Welcome back! In the previous lesson, you learned how to send a simple message to OpenAI's language model and receive a response using PHP. Now, we will take a step further by exploring model parameters that allow you to customize the AI's responses. These parameters are crucial for tailoring the chatbot's behavior to meet specific needs. In this lesson, we will focus on four key parameters: max_tokens, temperature, presence_penalty, and frequency_penalty. Understanding these parameters will enable you to control the creativity, length, and content of the AI's responses, enhancing your chatbot's functionality.

The max_tokens parameter sets a hard limit on the number of tokens the AI can generate in its response. A "token" can be a whole word or just part of a word. For example, "chatbot" might be one token, while "hello" could be split into two tokens: "hel" and "lo." It’s important to note that token counts vary across different models, words, and languages — so the same text might have a different token count depending on these factors.

When you set max_tokens, you specify the maximum number of tokens the AI can produce. This is a strict limit, meaning the model will stop generating text once it reaches this count, even if it results in an incomplete sentence or word.

Here’s an example where we set max_tokens to 100:

php
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1<?php
2require 'vendor/autoload.php';
3
4// Fetch API Key
5$apiKey = $_ENV['OPENAI_API_KEY'] ?? getenv('OPENAI_API_KEY');
6$baseUrl = $_ENV['OPENAI_BASE_URI'] ?? getenv('OPENAI_BASE_URI');
7
8$client = \OpenAI::factory()
9    ->withApiKey($apiKey)
10    ->withBaseUri($baseUrl)
11    ->make();
12
13// Define a simple user message to test the API
14$prompt = "Describe a sunset over the ocean";
15
16// Get response with specific parameters
17$response = $client->chat()->create([
18    'model' => 'gpt-4',
19    'messages' => [['role' => 'user', 'content' => $prompt]],
20    'max_tokens' => 100
21]);
22
23// Process the response
24$reply = trim($response['choices'][0]['message']['content']);
25echo "Assistant: $reply\n";
26?>

By setting max_tokens to 100, you cap the AI’s response at 100 tokens, which may result in abrupt cut-offs if the model hasn't finished its thought. This parameter helps you control response length, making it useful for avoiding verbose answers and reducing the cost of API requests.

Note: API usage costs money. Each request consumes both input tokens (from the user's message) and output tokens (generated by the AI). Setting max_tokens helps control response length and manage costs.
If the AI's response gets cut off due to reaching the max_tokens limit, you can check response['choices'][0]['finish_reason']. If it returns 'length', the response was truncated, and you might need to adjust max_tokens accordingly.

The temperature parameter is a fascinating aspect of AI interaction. It controls the randomness or creativity of the AI's responses. A lower temperature value, such as 0.2, makes the AI's output more deterministic and focused, often resulting in more predictable responses. Conversely, a higher temperature value, like 0.8, encourages the AI to generate more diverse and creative responses, which can be useful for tasks requiring imaginative outputs.

For example, consider the following code snippet where we set the temperature to 0.7:

php
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1<?php
2// Get response with specific parameters
3$response = $client->chat()->create([
4    'model' => 'gpt-4',
5    'messages' => [['role' => 'user', 'content' => $prompt]],
6    'temperature' => 0.7
7]);
8
9// Process the response
10$reply = trim($response['choices'][0]['message']['content']);
11echo "Assistant: $reply\n";
12?>

With a temperature of 0.7, the AI is likely to provide a response that balances creativity and coherence. Experimenting with different temperature values will help you find the right balance for your specific use case.

The presence_penalty parameter is a powerful tool for encouraging the AI to introduce new topics in its responses. It works by penalizing the AI for using words that have already appeared in the conversation, thus promoting diversity in the dialogue. A low presence_penalty value, such as 0.0, means the AI is less discouraged from repeating words, leading to more focused responses. In contrast, a high presence_penalty value, like 1.0, strongly encourages the AI to explore new topics, resulting in more varied and diverse responses.

