SECRET_KEY

Learn to integrate the OpenAI API with JavaScript and React for NLP tasks like text generation, classification, moderation, and embeddings in dynamic apps.

Using OpenAI API for Natural Language Processing in JavaScript.png

nodi.tar.gz

openai js

react-app

This course will teach you how to use the OpenAI API for natural language processing (NLP) in JavaScript, specifically focusing on the powerful GPT-3 models. You’ll begin by getting familiar with the registration process and OpenAI API overview, laying the foundation for deeper exploration into text generation and manipulation tasks.

Next, you’ll explore the core API functionality, including the completions endpoint, which performs various NLP tasks, such as text classification, transformation, and completing incomplete content. You’ll also gain hands-on experience using the moderation endpoint for content safety and embeddings for advanced text analysis.

Finally, you’ll develop your skills by integrating the OpenAI API into React, creating dynamic and interactive web applications. After completing this course, you’ll have the practical knowledge to build AI-driven applications to generate, analyze, and safely manage text-based data in real-world projects.

Using OpenAI API for Natural Language Processing in JavaScript

# Overview
The chat completions endpoint has the ability to translate from one language to another language, summarize the text, and convert the text to emojis or vice versa.




# Translation
The OpenAI API can translate from one language to another language.

Let's see how to provide the prompt to translate from English to other languages.

```text
Translate this into 1. French, 2. Spanish and 3. Japanese.

We provide an online learning platform made by developers, created for developers.
```

## Example

Let's try the above example in the code widget below:

// Define endpoint URL here
const endpointUrl = "https://api.openai.com/v1/chat/completions";

// Define Header Parameters here
const headerParameters = {
  "Authorization": "Bearer {{SECRET_KEY}}",
  "Content-Type": "application/json"
};

// Body Parameters
const bodyParameters = JSON.stringify({
  model: "gpt-3.5-turbo",
  messages: [{role:"system",content:"Translate this into 1. French, 2. Spanish and 3. Japanese."},
  {role:"user",content:"We provide an online learning platform made by developers, created for developers."}],
  temperature: 0,
  max_tokens: 100
});

// Setting API call options
const options = {
  method: "POST",
  headers: headerParameters,
  body: bodyParameters
};

// Function to make API call
async function translate() {
  try {
    const response = await fetch(`${endpointUrl}`, options);

    // Printing response
    printResponse(response);
  } catch (error) {
    // Printing error message
    printError(error);
  }
}

// Calling function to make API call
translate();

In the code above, `temperature` is set to `0` because we don’t need randomness in the translation and the value of the `max_tokens` is set to `100` because we know the approximate length of output tokens. All other parameter values are the default values.

Similarly, we can design a prompt to translate it back into English:
```text
Translate the following into the English language:

1. Nous fournissons une plateforme d'apprentissage en ligne créée par des développeurs, pour des développeurs.
2. Proporcionamos una plataforma de aprendizaje en línea creada por desarrolladores, para desarrolladores.
3. 開発者のために
```

Learn how to translate and summarize text and convert it to emojis using chat completions and its practical use cases.

Introduction

The Completions Endpoint

Miscellaneous Endpoints

APIs Integration in React

Conclusion

Appendix

Build a Writing Assistant Tool with Next.js and OpenAI

Transformation