Forum Discussion

KrisShenenbe782's avatar
KrisShenenbe782
Community Member
24 days ago

Integrating a Chatbot into My Storyline Project

Hi all,

I'd like to integrate chatbots in my Storyline courses in the near future. I tried a little test with my ChatGPT API key. It doesn't work because I don't want to buy API tokens. Also, I read other posts that let me know that I would be exposing myself to malicious hackers if I used my API key in a front-end server (I think I'm saying that right).

What I'd like to know is, has anyone successfully integrated a chatbot without using an API key? Is there a better option than ChatGPT? 

Thanks!

Kris

e-learning development
storyline 360
    • KrisShenenbe782's avatar
      KrisShenenbe782
      Community Member
      16 days ago

      Thanks Tom, I'll check him out. I was able to create a mentor-type AI assistant with ChatGPT. I'd share it but I'm using my personal API key. Thanks again!

  • AndersSloth-094's avatar
    AndersSloth-094
    Community Member
    5 days ago

    Hi Kris,
    Did you have any success embedding a ChatGPT-bot into you Articulate courses? How did you embed WITH and API-key in the first place?

    Best
    Anders

  • Dave-Ruckley's avatar
    Dave-Ruckley
    Community Member
    2 days ago

    I've used the API to get this working within storyline using this code:

    const player = GetPlayer();

// You should change the following 3 variables. Make sure that the text is enclosed by quotation marks.
const systemRequest = "XXXXX";
const userInputVariable = "Message_to_Colleague";
const aiOutputVariable = "gptresponse";
const colleagueChatVariable = "Colleague_Chat";

const userEntry = player.GetVar(userInputVariable);
const token = player.GetVar("OpenAI_API");
const auth = "Bearer " + token;

console.log("Authorization:", auth); // Log the entire Authorization header

function sendRequest() {
    fetch("https://api.openai.com/v1/chat/completions", {
        method: 'POST',
        headers: {
            'Authorization': auth,
            'Content-Type': 'application/json'
        },
        body: JSON.stringify({
            "model": "gpt-3.5-turbo",
            "messages": [
              {
                "role": "system",
                "content": systemRequest
              },
              {
                "role": "user",
                "content": userEntry
              }
            ]
        })
    }).then(response => {
        if (!response.ok) {
            return response.json().then(err => {
                throw new Error(`HTTP error! status: ${response.status}, message: ${err.error?.message || "Unknown error"}`);
            });
        }
        return response.json();
    }).then(data => {
        console.log("Response Data:", data); // Log the response data
        let aiText = data.choices[0].message.content;
        player.SetVar(aiOutputVariable, aiText);
        
        // Format and update the Colleague_Chat variable
        let formattedMessage = "<b>Q: </b>" + userEntry + "<br><b>A: </b>" + aiText;
        let currentChat = player.GetVar(colleagueChatVariable) || ""; // Get current chat history
        let updatedChat = currentChat + "<br>" + formattedMessage; // Append new message
        
        player.SetVar(colleagueChatVariable, updatedChat);

sendRequest();

    The slide is just a regular text input box, textbox and button plus the appropriate variables in storyline.

    The API is populated from a seperate XML file that's uploaded to the VLE seperately. That gives us more control over how and when students can use the chatGPT function and combined with the resource being available only to a select set of students, it's pretty secure.

    • KrisShenenbe782's avatar
      KrisShenenbe782
      Community Member
      2 days ago

      Thanks so much! I'm still new to JavaScript and putting together a separate XLM file is a bit above my head. I'll talk to tech. It would be better to have more control over it. Thank you for the script. I'll try it. Here's what I (and ChatGPT) came up with:

      // Step 1: Capture the learner's SMART goal from the Storyline variable
var player = GetPlayer();
var userGoal = player.GetVar("GoalText");  // Replace 'GoalText' with the actual variable name in Storyline

// Step 2: OpenAI API setup
const apiKey = 'myKey';  // Replace this with your OpenAI API key once you have it
const apiUrl = 'https://api.openai.com/v1/chat/completions';

