Implementing Code Completion

Welcome to our comprehensive guide on leveraging GPT-3.5 Turbo for automated code completion. In this tutorial, you’ll learn how to:

Build interactive HTML examples
Generate well-documented Python scripts
Produce ANSI-compliant SQL commands for table creation and queries

By following these steps, you can streamline development workflows and improve code quality across multiple languages.

1. Interactive HTML Example

To create a more dynamic HTML demo, we’ll inject JavaScript powered by GPT-3.5 Turbo responses. Here’s an example HTML file that requests code snippets and displays them in a live editor:

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8" />
  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
  <title>GPT-3.5 Turbo Code Preview</title>
  <style>
    body { font-family: Arial, sans-serif; margin: 2rem; }
    #editor { width: 100%; height: 300px; border: 1px solid #ccc; padding: 1rem; }
  </style>
</head>
<body>
  <h1>Auto-Generated Code Snippet</h1>
  <div id="editor">Loading...</div>
  <script>
    async function fetchSnippet() {
      const response = await fetch('/api/generate-code', {
        method: 'POST',
        headers: { 'Content-Type': 'application/json' },
        body: JSON.stringify({ prompt: 'Write a JavaScript function to reverse a string.' })
      });
      const data = await response.json();
      document.getElementById('editor').textContent = data.choices[0].text;
    }

    fetchSnippet();
  </script>
</body>
</html>

2. Generating Python Code with Explanations

Below is a Python script that uses GPT-3.5 Turbo to generate functions with inline comments. This approach ensures your code is both functional and self-documented.

import openai

openai.api_key = 'YOUR_API_KEY'

def generate_python_function(prompt: str) -> str:
    """
    Generate a Python function based on the provided prompt.
    Returns the generated code as a string.
    """
    response = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": prompt}],
        temperature=0.2,
        max_tokens=250
    )
    return response.choices[0].message.content

if __name__ == '__main__':
    prompt_text = "Create a Python function that checks if a number is prime, with comments."
    code = generate_python_function(prompt_text)
    print("Generated Python Code:\n", code)

Be sure to install the OpenAI Python client with pip install openai. Keep your API key secure and never commit it to a public repository.

3. Producing ANSI SQL Commands

For dataset management, GPT-3.5 Turbo can auto-generate ANSI-compliant SQL to create tables, insert data, and run queries. Below is an example prompt and the expected output:

-- Prompt: "Generate SQL to create a users table with id, name, email; insert three records; select all users."

CREATE TABLE users (
  id INT PRIMARY KEY,
  name VARCHAR(100),
  email VARCHAR(100) UNIQUE
);

INSERT INTO users (id, name, email) VALUES
 (1, 'Alice Smith', 'alice@example.com'),
 (2, 'Bob Johnson', 'bob@example.com'),
 (3, 'Carol White', 'carol@example.com');

SELECT * FROM users;

Always review generated SQL before executing it against production databases to avoid unintended data loss.

Introduction

What is Generative AI

Getting Started with OpenAI

Exploring ChatGPT

Understanding Prompt Engineering

Understanding Tokens and API Parameters

Implementing Word Completion