Consider the following code where we set the presence_penalty to 0.6:

php
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1<?php
2// Get response with specific parameters
3$response = $client->chat()->create([
4    'model' => 'gpt-4',
5    'messages' => [['role' => 'user', 'content' => $prompt]],
6    'presence_penalty' => 0.6
7]);
8
9// Process the response
10$reply = trim($response['choices'][0]['message']['content']);
11echo "Assistant: $reply\n";
12?>

With a presence_penalty of 0.6, the AI is more likely to explore new topics and provide varied responses. This can be particularly useful in scenarios where you want to keep the conversation fresh and engaging.

The frequency_penalty parameter helps reduce repetition in the AI's responses by penalizing the AI for using the same words or phrases multiple times within its response. This encourages more varied and interesting outputs. A low frequency_penalty value, such as 0.0, allows for more repetition, which can be useful for maintaining focus on a specific topic. Conversely, a high frequency_penalty value, like 1.0, discourages repetition, promoting a more dynamic and varied dialogue.

While presence_penalty encourages the AI to introduce new topics by penalizing the use of words that have already appeared in the conversation, frequency_penalty focuses on reducing repetition by penalizing the AI for using the same words or phrases multiple times within its response. This distinction allows you to manage both the diversity of topics and the variety of language in the AI's outputs.

In the following example, we set the frequency_penalty to 0.3:

php
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1<?php
2// Get response with specific parameters
3$response = $client->chat()->create([
4    'model' => 'gpt-4',
5    'messages' => [['role' => 'user', 'content' => $prompt]],
6    'frequency_penalty' => 0.3
7]);
8
9// Process the response
10$reply = trim($response['choices'][0]['message']['content']);
11echo "Assistant: $reply\n";
12?>

By applying a frequency_penalty of 0.3, you can minimize repetitive content in the AI's responses, making the conversation more dynamic and engaging. This parameter is particularly useful when you want to maintain a lively and varied dialogue.

Let's bring it all together with a complete code example that incorporates all the parameters we've discussed:

php
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1<?php
2require 'vendor/autoload.php';
3
4// Fetch API Key
5$apiKey = $_ENV['OPENAI_API_KEY'] ?? getenv('OPENAI_API_KEY');
6$baseUrl = $_ENV['OPENAI_BASE_URI'] ?? getenv('OPENAI_BASE_URI');
7
8$client = \OpenAI::factory()
9    ->withApiKey($apiKey)
10    ->withBaseUri($baseUrl)
11    ->make();
12
13// Define a simple user message to test the API
14$prompt = "Describe a sunset over the ocean";
15
16// Get response with specific parameters
17$response = $client->chat()->create([
18    'model' => 'gpt-4',
19    'messages' => [['role' => 'user', 'content' => $prompt]],
20    'temperature' => 0.7,  // Controls response creativity
21    'max_tokens' => 100,   // Limits response length
22    'presence_penalty' => 0.6,  // Encourages new topics
23    'frequency_penalty' => 0.3  // Reduces repetition
24]);
25
26// Process the response
27$reply = trim($response['choices'][0]['message']['content']);
28echo "Assistant: $reply\n";
29?>

In this example, we use all four parameters to customize the AI's response. By adjusting these parameters, you can fine-tune the chatbot's behavior to meet your specific requirements. When you run this code, you should see a response that reflects the balance of creativity, length, and content diversity that you've set.

In this lesson, we explored how to use model parameters to customize AI responses. You learned about the temperature, max_tokens, presence_penalty, and frequency_penalty parameters and saw how they can be applied in code. These tools allow you to control the creativity, length, and content of the AI's responses, enhancing your chatbot's functionality.

As you move on to the practice exercises, I encourage you to experiment with different parameter settings to see their effects firsthand. This hands-on practice will reinforce what you've learned and prepare you for the next unit, where we'll delve deeper into managing conversation history and message types. Keep up the great work, and enjoy the journey of creating your chatbot with OpenAI!