import { gptPromptKitFactory } from '../src/index';

const gptPromptKit = gptPromptKitFactory('Your API key');

const formatFree = gptPromptKit.formatFree(`
    Tilte: <Title>
    ## Abstract ##
    <Text of abstract>
    ## Sections ##
    <Numbered list of 10 top-level sections>
    ## Content ##
    <Text of entire arXiv pre-print in LaTeX notation>
`);

const description =
  'Generate an arXiv pre-print which the title is: What is GPT-3.';

formatFree(description).then(console.log);

/** 
 * ```Title: What is GPT-3.

## Abstract ##
In recent years, the field of natural language processing (NLP) has seen a significant breakthrough with the development of large-scale language models such as GPT-3. This paper aims to provide a comprehensive understanding of what GPT-3 is, how it works, and its potential applications. We discuss the technical details of GPT-3, including its architecture, training data, and inference process. Additionally, we highlight some of the limitations and ethical concerns associated with this technology. 

## Sections ##
1. Introduction
2. Background on NLP
3. Overview of GPT-3
4. Architecture of GPT-3
5. Training data for GPT-3
6. Inference process of GPT-3
7. Applications of GPT-3
8. Limitations of GPT-3
9. Ethical concerns with GPT-3
10. Conclusion

## Content ##

\section{Introduction}
In recent years, there has been a significant breakthrough in the field of natural language processing (NLP) with the development of large-scale language models such as GPT-3. GPT-3, which stands for Generative Pre-trained Transformer 3, is a state-of-the-art language model developed by OpenAI. It is capable of generating human-like text, completing sentences, and answering questions with a high degree of accuracy.

\section{Background on NLP}
NLP is a subfield of artificial intelligence (AI) that focuses on the interaction between computers and human language. It involves the development of algorithms and models that can understand, interpret, and generate human language. NLP has numerous applications, including machine translation, sentiment analysis, and chatbots.

\section{Overview of GPT-3}
GPT-3 is a language model that uses deep learning techniques to generate human-like text. It is a neural network that has been pre-trained on a massive amount of text data, allowing it to generate coherent and contextually appropriate text. GPT-3 is the largest and most powerful language model developed to date, with over 175 billion parameters.

\section{Architecture of GPT-3}
GPT-3 uses a transformer architecture, which is a type of neural network that is specifically designed for NLP tasks. The transformer architecture consists of an encoder and a decoder. The encoder processes the input text and creates a representation of the text, while the decoder generates the output text based on the representation created by the encoder.

\section{Training data for GPT-3}
GPT-3 was trained on a massive amount of text data, including books, articles, and websites. The training data was sourced from a variety of domains, including science, literature, and social media. The large amount of training data allows GPT-3 to generate text that is contextually appropriate and coherent.

\section{Inference process of GPT-3}
The inference process of GPT-3 involves feeding the model with a prompt, which is a piece of text that provides context for the generated text. The model uses the prompt to generate text that is contextually appropriate and coherent. GPT-3 can generate text in a variety of formats, including prose, poetry, and code.

\section{Applications of GPT-3}
GPT-3 has numerous applications, including content creation, chatbots, and language translation. It can be used to generate high-quality content for websites, social media, and marketing campaigns. GPT-3 can also be used to create chatbots that can interact with users in a natural and human-like way. Additionally, GPT-3 can be used for language translation, allowing users to translate text from one language to another with a high degree of accuracy.

\section{Limitations of GPT-3}
Despite its impressive capabilities, GPT-3 has some limitations. One of the main limitations is its inability to understand context beyond the prompt. This means that GPT-3 may generate text that is inappropriate or offensive if the prompt is not carefully crafted. Additionally, GPT-3 may generate text that is biased or discriminatory if the training data is biased.

\section{Ethical concerns with GPT-3}
GPT-3 raises several ethical concerns, including the potential for misuse and the impact on employment. GPT-3 can be used to generate fake news, propaganda, and malicious content, which can have a significant impact on society. Additionally, GPT-3 has the potential to automate many jobs that require human language skills, which could lead to widespread unemployment.

\section{Conclusion}
In conclusion, GPT-3 is a state-of-the-art language model that has the potential to revolutionize the field of NLP. It is capable of generating human-like text, completing sentences, and answering questions with a high degree of accuracy. However, it also raises several ethical concerns, and its limitations must be carefully considered. As NLP continues to evolve, it is essential to ensure that these technologies are developed and used in a responsible and ethical manner.```
*/