// Step 3: Prepare the data to send to OpenAI
const data = {
    model: "gpt-4",  // Model can be gpt-3.5-turbo or gpt-4 depending on your API access
    messages: [
        {
            role: "system",
            content: "You are an assistant that helps users write SMART goals. Provide feedback on Specific, Measurable, Achievable, Relevant, and Time-bound aspects of the goal. Please be succinct and ensure you can answer fully with the 500 max_limit tokens. Include a concise summary of your conclusions with a rating score of 1-5, with 5 being the highest quality."
        },
        {
            role: "user",
            content: `Here is the SMART goal: "${userGoal}". Please analyze and provide feedback on it.`
        }
    ],
    max_tokens: 500,  // Limit the response length to avoid using too many tokens
    temperature: 0.7  // Adjusts the creativity of the response (0.7 is a good balance)
};

// Step 4: Send the API request to OpenAI
fetch(apiUrl, {
    method: 'POST',
    headers: {
        'Authorization': `Bearer ${apiKey}`,
        'Content-Type': 'application/json'
    },
    body: JSON.stringify(data)
})
.then(response => response.json())
.then(data => {
    // Step 5: Handle the response and set it to a Storyline variable
    if (data && data.choices && data.choices.length > 0) {
        var feedback = data.choices[0].message.content.trim();  // Extract feedback from the response
        player.SetVar("AI_Feedback", feedback);  // Store the feedback in a Storyline variable
    } else {
        player.SetVar("AI_Feedback", "No valid feedback received.");  // In case no feedback is returned
    }
})
.catch(error => {
    console.error("Error:", error);
    player.SetVar("AI_Feedback", "There was an error connecting to the AI service.");
});

      It's geared towards mentoring about a specific topic. I'd like to embed a chatbot that users can access on any page of the course and ask questions about the content. That's a much different animal.

      • Dave-Ruckley's avatar
        Dave-Ruckley
        Community Member
        10 hours ago

        No worries. ChatGPT has helped me a lot with figring out the javascript tricks I now use. 

        The XML bit is supr simple. You just need to create file called something like keys.xml and structure the content like this:

        <?xml version="1.0" encoding="utf-8"?>
        <SO xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
          <!-- OpenAI API Key -->
          <folder type="OpenAI">
            <APIKey>12345</APIKey>
          </folder>
        </SO>

        then in storyline use this code as a javascript trigger that runs when the timeline starts:

        // Define getAPIKeys function
window.getAPIKeys = function(callback) {
    var OAPI = "";
    var player = GetPlayer(); // Now only called after Storyline is ready
    var xmlDoc = "";
    var xmlhttp = new XMLHttpRequest();
    var dataLoadError = false; // Flag for error tracking

    // Request the xml doc from the server (Keys)
    xmlhttp.open("GET", "keys.xml", true); // Asynchronous request

    xmlhttp.onload = function() {
        if (xmlhttp.status === 200) { // Check if the request was successful
            xmlDoc = xmlhttp.responseXML;

            try {
                // Retrieve the OpenAI API keys from the XML file
                var apiKeyElement = xmlDoc.getElementsByTagName("APIKey")[0];
                
                if (apiKeyElement && apiKeyElement.childNodes[0]) {
                    OAPI = apiKeyElement.childNodes[0].nodeValue;

                    // Set them as Storyline variables
                    player.SetVar("OpenAI_API", OAPI);

                    // Execute the callback if provided
                    if (callback) {
                        callback();
                    }
                } else {
                    throw new Error("API key not found in the XML.");
                }
            } catch (error) {
                console.error("Error processing XML: ", error.message);
                dataLoadError = true;
                player.SetVar("Data_Load_Error", true);
            }
        } else {
            console.error("Error loading XML: Status ", xmlhttp.status);
            dataLoadError = true;
            player.SetVar("Data_Load_Error", true);
        }
    };

    xmlhttp.onerror = function() {
        console.error("Network error while fetching keys.xml");
        dataLoadError = true;
        player.SetVar("Data_Load_Error", true);
    };

    xmlhttp.send();
};

        Then in your exported zip file, add the xml file to it and upload the whole thing to your VLE. If you want to remove access all you have to do is remove the xml file from the VLE.

Related Content