C# TE3 script to add measure name, measure description/purpose, and DAX code to the measure tooltip for each measure in a selected table

gistfile1.txt

// C# TE3 script to add measure name, measure description/purpose, and DAX code to the measure tooltip for each measure in a selected table
// developed by Brian Julius, Sep 27, 2024

string apiKey = System.Environment.GetEnvironmentVariable("OPEN_AI_TE3_API_KEY");
if (string.IsNullOrEmpty(apiKey))
{
    Error("API key not found in environment variable 'OPEN_AI_TE3_API_KEY'.");
    return;
}

var selectedTable = Selected.Table;
if (selectedTable == null)
{
    Error("Please select a table.");
    return;
}

var client = new System.Net.Http.HttpClient();
client.DefaultRequestHeaders.Authorization = new System.Net.Http.Headers.AuthenticationHeaderValue("Bearer", apiKey);
client.BaseAddress = new Uri("https://api.openai.com/");

foreach (var measure in selectedTable.Measures)
{
    // Build the prompt
    string prompt = $@"
Analyze the following DAX measure and provide its purpose.
Keep the total response under 100 tokens.

DAX Measure:

{measure.Name} =
{measure.Expression}

Provide the output in the following format:

Purpose: <Brief purpose of the measure>
";

    // Build the request body
    var requestBody = new
    {
        model = "gpt-4o-mini",
        messages = new[]
        {
            new { role = "system", content = "You are an expert in DAX measures and Power BI." },
            new { role = "user", content = prompt }
        },
        max_tokens = 100,
        temperature = 0.3
    };

    // Serialize the request body to JSON
    string jsonBody = Newtonsoft.Json.JsonConvert.SerializeObject(requestBody);

    // Create the content
    var content = new System.Net.Http.StringContent(jsonBody, System.Text.Encoding.UTF8, "application/json");

    try
    {
        // Send the POST request
        var response = client.PostAsync("/v1/chat/completions", content).Result;

        if (response.IsSuccessStatusCode)
        {
            // Read the response content
            var responseContent = response.Content.ReadAsStringAsync().Result;

            // Parse the JSON response
            var responseJson = Newtonsoft.Json.Linq.JObject.Parse(responseContent);

            // Extract the generated text
            var generatedText = responseJson["choices"][0]["message"]["content"].ToString().Trim();

            // Construct the Description metadata with blank lines
            string descriptionText = $@"
Name of Measure: {measure.Name}

{generatedText}

Code:
{measure.Expression}
";

            // Set the measure's description
            measure.Description = descriptionText.Trim();

            Output($"Description set for measure: {measure.Name}");
        }
        else
        {
            // Handle error
            Output($"Failed to get description for measure: {measure.Name}. Status Code: {response.StatusCode}");
            var errorContent = response.Content.ReadAsStringAsync().Result;
            Output($"Error: {errorContent}");
        }
    }
    catch (Exception ex)
    {
        Output($"Exception occurred for measure: {measure.Name}. Error: {ex.Message}");
    }

    // Optional: Delay between requests to respect rate limits
    System.Threading.Thread.Sleep(1000); // Sleep for 1 second
}