How to Build a GPT-3 Chatbot With Python

ChatGPT is a marvel of modern technology, a virtual entity that transcends the boundaries of traditional communication. Born from the vast expanse of data and trained on the collective knowledge of humanity, ChatGPT emerges as a digital conversationalist capable of engaging with users in a myriad of topics and contexts. Its neural network architecture empowers it to understand, generate, and respond to text with remarkable fluency and coherence.

Today, in this tutorial, we’re diving into the exciting world of artificial intelligence as we explore how to create a GPT chatbot using the Python OpenAI library. Get ready to unlock the power of language generation and conversational AI as we embark on this journey together. Let’s dive in and bring your ideas to life with ChatGPT!

Getting Started

Let’s kick off this tutorial by navigating through each step meticulously, commencing with establishing a virtual environment, proceeding to the installation of essential packages, and culminating in the crafting of the chatbot script.

Step 1: Set Up Virtual Environment

To initiate the project setup, begin by opening a terminal or command prompt. Next, navigate to the desired directory where you intend to house your project. Then, create a virtual environment by executing the following command:

$ python -m venv myenv

Replace `myenv` with the name you want to give to your virtual environment.

Once the virtual environment has been created, activate it to enable its functionality.

  • On Windows
$ myenv\Scripts\activate
  • On macOS and Linux
$ source myenv/bin/activate

Step 2: Install Required Packages

With the virtual environment active, proceed to install the OpenAI package using pip.

$ pip install openai

Step 3: Writing the Chatbot Script

After setting up the virtual environment and installing the OpenAI library, it’s time to craft the Python script for our chatbot. Let’s proceed by creating a new Python file named chatbot.py within our project directory.

  • Importing the openai Library
import openai

This line imports the openai library, which provides access to the OpenAI GPT (Generative Pre-trained Transformer) model and its functionalities.

  • Defining the GPTChatbot Class
class GPTChatbot:

This defines a Python class named GPTChatbot, which encapsulates the functionality of the chatbot.

  • Initializing the Chatbot Class
def __init__(self, api_key):
    openai.api_key = api_key
    self.chat_history = []

The __init__ method initializes the chatbot object with the provided OpenAI API key and an empty list to store the chat history.

  • Chat Method
def chat(self, user_input):
    prompt = self._construct_prompt(user_input)
    response = self._get_response(prompt)
    self._update_chat_history(user_input, response)
    return response

The chat method takes user input, constructs a prompt, gets a response from the OpenAI API, updates the chat history, and returns the bot’s response.

  • Constructing the Prompt
def _construct_prompt(self, user_input):
    prompt = ""
    if self.chat_history:
        prompt += f"Conversation History:\n"
        for i, (user, bot) in enumerate(self.chat_history, start=1):
            prompt += f"{i}. You: {user}\n   Bot: {bot}\n"
        prompt += "\n"
    prompt += f"You: {user_input}\nBot:"
    return prompt

The _construct_prompt method generates a prompt for the chatbot based on the current conversation history and the user’s input.

  • Getting the Response
def _get_response(self, prompt):
    response = openai.Completion.create(
        engine="davinci",
        prompt=prompt,
        temperature=0.7,
        max_tokens=150
    )
    return response.choices[0].text.strip()

The _get_response method sends the prompt to the OpenAI API and retrieves a response from the GPT model.

  • Updating the Chat History
def _update_chat_history(self, user_input, bot_response):
    self.chat_history.append((user_input, bot_response))

The _update_chat_history method updates the chat history with the user’s input and the bot’s response.

  • Main Function
def main():
    api_key = 'YOUR_OPENAI_API_KEY'  # Replace with your API key
    chatbot = GPTChatbot(api_key)
    
    print("Welcome to the OpenAI Chatbot! Type 'exit' to end the conversation.")
    while True:
        try:
            user_input = input("You: ")
            if user_input.lower() == 'exit':
                print("Goodbye!")
                break
            bot_response = chatbot.chat(user_input)
            print("Bot:", bot_response)
        except KeyboardInterrupt:
            print("\nExiting...")
            break
        except Exception as e:
            print("An error occurred:", e)

if __name__ == "__main__":
    main()

The main function sets up the chatbot, initializes it with the API key, and starts the conversation loop. It prompts the user for input, sends the input to the chatbot, and displays the bot’s response. It also handles keyboard interrupts and other exceptions gracefully.

NB: Substitute the placeholder “api_key = ‘YOUR_OPENAI_API_KEY‘” with your authentic OpenAI API key for seamless integration and functionality.

To obtain an OpenAI API key, follow these steps:

  1. Create an OpenAI account: If you don’t already have an account, sign up for one on the OpenAI website.
  2. Navigate to the API section: Once logged in, go to the API section of the OpenAI website. You can usually find it in the account settings or dashboard.
  3. Generate an API key: In the API section, you’ll find an option to generate an API key. Click on it, and OpenAI will provide you with a unique API key.
  4. Copy the API key: Once generated, copy the API key to your clipboard. Ensure to keep it secure, as it provides access to the OpenAI API.
  5. Use the API key: Now, you can use this API key in your applications to access the OpenAI API and utilize its various services, such as language generation with models like GPT.

Now that we’ve meticulously crafted various Python code blocks to construct our GPT chatbot, it’s time to consolidate our efforts. Let’s bring together all the aforementioned code blocks into a unified whole, ensuring seamless integration and coherence.

import openai

class GPTChatbot:
    def __init__(self, api_key):
        openai.api_key = api_key
        self.chat_history = []

    def chat(self, user_input):
        prompt = self._construct_prompt(user_input)
        response = self._get_response(prompt)
        self._update_chat_history(user_input, response)
        return response

    def _construct_prompt(self, user_input):
        prompt = ""
        if self.chat_history:
            prompt += f"Conversation History:\n"
            for i, (user, bot) in enumerate(self.chat_history, start=1):
                prompt += f"{i}. You: {user}\n   Bot: {bot}\n"
            prompt += "\n"
        prompt += f"You: {user_input}\nBot:"
        return prompt

    def _get_response(self, prompt):
        response = openai.Completion.create(
            engine="davinci",
            prompt=prompt,
            temperature=0.7,
            max_tokens=150
        )
        return response.choices[0].text.strip()

    def _update_chat_history(self, user_input, bot_response):
        self.chat_history.append((user_input, bot_response))

def main():
    api_key = 'YOUR_OPENAI_API_KEY'  # Replace with your API key
    chatbot = GPTChatbot(api_key)
    
    print("Welcome to the OpenAI Chatbot! Type 'exit' to end the conversation.")
    while True:
        try:
            user_input = input("You: ")
            if user_input.lower() == 'exit':
                print("Goodbye!")
                break
            bot_response = chatbot.chat(user_input)
            print("Bot:", bot_response)
        except KeyboardInterrupt:
            print("\nExiting...")
            break
        except Exception as e:
            print("An error occurred:", e)

if __name__ == "__main__":
    main()

Step 6: Run the Chatbot

To execute the Python script, first, ensure your virtual environment is activated. Then, navigate to the directory housing your chatbot.py script. Finally, run the script by executing the following command.

$ python chatbot.py

~ Happy Coding ~


Leave a Reply

Your email address will not be published. Required fields are marked *

DarkLight
×