<?php
// Version: 1.0
// File: class.phpopenaichat.php
// Name: PHP OpenAI API Chat Completions Class
// Description: A php class to use the OpenAI API chat completions to chat with a GPT-3.5 or a GPT-4 model.
// Have a conversation with a GPT-3.5 or GPT-4 model.
// Using: Curl, PHP 8.0
// Author: https://www.phpclasses.org/browse/author/144301.html
// License: BSD License
// Features:
// - Not designed for public/production use. Use at your own risk. If using for public usage, please check the security of input better.
// - Send messages to the model and get a response.
// - Estimate the token count of the messages to send to the model.
// - Set the model to use (gpt-3.5-turbo or gpt-4).
// - Set the max_tokens to use.
// - Set the temperature to use.
// - Set the frequency_penalty to use.
// - Set the presence_penalty to use.
// - Script attempts to estimate the token count of the messages to send to the model, and subtracts from max_tokens.
/*
Detailed description:
This is a class to use the OpenAI API chat completions to chat with a GPT-3.5 or a GPT-4 model.
Have a conversation with a GPT-3.5 or GPT-4 model.
Uses the OpenAI API chat completions to chat with a GPT-3.5 or a GPT-4 model.
*/
/*
Instructions for use:
1. Create an OpenAI account at https://beta.openai.com/
2. Create an API key at https://beta.openai.com/account/api-keys
3. Make a variable to store your API key in, let's say $apiKey
4. Create a new PHPOpenAIChat object, passing in your API key, like this:
$openAIChat = new PHPOpenAIChat($apiKey);
5. Send a message to the model and get a response, like this:
$messages = []; # create a conversation
// set agent
$messages = $openAIChat->set_agent($messages, "You are an assistant cat that can speak english and is named Henry.");
// add prompt to messages conversation
$messages = $openAIChat->add_prompt_to_messages($messages, "What is your name?");
$response = $openAIChat->sendMessage($messages);
print_r($response); # show entire returned array
// print text
echo "<br />response text: " . $openAIChat->get_response_text($response) ."<br />";
6. You can also set the model to use (gpt-3.5-turbo or gpt-4), the max_tokens to use, the temperature to use, the frequency_penalty to use, and the presence_penalty to use.
7. You can also estimate the token count of the messages to send to the model, and subtracts from max_tokens.
8. You should be able to get the text from the response by using $response['choices'][0]['message']['content']
9. You can append the text from the response to the messages to send to the model
10. You can also use the add_prompt_to_messages() function to add a prompt to the current conversation
11. Then you can repeat the cycle again by sending the messages to the model and getting another response.
*/
// TODO: A more pleasant example UI.
// Begin class PHPOpenAIChat
class PHPOpenAIChat {
private $apiKey;
private $apiUrl = "https://api.openai.com/v1/chat/completions";
private $max_tokens = 4096;
public $model = 'gpt-3.5-turbo'; // gpt-3.5-turbo, gpt-4
public $temperature = 1.0;
public $freq_penalty = 0.0;
public $pres_penalty = 0.0;
// constructor: set the api key
public function __construct($apiKey) { $this->apiKey = $apiKey; }
// send a message to the model and get a response
public function sendMessage($messages)
{
// get token size of messages and subtract from max_tokens
$temp_max_tokens = $this->max_tokens - $this->estimate_openai_token_count_messages($messages);
$data =
[
# 'model' => 'gpt-3.5-turbo',
'model' => $this->model,
'messages' => $messages,
'temperature' => $this->temperature,
'max_tokens' => $temp_max_tokens,
'frequency_penalty' => $this->freq_penalty,
'presence_penalty' => $this->pres_penalty,
];
$headers = [ 'Content-Type: application/json', 'Authorization: Bearer ' . $this->apiKey, ];
$ch = curl_init($this->apiUrl);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($data));
curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
$response = curl_exec($ch);
if (curl_errno($ch)) {
throw new Exception(curl_error($ch));
}
curl_close($ch);
return json_decode($response, true);
} // end sendMessage()
// estimate the token count of the messages to send to the model
public function estimate_openai_token_count_messages($messages) {
// count all characters in the messages (characters in both keys and values)
// and divide by 3.5 to get an estimate
// ONLY AN ESTIMATE!
$token_count = 0;
foreach ($messages as $message) {
foreach ($message as $key => $value) {
// add to token count
$token_count += strlen($key);
$token_count += strlen($value);
}
}
return ceil($token_count / 3.2);
} // end estimate_openai_token_count_messages()
// append response to messages ( This is the part that is sent to the model from the model )
public function append_response_to_messages($messages, $string) {
$messages[] = [
"role" => "assistant",
"content" => $string
];
return $messages;
} // end append_response_to_messages()
// add prompt to messages ( This is the part that is sent to the model from the user )
public function add_prompt_to_messages($messages, $prompt) {
$messages[] = [
"role" => "user",
"content" => $prompt
];
return $messages;
} // end add_prompt_to_messages()
/* agent functions */
public function get_agent($messages) {
foreach ($messages as $message) {
if ($message['role'] == 'system') {
return $message['content'];
}
}
return '';
} // end get_agent()
public function set_agent($messages, $agent) {
# first check if role:system exists and then set it to the new agent, otherwise just create the agent
# and prepend it to the messages array
$agent_set = false;
$msg_count = 0;
foreach ($messages as $message) {
if ($message['role'] == 'system') {
$messages[$msg_count]['content'] = $agent;
$agent_set = true;
return $messages;
}
$msg_count++;
}
if (!$agent_set) {
array_unshift($messages, [
"role" => "system",
"content" => $agent
]);
}
return $messages;
} // end set_agent()
/* end agent functions */
/* begin response functions */
public function get_response_text($response) {
if(!isset($response['choices'][0]['message']['content']))
return '';
return $response['choices'][0]['message']['content'];
} // end get_response_text()
/* end response functions */
public function set_model($model) {
$this->model = $model;
} // end set_model()
public function set_temperature($temperature) {
$this->temperature = $temperature;
} // end set_temperature()
public function set_freq_penalty($freq_penalty) {
$this->freq_penalty = $freq_penalty;
} // end set_freq_penalty()
public function set_pres_penalty($pres_penalty) {
$this->pres_penalty = $pres_penalty;
} // end set_pres_penalty()
public function set_max_tokens($max_tokens) {
$this->max_tokens = $max_tokens;
} // end set_max_tokens()
} // end class PHPOpenAIChat
?>
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