azure-content-safety

Azure AI Content Safety allows you to configure text blocklists by defining custom terms within the service's moderation settings. This enables you to filter specific words or phrases alongside the built-in content moderation categories.

To troubleshoot Azure Content Safety API errors, you can use expert guidance to diagnose and resolve issues related to configuration, limits, or security. This involves checking request payloads, verifying authentication, and reviewing service limits.

Best practices for tuning Azure content moderation thresholds involve adjusting sensitivity levels for different moderation categories to balance safety and usability. You should evaluate detection scores against your specific application requirements to minimize false positives.

Yes, you can deploy Azure Content Safety containers to perform various analysis types on your own infrastructure. This allows you to host the content safety solution locally, ensuring data privacy and meeting specific deployment architecture requirements.

Azure AI Content Safety has specific limits on request rates and payload sizes, alongside security configurations for access management. Understanding these constraints is crucial for designing secure, efficient content moderation architectures that avoid service disruptions.