Build a ChatGPT-Powered Python Chatbot: Step-by-Step Guide

Guide: This article shows developers how to create a Python program for a ChatGPT AI chatbot.

OpenAI has opened ChatGPT capabilities to everyone, allowing seamless integration of its powerful functions into applications at a low cost of $0.002 per 1,000 tokens.

The API currently offers features such as creating custom conversational agents, assisting developers with Python code, drafting emails or documents, integrating natural‑language interfaces into products, providing translation services, acting as a tutor for many subjects, and simulating video‑game characters.

OpenAI ChatGPT API: Getting Started Guide

Prerequisites

Visit https://chat.openai.com/ to create an account (Google or Microsoft login is supported). After creating an account, generate a personal API key at https://platform.openai.com/account/api-keys .

Creating the OpenAI API Key

Record the key and store it securely; it will not be visible again in the OpenAI account dashboard. Do not share the key and treat it as confidential, especially if it is linked to a paid plan.

Setting Up the Development Environment

Install Python and pip on your system. For Debian‑based Linux (e.g., Ubuntu): sudo apt-get install python3-pip For Fedora, RHEL, CentOS: sudo dnf install python3-pip For Arch Linux:

sudo pacman -S python-pip

Configuring the API Key

Best practice is to load the key from an environment variable or a file rather than hard‑coding it.

# Windows example
set API_KEY=your_key_here

# Linux example (add to /etc/environment)
API_KEY="your_key_here"

# In Python, load from file
openai.api_key_path = "/path/to/key.txt"

# Direct assignment (not recommended)
openai.api_key = "your_key_here"

Installing the OpenAI Python Library

pip install openai

Writing the Chatbot Program

import openai

# Load API key (choose one of the methods above)
openai.api_key = "your_key_here"

messages = []
system_message = input("What type of chatbot you want me to be?")
messages.append({"role": "system", "content": system_message})

print("Alright! I am ready to be your friendly chatbot
You can now type your messages.")
user_message = input()
messages.append({"role": "user", "content": user_message})

response = openai.ChatCompletion.create(
    model="gpt-3.5-turbo",
    messages=messages
)

reply = response["choices"][0]["message"]["content"]
print(reply)

Running the Code

Execute the script from a Python IDE or the command line:

python OpenAIDemo2.py

Sample Unformatted JSON Output

{
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": "As an AI language model, I don't have personal opinions, but I can tell you that kindness is a very positive and essential trait...",
        "role": "assistant"
      }
    }
  ],
  "created": <removed>,
  "id": "chatcmpl-<removed>",
  "model": "gpt-3.5-turbo-0301",
  "object": "chat.completion",
  "usage": {
    "completion_tokens": 91,
    "prompt_tokens": 22,
    "total_tokens": 113
  }
}

The formatted output presents the same information in a readable structure.

Full Python Code

import openai

openai.api_key = "<your key>"

messages = []
system_message = input("What type of chatbot you want me to be?")
messages.append({"role":"system","content":system_message})

print("Alright! I am ready to be your friendly chatbot
You can now type your messages.")
message = input("")
messages.append({"role":"user","content": message})

response = openai.ChatCompletion.create(
  model="gpt-3.5-turbo",
  messages=messages
)

reply = response["choices"][0]["message"]["content"]
print(reply)