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How to Use OpenAI API in JavaScript (Step-by-Step Guide)

#webdev #programming #javascript #beginners

Integrating OpenAI's powerful AI models into your JavaScript applications can enhance functionality with features like text generation, summarization, and code assistance. This guide walks you through the process step by step, from setup to making your first API request.

If you're looking to strengthen your JavaScript skills further, consider exploring the eBook JavaScript is Not Hard, which provides a structured approach to mastering JavaScript fundamentals.

Prerequisites

Before getting started, ensure you have:

  • A basic understanding of JavaScript (ES6+)
  • Node.js installed (for backend implementations)
  • An OpenAI API key

Step 1: Install the OpenAI Package

For Node.js applications, install the official openai package:

npm install openai
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For browser-based implementations, use a CDN:

<script src="https://cdn.jsdelivr.net/npm/openai@4.0.0/dist/openai.min.js"></script>
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Step 2: Set Up the OpenAI Client

Initialize the OpenAI client with your API key.

Node.js Example 

import OpenAI from 'openai';

const openai = new OpenAI({
  apiKey: 'your-api-key-here', // Securely store this (avoid hardcoding)
});
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Browser Example 

const openai = new window.OpenAI({
  apiKey: 'your-api-key-here',
});
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Security Note: Never expose your API key in client-side code. For production, use a backend service to handle requests.

Step 3: Make Your First API Request

Let’s generate text using the gpt-3.5-turbo model.

async function generateText() {
  try {
    const response = await openai.chat.completions.create({
      model: 'gpt-3.5-turbo',
      messages: [
        { role: 'system', content: 'You are a helpful assistant.' },
        { role: 'user', content: 'Explain JavaScript closures in simple terms.' },
      ],
    });

    console.log(response.choices[0].message.content);
  } catch (error) {
    console.error('Error calling OpenAI API:', error);
  }
}

generateText();
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Expected Output:

A clear explanation of JavaScript closures in plain language.

Step 4: Handle Different Use Cases

The OpenAI API supports various tasks. Here are a few examples:

Text Summarization 

const response = await openai.chat.completions.create({
  model: 'gpt-3.5-turbo',
  messages: [
    { role: 'user', content: 'Summarize this in one sentence: ' + longText },
  ],
});
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Code Generation 

const response = await openai.chat.completions.create({
  model: 'gpt-3.5-turbo',
  messages: [
    { role: 'user', content: 'Write a JavaScript function to reverse a string.' },
  ],
});
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Best Practices

  1. Secure Your API Key – Use environment variables (process.env.OPENAI_API_KEY) or a backend proxy.
  2. Rate Limiting – Handle API errors gracefully (retry logic, fallbacks).
  3. Optimize Costs – Use max_tokens to limit response length.

Further Learning

For a deeper dive into JavaScript, the eBook JavaScript is Not Hard offers practical examples and exercises to solidify your understanding.

Conclusion

Integrating the OpenAI API into JavaScript applications unlocks powerful AI capabilities with minimal setup. By following this guide, you can start building intelligent features like chatbots, automated content generation, and more.

Experiment with different models (gpt-4, dall-e) and explore the OpenAI documentation for advanced use cases.

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