Getting Started with ChatGPT: A Guide to Building AI-Powered Chatbots published 2/19/2023 | 6 min read

Have you heard about ChatGPT, the state-of-the-art natural language processing model that can be used to generate text for a wide range of applications? In this post, we'll show you how to get started using ChatGPT programatically in Node.js with TypeScript, and explore the many benefits of integrating ChatGPT into your projects.

Introduction

ChatGPT is a powerful natural language processing model that has been trained on a massive corpus of text data. With its advanced language generation capabilities, it can be used for a wide range of applications, including chatbots, virtual assistants, and content generation. In this post, we'll show you how to get started using ChatGPT programatically in Node.js with TypeScript, and explore the many benefits of integrating ChatGPT into your projects.

Getting Started

To get started with using ChatGPT programatically in Node.js with TypeScript, you'll need to install the "@openai/api" package from npm. This package provides a convenient wrapper around the OpenAI API, which allows you to interface with ChatGPT and use it to generate text.

To install the package, simply run the following command in your terminal:

  
npm install openai

Once you've installed the package, you'll need to sign up for an API key from OpenAI. You can do this by creating an account on their website and generating an API key.

With your API key in hand, you can now start using ChatGPT programatically in your Node.js project. Here's an example TypeScript code snippet that shows you how to generate text using ChatGPT:

  
import { Configuration, OpenAIApi } from 'openai';

const configuration = new Configuration({
  apiKey: 'YOUR_OPEN_AI_KEY',
});

const openai = new OpenAIApi(configuration);

const generateText = async (prompt: string): Promise<string> => {
  const response = await openai.createCompletion({
    model: 'text-davinci-003',
    prompt,
  }, { apiKey: openaiApiKey });

  return response.data.choices[0].text;
};

const main = async () => {
  const prompt = 'The quick brown fox jumps over the lazy dog';
  const generatedText = await generateText(prompt);
  console.log(generatedText);
};

main();

In this code snippet, we're importing the "openai" package and setting up our API key. We're also defining a function called "generateText" that takes a prompt as input and returns a Promise that resolves to the generated text. The function uses the "openai.Completion.create" method to generate text using the ChatGPT model.

OpenAI provides several pre-trained models for its completion API, each with different capabilities and characteristics. Here are brief descriptions of the models and their differences:

text-davinci-003: Most capable GPT-3 model. Can do any task the other models can do, often with higher quality, longer output and better instruction-following. Also supports inserting completions within text.
Good at: Complex intent, cause and effect, summarization for audience
text-curie-001: This model is less powerful than davinci, but still very capable. It's ideal for tasks like chatbots, question answering, and language translation.
Good at: Language translation, complex classification, text sentiment, summarization
text-babbage-001: This is a smaller and less powerful model, but it's faster and less expensive than the other three models. It's good for simple language tasks like autocomplete and text correction.
Good at: Moderate classification, semantic search classification
text-ada-001: Capable of very simple tasks, usually the fastest model in the GPT-3 series, and lowest cost.
Good at: Parsing text, simple classification, address correction, keywords

Each model has its own strengths and weaknesses, and the best model to use depends on the specific task at hand.

Benefits of Using ChatGPT

There are many benefits to using ChatGPT in your Node.js projects. Here are just a few:

Advanced language generation capabilities: ChatGPT is one of the most advanced natural language processing models available, and can be used to generate text that is virtually indistinguishable from human-written text.
Wide range of applications: ChatGPT can be used for a wide range of applications, including chatbots, virtual assistants, content generation, and more.
Improved user experience: By integrating ChatGPT into your projects, you can provide a more personalized and engaging user experience for your users.

Limitations and Considerations

While ChatGPT is a powerful tool, there are some limitations and considerations to keep in mind when using it in your projects. Here are a few:

Limited control over output: While ChatGPT API allows for some control over the length and tone of responses, it is still limited in terms of the overall output. This means that it may not always be possible to get the exact response you want.
Limited understanding of context: ChatGPT API is trained on a large amount of data and can generate responses based on that data, but it does not have a complete understanding of context. This means that sometimes the responses generated by ChatGPT API can be off-topic or irrelevant.
High cost: Depending on the level of usage and customization required, using ChatGPT API can be quite expensive.
Privacy concerns: As with any tool that uses AI and machine learning, there are privacy concerns to keep in mind. The data provided to ChatGPT API could be used to train models that are later used for other purposes.

Pricing

Multiple models, each with different capabilities and price points. Ada is the fastest model, while Davinci is the most powerful. Prices are per 1,000 tokens. You can think of tokens as pieces of words, where 1,000 tokens is about 750 words.

You can think of tokens as pieces of words used for natural language processing. For English text, 1 token is approximately 4 characters or 0.75 words. As a point of reference, the collected works of Shakespeare are about 900,000 words or 1.2M tokens.

Try this Tokenizer tool to get a feeling of the token system.

Below are the prices as per this month: February 2023

Davinci (Most powerful): $0.0200 per 1000 tokens
Curie: $0.0020 per 1000 tokens
Babbage: $0.0005 per 1000 tokens
Ada (Fastest): $0.0004 per 1000 tokens