Deploy a model and classify text using the runtime API

Članak
04/06/2022
4 min. za čitanje

After you're satisfied with your model, and made any necessary improvements, you can deploy it and start classifying text. Deploying a model makes it available for use through the runtime API.

Prerequisites

A custom text classification project with a configured Azure blob storage account,
Text data that has been uploaded to your storage account.
Tagged data and successfully trained model
Reviewed the model evaluation details to determine how your model is performing.
(optional) Made improvements to your model if its performance isn't satisfactory.

See the application development lifecycle for more information.

Deploy your model

Deploying a model hosts it and makes it available for predictions through an endpoint.

When a model is deployed, you will be able to test the model directly in the portal or by calling the API associated with it.

Note

You can only have ten deployment names.

Go to your project in Language studio.
From the left panel, select Deploy model.
Click on Add deployment to submit a new deployment job.
In the window that appears, you can create a new deployment name by or override an existing one. Then, you can add a trained model to this deployment name.

Delete deployment

To delete a deployment, select the deployment you want to delete and click Delete deployment

Tip

You can test your model in Language Studio by sending samples of text for it to classify.

Send a text classification request to your model

Using Language studio

After the deployment is completed, select the model you want to use and from the top menu click on Get prediction URL and copy the URL and body.
In the window that appears, under the Submit pivot, copy the sample request into your command line
Replace <YOUR_DOCUMENT_HERE> with the actual text you want to classify.
Submit the request
In the response header you receive extract jobId from operation-location, which has the format: {YOUR-ENDPOINT}/text/analytics/v3.2-preview.2/analyze/jobs/<jobId}>
Copy the retrieve request and replace <OPERATION-ID> with jobId received from the last step and submit the request.

You will need to use the REST API. Click on the REST API tab above for more information.

Using the REST API

First you will 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. Use endpoint for the API requests and you will need the key for Ocp-Apim-Subscription-Key header.

Submit a custom text classification task

Note

Project names are case sensitive.

Use this POST request to start an entity extraction task. Replace {projectName} with the project name where you have the model you want to use.

{YOUR-ENDPOINT}/text/analytics/v3.2-preview.2/analyze

Headers

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

Body

{
    "displayName": "MyJobName",
    "analysisInput": {
        "documents": [
            {
                "id": "doc1", 
                "text": "Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nunc tempus, felis sed vehicula lobortis, lectus ligula facilisis quam, quis aliquet lectus diam id erat. Vivamus eu semper tellus. Integer placerat sem vel eros iaculis dictum. Sed vel congue urna."
            },
            {
                "id": "doc2",
                "text": "Mauris dui dui, ultricies vel ligula ultricies, elementum viverra odio. Donec tempor odio nunc, quis fermentum lorem egestas commodo. Class aptent taciti sociosqu ad litora torquent per conubia nostra, per inceptos himenaeos."
            }
        ]
    },
    "tasks": {
        "customMultiClassificationTasks": [      
            {
                "parameters": {
                      "project-name": "MyProject",
                      "deployment-name": "MyDeploymentName"
                      "stringIndexType": "TextElements_v8"
                }
            }
        ]
    }
}

Key	Sample Value	Description
displayName	"MyJobName"	Your job Name
documents	[{},{}]	List of documents to run tasks on
ID	"doc1"	a string document identifier
text	"Lorem ipsum dolor sit amet"	You document in string format
"tasks"	[]	List of tasks we want to perform.
--	customMultiClassificationTasks	Task identifer for task we want to perform. Use `customClassificationTasks` for single label classification tasks and `customMultiClassificationTasks` for multi label classification tasks.
parameters	[]	List of parameters to pass to task
project-name	"MyProject"	Your project name. The project name is case-sensitive.
deployment-name	"MyDeploymentName"	Your deployment name

Replace the text of the document with movie summaries to classify.

Response

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

{YOUR-ENDPOINT}/text/analytics/v3.2-preview.2/analyze/jobs/<jobId>

You will use this endpoint to get the custom text classification task results.

Get the results for a custom text classification task

Use the following GET request to query the status/results of the custom classification task. You can use the endpoint you received from the previous step.

{YOUR-ENDPOINT}/text/analytics/v3.2-preview.2/analyze/jobs/<jobId>.

Headers

Key	Value
Ocp-Apim-Subscription-Key	Your Subscription 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": "3fa85f64-5717-4562-b3fc-2c963f66afa6",
    "lastUpdateDateTime": "2021-05-19T14:32:25.578Z",
    "status": "completed",
    "errors": [],
    "tasks": {
        "details": {
            "name": "MyJobName",
            "lastUpdateDateTime": "2021-03-29T19:50:23Z",
            "status": "completed"
        },
        "completed": 1,
        "failed": 0,
        "inProgress": 0,
        "total": 1,
        "tasks": {
    "customMultiClassificationTasks": [
        {
            "lastUpdateDateTime": "2021-05-19T14:32:25.579Z",
            "name": "MyJobName",
            "status": "completed",
            "results": {
                "documents": [
                    {
                        "id": "doc1",
                        "classes": [
                            {
                                "category": "Class_1",
                                "confidenceScore": 0.0551877357
                            }
                        ],
                        "warnings": []
                    },
                    {
                        "id": "doc2",
                        "classes": [
                            {
                                "category": "Class_1",
                                "confidenceScore": 0.0551877357
                            },
                                                        {
                                "category": "Class_2",
                                "confidenceScore": 0.0551877357
                            }
                        ],
                        "warnings": []
                    }
                ],
                "errors": [],
                "statistics": {
                    "documentsCount":0,
                    "erroneousDocumentsCount":0,
                    "transactionsCount":0
                }
                    }
                }
            ]
        }
    }

Use the client libraries

Go to your resource overview page in the Azure portal
From the menu on the left side, select Keys and Endpoint. Use endpoint for the API requests and you will need the key for Ocp-Apim-Subscription-Key header.
Download and install the client library package for your language of choice:

Language Package version

.NET 5.2.0-beta.2

Java 5.2.0-beta.2

JavaScript 5.2.0-beta.2

Python 5.2.0b2
After you've installed the client library, use the following samples on GitHub to start calling the API.

Single label classification:
- C#
- Java
- JavaScript
- Python
Multi label classification:
- C#
- Java
- JavaScript
- Python
See the following reference documentation for more information on the client, and return object:
- C#
- Java
- JavaScript
- Python

Language	Package version
.NET	5.2.0-beta.2
Java	5.2.0-beta.2
JavaScript	5.2.0-beta.2
Python	5.2.0b2