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How to Build an App with ChatGPT
leewayhertz.com/build-an-app-with-chatgpt
Artificial intelligence has always shown its potential for bringing new innovations to the
things we do in our daily lives. There are many AI-based techniques for developing
software models that have fulfilled various purposes and helped accomplish meaningful
work. Different kinds of AI models are slowly replacing almost all the possible tasks that
were once exclusive to humans.
Humanity is on the cusp of a new technological revolution, and it is poised to harness the
full potential of AI through the utilization of conversational AI that humanizes
communication between people and machines. One of the most advanced tools in this
area is ChatGPT, an AI-based chatbot that aims to evolve the relationship between
humans and machines in a way that blurs the lines between the two.
As new models such as conversational AI and generative AI continue to be developed,
ChatGPT has become a hot topic for technologists, industries, businesses, and societies
at large. ChatGPT is a highly advanced tool that allows non-technical users to access
powerful capabilities and reduces the time required to develop applications. Despite some
concerns that it may replace human jobs, ChatGPT is going to enhance human cognition,
giving us new opportunities to interact with the technology and making tedious tasks like
app development easy. The full potential of the tool can be harnessed by developing an
app, website, or chatbot. So, ChatGPT app development is soon going to be a new trend.
In this article, we will have a deep understanding of this emerging AI-based chatbot and
how we can build an app with ChatGPT.
Introduction to ChatGPT

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How does ChatGPT work?
Key components of ChatGPT
Features of ChatGPT
How to build an app with ChatGPT
Factors to consider while building an app with ChatGPT
Benefits of using ChatGPT for app development
Introduction to ChatGPT
ChatGPT is a significant step in creating a seamless connection between humans and a
chatbot. It goes beyond what one might expect from a conversational AI. The tool is
capable of handling complex questions and performing advanced tasks. The model
architecture of ChatGPT is based on the Generative Pre-training Transformer (GPT) and
is trained on a massive amount of text data.
It has the potential to produce human-like text for various natural language processing
tasks, such as language translation, question answering, and text summarization. The
model is pre-trained on a vast amount of text data and then fine-tuned for specific tasks.
This allows the model to understand the complexities of language and produce more
natural and accurate text.
Moving into details, ChatGPT was launched by OpenAI in November 2022. OpenAI is a
San Francisco-based AI and research company that has created many usable projects in
the field of AI. This AI-based chatbot was developed to address some of the issues of
traditional chatbots, such as limited understanding models and improvement capacity.
ChatGPT auto-detects words and provides outputs based on the inputs given by users.
The bot is easy-to-use and has already attracted over a million users.
It can be used for different purposes – all you have to do is ask!
ChatGPT is useful for a variety of purposes, including
Identifying keywords or topics for content.
Producing personalized communications, for example, email responses or product
recommendations.
Creating marketing content such as blog posts and social media captions.
Translating texts from one language to another
Summarizing long documents by providing a comprehensive overview of the full text
Automating customer service
How does ChatGPT work?
ChatGPT, a powerful language model, leverages fine-tuning, Reinforcement Learning
from Human Feedback (RLHF), embeddings, reward modeling, and Proximal Policy
Optimization (PPO) to provide high-quality, contextually relevant responses.

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How does ChatGPT work
Step 1
Collect demonstration
data and train a
supervised policy.
Explain reinforcement
learning to a 6 years old.
A prompt is
sampled from our
prompt dataset.
A labeler
demonstrates the
desired output
behavior.
Data is used to
Fine-tune GPT-3.5
with supervised
learning.
Explain reinforcement
learning to a 6 years old.
We give treats and
punishments to teach
SFT
Step 2
Collect comparison
data and train a reward
model.
D C A B D C A B
RM
A prompt and several
model outputs are
sampled.
A labeled ranks the
outputs from best
to worst.
Data is used
to train our
reward model.
D
C
A
B
In reinforcement
learning, the agent is
In machine learning
We give treats and
punishments to teach
Explain rewards..
Step 3
Optimize a policy
against the reward
model using the PPO
reinforcement learning
algorithm
A new prompt is
sampled from
the dataset.
The PPO model is
Initialised from the
supervised policy.
The policy
generates an
output.
The rewards model
calculates a reward
for the output.
The rewards is
used to update
the policy using
PPO.
Write a story
about otters
Once upon
a time
PPO RH
r
k
LeewayHertz
Embeddings
Embeddings play a crucial role in helping ChatGPT understand and generate contextually
relevant responses and are used in its pre-training phase. Embeddings are vector
representations of words, phrases, or sentences that capture the semantic and syntactic
relationships among them. They enable the model to process and generate human-like
language.
During the pretraining phase, ChatGPT learns embeddings from a vast corpus of text
data. The model captures the contextual information and relationships between words,
phrases and sentences in a high-dimensional space. These embeddings help ChatGPT
comprehend the input data’s meaning, nuances and dependencies. When a prompt is
given to ChatGPT, the model uses the learned embeddings to understand the context and
relationships between the words in the prompt. It then generates a contextually relevant
response by finding the embeddings that best match the input’s semantics and syntax.

