Agent skill

azure-ai-contentsafety-py

Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification.

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SKILL.md

Azure AI Content Safety SDK for Python

Detect harmful user-generated and AI-generated content in applications.

Installation

bash
pip install azure-ai-contentsafety

Environment Variables

bash
CONTENT_SAFETY_ENDPOINT=https://<resource>.cognitiveservices.azure.com
CONTENT_SAFETY_KEY=<your-api-key>

Authentication

API Key

python
from azure.ai.contentsafety import ContentSafetyClient
from azure.core.credentials import AzureKeyCredential
import os

client = ContentSafetyClient(
    endpoint=os.environ["CONTENT_SAFETY_ENDPOINT"],
    credential=AzureKeyCredential(os.environ["CONTENT_SAFETY_KEY"])
)

Entra ID

python
from azure.ai.contentsafety import ContentSafetyClient
from azure.identity import DefaultAzureCredential

client = ContentSafetyClient(
    endpoint=os.environ["CONTENT_SAFETY_ENDPOINT"],
    credential=DefaultAzureCredential()
)

Analyze Text

python
from azure.ai.contentsafety import ContentSafetyClient
from azure.ai.contentsafety.models import AnalyzeTextOptions, TextCategory
from azure.core.credentials import AzureKeyCredential

client = ContentSafetyClient(endpoint, AzureKeyCredential(key))

request = AnalyzeTextOptions(text="Your text content to analyze")
response = client.analyze_text(request)

# Check each category
for category in [TextCategory.HATE, TextCategory.SELF_HARM, 
                 TextCategory.SEXUAL, TextCategory.VIOLENCE]:
    result = next((r for r in response.categories_analysis 
                   if r.category == category), None)
    if result:
        print(f"{category}: severity {result.severity}")

Analyze Image

python
from azure.ai.contentsafety import ContentSafetyClient
from azure.ai.contentsafety.models import AnalyzeImageOptions, ImageData
from azure.core.credentials import AzureKeyCredential
import base64

client = ContentSafetyClient(endpoint, AzureKeyCredential(key))

# From file
with open("image.jpg", "rb") as f:
    image_data = base64.b64encode(f.read()).decode("utf-8")

request = AnalyzeImageOptions(
    image=ImageData(content=image_data)
)

response = client.analyze_image(request)

for result in response.categories_analysis:
    print(f"{result.category}: severity {result.severity}")

Image from URL

python
from azure.ai.contentsafety.models import AnalyzeImageOptions, ImageData

request = AnalyzeImageOptions(
    image=ImageData(blob_url="https://example.com/image.jpg")
)

response = client.analyze_image(request)

Text Blocklist Management

Create Blocklist

python
from azure.ai.contentsafety import BlocklistClient
from azure.ai.contentsafety.models import TextBlocklist
from azure.core.credentials import AzureKeyCredential

blocklist_client = BlocklistClient(endpoint, AzureKeyCredential(key))

blocklist = TextBlocklist(
    blocklist_name="my-blocklist",
    description="Custom terms to block"
)

result = blocklist_client.create_or_update_text_blocklist(
    blocklist_name="my-blocklist",
    options=blocklist
)

Add Block Items

python
from azure.ai.contentsafety.models import AddOrUpdateTextBlocklistItemsOptions, TextBlocklistItem

items = AddOrUpdateTextBlocklistItemsOptions(
    blocklist_items=[
        TextBlocklistItem(text="blocked-term-1"),
        TextBlocklistItem(text="blocked-term-2")
    ]
)

result = blocklist_client.add_or_update_blocklist_items(
    blocklist_name="my-blocklist",
    options=items
)

Analyze with Blocklist

python
from azure.ai.contentsafety.models import AnalyzeTextOptions

request = AnalyzeTextOptions(
    text="Text containing blocked-term-1",
    blocklist_names=["my-blocklist"],
    halt_on_blocklist_hit=True
)

response = client.analyze_text(request)

if response.blocklists_match:
    for match in response.blocklists_match:
        print(f"Blocked: {match.blocklist_item_text}")

Severity Levels

Text analysis returns 4 severity levels (0, 2, 4, 6) by default. For 8 levels (0-7):

python
from azure.ai.contentsafety.models import AnalyzeTextOptions, AnalyzeTextOutputType

request = AnalyzeTextOptions(
    text="Your text",
    output_type=AnalyzeTextOutputType.EIGHT_SEVERITY_LEVELS
)

Harm Categories

Category Description
Hate Attacks based on identity (race, religion, gender, etc.)
Sexual Sexual content, relationships, anatomy
Violence Physical harm, weapons, injury
SelfHarm Self-injury, suicide, eating disorders

Severity Scale

Level Text Range Image Range Meaning
0 Safe Safe No harmful content
2 Low Low Mild references
4 Medium Medium Moderate content
6 High High Severe content

Client Types

Client Purpose
ContentSafetyClient Analyze text and images
BlocklistClient Manage custom blocklists

Best Practices

  1. Use blocklists for domain-specific terms
  2. Set severity thresholds appropriate for your use case
  3. Handle multiple categories — content can be harmful in multiple ways
  4. Use halt_on_blocklist_hit for immediate rejection
  5. Log analysis results for audit and improvement
  6. Consider 8-severity mode for finer-grained control
  7. Pre-moderate AI outputs before showing to users

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

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