Build ChatGPT App for iOS with GPT4 and Chat API

Table of Contents

1. Introduction
2. Building the Chat GPT App
3. Using the Chat Completions API
4. Leveraging GPT4 for Contextual Responses
5. Tailoring Application with System Messages
6. Creating the Networking Layer
7. Building the ViewModel and Service
8. Implementing the User Interface
9. Sending and Receiving Messages
10. Styling and Customization

Building a Chat GPT App with the Chat Completions API and GPT4 for Contextual Responses

In this article, we will explore how to build a Chat GPT app using the Chat Completions API. By leveraging GPT4, we can obtain contextual responses and tailor our application to specific use cases. We will also discuss the importance of system messages and their role in enhancing the user experience. Additionally, we will cover the networking layer, ViewModel, service, and the implementation of the user interface. Finally, we will learn how to send and receive messages and customize the styling of our app.

Introduction

Many of you have been eagerly awaiting a follow-up video on building a Chat GPT app. In this article, we will take a deep dive into the process of creating this app using the Chat Completions API. By leveraging GPT4, we can obtain more contextual responses and provide a richer user experience. We will also explore the power of system messages and how they can be used to tailor our application to specific use cases.

Building the Chat GPT App

To get started, we need to open Xcode and create a new project. We will name our project "Chat GPT app" and set up the initial structure. In this article, we will take a different approach compared to the previous video. Instead of starting with the user interface, we will first create the networking layer, ViewModel, and service. By structuring the project in this way, we can ensure a smoother development process.

Using the Chat Completions API

To leverage the power of GPT4 and obtain contextual responses, we will use the Chat Completions API. This API allows us to send a list of messages to the chat model, providing it with the necessary context to generate accurate and Meaningful replies. By utilizing system messages, we can further enhance the user experience and customize the app's behavior.

Leveraging GPT4 for Contextual Responses

GPT4 is a Game-changer in the field of natural language processing. With its improved capabilities, we can expect more accurate and context-aware responses from our chat model. By upgrading from GPT3.5 Turbo to GPT4, we can take full advantage of the system message feature and achieve a higher level of customization.

Tailoring Application with System Messages

System messages play a crucial role in tailoring our application to specific use cases. By providing the chat model with system messages, we can guide its responses and ensure that it focuses on specific topics or domains. For example, if we want our app to specialize in providing coding assistance, we can send a system message indicating that the app is focused on Swift coding and doesn't have sufficient knowledge of other programming languages.

Creating the Networking Layer

Before we can start implementing the functionality of our app, we need to create a networking layer. This layer will handle the communication between our app and the OpenAI API. We will use the Alamofire library for this purpose, which provides a convenient and efficient way to make network requests in Swift.

Building the ViewModel and Service

The ViewModel and service components are responsible for managing the data and business logic of our app. The ViewModel will observe changes in the messages and provide them to the user interface. The service, on the other HAND, will handle the actual network requests to the OpenAI API and process the responses.

Implementing the User Interface

The user interface is a crucial aspect of any app. In this section, we will build the UI for our Chat GPT app. We will use SwiftUI, Apple's modern UI framework, to create a sleek and intuitive interface. The UI will consist of a scrolling view to display the chat messages, a text field for input, and a button to send messages.

Sending and Receiving Messages

Now that we have set up the networking layer and the user interface, we can implement the functionality to send and receive messages. When the user enters a message and taps the Send button, the message will be sent to the OpenAI service via the networking layer. The response from the API will then be processed and displayed in the chat interface.

Styling and Customization

To enhance the visual appeal of our app, we will apply some basic styling and customization. We will add padding, colors, and background elements to make the user interface more aesthetically pleasing. Additionally, we will explore options for adding a typing indicator and optimizing the response time of our app.

Pros:

• Integration with the Chat Completions API allows for more accurate and contextual responses.
• Leveraging GPT4 greatly enhances the capabilities of the chat model.
• Utilizing system messages allows for customization and tailoring of the application.

Cons:

• Response time may be slower depending on network connectivity and API performance.
• Styling and customization may require additional effort for a visually appealing interface.

Highlights

• Building a Chat GPT app using the Chat Completions API and GPT4
• Leveraging system messages to tailor the application
• Implementing the networking layer with Alamofire
• Creating the ViewModel and service components
• Building the user interface with SwiftUI
• Sending and receiving messages
• Styling and customizing the app interface

Frequently Asked Questions

Q: Can I use the Chat Completions API with GPT3.5 Turbo? A: Yes, you can use the Chat Completions API with GPT3.5 Turbo. However, the functionality of system messages is limited in this version.

Q: How can I ensure fast response times for my application? A: To optimize response times, you can implement a typing indicator and consider using stream functionality to receive partial responses from the API.

Q: Is GPT4 available for public use? A: GPT4 is currently available on a waitlist basis. You can join the waitlist on the OpenAI website to gain access.

Q: Can I customize the prompts and responses of the chat model? A: Yes, by utilizing system messages and providing specific context, you can customize the prompts and shape the responses of the chat model based on your application's requirements.

Q: Are there any limitations or usage restrictions for the Chat Completions API? A: It's important to refer to the OpenAI documentation for any limitations or usage restrictions that may apply to the Chat Completions API. OpenAI periodically updates their APIs, so it's always a good practice to stay informed.