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You're reading from  Building AI Applications with ChatGPT APIs

Product typeBook
Published inSep 2023
PublisherPackt
ISBN-139781805127567
Edition1st Edition
Concepts
GPT/LLMs
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Author (1)
Martin Yanev
Martin Yanev
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Martin Yanev

Martin Yanev is an experienced Software Engineer who has worked in the aerospace and industries for over 8 years. He specializes in developing and integrating software solutions for air traffic control and chromatography systems. Martin is a well-respected instructor with over 280,000 students worldwide, and he is skilled in using frameworks like Flask, Django, Pytest, and TensorFlow. He is an expert in building, training, and fine-tuning AI systems with the full range of OpenAI APIs. Martin has dual master's degrees in Aerospace Systems and Software Engineering, which demonstrates his commitment to both practical and theoretical aspects of the industry.
Read more about Martin Yanev

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What this book covers

Chapter 1, Beginning with the ChatGPT API for NLP Tasks, introduces ChatGPT and the ChatGPT API, guides you in setting up your Python environment and necessary downloads, and explores OpenAI account registration, API token usage, and the pricing model to utilize OpenAI APIs.

Chapter 2, Building a ChatGPT Clone, provides a step-by-step guide on designing a ChatGPT clone, covering backend development using the ChatGPT API, deploying the project locally, and designing the frontend using HTML, CSS, and basic JavaScript, offering a hands-on project to prepare you for the more advanced SaaS app development covered in subsequent chapters.

Chapter 3, Creating and Deploying an AI Code Bug Fixing SaaS Application Using Flask, guides you through building and deploying a robust SaaS app using the ChatGPT API. It shows you how to build a complete development cycle, from deployment to web hosting, enabling global usage. The app, leveraging ChatGPT, offers code debugging and error description, introducing a unique and valuable project.

Chapter 4, Integrating the Code Bug Fixer Application with a Payment Service, provides insights into integrating a payment service into a ChatGPT application, utilizing visitor tracking to implement a Stripe API-based payment mechanism. Readers will also gain knowledge on incorporating a basic database into their projects.

Chapter 5, Quiz Generation App with ChatGPT and Django, provides a comprehensive guide on integrating the ChatGPT API into Django, teaching you how to create Django pages and views with AI capabilities. You will learn how to build a Django project generating exam questions from study material and run it locally as a SaaS application.

Chapter 6, Language Translation Desktop App with ChatGPT API and Microsoft Word, guides you through utilizing the ChatGPT API for Microsoft Word text translation, while also teaching you how to package your Python script into a functional desktop application using Tkinter. It introduces the integration of the ChatGPT API with Microsoft Office automation tools, empowering you to create a custom text translation application.

Chapter 7, Building an Outlook Email Reply Generator, provides a practical guide to building an app that utilizes Outlook email data to generate personalized replies and prompt design.

Chapter 8, Essay Generation Tool with PyQt and ChatGPT API, provides you with a step-by-step guide on how to integrate the ChatGPT API with PyQt for desktop app development, and how to control API tokens from the app frontend.

Chapter 9, Integrating ChatGPT and DALL-E API: Build End-to-End PowerPoint Presentation Generator, provides a hands-on approach to integrating two AI APIs, ChatGPT and DALL-E, and creating an AI-generated PowerPoint presentation.

Chapter 10, Speech Recognition and Text-to-Speech with Whisper API, provides you with an overview of the Whisper API and guides you through a practical project to generate subtitles and translations using audio files.

Chapter 11, Choosing the Right ChatGPT API Model, provides an overview of ChatGPT API models and parameters, helping you to choose the best model for your project and understand the limitations of the models.

Chapter 12, Fine-Tuning ChatGPT to Create Unique API Models, provides an overview of fine-tuning the ChatGPT API model, along with a case study to illustrate how to use this process in a real-world application to reduce the cost of building AI applications.

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Building AI Applications with ChatGPT APIs
Published in: Sep 2023Publisher: PacktISBN-13: 9781805127567
© 2023 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Martin Yanev

Martin Yanev is an experienced Software Engineer who has worked in the aerospace and industries for over 8 years. He specializes in developing and integrating software solutions for air traffic control and chromatography systems. Martin is a well-respected instructor with over 280,000 students worldwide, and he is skilled in using frameworks like Flask, Django, Pytest, and TensorFlow. He is an expert in building, training, and fine-tuning AI systems with the full range of OpenAI APIs. Martin has dual master's degrees in Aerospace Systems and Software Engineering, which demonstrates his commitment to both practical and theoretical aspects of the industry.
Read more about Martin Yanev

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