload functionality, polling transcription status, showing progress animations, and displaying the final transcription. By the end, you'll have a working audio transcription front end integrated with AssemblyAI, ready to expand with additional features.

We'll cover the following...

Now that we have all the required helper functions, we can begin work on the Streamlit UI.

However, before moving on to the actual code of the Streamlit UI, let’s take a look at the Streamlit components that we’ll use to build the UI.

Streamlit components

  • header(string), subheader(string), text(string):  These components display text of various sizes on our UI. The header() can be thought of as the <h1> tag, subheader() as <h2> and text() as <p>.

  • file_uploader(label): This creates a button to upload the file. The parameter label is the string to be displayed above the button. It returns a file object. We’ll use this button to accept files from the user.

  • progress(integer): This creates a progress bar. The integer has to be ...