Skip to main content

Developing LLM App Frontends with Streamlit

1h 43m 52s
English
Paid

Course description

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

Read more about the course

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

This is a demo lesson (10:00 remaining)

You can watch up to 10 minutes for free. Subscribe to unlock all 20 lessons in this course and access 10,000+ hours of premium content across all courses.

View Pricing

Watch Online Developing LLM App Frontends with Streamlit

0:00
/
#1: Introduction

All Course Lessons (20)

#Lesson TitleDurationAccess
1
Introduction Demo
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

Unlock unlimited learning

Get instant access to all 19 lessons in this course, plus thousands of other premium courses. One subscription, unlimited knowledge.

Learn more about subscription

Comments

0 comments

Want to join the conversation?

Sign in to comment

Similar courses

Full-Stack Fundamentals 4 - Payments

Full-Stack Fundamentals 4 - Payments

Sources: Mckay Wrigley (takeoff)
In the previous section, we successfully implemented user authentication using Clerk. Now, based on this project, we will add online payment processing with...
54 minutes 17 seconds
Distributed Tasks Demystified with Celery, SQS & Python

Distributed Tasks Demystified with Celery, SQS & Python

Sources: udemy
This course teaches beginners to industry professionals the fundamental concepts of Distributed Programming in the context of python & Django. We look at how t
4 hours 27 minutes 50 seconds
Complete Backend (API) Development with Python A-Z

Complete Backend (API) Development with Python A-Z

Sources: udemy
This course for anyone who wants to be python backend developer. You will learn what is API and some python API frameworks. You will find all the fundamentals about backend deve...
12 hours 35 minutes 9 seconds