Mastering Generative AI with OpenAI

Implementing Code Completion

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)

Note

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', '[email protected]'),
 (2, 'Bob Johnson', '[email protected]'),
 (3, 'Carol White', '[email protected]');

SELECT * FROM users;

Warning

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

References

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