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Azure Text Analytics Modern Content Moderation Approach

Hello techies, Today we are going to learn the new concept "Azure Content Moderator". Azure Content Moderator, part of Microsoft Azure’s Cognitive Services suite, provides businesses with a robust solution for moderating and filtering content on their online platforms. By leveraging machine learning algorithms, Azure Content Moderator can effectively detect and filter out objectionable or inappropriate content, ensuring a safe and controlled environment for users.

Getting started with Azure content moderator

To begin using Azure Content Moderator, you need an Azure subscription. Once you have that, follow these simple steps.

  1. Create a Content moderator resource: In the Azure portal, create a new Content Moderator resource. This resource will provide you with access to the Content Moderator API.
  2. Generate an API key: After creating the resource, you will receive an API key. This key is used to authenticate and authorize your requests to the Content Moderator API.
  3. Integrate content moderator into your solution: You can now integrate a Content Moderator into your application or solution. The API offers endpoints for text moderation, image moderation, and video moderation, allowing you to incorporate content moderation into your platform.

Text Moderation Example

Let’s take a look at an example of how to moderate text using the Azure Content Moderator API. We’ll use the REST API endpoint and make a POST request. Here’s an example using Python.

Source code

import requests
api_key = 'YOUR_API_KEY'
# Endpoint URL
url = 'https://api.cognitive.microsoft.com/contentmoderator/moderate/v1.0/ProcessText/Screen'
# Request headers
headers = {
    'Content-Type': 'text/plain',
    'Ocp-Apim-Subscription-Key': api_key
}
# Request body
body = 'Text to be moderated'
# POST request
response = requests.post(url, headers=headers, data=body)
# Process the response
if response.status_code == 200:
    result = response.json()
    # Analyze the result and take appropriate actions
else:
    print('Error:', response.status_code, response.text)

Image moderation example

In a similar fashion, we can moderate images using the Azure Content Moderator API. Here’s an example of how to send an image for moderation.

Source Code

import requests
api_key = 'YOUR_API_KEY'
# Endpoint URL
url = 'https://api.cognitive.microsoft.com/contentmoderator/moderate/v1.0/ProcessImage/Evaluate'
# Request headers
headers = {
    'Content-Type': 'application/json',
    'Ocp-Apim-Subscription-Key': api_key
}
# Request body
body = {
    'DataRepresentation': 'URL',
    'Value': 'URL_OF_THE_IMAGE'
}
# POST request
response = requests.post(url, headers=headers, json=body)
# Process the response
if response.status_code == 200:
    result = response.json()
    # Analyze the result and take appropriate actions
else:
    print('Error:', response.status_code, response.text)

The API response provides detailed information about the content, including its moderation status, adult/racy scores, and more. You can use this information to filter or take appropriate actions based on your application’s requirements.

Conclusion

Finally, The Azure Content Moderator is a comprehensive content moderation solution that empowers businesses to maintain a safe and controlled online environment. By leveraging its capabilities, you can effectively moderate text, images, and videos, ensuring that your platform adheres to policy guidelines and protects your users from objectionable content. Implementing Azure Content Moderator as part of your AI solution enables you to provide a secure and user-friendly experience to your audience.


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