Build an Interactive CLI ChatBot

Table of Contents

1. Introduction
2. Setting Up the Node.js Application
3. Initializing the Node.js Project
4. Installing Dependencies
5. Creating the Code File
6. Configuring OpenAI API
7. Testing the Create Chat Completion Endpoint
8. Making the Application Interactive
9. Implementing User Interface with readline
10. Continuously Interacting with the Chatbot
11. Conclusion

Introduction

In this tutorial, we will create an interactive CLI application using Node.js and OpenAI's GPT-3.5 Turbo model. We will walk through the process of setting up the project, configuring the OpenAI API, and testing the create chat completion endpoint. Then, we will make the application interactive by implementing a user interface with the readline module. Finally, we will continuously interact with the chatbot, allowing users to ask questions and receive responses in the terminal.

Setting Up the Node.js Application

To get started, we need to set up the Node.js application and install the necessary dependencies. Follow the steps below:

Step 1: Initializing the Node.js Project

Create a new folder for your project and navigate to it in the terminal. Run the following command to initialize the project:

mkdir project-name
cd project-name
npm init -y

Step 2: Installing Dependencies

Next, we need to install the required dependencies. Run the following command:

npm install openai readline

Creating the Code File

In the project folder, create a new file named index.js. This will contain the code for the CLI application.

Configuring OpenAI API

To use the OpenAI API, we need to set up the configuration. Follow these steps:

1. Log in to your OpenAI account and go to the API Keys section.
2. Generate a new API key and copy it.
3. In the index.js file, import the openai Package and set up the configuration using your API key:

const openai = require('openai');
const configuration = new openai.Configuration({
  api_key: 'YOUR_API_KEY',
});

Testing the Create Chat Completion Endpoint

Now, let's test the create chat completion endpoint to ensure it is working as expected. Add the following code to the index.js file:

const openai = require('openai');
const configuration = new openai.Configuration({
  api_key: 'YOUR_API_KEY',
});

const openaiApi = new openai.OpenAIApi(configuration);

const prompt = 'Hello, how may I assist you today?';

openaiApi.createChatCompletion(prompts).then((response) => {
  const message = response.data.choices[0].message.content;
  console.log(message);
});

Making the Application Interactive

To make the CLI application interactive, we will use the readline module. Follow these steps:

1. Import the readline module:

const readline = require('readline');

2. Create a user interface with readline:

const userInterface = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
});

3. Prompt the user for input:

userInterface.question('Enter your message: ', (input) => {
  // Code to process the user input
});

4. Replace the hardcoded prompt with the user input in the createChatCompletion function:

const prompt = input;

Implementing User Interface with readline

To Interact with the chatbot through the terminal, we will modify the code inside the readline callback. Update your code as follows:

userInterface.question('Enter your message: ', (input) => {
  const prompt = input;

  openaiApi.createChatCompletion(prompt).then((response) => {
    const message = response.data.choices[0].message.content;
    console.log(message);

    userInterface.prompt();
  });
});

Continuously Interacting with the Chatbot

To continuously interact with the chatbot, we need to wrap the readline code inside a recursive function. Update your code as follows:

function chat() {
  userInterface.question('Enter your message: ', (input) => {
    const prompt = input;

    openaiApi.createChatCompletion(prompt).then((response) => {
      const message = response.data.choices[0].message.content;
      console.log(message);

      chat();
    });
  });
}

chat();

Now, the application will keep prompting the user for input after each response from the chatbot.

Conclusion

In this tutorial, we have learned how to create an interactive CLI application using Node.js and OpenAI's GPT-3.5 Turbo model. We set up the project, configured the OpenAI API, and tested the create chat completion endpoint. We made the application interactive by implementing a user interface with the readline module. Finally, we continuously interacted with the chatbot by prompting the user for input after each response. Feel free to explore more functionalities and enhance the application as per your requirements.

Highlights

• Create an interactive CLI application using Node.js and OpenAI's GPT-3.5 Turbo model
• Set up the project and install dependencies
• Configure the OpenAI API and test the create chat completion endpoint
• Implement a user interface with the readline module
• Continuously interact with the chatbot by prompting the user for input after each response

FAQ:

Q: Can I use a different API key? A: Yes, you can replace 'YOUR_API_KEY' with your own OpenAI API key.

Q: How can I customize the messages sent to the chatbot? A: You can modify the prompt variable to send different messages to the chatbot.

Q: What happens if I enter an invalid input? A: The chatbot will provide a response based on the prompt it receives. Invalid inputs may result in unexpected or nonsensical responses.

Q: Can I add more functionality to the CLI application? A: Absolutely! You can explore additional functionalities, such as handling multiple messages and creating a conversation history.