ChatGPT JavaScript: Complete Guide with 20 Examples

Why use ChatGPT for JavaScript development?

If you write JavaScript, adding ChatGPT to your workflow can save time on boilerplate, debugging, and idea generation. Using chatgpt javascript lets you ask for component scaffolding, unit tests, or explanations in plain English. ChatGPT is particularly useful when you need quick examples, alternate implementations, or simple refactors. Treat it like a helpful pair programmer: give context, show failing code, and ask for small, testable changes.

I once had a late-night bug that looked like it would take an hour to fix, I asked ChatGPT for a quick refactor and it shaved that hour down to ten minutes. True story: it won't replace a senior dev, but it will stop you from Googling the same error message five times in a row.

For absolute beginners who need setup and safety tips, start with the beginner walkthrough in the ChatGPT programming beginner to get comfortable with accounts, prompts, and simple examples.

Tip: good prompts say the goal, the environment (Node, browser, React), any constraints, and sample input or error messages. For platform-level guidance on crafting prompts and avoiding unsafe requests, refer to the Best Practices for Prompt Engineering with the OpenAI API article which explains how to avoid asking for sensitive personal data and how to format examples for the model.

Setup: API keys, SDKs, and quick project templates

Before asking ChatGPT to generate code, set up a safe environment: store your API key in an environment variable, add the OpenAI SDK or use fetch, and create a minimal project folder with package.json and a test runner. Use short, copyable snippets when you first test the API so you can iterate quickly.

• Prerequisites:
  • Node 18+ or modern browser
  • An OpenAI API key saved as OPENAI_API_KEY
  • A code editor and terminal

Here is a tiny Node fetch example to call the Chat Completions endpoint. Copy and run after setting your env var.

// Node (simple fetch example)
import fetch from 'node-fetch';
const API_KEY = process.env.OPENAI_API_KEY;

async function ask(prompt) {
  const res = await fetch('https://api.openai.com/v1/chat/completions', {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      'Authorization': `Bearer ${API_KEY}`,
    },
    body: JSON.stringify({
      model: 'gpt-4o-mini',
      messages: [{ role: 'user', content: prompt }],
      max_tokens: 400,
    }),
  });
  return (await res.json()).choices[0].message.content;
}

ask('Write a short ES module that converts miles to kilometers.').then(console.log);

For a step-by-step ChatGPT coding workflow and practical examples, see the detailed ChatGPT coding guide. Also, for examples of how to format chat model inputs and the chat-style messages pattern, check out the Cookbook example on How to format inputs to ChatGPT models.

20 Code Examples, Part 1 (1, 10)

Below are short, copyable JavaScript examples you can paste and run. Each snippet shows a prompt pattern you can send to ChatGPT and the minimal code it can produce. Use them as starting points and test carefully, AI code can need tuning.

1) Miles to kilometers (simple function)

// 1
export const milesToKm = (miles) => miles * 1.60934;

2) Readable API call wrapper (fetch)

// 2
export async function chatComplete(prompt) {
  const res = await fetch('/api/chat', { method: 'POST', body: JSON.stringify({ prompt }) });
  return res.json();
}

3) Small CLI prompt (Node)

// 3
import readline from 'readline/promises';
const rl = readline.createInterface({ input: process.stdin, output: process.stdout });
const q = await rl.question('Describe what you want: ');
console.log('You asked:', q);
rl.close();

4) Simple React stateless component generator

// 4
export default function Hello({ name = 'world' }) {
  return <div>Hello, {name}!</div>;
}

5) Express route that uses a chat helper

// 5
import express from 'express';
const app = express();
app.use(express.json());
app.post('/explain', async (req, res) => {
  const { code } = req.body;
  const explanation = await ask('Explain this code: ' + code);
  res.json({ explanation });
});

6) Regex generator for YYYY-MM-DD dates

// 6
const dateRegex = /^\d{4}-\d{2}-\d{2}$/;
console.log(dateRegex.test('2025-01-02')); // true

7) Unit test example (Jest)

// 7
import { milesToKm } from './util';
test('converts miles to km', () => expect(milesToKm(1)).toBeCloseTo(1.60934));

8) Commit message generator

// 8
export function makeCommitMessage(changes) { return `feat: ${changes.summary}`; }

9) ESLint autofix prompt (pattern only)

// 9
// Prompt ChatGPT to output a .eslintrc.js using your chosen style rules.

