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ChatGPT for Conversational AI and Chatbots

ChatGPT for Conversational AI and Chatbots

By : Adrian Thompson
5 (3)
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ChatGPT for Conversational AI and Chatbots

ChatGPT for Conversational AI and Chatbots

5 (3)
By: Adrian Thompson

Overview of this book

ChatGPT for Conversational AI and Chatbots is a definitive resource for exploring conversational AI, ChatGPT, and large language models. This book introduces the fundamentals of ChatGPT and conversational AI automation. You’ll explore the application of ChatGPT in conversation design, the use of ChatGPT as a tool to create conversational experiences, and a range of other practical applications. As you progress, you’ll delve into LangChain, a dynamic framework for LLMs, covering topics such as prompt engineering, chatbot memory, using vector stores, and validating responses. Additionally, you’ll learn about creating and using LLM-enabling tools, monitoring and fine tuning, LangChain UI tools such as LangFlow, and the LangChain ecosystem. You’ll also cover popular use cases, such as using ChatGPT in conjunction with your own data. Later, the book focuses on creating a ChatGPT-powered chatbot that can comprehend and respond to queries directly from your unique data sources. The book then guides you through building chatbot UIs with ChatGPT API and some of the tools and best practices available. By the end of this book, you’ll be able to confidently leverage ChatGPT technologies to build conversational AI solutions.
Table of Contents (15 chapters)
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Part 1: Foundations of Conversational AI
4
Part 2: Using ChatGPT, Prompt Engineering, and Exploring LangChain
9
Part 3: Building and Enhancing ChatGPT-Powered Applications

Scoping our ChatGPT project

Everyone likes a holiday, and helping travelers with smart conversational automations is an area I’m very passionate about, so for our use case, we are going to create our own ChatGPT-powered travel assistant.

At this point, we must be realistic with scope; an online travel agent could potentially do thousands of different tasks with varying levels of complexity, but let’s choose a handful of specific use cases that are not only interesting to implement but also bring together the techniques we’ve covered so far in the book.

A holiday assistant use case

You work for an online travel agent, and you’ve been tasked with creating an LLM-powered holiday assistant designed to revolutionize the way travelers choose their accommodations. Online travel agents tend to be limited in their accommodation searches, so your challenge is to provide a more personalized granular search. Drawing on a dataset of hotels, complete with descriptions...

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