Adapt OpenAI Extension

This Adapt extension allows integration with OpenAI's conversational AI API to enable interactive conversations within your Adapt courses. Note that you can use it with any Chat AI that implements the OpenAI conversation API.

Installation

Via Authoring Tool

1. Install the plugin via the plugin management interface

Into framework

1. Clone or download the repository to your local machine.
2. Copy the adapt-odi-openAI folder to your Adapt project's src/extensions/ directory.

Configuration

Before using the extension, you need to configure it with your OpenAI API key and other settings. Configuration can be done via the Adapt authoring tool or directly in the code.

Via Adapt Authoring Tool

1. In the Adapt authoring tool, navigate to configuration settings of the course
2. Find the OpenAI API extension settings.
3. Enter your OpenAI API endpoint and other necessary settings.

Directly in config.json

Alternatively, you can configure the extension directly in your course's config.json file. Here's an example configuration:

"_openaiodi": {
    "apiUrl": "https://api.openai.com/v1/completions",
    "apiKey": "your_api_key_here",
    "_testMode": false,
    "_testModeResponse": "Hello, I'm not an AI but the answer you are looking for is 42!",
    "model": "gpt-3.5-turbo",
    "temperature": 0.7,
    "max_tokens": 150,
    "topP": 1.0,
    "frequencyPenalty": 0,
    "presencePenalty": 0,
    "n": 1,
    "stop": ["\n", ""],
    "useClientAPIKey": true,
    "clientAuthServer": "https://your-auth-server.com/authenticate"
}

WARNING

Remember: Adapt outputs and code is all client side executed. This includes any apiKeys! So any user could easily find the API key in your config file. Also if you put the output source code on a public server, then anyone can find the API Key! If you are using OpenAI, they will mostly likely detect the key and instantly revoke it as you have been stoopid.

You should consider using a proxy or a custom key authentication server (see below)

Using a Custom Key Authentication Server

The Adapt OpenAI Extension supports the use of a custom key authentication server for managing API keys. This allows for more flexible and secure handling of authentication tokens.

Configuration

To use a custom key authentication server, set the useClientAPIKey parameter to true in your configuration. Additionally, provide the URL of your custom key authentication server using the clientAuthServer parameter.

How it Works

When useClientAPIKey is set to true and a clientAuthServer URL is provided, the extension generates an API key locally (as a GUID) and includes it in the request to the authentication server (which is displayed as an overlay in an iFrame). This server is responsible for validating the user (e.g. via OAuth) and the API key and updating the apiUrl service so this key is valid.

The plugin continues to poll the apiUrl with this key until it receives a valid response, indicating that the API key has been authenticated and is now valid for use with the OpenAI API.

By leveraging a custom key authentication server, you can implement user authentication and key validation logic tailored to your specific requirements, ensuring secure and controlled access to the OpenAI services.

Apologies for the oversight. Let's move the explanation to the beginning of the "Usage" section. Here's the revised version:

Usage

Once the extension is installed and configured, you can employ it to create interactive conversations within your Adapt courses. The plugin sends a trigger Adapt.trigger('openai:ready') upon successfully connecting to the OpenAI API and being ready for conversations. Other plugins can listen for this trigger to perform additional actions such as creating conversations, displaying UI elements, or triggering specific events based on the readiness of the AI service.

Here's how you can use it:

1. Create a new instance of the conversation:

const conversation = Adapt.openaiodi.createConversation();

2. Add messages to the conversation using the addMessage method:

conversation.addMessage({ role: 'user', content: 'Hello!' });

3. Obtain a response from the AI using the getResponse method:

conversation.getResponse()
    .then(response => {
        console.log('AI Response:', response);
    })
    .catch(error => {
        console.error('Error fetching response:', error.message);
    });

4. Clear messages from the conversation when necessary:

conversation.clearMessages();

Testing

You can test the functionality of the extension by enabling test mode in the configuration and providing test responses. This allows you to simulate interactions without making actual API.

License

This project is licensed under the MIT License.