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Embeddings enable ChatGPT to generate coherent and contextually appropriate
responses and allow the model to generalize its knowledge to new, unseen inputs. This is
possible because the embeddings capture the underlying structure and patterns in the
language, enabling the model to adapt its responses to a wide range of prompts. At this
stage, the model gains a generalized understanding of language.
Fine-tuning
Once the pretraining phase is complete, fine-tuning comes into play. ChatGPT is further
trained on a smaller, carefully curated dataset tailored to the target domain or task. This
dataset consists of input-output pairs generated by human labelers who provide the
expected responses to a list of prompts.
ChatGPT’s parameters are updated during fine-tuning to better align with the target task
or domain. This process allows the model to generate more accurate, relevant and useful
responses to the specific context or problem at hand. Fine-tuning adjusts the general
language skills of ChatGPT acquired from pretraining to fit the particular demands of a
desired task.
The fine-tuning phase may also involve techniques such as Reinforcement Learning from
Human Feedback (RLHF), which helps minimize harmful, untruthful, or biased outputs.
This technique involves a combination of supervised fine-tuning, reward modeling, and
Proximal Policy Optimization (PPO). RLHF aims to optimize the model’s responses based
on human preferences, ensuring that the model generates text that is accurate, user-
friendly and aligned with the desired output.
Key components of ChatGPT
ChatGPT combines various components, including machine learning, natural language
processing, and others. This is to understand and respond to users in a better, natural
and human-like way. There are also several technologies involved to improve the
interaction. Here we will learn about each component and technology of ChatGPT.
1. Machine learning: Machine learning is a branch of artificial intelligence that uses
algorithms, features, and data sets that improve over time. With ML as an integral
component, ChatGPT recognizes input patterns efficiently and responds to queries more
accurately.
2. Natural language processing: NLP is a significant part of ChatGPT that focuses on
converting unstructured data, such as text or speech, into a computer-readable format.
NLP involves several steps, including input generation, analysis, dialog management, and
reinforcement learning. These steps work together to understand human language and
generate appropriate responses.
3. Data mining: Data mining is another important component that involves analyzing data
using unsupervised learning. While machine learning focuses on making predictions
based on current data, data mining is used to discover unknown attributes.

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4. Intent analysis: Natural Language Understanding (NLU) is a set of techniques that
allows ChatGPT to determine the correct intent (or topic) of a request and extract
additional information that can be used to trigger additional actions, such as context,
account preferences, and entity extraction.
5. Response generation: ChatGPT is the model for NLG that generates text using a
convolutional neural network (CNN). Natural Language Generation (NLG), another
element of NLP, allows the creation of text in a way that it resembles the appearance,
emotion, and tone of natural speech.
Features of ChatGPT
ChatGPT is a highly popular AI chatbot with several key features that set it apart from
other chatbots.
1. Text generation: ChatGPT can easily generate text responding to prompts, queries, or
other input. It also generates text similar in style and content to the input it receives,
making it an ideal choice for text-generation tasks.
2. Natural language processing: ChatGPT is trained on a large dataset of human-
generated content, which allows it to understand and respond to natural language input.
This makes it useful for answering questions and providing accurate information.
3. Contextual understanding: ChatGPT can understand the context of a conversation
and generate appropriate responses. Users seeking answers to their questions are at a
great advantage with this unique feature of ChatGPT.
4. Customization: ChatGPT can be customized to generate text in a specific style or
tone by training it on a specific dataset. This makes it versatile and attracts more and
more users.
5. Versatility: ChatGPT can be used for various applications, such as automated
customer services, chatbots, language translation, etc.
6. Cost saving and multiple language support: ChatGPT helps reduce expenses and
costly resources by efficiently handling a high volume of inquiries. Additionally, it can
support multiple languages, making it valuable for businesses with a global audience.
How to build an app with ChatGPT
Let’s understand the process of creating an app using ChatGPT with an example.
Consider that we want to build a to-do list application using React Native. Now with the
help of ChatGPT, we will start the development process.
Before you begin, register and log in to your ChatGPT account. Start the development
process and input a query in ChatGPT, asking how to build a to-do list application using
React Native. Based on the result, move step by step and ask the tool to write codes.

