const OpenAI = require('openai-api');

// Load your key from an environment variable or secret management service
// (do not include your key directly in your code)
const OPENAI_API_KEY = process.env.OPENAI_API_KEY;

const openai = new OpenAI(OPENAI_API_KEY);

(async () => {
    const gptResponse = await openai.complete({
        engine: 'davinci',
        prompt: 'this is a test',
        maxTokens: 5,
        temperature: 0.9,
        topP: 1,
        presencePenalty: 0,
        frequencyPenalty: 0,
        bestOf: 1,
        n: 1,
        stream: false,
        stop: ['\n', "testing"]
    });

    console.log(gptResponse.data);
})();

{
    id: 'some-long-id',
    object: 'text_completion',
    created: 1616791508,
    model: 'davinci:2020-05-03',
    choices: [
        {
          text: " predicted text...",
          index: 0,
          logprobs: null,
          finish_reason: 'length'
        }
    ]
}

(async () => {
    const gptResponse = await openai.search({
        engine: 'davinci',
        documents: ["White House", "hospital", "school"],
        query: "the president"
    });

    console.log(gptResponse.data);
})();

(async () => {
    const gptResponse = await openai.answers({
      "documents": ["Puppy A is happy.", "Puppy B is sad."],
      "question": "which puppy is happy?",
      "search_model": "ada",
      "model": "curie",
      "examples_context": "In 2017, U.S. life expectancy was 78.6 years.",
      "examples": [["What is human life expectancy in the United States?", "78 years."]],
      "max_tokens": 5,
      "stop": ["\n", "<|endoftext|>"],
    });

    console.log(gptResponse.data);
})();

(async () => {
  const gptResponse = await openai.classification({
    "examples": [
      ["A happy moment", "Positive"],
      ["I am sad.", "Negative"],
      ["I am feeling awesome", "Positive"]
    ],
    "labels": ["Positive", "Negative", "Neutral"],
    "query": "It is a raining day :(",
    "search_model": "ada",
    "model": "curie"
  });

  console.log(gptResponse.data);
})();

(async () => {
    const gptResponse = await openai.engines();

    console.log(gptResponse.data);
})();

(async () => {
  const gptResponse = await openai.embeddings({
    "engine": "text-similarity-babbage-001",
    "input": [
      "A happy moment",
      "I am sad.",
      "I am feeling awesome"
    ],
  });

  console.log(gptResponse.data); // see index.d.ts interface Embedding
})();

openai.encode('This is an encoding test. Number of tokens is not necessarily the same as word count.').then((result) => {
     console.log("Number of tokens for string:" + result.length);
 });