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Send text classification requests to your model

After you successfully deploy a model, you can query the deployment to classify text based on the model you assigned to the deployment. You can query the deployment programmatically Prediction API or through the client libraries (Azure SDK).

Send a text classification request to your model (REST API)

First you need to get your resource key and endpoint:

  1. Go to your resource overview page in the Azure portal

  2. From the menu on the left side, select Keys and Endpoint. You use the endpoint and key for the API requests

    A screenshot showing the key and endpoint page in the Azure portal.

Submit a custom text classification task

Use this POST request to start a text classification task.

{ENDPOINT}/language/analyze-text/jobs?api-version={API-VERSION}
Placeholder Value Example
{ENDPOINT} The endpoint for authenticating your API request. https://<your-custom-subdomain>.cognitiveservices.azure.com
{API-VERSION} The version of the API you're calling. The value referenced is for the latest version released. For more information, see Model lifecycle. 2022-05-01

Headers

Key Value
Ocp-Apim-Subscription-Key Your key that provides access to this API.

Body

{
  "displayName": "Classifying documents",
  "analysisInput": {
    "documents": [
      {
        "id": "1",
        "language": "{LANGUAGE-CODE}",
        "text": "Text1"
      },
      {
        "id": "2",
        "language": "{LANGUAGE-CODE}",
        "text": "Text2"
      }
    ]
  },
  "tasks": [
     {
      "kind": "CustomMultiLabelClassification",
      "taskName": "Multi Label Classification",
      "parameters": {
        "projectName": "{PROJECT-NAME}",
        "deploymentName": "{DEPLOYMENT-NAME}"
      }
    }
  ]
}
Key Placeholder Value Example
displayName {JOB-NAME} Your job name. MyJobName
documents [{},{}] List of documents to run tasks on. [{},{}]
id {DOC-ID} Document name or ID. doc1
language {LANGUAGE-CODE} A string specifying the language code for the document. If this key isn't specified, the service will assume the default language of the project that was selected during project creation. See language support for a list of supported language codes. en-us
text {DOC-TEXT} Document task to run the tasks on. Lorem ipsum dolor sit amet
tasks List of tasks we want to perform. []
taskName CustomMultiLabelClassification The task name CustomMultiLabelClassification
parameters List of parameters to pass to the task.
project-name {PROJECT-NAME} The name for your project. This value is case-sensitive. myProject
deployment-name {DEPLOYMENT-NAME} The name of your deployment. This value is case-sensitive. prod

Response

You receive a 202 response indicating success. In the response headers, extract operation-location. operation-location is formatted like this:

{ENDPOINT}/language/analyze-text/jobs/{JOB-ID}?api-version={API-VERSION}

You can use this URL to query the task completion status and get the results when task is completed.

Get task results (Azure SDK)

Use the following GET request to query the status/results of the text classification task.

{ENDPOINT}/language/analyze-text/jobs/{JOB-ID}?api-version={API-VERSION}
Placeholder Value Example
{ENDPOINT} The endpoint for authenticating your API request. https://<your-custom-subdomain>.cognitiveservices.azure.com
{API-VERSION} The version of the API you're calling. The value referenced is for the latest released model version version. 2022-05-01

Headers

Key Value
Ocp-Apim-Subscription-Key Your key that provides access to this API.

Response body

The response will be a JSON document with the following parameters.

{
  "createdDateTime": "2021-05-19T14:32:25.578Z",
  "displayName": "MyJobName",
  "expirationDateTime": "2021-05-19T14:32:25.578Z",
  "jobId": "xxxx-xxxxxx-xxxxx-xxxx",
  "lastUpdateDateTime": "2021-05-19T14:32:25.578Z",
  "status": "succeeded",
  "tasks": {
    "completed": 1,
    "failed": 0,
    "inProgress": 0,
    "total": 1,
    "items": [
      {
        "kind": "customMultiClassificationTasks",
        "taskName": "Classify documents",
        "lastUpdateDateTime": "2020-10-01T15:01:03Z",
        "status": "succeeded",
        "results": {
          "documents": [
            {
              "id": "{DOC-ID}",
              "classes": [
                  {
                      "category": "Class_1",
                      "confidenceScore": 0.0551877357
                  }
              ],
              "warnings": []
            }
          ],
          "errors": [],
          "modelVersion": "2020-04-01"
        }
      }
    ]
  }
}

First you need to get your resource key and endpoint:

  • Go to your resource overview page in the Azure portal

  • From the menu on the left side, select Keys and Endpoint. The endpoint and key are used for API requests.

A screenshot showing the key and endpoint page in the Azure portal.

  1. Download and install the client library package for your language of choice:

    Language Package version
    .NET 5.2.0-beta.3
    Java 5.2.0-beta.3
    JavaScript 6.0.0-beta.1
    Python 5.2.0b4

  2. After you install the client library, use the following samples on GitHub to start calling the API.

    Single label classification:

    Multi label classification:

  3. See the following reference documentation on the client, and return object:

Next steps

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