openai-node

A library for using the OpenAI GPT-3 API in Node. It tries to resemble OpenAI's provided Python bindings as closely as possible but with the additional asynchronous ways of Node.

I am not affiliated with OpenAI.

All methods require that the api_key is set to something.

organization is optional for your organization ID, but if it's set to something, it'll be included in the header.

Usage

Install

npm i openai-node

Completion

Completion takes the normal GPT-3 parameters. The only one that is actually required in this library is prompt, the rest have the default values shown below.

var openai = require("openai-node");

openai.api_key = "YOUR API KEY"; // required
openai.organization = "YOUR ORGANIZATION ID"; // optional

//Completion
openai.Completion.create({
    engine: "davinci",
    prompt: "Original: She no went to the market.\nStandard American English:",
    temperature: 1,
    max_tokens: 64,
    top_p: 1,
    frequency_penalty: 0,
    presence_penalty: 1,
    n: 1,
    stream: false,
    logprobs: null,
    echo: false,
    best_of: 1,
    stop: null,
}).then((response) => {
    console.log(response);
    //EXAMPLE OUTPUT: She didn't go to the market.
});

Search

Search takes the normal GPT-3 parameters. documents and query must not be empty. Davinci is chosen by default.

var openai = require("openai-node");

openai.api_key = "YOUR API KEY"; // required
openai.organization = "YOUR ORGANIZATION ID"; // optional

//Search
openai
    .Engine("davinci")
    .search({
        documents: ["whitehouse", "school", "hospital"],
        query: "president",
    })
    .then((response) => {
        console.log(response);
    });
/*
OUTPUT:
{
    object: 'list',
    data: [
        { object: 'search_result', document: 0, score: 563.445 },
        { object: 'search_result', document: 1, score: 155.26 },
        { object: 'search_result', document: 2, score: 241.302 }
    ],
    model: 'davinci:2020-05-03'
}*/

Engine List

Engine List returns a list off all the engines GPT-3 has available. (api_key is still required)

openai.Engine.list().then((res) => console.log(res));

Engine Retrieve

Returns engine information. (api_key is still required)

openai.Engine.retrieve("ada").then((res) => console.log(res));
/*
OUTPUT:
{
    id: 'ada',
    object: 'engine',
    created: null,
    max_replicas: null,
    owner: 'openai',
    permissions: null,
    ready: true,
    ready_replicas: null,
    replicas: null
}
*/

File

List

Lists all available files that belong to your organization.

openai.File.list().then((res) => {
    console.log(res);
});

Create

Sends a new file to the endpoint and returns back it's ID for use with Search and Classification. Learn more about files at OpenAI's documention. File must be a .jsonl (JSON Lines).

const fs = require("fs");

openai.File.create({
    purpose: "answers",
    file: fs.createReadStream("./traning.jsonl"),
}).then((res) => {
    console.log(res);
    /* OUTPUT: 
    {
      "id": "file-Twfy8T7YyIZR6jxPpIipbpxh",
      "object": "file",
      "bytes": 140,
      "created_at": 1616240608,
      "filename": "training.jsonl",
      "purpose": "answers"
    }
    */
});

Remove

Removes file from your organization. OpenAI's Python library calls this function delete but that's a reserved word in JS.

openai
    .File("file-Twfy8T7YyIZR6jxPpIipbpxh")
    .remove()
    .then((res) => {
        console.log(res);
    });
/* OUTPUT: 
{
  "id": "file-Twfy8T7YyIZR6jxPpIipbpxh",
  "object": "file",
  "deleted": true
}
*/

Classifications (new)

Creates a new classification request. All parameters match OpenAI's. You can see them here

openai.Classification.create({
    search_model: "ada",
    model: "curie",
    file: "file-XsOVjn4yoY2BRweTtcZB1P1B"
    query: "It is a raining day :(",
    labels: ["Positive", "Negative", "Neutral"],
}).then(res => {
    console.log(res);
})

Answer

Creates a new answer request. All parameters match OpenAI's. You can see them here

openai.Answer.create({
    search_model: "ada",
    mode: "curie",
    question: "which puppy is happy?",
    documents: ["Puppy A is happy.", "Puppy B is sad."],
    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|>"
}).then(res => {
    console.log(res);
})