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집 Skill 보안 azure-ai-contentsafety-java

azure-ai-contentsafety-java

microsoft/skills microsoft/skills

Java용 Azure AI 콘텐츠 안전성 SDK를 사용하여 텍스트와 이미지의 유해한 콘텐츠를 분석하세요. 차단 목록 관리를 통해 혐오, 폭력, 성적 콘텐츠 및 자해 관련 콘텐츠 탐지를 지원합니다.

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업데이트 된 시간 2026년 9월 14일

Java용 Azure AI 콘텐츠 안전성 SDK

Java용 Azure AI 콘텐츠 안전성 SDK를 사용하여 콘텐츠 검토 애플리케이션을 구축하세요.

설치


    com.azure
    azure-ai-contentsafety
    1.1.0-beta.1

클라이언트 생성

API 키 사용

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();

DefaultAzureCredential 사용 시

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();
// 또는 프로덕션 환경에서 특정 자격 증명을 직접 사용:
// https://learn.microsoft.com/java/api/overview/azure/identity-readme?view=azure-java-stable#credential-classes 참조
// TokenCredential credential = new ManagedIdentityCredentialBuilder().build();

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

핵심 개념

유해성 범주

범주 설명
증오 정체성 집단에 기반한 차별적 언어
성적 성적 콘텐츠, 관계, 행위
폭력 신체적 피해, 무기, 부상
자해 자해, 자살 관련 콘텐츠

심각도 수준

  • 텍스트: 0~7점 척도 (기본 출력값: 0, 2, 4, 6)
  • 이미지: 0, 2, 4, 6 (축소된 척도)

핵심 패턴

텍스트 분석

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("카테고리: %s, 심각도: %d%n",
        category.getCategory(),
        category.getSeverity());
}

옵션을 사용하여 텍스트 분석하기

AnalyzeTextOptions options = new AnalyzeTextOptions("분석할 텍스트")
    .setCategories(Arrays.asList(
        TextCategory.HATE,
        TextCategory.VIOLENCE))
    .setOutputType(AnalyzeTextOutputType.EIGHT_SEVERITY_LEVELS);

AnalyzeTextResult result = contentSafetyClient.analyzeText(options);

차단 목록을 사용하여 텍스트 분석

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("차단 목록: %s, 항목: %s, 텍스트: %s%n",
            match.getBlocklistName(),
            match.getBlocklistItemId(),
            match.getBlocklistItemText());
    }
}

이미지 분석

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

// 파일에서 불러오기
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("카테고리: %s, 심각도: %d%n",
        category.getCategory(),
        category.getSeverity());
}

URL에서 이미지 분석

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

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

차단 목록 관리

차단 목록 생성 또는 업데이트

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 description = Map.of("description", "사용자 지정 차단 목록");
BinaryData resource = BinaryData.fromObject(description);

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

if (response.getStatusCode() == 201) {
    System.out.println("차단 목록 생성됨");
} else if (response.getStatusCode() == 200) {
    System.out.println("차단 목록 업데이트됨");
}

차단 항목 추가

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

List items = Arrays.asList(
    new TextBlocklistItem("badword1").setDescription("모욕적인 단어"),
    new TextBlocklistItem("badword2").setDescription("또 다른 단어")
);

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

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

차단 목록 열기

PagedIterable blocklists = blocklistClient.listTextBlocklists();

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

차단 목록 가져오기

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

차단 항목 나열

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

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

블록 항목 제거

 itemIds = Arrays.asList("item-id-1", "item-id-2");

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

차단 목록 삭제

blocklistClient.deleteTextBlocklist("my-blocklist");

오류 처리

import com.azure.core.exception.HttpResponseException;

try {
    contentSafetyClient.analyzeText(new AnalyzeTextOptions("test"));
} catch (HttpResponseException e) {
    System.out.println("상태: " + e.getResponse().getStatusCode());
    System.out.println("오류: " + e.getMessage());
    // 일반적인 오류 코드: InvalidRequestBody, ResourceNotFound, TooManyRequests
}

환경 변수

 CONTENT_SAFETY_ENDPOINT=https://.cognitiveservices.azure.com/ # 모든 인증 방식에 필수
CONTENT_SAFETY_ENDPOINT=https:// .cognitiveservices.azure.com/ # 모든 인증 방식에 필수
AZURE_TOKEN_CREDENTIALS=prod  # 프로덕션 환경에서 DefaultAzureCredential을 사용하는 경우에만 필수

모범 사례

  1. 차단 목록 지연: 변경 사항이 적용되는 데 약 5분이 소요됩니다
  2. 카테고리 선택: 지연 시간을 줄이기 위해 필요한 카테고리만 요청하십시오
  3. 중요도 임계값: 엄격한 검토를 위해서는 일반적으로 중요도 4 이상인 항목을 차단하십시오
  4. 일괄 처리: 처리량을 높이기 위해 여러 항목을 병렬로 처리하십시오
  5. 캐싱: 적절한 경우 차단 목록 결과를 캐싱하십시오

트리거 문구

  • "콘텐츠 안전성 Java"
  • "콘텐츠 검토 Azure"
  • "텍스트 안전성 분석"
  • "이미지 검토 Java"
  • "차단 목록 관리"
  • "혐오 발언 탐지"
  • "유해 콘텐츠 필터"
GitHub에서 보기
---
name: azure-ai-contentsafety-java
description: Analyze text and images for harmful content using Azure AI Content Safety SDK for Java. Supports hate, violence, sexual content, and self-harm detection with blocklist management.
license: MIT
---

# Azure AI Content Safety SDK for Java

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

## Installation

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

## Client Creation

### With API Key

```java
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

```java
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
| Category | Description |
|----------|-------------|
| Hate | Discriminatory language based on identity groups |
| Sexual | Sexual content, relationships, acts |
| Violence | Physical harm, weapons, injury |
| Self-harm | Self-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

```java
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

```java
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

```java
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

```java
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

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

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

## Blocklist Management

### Create or Update Blocklist

```java
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

```java
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

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

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

### Get Blocklist

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

### List Block Items

```java
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

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

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

### Delete Blocklist

```java
blocklistClient.deleteTextBlocklist("my-blocklist");
```

## Error Handling

```java
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

```bash
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"

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azure-ai-contentsafety-java 설치

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저장소를 클론하고 스킬 파일을 프로젝트에 복사하세요.

git clone https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-java/skills/azure-ai-contentsafety-java # Copy SKILL.md to your .claude/skills/ directory

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