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Here’s how we did it.
Input query: How to build a to-do list application using React Native?
Result we got:
To build a to-do list application using React Native, you will first need to set up your
development environment by installing the required tools such as Node.js, React Native
CLI, and an Android or iOS emulator.
1. Install Node.js: https://nodejs.org/en/download/
2. Install React Native CLI: npm install -g react-native-cli
3. Create a new project: react-native init ToDoList
4. Navigate to the project directory: cd ToDoList
5. Start the emulator:
for Android: react-native run-android
for iOS: react-native run-ios
6. Create a new component for the to-do list: touch src/components/ToDoList.js
7. Open the newly created file and add the code for the to-do list component
8. Import the ToDoList component in the App.js file and render it
9. Run the application:
for Android: react-native run-android
for iOS: react-native run-ios
Input query: How to install Node.js for the application?
Result we got:
To install Node.js on your machine, you can use the following command:
curl -sL https://deb.nodesource.com/setup_14.x | sudo -E bash -
sudo apt-get install -y nodejs
This command installs the latest version (14.x) of Node.js and its package manager, npm,
on a Debian-based Linux distribution.
Alternatively, you can also download the installation package from the official website and
run it:
https://nodejs.org/en/download/
If you’re using Windows or macOS, you can download the appropriate installer package
from the website and run it to install Node.js.
Note that you may need to open terminal as administrator or use sudo in the command
depending on your system setup
Input query: How to install React Native CLI
Result we got:
To install the React Native CLI, you can use the following command:

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npm install -g react-native-cli
This command installs the React Native CLI globally on your machine, allowing you to
use the react-native command in the terminal to create and manage React Native
projects.
Alternatively, you can also install it as a development dependency in your project:
npm install --save-dev react-native-cli
This will install the React Native CLI in the node_modules directory of your project, and
you can use it by referencing the local installation path.
Note that you may need to open the terminal as administrator or use sudo in the
command depending on your system setup
input Query: How to create a new React Native project using the React Native CLI
Result we got:
To create a new React Native project using the React Native CLI, you can use the
following command:
react-native init MyProject
This command creates a new directory called MyProject and sets up a basic React Native
project structure within it. The directory will contain the necessary files and directories for
a React Native application, including the index.js file that serves as the entry point for
your application.
You can replace MyProject with the desired name for your project.
This command also sets up the basic structure for an application with the name
MyProject. The structure will have index.js as the entry point for the application.
Alternatively, you can use the following command to create a new project by specifying
the template.
npx react-native init MyProject --template react-native-template-typescript
This command will create a new project with the specified template, in this case it is
react-native-template-typescript.
Please note that you may need to navigate to the directory where you want to create the
project before running this command, and that you may need to open terminal as
administrator or use sudo in the command depending on your system setup.
Input query: How to navigate to the project directory
Result we got:
To navigate to the project directory, you can use the cd command in the terminal.

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For example, if you have created a project called MyProject, you can navigate to the
project directory by using the following command:
cd MyProject
This command will take you to the MyProject directory, where you can access the files
and directories for your React Native project.
You can also use relative path to navigate to the project directory. For example, if you
created the project in a directory called ReactNativeProjects:
cd ReactNativeProjects/MyProject
You can also use the absolute path to navigate to the project directory:
cd /path/to/MyProject
It’s important to make sure you are in the correct directory before running any commands
related to the project, such as react-native run-android or react-native run-ios.
Input Query: How to start the emulator on android and IoS
Result we got:
To start an emulator for your React Native project, you will need to have an Android or
iOS emulator installed and configured on your machine.
For Android:
react-native run-android
This command will start the emulator and run the application on it. If the emulator is not
running, it will start the emulator first before running the application.
For iOS:
react-
Input Query: How to create new components for the to-do list
Result we got:
To create a new component for the to-do list in your React Native project, you can use the
following command:
touch src/components/ToDoList.js
This command creates a new file called ToDoList.js in the src/components directory of
your project.
Alternatively, you can also create the file manually by using your file explorer, or by using
the mkdir command to create the src/components directory and the touch command to
create the ToDoList.js file.
mkdir -p src/components

