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  • License MIT

Tiny OpenAI API wrapper

Package Exports

  • openai
  • openai/dist/index.js

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (openai) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

Build Status npm License: MIT

OpenAI

A tiny async production-ready wrapper for OpenAI GPT-3 API.

This is an unofficial library and has no affiliations with OpenAI

Installation

Via npm

npm install openai

Via yarn

yarn add openai

Usage

Initialize OpenAI

import { OpenAI } from 'openai';
// or the commonJS way:
const { OpenAI } = require('openai');

// new OpenAI(apikey: string, organization?: string, version?: string)
const openai = new OpenAI(process.env.API_KEY, 'my-organization');

Engine

Get all engines:

const engines = await openai.getEngines();

Get specific engine:

const engine = await openai.getEngine('curie');

Completion

Make a completion:

const completion = await openai.complete('curie', {
    prompt: 'Q: Hello\nA:',
    user: 'user-123'
});

The options argument(2nd) properties follow the exactly same names as shown on official docs.

Make a completion from a fine-tuned model:

const completion = await openai.completeFromModel('FINE_TUNED_MODEL', {
    prompt: 'Q: Hello\nA:'
});

Make a completion and stream the response:

const stream = await openai.completeAndStream('curie', { // or completeFromModelAndStream
    prompt: 'Q: Hello\nA:',
    user: 'user-123'
});

stream.pipe(response)

Make a content filter:

const isSafe = (await openai.contentFilter('hi I am cool')) === 0;

Make a search:

const search = await openai.search('curie', {
    query: 'the president',
    documents: [
        'whitehouse',
        'school',
        'hospital'
    ]
});

The options argument(2nd) properties follow the exactly same names as shown on official docs.

Classification

Classify a document:

const classification = await openai.classify({
    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'
});

The argument properties follow the exactly same names as shown on official docs.

Answer

Answer a question:

const answer = await openai.answer({
    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.']],
});

The argument properties follow the exactly same names as shown on official docs.

File

Get all files:

const files = await openai.getFiles();

Upload a single file:

const result = await openai.uploadFile('filename.json', await fs.readFileSync('somefile.json'), 'fine-tune');

Get a single file by id:

const file = await openai.getFile('file-29u89djwq');

Delete a single file by id:

await openai.deleteFile('file-29u89djwq');

Fine-tuning

Fine-tune from a file:

const result = await openai.finetune({
    training_file: 'file-29u89djwq'
});

The argument properties follow the exactly same names as shown on official docs.

Get all fine-tunes:

const finetunes = await openai.getFinetunes();

Get a specific fine-tune:

const finetune = await openai.getFinetune('ftjob-AF1WoRqd3aJ');

Cancel a fine-tune:

await openai.cancelFinetune('ftjob-AF1WoRqd3aJ');

Get fine-tune events of a fine-tune:

const events = await openai.getFinetuneEvents('ftjob-AF1WoRqd3aJ');