Using OpenAI API with MATLAB

Introduction

This tutorial demonstrates how to integrate and use the OpenAI API with MATLAB to leverage advanced AI capabilities in your scripts.

1. Setting Up Your OpenAI API Key

Before starting, make sure you have your OpenAI API key ready. You can obtain it from the OpenAI website after signing up for an account.

2. Sending API Requests

To use the OpenAI API in your MATLAB scripts, you will need to use the `webwrite` function to send HTTP requests and the `jsondecode` function to handle JSON data.

Text Completion

Here’s an example of making a request for text completion:

% MATLAB Script for Text Completion using OpenAI API

api_key = 'YOUR_API_KEY_HERE';
prompt = 'Translate English to French: Hello, how are you?';
model = 'text-davinci-003';
max_tokens = 50;

headers = http_createHeader('Authorization', ['Bearer ' api_key]);
options = weboptions('HeaderFields', headers, 'MediaType', 'application/json');
data = struct('model', model, 'prompt', prompt, 'max_tokens', max_tokens);

response = webwrite('https://api.openai.com/v1/completions', data, options);
result = jsondecode(response);

disp('Output:');
disp(result.choices.text);
                    

This MATLAB script sends a POST request to the OpenAI API for text completion and prints the API response.

Code Generation

Here’s an example of making a request for code generation:

% MATLAB Script for Code Generation using OpenAI API

api_key = 'YOUR_API_KEY_HERE';
prompt = 'Generate Python code to sort an array using bubble sort';
model = 'davinci-codex';
max_tokens = 150;

headers = http_createHeader('Authorization', ['Bearer ' api_key]);
options = weboptions('HeaderFields', headers, 'MediaType', 'application/json');
data = struct('model', model, 'prompt', prompt, 'max_tokens', max_tokens);

response = webwrite(['https://api.openai.com/v1/engines/' model '/completions'], data, options);
result = jsondecode(response);

disp('Output:');
disp(result.choices.text);
                    

def bubble_sort(arr):
    n = len(arr)
    for i in range(n):
        for j in range(0, n-i-1):
            if arr[j] > arr[j+1]:
                arr[j], arr[j+1] = arr[j+1], arr[j]
    return arr
                        

This MATLAB script sends a POST request to the OpenAI Codex engine for code generation and prints the generated code.

3. Handling Responses

Once you receive a response from the API, you can handle it in your MATLAB script.

Text Completion

Here’s how you might handle the completion response:

% MATLAB Script to Handle Text Completion Response

response = webwrite('https://api.openai.com/v1/completions', data, options);
result = jsondecode(response);

disp('Translated Text:');
disp(result.choices.text);
                    

In this example, `response` contains the JSON response from the OpenAI API, and `disp` is used to print the translated text.

Code Generation

Here’s how you might handle the code generation response:

% MATLAB Script to Handle Code Generation Response

response = webwrite(['https://api.openai.com/v1/engines/' model '/completions'], data, options);
result = jsondecode(response);

disp('Generated Code:');
disp(result.choices.text);
                    

In this example, `response` contains the JSON response from the OpenAI API with the generated code, and `disp` is used to print the code.

Conclusion

Integrating the OpenAI API with MATLAB allows you to enhance your scripts with powerful AI capabilities. Explore more API endpoints and functionalities to innovate further.