LLM Engineering in Practice with Streamlit and OpenAI

سرفصل های دوره

Build, optimize, and deploy LLM-based solutions with a hands-on real-world project.

1 - Introduction to the Course

1 -Introduction to the Course

2 -What does the course cover

3 -The Interview Tools Specifics

2 - Planning stage

1 -Hosting an LLM vs Using an API

2 -Open-Source vs Closed-Source Models

3 -Tokens

4 -Pricing Hosting an LLM vs Pay-by-Token

5 -Initial Prompt Development Part 1

6 -Initial Prompt Development Part 2

7 -Database Design and Schema Development

8 -What Is an Activity Diagram

9 -Creating an Activity Diagram

10 -Concluding the Planning Stage

3 - Crafting and Testing AI Prompts

1 -The OpenAI Playground

2 -Optimizing Temperature and Top P for Different Use Cases

2 -model-settings-usecases.zip

3 -Prompt Engineering for Software Development

4 -How to Test Out a Prompt Template

4 - Getting to Know Streamlit

1 -Setting up environment

2 -Streamlits Pros and Cons

3 -Streamlit Elements Titles, Headers, and Formatting

4 -Streamlit Elements Text Methods

5 -Streamlit Elements Chat Elements

6 -Sessin State

6 -session st solution.zip

5 - Developing the prototype

1 -Initializing an OpenAI Client

2 -Implementing the Chat Functionality

2 -app1.zip

3 -Building the Setup Page

3 -app2.zip

4 -Enhancing Chatbot Interaction with Session State

4 -app3.zip

5 -Refining Our Project

6 -Implementing Feedback Functionality Part 1

7 -Implementing Feedback Functionality Part 2

7 -app.zip

8 -Uploading Your Project in GitHub

9 -Deploying Your Streamlit App

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تولید کننده: Udemy