azure-ai-contentsafety-java

Build content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text/image analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.

npx skills add https://github.com/microsoft/skills --skill azure-ai-contentsafety-java

Azure AI Content Safety SDK for Java

Build content moderation applications using the Azure AI Content Safety SDK for Java.

Installation

<dependency>
    <groupId>com.azure</groupId>
    <artifactId>azure-ai-contentsafety</artifactId>
    <version>1.1.0-beta.1</version>
</dependency>

Client Creation

With API Key

import com.azure.ai.contentsafety.ContentSafetyClient;
import com.azure.ai.contentsafety.ContentSafetyClientBuilder;
import com.azure.ai.contentsafety.BlocklistClient;
import com.azure.ai.contentsafety.BlocklistClientBuilder;
import com.azure.core.credential.KeyCredential;

String endpoint = System.getenv("CONTENT_SAFETY_ENDPOINT");
String key = System.getenv("CONTENT_SAFETY_KEY");

ContentSafetyClient contentSafetyClient = new ContentSafetyClientBuilder()
    .credential(new KeyCredential(key))
    .endpoint(endpoint)
    .buildClient();

BlocklistClient blocklistClient = new BlocklistClientBuilder()
    .credential(new KeyCredential(key))
    .endpoint(endpoint)
    .buildClient();

With DefaultAzureCredential

import com.azure.core.credential.TokenCredential;
import com.azure.identity.AzureIdentityEnvVars;
import com.azure.identity.DefaultAzureCredentialBuilder;
import com.azure.identity.ManagedIdentityCredentialBuilder;

TokenCredential credential = new DefaultAzureCredentialBuilder()
    .requireEnvVars(AzureIdentityEnvVars.AZURE_TOKEN_CREDENTIALS)
    .build();
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/java/api/overview/azure/identity-readme?view=azure-java-stable#credential-classes
// TokenCredential credential = new ManagedIdentityCredentialBuilder().build();

ContentSafetyClient client = new ContentSafetyClientBuilder()
    .credential(credential)
    .endpoint(endpoint)
    .buildClient();

Key Concepts

Harm Categories

CategoryDescription
HateDiscriminatory language based on identity groups
SexualSexual content, relationships, acts
ViolencePhysical harm, weapons, injury
Self-harmSelf-injury, suicide-related content

Severity Levels

  • Text: 0-7 scale (default outputs 0, 2, 4, 6)
  • Image: 0, 2, 4, 6 (trimmed scale)

Core Patterns

Analyze Text

import com.azure.ai.contentsafety.models.*;

AnalyzeTextResult result = contentSafetyClient.analyzeText(
    new AnalyzeTextOptions("This is text to analyze"));

for (TextCategoriesAnalysis category : result.getCategoriesAnalysis()) {
    System.out.printf("Category: %s, Severity: %d%n",
        category.getCategory(),
        category.getSeverity());
}

Analyze Text with Options

AnalyzeTextOptions options = new AnalyzeTextOptions("Text to analyze")
    .setCategories(Arrays.asList(
        TextCategory.HATE,
        TextCategory.VIOLENCE))
    .setOutputType(AnalyzeTextOutputType.EIGHT_SEVERITY_LEVELS);

AnalyzeTextResult result = contentSafetyClient.analyzeText(options);

Analyze Text with Blocklist

AnalyzeTextOptions options = new AnalyzeTextOptions("I h*te you and want to k*ll you")
    .setBlocklistNames(Arrays.asList("my-blocklist"))
    .setHaltOnBlocklistHit(true);

AnalyzeTextResult result = contentSafetyClient.analyzeText(options);

if (result.getBlocklistsMatch() != null) {
    for (TextBlocklistMatch match : result.getBlocklistsMatch()) {
        System.out.printf("Blocklist: %s, Item: %s, Text: %s%n",
            match.getBlocklistName(),
            match.getBlocklistItemId(),
            match.getBlocklistItemText());
    }
}