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touch src/components/ToDoList.js
Once the file is created, you can open it and start adding the code for your to-do list
component. This component can be a class-based or functional component, it depends
on your preference.
In this file you will define the structure and functionality of the to-do list component. This
can include JSX for the layout, state for managing the list items, and event handlers for
adding and removing items from the list.
Please note that the above command assumes that you have already navigate to the root
of your project directory where the package.json file is located and that you may need to
open terminal as administrator or use sudo in the command depending on your system
setup.
Input Query: How to open a newly created file and add the code for the to-do list
component
Result we got:
You can open the newly created file ToDoList.js with any text editor and add the code for
the to-do list component.
You can use the following command to open the file in the terminal using the nano editor:
nano src/components/ToDoList.js
You can also open the file using any text editor of your choice, such as Sublime Text,
Visual Studio Code, or Atom.
Here is an example of how you can add code for a to-do list component in the ToDoList.js
file:
import React, { useState } from 'react';
import { View, Text, Button, TextInput } from 'react-native';
const ToDoList = () => {
const [tasks, setTasks] = useState([]); // state to hold the list of tasks
const [newTask, setNewTask] = useState(''); // state to hold the value of new task input
const addTask = () => {
setTasks([...tasks, newTask]); // add new task to the list
setNewTask(''); // clear the input field
};
const removeTask = (index) => {
setTasks(tasks.filter((task, i) => i !== index)); // remove task from the list
};
return (
New Task:
setNewTask(text)}
/>

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Tasks:
{tasks.map((task, index) => (
{task}
< button title="Remove"> removeTask(index)} />
< /button>
))}
);
}
export default ToDoList;
This code defines a functional component called ToDoList that renders a view with two
children views. The first view is for inputting new task and adding it to the list and the
second view is for displaying the list of tasks and removing them. The component uses
TextInput from react-native, which is a built-in component for inputting text.
Please note that this is just an example and you may need to customize this code to fit
your specific requirements. Also, you may need to import some react-native components
that are not imported in the above code snippet.
Please also note that, you have to save the file before exiting the nano editor by pressing
ctrl + o and then ctrl + x to exit the editor.
Input Query: How to import the todolist component in the App.js file and render it
Result we got:
To import the ToDoList component in the App.js file and render it, you will need to add the
following code:
import React from 'react';
import { View } from 'react-native';
import ToDoList from './src/components/ToDoList'; // import the ToDoList component
const App = () => {
return (
< View>
// render the ToDoList component
< /View>
);
};
export default App;
In this example, the App component is importing the ToDoList component and render it as
a child of the View component.
Please note that the above code assumes that the App.js file is located in the root of your
project directory and that the ToDoList.js file is located in the src/components directory. If
the component is located in another directory, you should adjust the path accordingly.
Also, you may need to import other components or modules that are used in the ToDoList
component but not imported in the above code snippet in App.js file.

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Input Query: How to run the application
Result we got:
To run the application in your React Native project, you can use the following commands:
For Android:
react-native run-android
This command will start the emulator and run the application on it. If the emulator is not
running, it will start the emulator first before running the application.
For iOS:
react-native run-ios
This command will start the iOS simulator and run the application on it. If the simulator is
not running, it will start the simulator first before running the application.
You should run this command from the root of your project directory, where the
package.json file is located.
Please note that, you have to open the emulator or simulator and have the development
server running in another terminal window before running this command. Also, you may
need to open terminal as administrator or use sudo in the command depending on your
system setup.
After running this command, the application will be built and deployed to the emulator or
simulator. If everything is set up correctly, you should see the to-do list application running
on the emulator or simulator.
In the same way, if you want to add more functionalities to your react-native application,
style the view container, or change its background color, input a query in the ChatGPT
asking for the code and steps.
You can build a fully functional react-native application by following all the commands,
steps, and code the tool generates. If there is an error or bug in the code, the tool also
helps fix the issues by providing example codes and suggesting ways to debug codes.
Thus, many other usable applications can be built with the help of ChatGPT – all we have
to do is ask questions.
Factors to consider while building an app with ChatGPT
Current generative AI models such as ChatGPT come with certain shortfalls which need
to be addressed properly to tread carefully while building an app with ChatGPT. Here are
some of them:
Removing bias and toxicity

