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Unlocking the Power of Auto-GPT and Its Plugins

You're reading from Unlocking the Power of Auto-GPT and Its Plugins Implement, customize, and optimize Auto-GPT for building robust AI applications

Product type Paperback

Published in Sep 2024

Publisher Packt

ISBN-13 9781805128281

Length 142 pages

Edition 1st Edition

Tools

Docker

Concepts

Artificial Intelligence

Author (1):

Wladislav Cugunov

View More author details

Table of Contents (10) Chapters

Preface

1. Chapter 1: Introducing Auto-GPT

2. Chapter 2: From Installation to Your First AI-Generated Text FREE CHAPTER

3. Chapter 3: Mastering Prompt Generation and Understanding How Auto-GPT Generates Prompts

4. Chapter 4: Short Introduction to Plugins

5. Chapter 5: Use Cases and Customization through Applying Auto-GPT to Your Projects

6. Chapter 6: Scaling Auto-GPT for Enterprise-Level Projects with Docker and Advanced Setup

7. Chapter 7: Using Your Own LLM and Prompts as Guidelines

8. Index

Why subscribe?

9. Other Books You May Enjoy

Mastering Prompt Generation and Understanding How Auto-GPT Generates Prompts

You are really into the book! Congratulations on reaching this chapter!

In the previous chapters, we explored the basics of Auto-GPT and its installation. Now, we are going to delve deeper into one of the most crucial aspects of working with this powerful language model – prompt generation. In this chapter, we will demystify the process of how Auto-GPT generates prompts, understand why they are so important, and learn how to craft effective prompts to get the most out of Auto-GPT. Let’s get started!

In this chapter, we will explore these topics:

What are prompts, and why are they important?
Tips to craft effective prompts
An overview of how Auto-GPT generates prompts
Examples of what works and what confuses GPT

The rest of the chapter is locked

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Authors (1)

Wladislav Cugunov

Wladislav Cugunov

Wladislav Cugunov is a senior software developer and visionary technologist known for his exceptional skills and innovative, determined mindset. At age 12, he built a LEGO helicopter to prove to his dad that LEGO could indeed fly, even though it exploded after he doubled the electricity. At 15, he constructed his first Tesla coil, causing an electromagnetic pulse (EMP) when attempting to drive a coilgun with it. His coding journey began with Batch and VBA when he tried to replicate Jarvis from Iron Man in 2008, progressing to Node.js to build a trading bot, Bash, Java, Ruby, C, Python, Kotlin, C#, PHP, and Swift. Dissatisfied with the direction of Auto-GPT, he started making suggestions and improvements until he was invited to come on board and help AutoGPT grow.

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