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azure-ai-contentsafety-ts

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使用 Azure AI 内容安全服务分析文本和图像中的有害内容,并支持自定义黑名单和严重程度阈值。

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更新时间 2026-09-15

Azure AI 内容安全 TypeScript REST SDK

使用可自定义的屏蔽列表分析文本和图像中的有害内容。

安装

npm install @azure-rest/ai-content-safety @azure/identity @azure/core-auth

环境变量

CONTENT_SAFETY_ENDPOINT=https://<resource>.cognitiveservices.azure.com
CONTENT_SAFETY_KEY=<api-key>
AZURE_TOKEN_CREDENTIALS=prod # 仅在生产环境中使用 DefaultAzureCredential 时需要
</api-key></resource>

身份验证

重要提示:这是一个 REST 客户端。ContentSafetyClient 是一个函数,而不是类。

API 密钥

import ContentSafetyClient from "@azure-rest/ai-content-safety";
import { AzureKeyCredential } from "@azure/core-auth";

const client = ContentSafetyClient(
  process.env.CONTENT_SAFETY_ENDPOINT!,
  new AzureKeyCredential(process.env.CONTENT_SAFETY_KEY!)
);

DefaultAzureCredential

import ContentSafetyClient from "@azure-rest/ai-content-safety";
import { DefaultAzureCredential, ManagedIdentityCredential } from "@azure/identity";

// 本地开发:DefaultAzureCredential。生产环境:设置 AZURE_TOKEN_CREDENTIALS=prod 或 AZURE_TOKEN_CREDENTIALS=<specific_credential>
const credential = new DefaultAzureCredential({requiredEnvVars: ["AZURE_TOKEN_CREDENTIALS"]});
// 或者在生产环境中直接使用特定的凭据:
// 请参阅 https://learn.microsoft.com/javascript/api/overview/azure/identity-readme?view=azure-node-latest#credential-classes
// const credential = new ManagedIdentityCredential();

const client = ContentSafetyClient(
  process.env.CONTENT_SAFETY_ENDPOINT!,
  credential
);
</specific_credential>

分析文本

import ContentSafetyClient, { isUnexpected } from "@azure-rest/ai-content-safety";

const result = await client.path("/text:analyze").post({
  body: {
    text: "要分析的文本内容",
    categories: ["Hate", "Sexual", "Violence", "SelfHarm"],
    outputType: "FourSeverityLevels"  // 或 "EightSeverityLevels"
  }
});

if (isUnexpected(result)) {
  throw result.body;
}

for (const analysis of result.body.categoriesAnalysis) {
  console.log(`${analysis.category}: 严重程度 ${analysis.severity}`);
}

分析图像

Base64 内容

import { readFileSync } from "node:fs";

const imageBuffer = readFileSync("./image.png");
const base64Image = imageBuffer.toString("base64");

const result = await client.path("/image:analyze").post({
  body: {
    image: { content: base64Image }
  }
});

if (isUnexpected(result)) {
  throw result.body;
}

for (const analysis of result.body.categoriesAnalysis) {
  console.log(`${analysis.category}: 严重程度 ${analysis.severity}`);
}

Blob URL

const result = await client.path("/image:analyze").post({
  body: {
    image: { blobUrl: "https://storage.blob.core.windows.net/container/image.png" }
  }
});

屏蔽列表管理

创建屏蔽列表

const result = await client
  .path("/text/blocklists/{blocklistName}", "my-blocklist")
  .patch({
    contentType: "application/merge-patch+json",
    body: {
      description: "禁止术语的自定义屏蔽列表"
    }
  });

if (isUnexpected(result)) {
  throw result.body;
}

console.log(`已创建: ${result.body.blocklistName}`);