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As much as we value the power of generative AI, we must acknowledge that with great
power comes great responsibility. It’s important to recognize that these models are trained
on data derived from the vast and often unpredictable expanse of the internet. As a result,
they can contain deeply ingrained biases and toxic language that may inadvertently
surface in the final product. That’s why responsible AI practices are more crucial than
ever before. We must ensure that our AI models are developed and deployed ethically
and socially responsibly. By prioritizing responsible AI practices, we can help mitigate the
risks of biased and toxic content while harnessing the full potential of generative AI to
bring about a better world. Additionally, to ensure that the output generated by AI models
is free from bias and toxicity, it’s important to take a proactive approach, including filtering
the training datasets to remove any potentially harmful content and implementing
additional watchdog models to monitor the output in real-time. Furthermore, enterprises
can enhance the quality of their AI models by leveraging their own first-party data to train
and fine-tune their models. By doing so, they can tailor the output to meet their specific
use cases and improve overall performance.
Improving hallucination
While ChatGPT has the ability to generate highly persuasive arguments, it’s important to
note that these arguments may not always be factually accurate. In fact, this
phenomenon is known as “hallucination” within the developer community, and it can limit
the reliability of the output generated by AI models. To address this issue, OpenAI and
other vendors are taking a variety of measures, such as data augmentation, adversarial
training, improved model architectures, and human evaluation. These steps aim to
improve the output’s accuracy and reduce the risk of hallucination. If you’re building an
app with ChatGPT, it’s important to follow similar measures to ensure that the output
generated by the model is as accurate and reliable as possible. By doing so, you can help
build user trust in your app and ensure that it delivers high-quality results.
Preventing data leakage
Clear policies should be in place so that it can prohibit developers from entering sensitive
information into ChatGPT, which could become incorporated into the model and
potentially resurface later in a public context. By instituting these policies, we can help
prevent the inadvertent disclosure of sensitive information and protect the privacy and
security of individuals and organizations. It’s critical that we remain vigilant in
safeguarding against the potential risks associated with the use of AI models like
ChatGPT, and that we take proactive measures to mitigate these risks.
Incorporating queries and actions
While current generative models are capable of providing answers based on their initial
large training data set or smaller “fine-tuning” data sets, both of which are essentially
snapshots of the past, the next generation of models will take things to the next level.
These models will have the ability to identify when they need to look something up in
external sources such as a database or Google, or when to trigger actions in external

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systems. This will transform generative models from disconnected oracles to fully
connected conversational interfaces to the world. By enabling this new level of
connectivity, it is possible to unlock a whole new set of use cases and possibilities for
these models allowing a more dynamic and seamless user experience that can provide
real-time, relevant information and insights.
So, as we move forward with the development and deployment of generative models, we
must keep in mind this exciting potential for integration with external systems and
information sources enabling us to create a new generation of AI-powered applications
that are more useful, powerful, and impactful than ever before.
Benefits of using ChatGPT for app development
In modern app development, artificial intelligence and AI-based development tools have
become one of the key driving forces. These are becoming virtually endless, helping
businesses achieve micro or macro goals efficiently and effectively – regardless of the
industry type. ChatGPT for app development can greatly streamline the process while
enhancing the in-app user experience. In light of this, let’s take a closer look at how this
AI-based chatbot is changing app development.
Here’s what you need to know.
Writing codes
App development often requires writing intricate and time-consuming code. However, with
the help of ChatGPT, both professionals and beginners in app development can
streamline their coding process. Additionally, if developers encounter any issues with
their code, they can use the tool to modify or fix them quickly. Furthermore, ChatGPT can
be utilized to write code in any programming language.
Improved efficiency
ChatGPT can provide significant benefits for app development companies by streamlining
various tasks and processes, providing quick solutions, and allowing developers to focus
on more critical responsibilities. This can lead to an increase in efficiency and productivity,
resulting in businesses saving time and being able to focus on growth opportunities. This
tool can be a powerful asset for companies looking to optimize their operations and drive
success.
Debugging codes
As a programmer, you can leverage ChatGPT’s capabilities to your advantage by utilizing
it to identify and troubleshoot errors in your code. By requesting ChatGPT to review a
piece of code for mistakes, it will not only point out the issues but also provide
suggestions on how to fix them, including specific examples.
ChatGPT’s code generation capabilities ensure that the resulting code is:

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Error-free and bug-free
Clearly and thoroughly documented
Simple to comprehend and maintain
Tailored to meet specific business requirements
Built to perform well in the production environment
Conclusion
By following the steps outlined, ChatGPT can be utilized to develop a fully functional and
robust app. Its advanced and intelligent capabilities are poised to significantly impact
various industries, including the business world and daily life. Its potential to enhance
search engines, improve user service, and generate written content more sophisticatedly
is expected to drive innovation and automation of routine tasks and non-creative
functions.
The use of ChatGPT in various industries is expected to bring significant benefits, as
businesses will be able to optimize different business processes through it. AI-based
systems, such as ChatGPT, are expected to revolutionize human and machine
interactions. Businesses can continue to grow by staying informed and utilizing these
artificial intelligence-based systems.
If you want to integrate ChatGPT model-powered solutions into your business, contact
LeewayHertz’s ChatGPT developers.