Installation
You can install the package via composer:
composer require orhanerday/open-ai
use Orhanerday\OpenAi\OpenAi;
// Load your key from an environment variable
$open_ai = new OpenAi(env('OPEN_AI_API_KEY'));
/**Completions
* Given a prompt, the model will return one or more predicted completions,
* and can also return the probabilities of alternative tokens at each position.
* */
$complete = $open_ai->complete([
'engine' => 'davinci',
'prompt' => "Hello",
'temperature' => 0.9,
"max_tokens" => 150,
"frequency_penalty" => 0,
"presence_penalty" => 0.6,
]);
/** Searches
*
* Given a query and a set of documents or labels,
* the model ranks each document based on its semantic
* similarity to the provided query.
* */
$search = $open_ai->search([
'engine' => 'ada',
'documents' => ["White House", "hospital", "school"],
'query' => "the president",
]);
/** Answers
*
* Given a question, a set of documents, and some examples,
* the API generates an answer to the question based on the information in the set of documents.
* This is useful for question-answering applications on sources of truth,
* like company documentation or a knowledge base.
* */
$answer = $open_ai->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."]],
"max_tokens" => 5,
"stop" => ["\n", "<|endoftext|>"],
]);
/** Classifications
*
* Given a query and a set of labeled examples,
* the model will predict the most likely label for the query.
* Useful as a drop-in replacement for any ML classification or text-to-label task.
* */
$classification = $open_ai->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",
]);
/** List engines
*
* Lists the currently available engines,
* and provides basic information about each one such as the owner and availability.
*/
$engines = $open_ai->engines();
/** Retrieve engine
*
* Retrieves an engine instance,
* providing basic information about the engine such as the owner and availability.
*/
$engine = $open_ai->engine('davinci');
// this will print $search
echo $search;
Download Details:
Author: orhanerday
Source Code: https://github.com/orhanerday/open-ai
License: MIT