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ChatGPT for Conversational AI and Chatbots

You're reading from   ChatGPT for Conversational AI and Chatbots Learn how to automate conversations with the latest large language model technologies

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781805129530
Length 250 pages
Edition 1st Edition
Tools
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Author (1):
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Adrian Thompson Adrian Thompson
Author Profile Icon Adrian Thompson
Adrian Thompson
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Table of Contents (15) Chapters Close

Preface 1. Part 1: Foundations of Conversational AI FREE CHAPTER
2. Chapter 1: An Introduction to Chatbots, Conversational AI, and ChatGPT 3. Chapter 2: Using ChatGPT with Conversation Design 4. Part 2: Using ChatGPT, Prompt Engineering, and Exploring LangChain
5. Chapter 3: ChatGPT Mastery – Unlocking Its Full Potential 6. Chapter 4: Prompt Engineering with ChatGPT 7. Chapter 5: Getting Started with LangChain 8. Chapter 6: Advanced Debugging, Monitoring, and Retrieval with LangChain 9. Part 3: Building and Enhancing ChatGPT-Powered Applications
10. Chapter 7: Vector Stores as Knowledge Bases for Retrieval-augmented Generation 11. Chapter 8: Creating Your Own LangChain Chatbot Example 12. Chapter 9: The Future of Conversational AI with LLMs 13. Index 14. Other Books You May Enjoy

Going into production

You’ve made some great progress in increasing your knowledge of how to create a ChatGPT-powered conversational agent as you’ve progressed through the book. Hopefully, you’ve also been educated on some of the limitations, challenges, and pitfalls of creating systems powered by LLMs and, most importantly, getting them production-ready. These challenges are not to be underestimated, and it’s no surprise that despite the huge adoption of LLMs over the past year or so, examples of conversational AI agents entirely powered by LLMs are thin on the ground, and the ones that are have come under some intense scrutiny and unfortunately have underperformed in some cases. Let’s look at one in the next section.

Understanding the dangers of going into production

One recent example of how LLMs in production can quickly land you in hot water is the issues found with a chatbot deployed by a delivery firm of note. I’m not going to...

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