azure-ai-contentsafety-py
🤖 AI Summary
Detects harmful content in text and images using Azure AI Content Safety, returning multi-severity classifications (safe, low, medium, high) for categories like hate, self-harm, sexual, and violence.
How to Install
Claude Code:
git clone --depth 1 https://github.com/sickn33/antigravity-awesome-skills.git && cp antigravity-awesome-skills/skills/azure-ai-contentsafety-py ~/.claude/skills/azure-ai-contentsafety-py -rAzure AI Content Safety SDK for Python
Detect harmful user-generated and AI-generated content in applications.
Installation
pip install azure-ai-contentsafety
Environment Variables
CONTENT_SAFETY_ENDPOINT=https://<resource>.cognitiveservices.azure.com
CONTENT_SAFETY_KEY=<your-api-key>
Authentication
API Key
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
from azure.ai.contentsafety import ContentSafetyClient
from azure.identity import DefaultAzureCredential
client = ContentSafetyClient(
endpoint=os.environ["CONTENT_SAFETY_ENDPOINT"],
credential=DefaultAzureCredential()
)
Analyze Text
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
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
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
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
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
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):
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
- Use blocklists for domain-specific terms
- **Set severity th
Details
| Category | DevOps → cicd |
| Source | sickn33/antigravity-awesome-skills |
| SKILL.md | View on GitHub → |
| Repo Stars | ★ 41.5K |
| Est. per Skill | 47 (shared across 868 skills from this repo) |
| Difficulty | Intermediate |
| Risk Level | N/A |
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