This example uses the OpenAI API to perform two common tasks: generating code from a description and creating documentation for an existing function.

# Requires: pip install openai python-dotenv

from openai import OpenAI
import os
from dotenv import load_dotenv

load_dotenv()
openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

# TASK 1: Generate a function from a description
def generate_function(description):
    prompt = f"""
    Write a Python function based on the following description.
    Provide only the code, no explanation.

    Description: {description}
    """

    response = openai_client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": prompt}],
        temperature=0.1  # Low temperature for more deterministic code
    )
    return response.choices[0].message.content

# TASK 2: Document an existing function
def document_function(code_snippet):
    prompt = f"""
    Write a professional docstring for the following Python function.
    Use the Google style format, including Args and Returns sections.

    Code:
    {code_snippet}
    """

    response = openai_client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": prompt}]
    )
    return response.choices[0].message.content

# --- Example Usage ---
# 1. Generate Code
description = "A function that connects to a PostgreSQL database using psycopg2 and fetches the top 10 users from a 'users' table."
new_code = generate_function(description)
print("*** Generated Function ***")
print(new_code)

# 2. Document Code
existing_code = """
def calculate_metrics(data):
    if not data:
        return None
    total = sum(data)
    count = len(data)
    average = total / count
    variance = sum((x - average) ** 2 for x in data) / count
    return {'mean': average, 'std_dev': variance ** 0.5}
"""
new_docstring = document_function(existing_code)
print("n*** Generated Documentation ***")
print(new_docstring)