Quickstart: Get intent using C#

In this quickstart, use an available public LUIS app to determine a user's intention from conversational text. Send the user's intention as text to the public app's HTTP prediction endpoint. At the endpoint, LUIS applies the public app's model to analyze the natural language text for meaning, determining overall intent and extracting data relevant to the app's subject domain.

This quickstart uses the endpoint REST API. For more information, see the endpoint API documentation.

For this article, you need a free LUIS account.



The complete solution is available from the cognitive-services-language-understanding GitHub repository.

Get LUIS key

Access to the prediction endpoint is provided with an endpoint key. For the purposes of this quickstart, use the free starter key associated with your LUIS account.

  1. Sign in using your LUIS account.

    Screenshot of Language Understanding (LUIS) app list

  2. Select your name in the top right menu, then select Settings.

    LUIS user settings menu access

  3. Copy the value of the Authoring key. You will use it later in the quickstart.

    Screenshot of Language Understanding (LUIS) user settings

    The authoring key allows free unlimited requests to the authoring API and up to 1000 queries to the prediction endpoint API per month for all your LUIS apps.

Get intent with browser

To understand what a LUIS prediction endpoint returns, view a prediction result in a web browser. In order to query a public app, you need your own key and the app ID. The public IoT app ID, df67dcdb-c37d-46af-88e1-8b97951ca1c2, is provided as part of the URL in step one.

The format of the URL for a GET endpoint request is:

  1. The endpoint of the public IoT app is in this format: https://westus.api.cognitive.microsoft.com/luis/v2.0/apps/df67dcdb-c37d-46af-88e1-8b97951ca1c2?subscription-key=<YOUR_KEY>&q=turn on the bedroom light

    Copy the URL and substitute your key for the value of <YOUR_KEY>.

  2. Paste the URL into a browser window and press Enter. The browser displays a JSON result that indicates that LUIS detects the HomeAutomation.TurnOn intent as the top intent and the HomeAutomation.Room entity with the value bedroom.

      "query": "turn on the bedroom light",
      "topScoringIntent": {
        "intent": "HomeAutomation.TurnOn",
        "score": 0.809439957
      "entities": [
          "entity": "bedroom",
          "type": "HomeAutomation.Room",
          "startIndex": 12,
          "endIndex": 18,
          "score": 0.8065475
  3. Change the value of the q= parameter in the URL to turn off the living room light, and press Enter. The result now indicates that LUIS detected the HomeAutomation.TurnOff intent as the top intent and the HomeAutomation.Room entity with value living room.

      "query": "turn off the living room light",
      "topScoringIntent": {
        "intent": "HomeAutomation.TurnOff",
        "score": 0.984057844
      "entities": [
          "entity": "living room",
          "type": "HomeAutomation.Room",
          "startIndex": 13,
          "endIndex": 23,
          "score": 0.9619945

Get intent programmatically

Use C# to query the prediction endpoint GET API to get the same results as you saw in the browser window in the previous section.

  1. Create a new console application in Visual Studio.

    Create a new console application in Visual Studio

  2. In the Visual Studio project, in the Solutions Explorer, select Add reference, then select System.Web from the Assemblies tab.

    select Add reference, then select System.Web from the Assemblies tab

  3. Overwrite Program.cs with the following code:

    using System;
    using System.Net.Http;
    using System.Web;
        You can use the authoring key instead of the endpoint key. 
        The authoring key allows 1000 endpoint queries a month.
    namespace ConsoleLuisEndpointSample
        class Program
            static void Main(string[] args)
                Console.WriteLine("Hit ENTER to exit...");
            static async void MakeRequest()
                var client = new HttpClient();
                var queryString = HttpUtility.ParseQueryString(string.Empty);
                // This app ID is for a public sample app that recognizes requests to turn on and turn off lights
                var luisAppId = "df67dcdb-c37d-46af-88e1-8b97951ca1c2";
                var endpointKey = "YOUR_KEY";
                // The request header contains your subscription key
                client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", endpointKey);
                // The "q" parameter contains the utterance to send to LUIS
                queryString["q"] = "turn on the left light";
                // These optional request parameters are set to their default values
                queryString["timezoneOffset"] = "0";
                queryString["verbose"] = "false";
                queryString["spellCheck"] = "false";
                queryString["staging"] = "false";
                var endpointUri = "https://westus.api.cognitive.microsoft.com/luis/v2.0/apps/" + luisAppId + "?" + queryString;
                var response = await client.GetAsync(endpointUri);
                var strResponseContent = await response.Content.ReadAsStringAsync();
                // Display the JSON result from LUIS
  4. Replace the value of YOUR_KEY with your LUIS key.

  5. Build and run the console application. It displays the same JSON that you saw earlier in the browser window.

    Console window displays JSON result from LUIS

LUIS keys

This quickstart uses the authoring key for convenience. The key is primarily for authoring the model but does allow a small number (1000) of endpoint requests. When you are ready for more endpoint requests in a test, stage or production environment, create a Language Understanding resource in the Azure portal and assign it to the LUIS app in the LUIS portal.

Clean up resources

When you are finished with this quickstart, close the Visual Studio project and remove the project directory from the file system.

Next steps