Analyze Image

import com.azure.ai.contentsafety.models.*;
import com.azure.core.util.BinaryData;
import java.nio.file.Files;
import java.nio.file.Paths;

// From file
byte[] imageBytes = Files.readAllBytes(Paths.get("image.png"));
ContentSafetyImageData imageData = new ContentSafetyImageData()
    .setContent(BinaryData.fromBytes(imageBytes));

AnalyzeImageResult result = contentSafetyClient.analyzeImage(
    new AnalyzeImageOptions(imageData));

for (ImageCategoriesAnalysis category : result.getCategoriesAnalysis()) {
    System.out.printf("Category: %s, Severity: %d%n",
        category.getCategory(),
        category.getSeverity());
}

Analyze Image from URL

ContentSafetyImageData imageData = new ContentSafetyImageData()
    .setBlobUrl("https://example.com/image.jpg");

AnalyzeImageResult result = contentSafetyClient.analyzeImage(
    new AnalyzeImageOptions(imageData));

Blocklist Management

Create or Update Blocklist

import com.azure.core.http.rest.RequestOptions;
import com.azure.core.http.rest.Response;
import com.azure.core.util.BinaryData;
import java.util.Map;

Map<String, String> description = Map.of("description", "Custom blocklist");
BinaryData resource = BinaryData.fromObject(description);

Response<BinaryData> response = blocklistClient.createOrUpdateTextBlocklistWithResponse(
    "my-blocklist", resource, new RequestOptions());

if (response.getStatusCode() == 201) {
    System.out.println("Blocklist created");
} else if (response.getStatusCode() == 200) {
    System.out.println("Blocklist updated");
}

Add Block Items

import com.azure.ai.contentsafety.models.*;
import java.util.Arrays;

List<TextBlocklistItem> items = Arrays.asList(
    new TextBlocklistItem("badword1").setDescription("Offensive term"),
    new TextBlocklistItem("badword2").setDescription("Another term")
);

AddOrUpdateTextBlocklistItemsResult result = blocklistClient.addOrUpdateBlocklistItems(
    "my-blocklist",
    new AddOrUpdateTextBlocklistItemsOptions(items));

for (TextBlocklistItem item : result.getBlocklistItems()) {
    System.out.printf("Added: %s (ID: %s)%n",
        item.getText(),
        item.getBlocklistItemId());
}

List Blocklists

PagedIterable<TextBlocklist> blocklists = blocklistClient.listTextBlocklists();

for (TextBlocklist blocklist : blocklists) {
    System.out.printf("Blocklist: %s, Description: %s%n",
        blocklist.getName(),
        blocklist.getDescription());
}

Get Blocklist

TextBlocklist blocklist = blocklistClient.getTextBlocklist("my-blocklist");
System.out.println("Name: " + blocklist.getName());

List Block Items

PagedIterable<TextBlocklistItem> items = 
    blocklistClient.listTextBlocklistItems("my-blocklist");

for (TextBlocklistItem item : items) {
    System.out.printf("ID: %s, Text: %s%n",
        item.getBlocklistItemId(),
        item.getText());
}

Remove Block Items

List<String> itemIds = Arrays.asList("item-id-1", "item-id-2");

blocklistClient.removeBlocklistItems(
    "my-blocklist",
    new RemoveTextBlocklistItemsOptions(itemIds));

Delete Blocklist

blocklistClient.deleteTextBlocklist("my-blocklist");

Error Handling

import com.azure.core.exception.HttpResponseException;

try {
    contentSafetyClient.analyzeText(new AnalyzeTextOptions("test"));
} catch (HttpResponseException e) {
    System.out.println("Status: " + e.getResponse().getStatusCode());
    System.out.println("Error: " + e.getMessage());
    // Common codes: InvalidRequestBody, ResourceNotFound, TooManyRequests
}

