ChatGPT Clone using React.JS Step-by-Step

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ChatGPT clone using React, you will need to do the following steps:

Set up a new React project using a tool like create-react-app.
Create a new component for the chat interface, including input fields for the user to type their message and a display area for the chatbot’s response.
Use the OpenAI API to send the user’s message to the GPT-3 model, and receive the chatbot’s response.
Display the chatbot’s response in the chat interface.
Use React state and props to keep track of the conversation history and update the display as new messages are sent and received.
Add additional features like buttons to clear the chat history or change the chatbot’s language.

Disclaimer 1. It would be a good idea to check the OpenAI documentation for more information on how to use their API and the various options available for customization. Also, it is important to note that you need to have OpenAI API key to use GPT-3 model and check the pricing and usage limits as well.

ChatGPT React.JS CODEs And Expalnations

Step 1. Setting up a new React project:

npx create-react-app my-chatbot-app
cd my-chatbot-app
npm start

Step 2: Creating a new component for the chat interface:

import React, { useState } from 'react';

function Chatbot() {
  const [message, setMessage] = useState('');
  const [chatbotResponse, setChatbotResponse] = useState('');

  function handleChange(e) {
    setMessage(e.target.value);
  }

  async function handleSubmit(e) {
    e.preventDefault();
    // Send message to OpenAI API
    const response = await fetch(`https://api.openai.com/v1/engines/davinci/completions`, {
      method: 'POST',
      headers: {
        'Content-Type': 'application/json',
        'Authorization': `Bearer ${YOUR_API_KEY}`
      },
      body: JSON.stringify({
        prompt: message,
        max_tokens: 100,
        temperature: 0.5
      })
    });
    const data = await response.json();
    setChatbotResponse(data.choices[0].text);
  }

  return (
    <div>
      <form onSubmit={handleSubmit}>
        <input type="text" value={message} onChange={handleChange} />
        <button type="submit">Send</button>
      </form>
      <div>{chatbotResponse}</div>
    </div>
  );
}

export default Chatbot;

Step 3: Use the OpenAI API to send the user’s message to the GPT-3 model, and receive the chatbot’s response.

const response = await fetch(`https://api.openai.com/v1/engines/davinci/completions`, {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': `Bearer ${YOUR_API_KEY}`
  },
  body: JSON.stringify({
    prompt: message,
    max_tokens: 100,
    temperature: 0.5
  })
});
const data = await response.json();
setChatbotResponse(data.choices[0].text);

It is important to note that the above is just an example and might need modification as per the requirement. Also, It is important to check the Open AI documentation for more information on how to use their API and the various options available for customization.

Lets’ continue the good work..

To continue, you can use React state and props to keep track of the conversation history and update the display as new messages are sent and received:

const [conversation, setConversation] = useState([]);

// Add new message to the conversation
setConversation([...conversation, { message, type: 'user' }, { message: chatbotResponse, type: 'bot' }]);

You can then use this conversation state to display the entire conversation history in the chat interface:

<div>
  {conversation.map((msg, i) => (
    <div key={i} className={`message ${msg.type}`}>
      {msg.message}
    </div>
  ))}
</div>

And you can also add additional features like buttons to clear the chat history or change the chatbot’s language:

<button onClick={() => setConversation([])}>Clear Chat</button>
<button onClick={() => setLanguage('fr')}>Change Language</button>

Keep in mind that in this example, the 'setLanguage' function would need to be defined and used to update the language setting in the OpenAI API request.

You can also add more styling and customizations to the chatbot interface to make it more user-friendly. Please remember that this is just an example and you will have to adapt the code to match your specific requirements and also you need to have OpenAI API key to use GPT-3 model and check the pricing and usage limits as well.

