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Azure AI Content Safety SDK for Python.
Passed 22 of 22 test cases with the skill, and 14 of 22 without it.
and 6 more in the full report
8 fixed14 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
When analyzing a local image file with `AnalyzeImageOptions` in the Azure AI Content Safety Python SDK, what format must the raw file bytes be converted into before populating the `ImageData` object?
| Checked | Without skill | With skill |
|---|---|---|
| The response states that raw image bytes must be base64-encoded into a UTF-8 string. | Missed | Passed |
The instructions your model reads when the skill loads.
Detect harmful user-generated and AI-generated content in applications.
pip install azure-ai-contentsafety
CONTENT_SAFETY_ENDPOINT=https://<resource>.cognitiveservices.azure.com # Required for all auth methods
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production
CONTENT_SAFETY_KEY=<your-api-key> # Only required for the legacy API-key auth path below
🔑 Two rules apply to every code sample below:
- Prefer
DefaultAzureCredential. It works locally (Azure CLI / VS Code / Developer CLI) and in Azure (managed identity, workload identity) with no code change. Avoid connection strings, account/API keys — they bypass Entra audit and rotation.
- Local dev:
DefaultAzureCredentialworks as-is.- Production: set
AZURE_TOKEN_CREDENTIALS=prod(orAZURE_TOKEN_CREDENTIALS=<specific_credential>) to constrain the credential chain to production-safe credentials.- Wrap every client in a context manager so HTTP transports, sockets, and token caches are released deterministically:
- Sync:
with <Client>(...) as client:- Async:
async with <Client>(...) as client:andasync with DefaultAzureCredential() as credential:(fromazure.identity.aio)Snippets may abbreviate this setup, but production code should always follow both rules.
import os
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
from azure.ai.contentsafety import ContentSafetyClient
from azure.ai.contentsafety.models import AnalyzeTextOptions
# Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# Or use a specific credential directly in production:
test cases passed, vs 14 / 22 without
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