How to Create a Python Virtual Environment and Build a Simple OpenAI Chat Script

If you’re working with Python and APIs like OpenAI, using a virtual environment (venv) is no longer optional—it’s a best practice. In this guide, you’ll learn how to:

• Create and activate a Python virtual environment

• Install dependencies safely (without touching global Python)

• Load an OpenAI API key using .env

• Build a simple OpenAI client

• Upgrade the script to accept user input instead of a hardcoded prompt

This tutorial is beginner-friendly and works on Windows, macOS, and Linux.

Why You Should Always Use a Python Virtual Environment

A virtual environment allows you to:

• Isolate project dependencies

• Avoid version conflicts

• Reproduce your setup later

• Match professional and enterprise workflows

Each project gets its own Python and packages, separate from the system installation.

Step 1: Create a Project Folder

Open a terminal or PowerShell and navigate to your project directory:

Example (Windows):

Step 2: Create a Virtual Environment

Run the following command inside your project folder.

Windows

macOS / Linux

This creates a venv folder containing an isolated Python runtime.

Step 3: Activate the Virtual Environment

Windows (PowerShell)

If PowerShell blocks the script:

macOS / Linux

When activated, your terminal prompt will show:

This means all installs are now local to this project.

Step 4: Install Required Packages (Inside venv Only)

With the virtual environment active:

Using python -m pip guarantees the packages install into the active venv.

Step 5: Create a .env File for Your API Key

In the project root (same level as your Python file), create a file named .env:

Important notes:

• No quotes

• No spaces

• Never commit this file to Git

Step 6: Python Script with OpenAI Client (User Input Enabled)

Below is a clean, production-safe script that:

• Loads the API key from .env

• Uses object-oriented design

• Prompts the user for input instead of a hardcoded string

<?php

# ===== START CODE BLOCK =====

from openai import OpenAI
from dotenv import load_dotenv
import os

load_dotenv()

def get_api_key() -> str:
    api_key = os.getenv("OPENAI_API_KEY")
    if not api_key:
        raise ValueError("OPENAI_API_KEY environment variable not set")
    return api_key


class LLMClient:
    def __init__(self, api_key: str, model: str = "gpt-4.1-mini"):
        self.client = OpenAI(api_key=api_key)
        self.model = model

    def chat(self, prompt: str) -> str:
        response = self.client.chat.completions.create(
            model=self.model,
            messages=[{"role": "user", "content": prompt}]
        )
        return response.choices[0].message.content



if __name__ == "__main__":
    api_key = get_api_key()
    llm_client = LLMClient(api_key)

    user_prompt = input("Enter your question: ")
    response = llm_client.chat(user_prompt)
    print("LLM Response:", response)
    
# ===== END CODE BLOCK =====