Disclaimer 2: The code examples I provided should cover the basic functionality of a ChatGPT clone using React. However, there are a few additional things you might consider to make the chatbot more robust and user-friendly:

Error handling:

You should add error handling to your code to handle any issues that might arise when communicating with the OpenAI API, such as invalid API keys or server errors.

async function handleSubmit(e) {
  e.preventDefault();
  try {
    // Send message to OpenAI API
    const response = await fetch(`https://api.openai.com/v1/engines/davinci/completions`, {
      method: 'POST',
      headers: {
        'Content-Type': 'application/json',
        'Authorization': `Bearer ${YOUR_API_KEY}`
      },
      body: JSON.stringify({
        prompt: message,
        max_tokens: 100,
        temperature: 0.5
      })
    });
    const data = await response.json();
    setChatbotResponse(data.choices[0].text);
    setConversation([...conversation, { message, type: 'user' }, { message: chatbotResponse, type: 'bot' }]);
  } catch (error) {
    setChatbotResponse('Sorry, there was an error processing your message.');
  }
}

2. Loading states:

You can add a loading state to your chatbot interface to let users know that their message is being processed.

const [isLoading, setIsLoading] = useState(false);

function handleSubmit(e) {
  e.preventDefault();
  setIsLoading(true);
  // Send message to OpenAI API and handle response
  // ...
  setIsLoading(false);
}

return (
  <div>
    <form onSubmit={handleSubmit}>
      <input type="text" value={message} onChange={handleChange} />
      <button type="submit" disabled={isLoading}>
        {isLoading ? 'Loading...' : 'Send'}
      </button>
    </form>
    <div>{chatbotResponse}</div>
  </div>
);

3. Customizing the API requests:

You can customize the API requests you’re making to the OpenAI API to fine-tune the chatbot’s responses. For example, you can change the temperature parameter to control how confident the chatbot is in its responses.

function handleChange(e) {
    setMessage(e.target.value);
    // You can update the temperature based on the user's input
    setTemperature(e.target.value.length > 10 ? 0.7 : 0.5);
}

async function handleSubmit(e) {
    e.preventDefault();
    // Send message to OpenAI API
    const response = await fetch(`https://api.openai.com/v1/engines/davinci/completions`, {
        method: 'POST',
        headers: {
            'Content-Type': 'application/json',
            'Authorization': `Bearer ${YOUR_API_KEY}`
        },
        body: JSON.stringify({
            prompt: message,
            max_tokens: 100,
            temperature: temperature
        })
    });
    const data = await response.json();
    setChatbotResponse(data.choices[0].text);
    setConversation([...conversation, { message, type: 'user' }, { message: chatbotResponse, type: 'bot' }]);
}

4. Adding more functionality:

You can add more functionality to the chatbot such as keeping the history of the chat and also giving options to the user to change the language of the chatbot.

const [language, setLanguage] = useState('en');
function handleLanguageChange(e) {
    setLanguage(e.target.value);
}

async function handleSubmit(e) {
    e.preventDefault();
    // Send message to OpenAI API
    const response = await fetch(`https://api.openai.com/v1/engines/davinci/completions`, {
        method: 'POST',
        headers: {
            'Content-Type': 'application/json',
            'Authorization': `Bearer ${YOUR_API_KEY}`
        },
        body: JSON.stringify({
            prompt: message,
            max_tokens: 100,
            temperature: temperature,
            language: language
        })
    });
    const data = await response.json();
    setChatbotResponse(data.choices[0].text);
    setConversation([...conversation, { message, type: 'user' }, { message: chatbotResponse, type: 'bot' }]);
}

return (
    <div>
        <form onSubmit={handleSubmit}>
            <input type="text" value={message} onChange={handleChange} />
            <select value={language} onChange={handleLanguageChange}>
                <option value="en">English</option>
                <option value="fr">French</option>
                <option value="es">Spanish</option>
            </select>
            <button type="submit">Send</button>
        </form>
        <div>{chatbotResponse}</div>
    </div>
);

5. Enhancing the UI:

You can enhance the UI of your chatbot to make it more user-friendly and interactive.

import './chatbot.css';

function Chatbot() {
  // ...

