Quickstart: Custom categories (standard mode) (preview)

Follow this guide to use Azure AI Content Safety Custom categories (standard) REST API to create your own content categories for your use case and train Azure AI Content Safety to detect them in new text content.

For more information on Custom categories, see the Custom categories concept page. For API input limits, see the Input requirements section of the Overview.

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This feature is only available in certain Azure regions. See Region availability.

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Allow enough time for model training

The end-to-end execution of custom category training can take from around five hours to ten hours. Plan your moderation pipeline accordingly.

Prerequisites

• An Azure subscription - Create one for free
• Once you have your Azure subscription, create a Content Safety resource in the Azure portal to get your key and endpoint. Enter a unique name for your resource, select your subscription, and select a resource group, supported region, and supported pricing tier. Then select Create.
  • The resource takes a few minutes to deploy. After it finishes, Select go to resource. In the left pane, under Resource Management, select Subscription Key and Endpoint. Copy the endpoint and either of the key values to a temporary location for later use.
• Also create an Azure blob storage container where you'll keep your training annotation file.
• One of the following installed:
  • cURL for REST API calls.
  • Python 3.x installed

Prepare your training data

To train a custom category, you need example text data that represents the category you want to detect. In this guide, you can use sample data. The provided annotation file contains text prompts about survival advice in camping/wilderness situations. The trained model will learn to detect this type of content in new text data.

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For tips on creating your own data set, see the How-to guide.

1. Download the sample text data file from the GitHub repository.
2. Upload the .jsonl file to your Azure Storage account blob container. Then copy the blob URL to a temporary location for later use.

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The user's storage account is set up as a hierarchical namespace account, which cannot be supported by Custom Categories. Please try using a regular storage account instead. For example, your blob URL cannot be split into two layers, such as example/example1/, and should only have one layer. For more details, refer to the documentation: Azure Data Lake Storage hierarchical namespace - Azure Storage.

Grant storage access

Next, you need to give your Content Safety resource access to read from the Azure Storage resource. Enable system-assigned Managed identity for the Azure AI Content Safety instance and assign the role of Storage Blob Data Contributor/Owner to the identity:

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Only Storage Blob Data Contributor or Storage Blob Data Owner are valid roles to proceed.

1. Enable managed identity for the Azure AI Content Safety instance.

   

2. Assign the role of Storage Blob Data Contributor/Owner to the Managed identity. Any roles highlighted below should work.

   

   

   

Create and train a custom category

cURL

In the command below, replace <your_api_key>, <your_endpoint>, and other necessary parameters with your own values. Then enter each command in a terminal window and run it.

Create new category version

Bash

curl -X PUT "<your_endpoint>/contentsafety/text/categories/<your_category_name>?api-version=2024-09-15-preview" \
     -H "Ocp-Apim-Subscription-Key: <your_api_key>" \
     -H "Content-Type: application/json" \
     -d "{
            \"categoryName\": \"survival-advice\",
            \"definition\": \"text prompts about survival advice in camping/wilderness situations\",
            \"sampleBlobUrl\": \"https://<your-azure-storage-url>/example-container/survival-advice.jsonl\"
        }"

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Every time you change your category name, definition or samples,a new version will be created. You can use the version number to trace back to previous versions. Please remember this version number, as it will be required in the URL for the next step- training custom categories.

API Request

Field	Description	Example Value
categoryName	The name of the category or topic the request relates to.	survival-advice
definition	A brief description of the content type for the category.	text prompts about survival advice in camping/wilderness situations
sampleBlobUrl	URL to access a sample JSONL file containing data examples for the category.	Link

API Response

Field	Description	Example Value
categoryName	The name of the category or topic the response relates to.	survival-advice
definition	A brief description of the content type for the category.	text prompts about survival advice in camping/wilderness situations
sampleBlobUrl	URL to access a sample JSONL file containing data examples for the category.	Link
sampleBlobSnapshotUrl	Snapshot URL of the sample JSONL file, which provides access to a specific version of the data.	Snapshot URL
version	The version number of the category data.	1
createdTime	Timestamp when the category data was created.	2024-10-28T22:06:59.4626988Z
status	Current status of the category data processing.	Succeeded

Start the category build process

Replace <your_api_key> and <your_endpoint> with your own values, and also append the version number in the url you obtained from the last step. Allow enough time for model training: the end-to-end execution of custom category training can take from around five hours to ten hours. Plan your moderation pipeline accordingly. After you receive the response, store the operation ID (referred to as id) in a temporary location. This ID will be necessary for retrieving the build status using the Get status API in the next section.