Environment Variables

CONTENT_SAFETY_ENDPOINT=https://<resource>.cognitiveservices.azure.com/ # Required for all auth methods
CONTENT_SAFETY_KEY=<your-api-key> # Only required for AzureKeyCredential auth
AZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production

Best Practices

  1. Blocklist Delay: Changes take ~5 minutes to take effect
  2. Category Selection: Only request needed categories to reduce latency
  3. Severity Thresholds: Typically block severity >= 4 for strict moderation
  4. Batch Processing: Process multiple items in parallel for throughput
  5. Caching: Cache blocklist results where appropriate

Trigger Phrases

  • "content safety Java"
  • "content moderation Azure"
  • "analyze text safety"
  • "image moderation Java"
  • "blocklist management"
  • "hate speech detection"
  • "harmful content filter"

Mais skills de microsoft

oss-growth
microsoft
Persona de growth hacker OSS
agent-framework-azure-ai-py
microsoft
Crie agentes do Azure AI Foundry usando o SDK Python do Microsoft Agent Framework (agent-framework-azure-ai). Use ao criar agentes persistentes com AzureAIAgentsProvider, usando ferramentas hospedadas (interpretador de código, pesquisa de arquivos, pesquisa na web), integrando servidores MCP, gerenciando threads de conversa ou implementando respostas em streaming. Abrange ferramentas de função, saídas estruturadas e agentes com múltiplas ferramentas.
development
airunway-aks-setup
microsoft
Configure o AI Runway no AKS — do cluster vazio ao modelo em execução. Abrange verificação do cluster, instalação do controlador, avaliação de GPU, configuração do provedor e primeira implantação. QUANDO: "configurar AI Runway", "integrar cluster AKS", "instalar AI Runway", "configuração do airunway", "implantar modelo no AKS", "inferência GPU no AKS", "configuração KAITO no AKS", "executar LLM no AKS", "vLLM no AKS", "configurar serviço de modelo no AKS", "controlador AI Runway".
devops
appinsights-instrumentation
microsoft
Orientação para instrumentar aplicações web com Azure Application Insights. Fornece padrões de telemetria, configuração de SDK e referências de configuração. QUANDO: como instrumentar o app, SDK do App Insights, padrões de telemetria, o que é App Insights, orientação sobre Application Insights, exemplos de instrumentação, melhores práticas de APM.
devops
applicationinsights-web-ts
microsoft
Instrumente aplicativos de navegador/web com o SDK JavaScript do Application Insights (@microsoft/applicationinsights-web). Use para Real User Monitoring (RUM) — visualizações de página, cliques, dependências AJAX/fetch, exceções, eventos personalizados e rastreamentos de agentes GenAI no lado do navegador correlacionados a rastreamentos OpenTelemetry no backend. Abrange o Script de Carregamento do SDK e a configuração via npm, extensões de frameworks (React, React Native, Angular), Click Analytics, inicializadores de telemetria e convenções semânticas GenAI do OTel para spans de agente/ferramenta/modelo emitidos pelo navegador.
devops
azure-ai-anomalydetector-java
microsoft
Crie aplicativos de detecção de anomalias com o SDK do Azure AI Anomaly Detector para Java. Use ao implementar detecção de anomalias univariada/multivariada, análise de séries temporais ou monitoramento com IA.
development
azure-ai-language-conversations-py
microsoft
Implemente o reconhecimento de linguagem conversacional (CLU) usando o SDK Python azure-ai-language-conversations. Use ao trabalhar com ConversationAnalysisClient para analisar intenção e entidades de conversas, criar recursos de NLP ou integrar o reconhecimento de linguagem em aplicativos.
development
azure-ai-ml-py
microsoft
SDK v2 do Azure Machine Learning para Python. Use para workspaces de ML, jobs, modelos, conjuntos de dados, computação e pipelines. Gatilhos: "azure-ai-ml", "MLClient", "workspace", "registro de modelos", "jobs de treinamento", "conjuntos de dados".
development