  return (
    <div className="chatbot-container">
      <div className="conversation-container">
        {conversation.map((msg, i) => (
          <div key={i} className={`message ${msg.type}`}>
            {msg.message}
          </div>
        ))}
      </div>
      <form onSubmit={handleSubmit}>
        <input className="message-input" type="text" value={message} onChange={handleChange} />
        <button className="send-button" type="submit">Send</button>
      </form>
    </div>
  );
}

6. Monitoring and tracking:

You can also add monitoring and tracking to measure how users interact with the chatbot, and use that data to improve the chatbot’s performance.

import Analytics from 'analytics-react-native';

const analytics = new Analytics('YOUR_WRITE_KEY');

function handleSubmit(e) {
    e.preventDefault();
    // Send message to OpenAI API
    // ...
    analytics.track('Chatbot Message', {
        message: message
    });
}

Keep in mind that this is just a starting point and you may need to make adjustments and add additional functionality to suit your specific use case.

In this example, I am using ‘analytics-react-native’ library for tracking the events, you can use any library or package of your choice for tracking.

Disclaimer 3: It’s important to keep in mind that this is just an example and you will have to adapt the code to match your specific requirements and also you need to have OpenAI API key to use GPT-3 model and check the pricing and usage limits as well. Also, it is important to check the OpenAI documentation for more information on how to use their API and the various options available for customization.

CSS for ChatBot in this project

Here’s an example of what the CSS for the chatbot interface might look like.

.chatbot-container {
  width: 100%;
  height: 100%;
  display: flex;
  flex-direction: column;
  align-items: center;
}

.conversation-container {
  width: 80%;
  height: 80%;
  overflow-y: scroll;
  padding: 20px;
  display: flex;
  flex-direction: column;
  align-items: flex-start;
}

.message {
  padding: 10px;
  margin-bottom: 10px;
  border-radius: 10px;
}

.user {
  background-color: #ccc;
  align-self: flex-end;
}

.bot {
  background-color: #4da6ff;
  align-self: flex-start;
}

.message-input {
  width: 80%;
  padding: 10px;
  margin-bottom: 10px;
  border-radius: 10px;
  border: none;
  outline: none;
}

.send-button {
  width: 15%;
  padding: 10px;
  margin-left: 5%;
  background-color: #4da6ff;
  color: #fff;
  border-radius: 10px;
  border: none;
  outline: none;
  font-weight: bold;
  cursor: pointer;
}

This CSS will give you the basic layout of a chatbot interface with a scrolling conversation container and a message input field. You can customize this CSS to match your desired design and layout.

Structure of your Files

Here’s an example of how you might structure your files and components for a ChatGPT clone using React:

my-chatbot-app/
  |
  |-src/
    |
    |-components/
    |  |
    |  |-Chatbot/
    |     |
    |     |-Chatbot.js (component code)
    |     |-Chatbot.css (component styling)
    |
    |-App.js (entry point of the application)
    |-index.js (renders the App component)

In the src folder, you would have your main application files such as App.js and index.js.
In the components folder, you would have your chatbot component, Chatbot.js and Chatbot.css
App.js would import the Chatbot component and render it.
index.js would render the App component, which in turn renders the Chatbot component.

Here’s an example of what the App.jsfile might look like:

import React from 'react';
import Chatbot from './components/Chatbot/Chatbot';

function App() {
  return (
    <div className="App">
      <Chatbot />
    </div>
  );
}

export default App;

andindex.jsfile might look like:

import React from 'react';
import ReactDOM from 'react-dom';
import App from './App';

ReactDOM.render(<App />, document.getElementById('root'));

Here’s an example of what the Chatbot.jsfile might look like:

import React, { useState, useEffect } from 'react';
import axios from 'axios';

import './Chatbot.css';

const API_URL = 'https://api.openai.com/v1/engines/davinci-codex/completions';

function Chatbot() {
  const [conversation, setConversation] = useState([]);
  const [message, setMessage] = useState('');
  const [apiKey, setApiKey] = useState('YOUR_API_KEY');

  useEffect(() => {
    setConversation([{ message: 'Hello! How can I help you today?', type: 'bot' }]);
  }, []);

  const handleChange = (e) => {
    setMessage(e.target.value);
  };

  const handleSubmit = async (e) => {
    e.preventDefault();