Bash

curl -X POST "<your_endpoint>/contentsafety/text/categories/survival-advice:build?api-version=2024-09-15-preview&version={version}" \
     -H "Ocp-Apim-Subscription-Key: <your_api_key>" \
     -H "Content-Type: application/json"

API Response

Field	Description	Example Value
operation id	Unique identifier for retrieving the build status	b6c69dc1-2338-484e-85a5b-xxxxxxxxxxxx
status	Current status of the request	Succeeded

Get the category build status

To retrieve the status, utilize the id obtained from the previous API response and place it in the path of the API below.

Bash

curl -X GET "<your_endpoint>/contentsafety/text/categories/operations/<id>?api-version=2024-09-15-preview" \
     -H "Ocp-Apim-Subscription-Key: <your_api_key>" \
     -H "Content-Type: application/json"

API Response

Field	Description	Example Value
operation id	Unique identifier for retrieving the build status	b6c69dc1-2338-484e-855b-xxxxxxxxxxxx
status	Current status of the request	Succeeded

Analyze text with a customized category

Run the following command to analyze text with your customized category. Replace <your_api_key> and <your_endpoint> with your own values.

Bash

curl -X POST "<your_endpoint>/contentsafety/text:analyzeCustomCategory?api-version=2024-09-15-preview" \
     -H "Ocp-Apim-Subscription-Key: <your_api_key>" \
     -H "Content-Type: application/json" \
     -d "{
            \"text\": \"<Example text to analyze>\",
            \"categoryName\": \"survival-advice\", 
            \"version\": 1
        }"

API Request

Field	Description
text	The text content or message intended for category detection
categoryName	The name of the category the text aims to be detected under
version	Version number of the category

API Response

Field	Description	Example Value
customCategoryAnalysis	Object containing the analysis result for the category.	—
detected	Indicates whether the specified category was detected.	false

Python

First, you need to install the required Python library:

Bash

pip install requests

Then, open a new Python script and define the necessary variables with your own Azure resource details:

Python

import requests

API_KEY = '<your_api_key>'
ENDPOINT = '<your_endpoint>'

headers = {
    'Ocp-Apim-Subscription-Key': API_KEY,
    'Content-Type': 'application/json'
}

Create a new category

You can create a new category with category name, definition and sample_blob_url, and you'll get the autogenerated version number of this category.

Python

def create_new_category_version(category_name, definition, sample_blob_url):
    url = f"{ENDPOINT}/contentsafety/text/categories/{category_name}?api-version=2024-09-15-preview"
    data = {
        "categoryName": category_name,
        "definition": definition,
        "sampleBlobUrl": sample_blob_url
    }
    response = requests.put(url, headers=headers, json=data)
    return response.json()

# Replace the parameters with your own values
category_name = "survival-advice"
definition = "text prompts about survival advice in camping/wilderness situations"
sample_blob_url = "https://<your-azure-storage-url>/example-container/survival-advice.jsonl"

result = create_new_category_version(category_name, definition, sample_blob_url)
print(result)

Start the category build process

You can start the category build process with the category name and version number. Allow enough time for model training: the end-to-end execution of custom category training can take from around five hours to ten hours. Plan your moderation pipeline accordingly. After receiving the response, ensure that you store the operation ID (referred to as id) somewhere like your notebook. This ID will be necessary for retrieving the build status using the ‘get_build_status’ function in the next section.

Python

def trigger_category_build_process(category_name, version):
    url = f"{ENDPOINT}/contentsafety/text/categories/{category_name}:build?api-version=2024-09-15-preview&version={version}"
    response = requests.post(url, headers=headers)
    return response.status_code

# Replace the parameters with your own values
category_name = "survival-advice"
version = 1

result = trigger_category_build_process(category_name, version)
print(result)

Get the category build status:

To retrieve the status, utilize the id obtained from the previous response.

