Developing LLM App Frontends with Streamlit

Name: Developing LLM App Frontends with Streamlit
Price: 9 USD
Availability: InStock

1h 43m 52s

English

Paid

May 23, 2024

This byte-sized course will teach Streamlit fundamentals and how to use Streamlit to create a frontend for your LLM-powered applications.

In this project-based course you'll learn to use Streamlit to create a frontend for an LLM-powered Q&A application. 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.

Watch Online Developing LLM App Frontends with Streamlit

Join premium to watch

Go to premium

#	Title	Duration
1	Introduction	03:08
2	Introduction to Streamlit	04:15
3	Streamlit Main Concepts	05:28
4	Displaying Data on the Screen: st.write() and Magic	05:32
5	Widgets Part 1: text_input, number_input, button	05:10
6	Widgets Part 2: checkbox, radio, select	07:25
7	Widgets Part 3: slider, file_uploader, camera_input, image	08:15
8	Layout: Sidebar	01:57
9	Layout: Columns	04:30
10	Layout: Expander	02:10
11	Displaying a Progress Bar	03:08
12	Session State	07:35
13	Callbacks	06:08
14	Project Introduction and Library Installation	04:09
15	Defining Functions	06:14
16	Creating the Sidebar	06:04
17	Reading, Chunking, and Embedding Data	06:22
18	Asking Questions and Getting Answers	05:25
19	Saving the Chat History	06:00
20	Clearing Session State History using Callback Functions	04:57