10) Small CSV to JSON mapper

// 10
export function csvToJson(csv) {
  const [h,...rows] = csv.split('\n');
  const headers = h.split(',');
  return rows.map(r => Object.fromEntries(r.split(',').map((v,i) => [headers[i], v])));
}

For more ready-to-use snippets you can adapt, browse the Chat GPT codes collection which complements these examples with direct samples.

20 Code Examples, Part 2 (11, 20)

11) Generate SQL from natural language

// 11
// Send: "Write a SQL query to sum revenue by month for 2024"

12) Simple input validator (email)

// 12
export const isEmail = email => /^\S+@\S+\.\S+$/.test(email);

13) Throttle / debounce helper

// 13
export function debounce(fn, wait) {
  let t;
  return (...a) => { clearTimeout(t); t = setTimeout(() => fn(...a), wait); };
}

14) Translate helper (calls a translate model)

// 14
export async function translate(text, to='es') {
  return ask(`Translate to ${to}: ${text}`);
}

15) Small production-ready logger wrapper

// 15
export const logger = (...args) => console.log(new Date().toISOString(), ...args);

16) Generate a basic chart dataset

// 16
export function monthlyData(items) { return items.map(i => ({ x: i.month, y: i.value })); }

17) Simple OAuth redirect handler (pattern)

// 17
app.get('/auth/callback', (req, res) => {
  const { code } = req.query; // exchange for token server-side
  res.send('OK');
});

18) Automated test-case generator prompt (pattern)

// 18
// Ask ChatGPT: "Create 5 unit tests for this function with edge cases." Paste the function.

19) Commit lint rule generator

// 19
// Prompt: "Suggest commitlint rules for Angular-style commit messages"

20) Generate a tiny accessibility checklist

// 20
export const a11yChecklist = ['use semantic HTML', 'add alt for images', 'ensure color contrast'];

You can use an AI assistant as a code helper to iterate on these snippets while you test locally, learn recommended patterns and workflows in the article about using AI to write code: AI to write code.

Prompts, patterns, and safety: getting reliable results

To get repeatable results, start prompts with a clear role and expected output format. Use system messages to lock style and use examples as input. When you need reproducible behavior for code formatting or error handling, system prompt engineering helps you set constraints and coding style across requests, see the guide on System prompt engineering for ideas on consistent assistant setup.

• Prompt pattern (example):

System: You are an expert JavaScript developer. Use ES modules and modern syntax.
User: Convert the following function to TypeScript and include types. Function: ...

• Best practices:
  • Provide the runtime (Node/browser), frameworks (React/Express), and exact error messages.
  • Ask for tests and small run instructions.
  • Avoid sharing secrets in prompts; never paste API keys or PII.

For prompt templates specialized for coding tasks, see our guide to ChatGPT prompts for coding which shows exact prompt patterns used to create reliable code samples.

If you want to tune the prompt for clarity, follow optimization techniques in Optimize ChatGPT prompts. And when deciding whether to accept AI-produced code without review, remember the trade-offs explained in the article about AI code helper, it describes when to rely on AI-generated code and when to apply stricter manual checks.

Conclusion and next steps

You now have a practical set of 20 JavaScript examples and clear ways to integrate ChatGPT into your workflow. Use chatgpt javascript prompts to scaffold features, generate tests, and debug faster, but always verify and run generated code locally. For deeper, example-driven workflows and more code patterns, the ChatGPT coding guide offers a step-by-step path to make ChatGPT a dependable coding partner.

Try this next: pick one snippet above, paste it into your editor, and ask ChatGPT to add tests and edge cases. Small iterations and specific prompts produce the best results. For extra guidance on message formats and practical API call examples, consult the OpenAI docs and the guide on Six Strategies for Getting Better Results.