Python

def get_build_status(id):
    url = f"{ENDPOINT}/contentsafety/text/categories/operations/{id}?api-version=2024-09-15-preview"
    response = requests.get(url, headers=headers)
    return response.status_code

# Replace the parameter with your own value
id = "your-operation-id"

result = get_build_status(id)
print(result)

Analyze text with a customized category

You need to specify the category name and the version number (optional; the service uses the latest one by default) during inference. You can specify multiple categories if they're already defined.

Python

def analyze_text_with_customized_category(text, category_name, version):
    url = f"{ENDPOINT}/contentsafety/text:analyzeCustomCategory?api-version=2024-09-15-preview"
    data = {
        "text": text,
        "categoryName": category_name,
        "version": version
    }
    response = requests.post(url, headers=headers, json=data)
    return response.json()

# Replace the parameters with your own values
text = "<Example text to analyze>"
category_name = "survival-advice"
version = 1

result = analyze_text_with_customized_category(text, category_name, version)
print(result)

Other custom categories operations

Remember to replace the placeholders below with your actual values for the API key, endpoint, and specific content (category name, definition, and so on). These examples help you to manage the customized categories in your account.

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Use API keys with caution. Don't include the API key directly in your code, and never post it publicly. If you use an API key, store it securely in Azure Key Vault. For more information about using API keys securely in your apps, see API keys with Azure Key Vault.

For more information about AI services security, see Authenticate requests to Azure AI services.

cURL

Get a customized category or a specific version of it

Replace the placeholders with your own values and run the following command in a terminal window:

Bash

curl -X GET "<endpoint>/contentsafety/text/categories/<your_category_name>?api-version=2024-09-15-preview&version=1" \
     -H "Ocp-Apim-Subscription-Key: <your_api_key>" \
     -H "Content-Type: application/json"

List categories of their latest versions

Replace the placeholders with your own values and run the following command in a terminal window:

Bash

curl -X GET "<endpoint>/contentsafety/text/categories?api-version=2024-09-15-preview" \
     -H "Ocp-Apim-Subscription-Key: <your_api_key>" \
     -H "Content-Type: application/json"

Delete a customized category or a specific version of it

Replace the placeholders with your own values and run the following command in a terminal window:

Bash

curl -X DELETE "<endpoint>/contentsafety/text/categories/<your_category_name>?api-version=2024-09-15-preview&version=1" \
     -H "Ocp-Apim-Subscription-Key: <your_api_key>" \
     -H "Content-Type: application/json"

Python

First, make sure you've installed the required Python library:

Bash

pip install requests

Then, set up the necessary configurations with your own AI resource details:

Python

import requests

API_KEY = '<your_api_key>'
ENDPOINT = '<your_endpoint>'

headers = {
    'Ocp-Apim-Subscription-Key': API_KEY,
    'Content-Type': 'application/json'
}

Get a customized category or a specific version of it

Replace the placeholders with your own values and run the following code in your Python script:

Python

def get_customized_category(category_name, version=None):
    url = f"{ENDPOINT}/contentsafety/text/categories/{category_name}?api-version=2024-09-15-preview"
    if version:
        url += f"&version={version}"
    
    response = requests.get(url, headers=headers)
    return response.json()

# Replace the parameters with your own values
category_name = "DrugAbuse"
version = 1

result = get_customized_category(category_name, version)
print(result)

List categories of their latest versions

Python

def list_categories_latest_versions():
    url = f"{ENDPOINT}/contentsafety/text/categories?api-version=2024-09-15-preview"
    response = requests.get(url, headers=headers)
    return response.json()

result = list_categories_latest_versions()
print(result)

Delete a customized category or a specific version of it

Replace the placeholders with your own values and run the following code in your Python script:

Python

def delete_customized_category(category_name, version=None):
    url = f"{ENDPOINT}/contentsafety/text/categories/{category_name}?api-version=2024-09-15-preview"
    if version:
        url += f"&version={version}"
    
    response = requests.delete(url, headers=headers)
    return response.status_code

# Replace the parameters with your own values
category_name = "<your_category_name>"
version = 1

result = delete_customized_category(category_name, version)
print(result)

Related content

• Custom categories concepts
• Moderate content with Content Safety