    // Send message to OpenAI API
    try {
      const response = await axios.post(API_URL, {
        prompt: `User: ${message}\nBot: ${conversation[conversation.length - 1].message}`,
        temperature: 0.5,
        max_tokens: 50,
      }, {
        headers: {
          'Content-Type': 'application/json',
          'Authorization': `Bearer ${apiKey}`,
        },
      });

      // Update conversation state with user's message
      setConversation([...conversation, { message, type: 'user' }]);

      // Update conversation state with bot's response
      setConversation([...conversation, { message: response.data.choices[0].text, type: 'bot' }]);
    } catch (err) {
      console.error(err);
    }
    // Clear input field
    setMessage('');
  };

  return (
    <div className="chatbot-container">
      <div className="conversation-container">
        {conversation.map((msg, i) => (
          <div key={i} className={`message ${msg.type}`}>
            {msg.message

Here’s an example of what the Chatbot.css file might look like:

.chatbot-container {
  width: 100%;
  height: 100%;
  display: flex;
  flex-direction: column;
  align-items: center;
}

.conversation-container {
  width: 80%;
  height: 80%;
  overflow-y: scroll;
  padding: 20px;
  display: flex;
  flex-direction: column;
  align-items: flex-start;
}

.message {
  padding: 10px;
  margin-bottom: 10px;
  border-radius: 10px;
}

.user {
  background-color: #ccc;
  align-self: flex-end;
}

.bot {
  background-color: #4da6ff;
  align-self: flex-start;
}

.message-input {
  width: 80%;
  padding: 10px;
  margin-bottom: 10px;
  border-radius: 10px;
  border: none;
  outline: none;
}

.send-button {
  width: 15%;
  padding: 10px;
  margin-left: 5%;
  background-color: #4da6ff;
  color: #fff;
  border-radius: 10px;
  border: none;
  outline: none;
  font-weight: bold;
  cursor: pointer;
}

This CSS will give you the basic layout of a chatbot interface with a scrolling conversation container and a message input field. You can customize this CSS to match your desired design and layout.

Please note that you should import the Chatbot.css file in the Chatbot.js file.

Thank you for holding there from the beginning to this end where we developed ChatGPT from start to the end.

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ChatGPT Clone using React.JS Step-by-Step

ChatGPT clone using React, you will need to do the following steps:

ChatGPT React.JS CODEs And Expalnations

Step 1. Setting up a new React project:

Step 2: Creating a new component for the chat interface:

Step 3: Use the OpenAI API to send the user’s message to the GPT-3 model, and receive the chatbot’s response.

Error handling:

You should add error handling to your code to handle any issues that might arise when communicating with the OpenAI API, such as invalid API keys or server errors.

2. Loading states:

3. Customizing the API requests:

4. Adding more functionality:

5. Enhancing the UI:

6. Monitoring and tracking:

CSS for ChatBot in this project

Structure of your Files

Quick Links

Resources

Registrations

ChatGPT clone using React, you will need to do the following steps:

ChatGPT React.JS CODEs And Expalnations

Step 1. Setting up a new React project:

Step 2: Creating a new component for the chat interface:

Step 3: Use the OpenAI API to send the user’s message to the GPT-3 model, and receive the chatbot’s response.

Error handling:

You should add error handling to your code to handle any issues that might arise when communicating with the OpenAI API, such as invalid API keys or server errors.

2. Loading states:

3. Customizing the API requests:

4. Adding more functionality:

5. Enhancing the UI:

6. Monitoring and tracking:

CSS for ChatBot in this project

Structure of your Files

Quick Links

Resources

Registrations

Cookie Notice