向屏蔽列表添加项目

const result = await client
  .path("/text/blocklists/{blocklistName}:addOrUpdateBlocklistItems", "my-blocklist")
  .post({
    body: {
      blocklistItems: [
        { text: "prohibited-term-1", description: "第一个被屏蔽的术语" },
        { text: "prohibited-term-2", description: "第二个被屏蔽的术语" }
      ]
    }
  });

if (isUnexpected(result)) {
  throw result.body;
}

for (const item of result.body.blocklistItems ?? []) {
  console.log(`已添加: ${item.blocklistItemId}`);
}

使用屏蔽列表进行分析

const result = await client.path("/text:analyze").post({
  body: {
    text: "可能包含屏蔽术语的文本",
    blocklistNames: ["my-blocklist"],
    haltOnBlocklistHit: false
  }
});

if (isUnexpected(result)) {
  throw result.body;
}

// 检查屏蔽列表匹配项
if (result.body.blocklistsMatch) {
  for (const match of result.body.blocklistsMatch) {
    console.log(`已屏蔽: "${match.blocklistItemText}" 来自 ${match.blocklistName}`);
  }
}

列出屏蔽列表

const result = await client.path("/text/blocklists").get();

if (isUnexpected(result)) {
  throw result.body;
}

for (const blocklist of result.body.value ?? []) {
  console.log(`${blocklist.blocklistName}: ${blocklist.description}`);
}

删除屏蔽列表

await client.path("/text/blocklists/{blocklistName}", "my-blocklist").delete();

有害类别

类别API 术语描述
仇恨与公平性`Hate`针对身份群体的歧视性语言
色情`Sexual`色情内容、裸体、淫秽物品
暴力`Violence`身体伤害、武器、恐怖主义
自残`SelfHarm`自伤、自杀、饮食失调

严重程度级别

级别风险建议操作
0安全允许
2审查或允许但带有警告
4屏蔽或要求人工审查
6立即屏蔽

输出类型

  • FourSeverityLevels(默认):返回 0, 2, 4, 6
  • EightSeverityLevels:返回 0-7

内容审核助手

import ContentSafetyClient, { 
  isUnexpected, 
  TextCategoriesAnalysisOutput 
} from "@azure-rest/ai-content-safety";

interface ModerationResult {
  isAllowed: boolean;
  flaggedCategories: string[];
  maxSeverity: number;
  blocklistMatches: string[];
}

async function moderateContent(
  client: ReturnType<typeof>,
  text: string,
  maxAllowedSeverity = 2,
  blocklistNames: string[] = []
): Promise<moderationresult> {
  const result = await client.path("/text:analyze").post({
    body: { text, blocklistNames, haltOnBlocklistHit: false }
  });

  if (isUnexpected(result)) {
    throw result.body;
  }

  const flaggedCategories = result.body.categoriesAnalysis
    .filter(c => (c.severity ?? 0) > maxAllowedSeverity)
    .map(c => c.category!);

  const maxSeverity = Math.max(
    ...result.body.categoriesAnalysis.map(c => c.severity ?? 0)
  );

  const blocklistMatches = (result.body.blocklistsMatch ?? [])
    .map(m => m.blocklistItemText!);

  return {
    isAllowed: flaggedCategories.length === 0 && blocklistMatches.length === 0,
    flaggedCategories,
    maxSeverity,
    blocklistMatches
  };
}
</moderationresult></typeof>

API 端点

操作方法路径
分析文本POST`/text:analyze`
分析图像POST`/image:analyze`
创建/更新屏蔽列表PATCH`/text/blocklists/{blocklistName}`
列出屏蔽列表GET`/text/blocklists`
删除屏蔽列表DELETE`/text/blocklists/{blocklistName}`
添加屏蔽列表项目POST`/text/blocklists/{blocklistName}:addOrUpdateBlocklistItems`
列出屏蔽列表项目GET`/text/blocklists/{blocklistName}/blocklistItems`
移除屏蔽列表项目POST`/text/blocklists/{blocklistName}:removeBlocklistItems`

关键类型

import ContentSafetyClient, {
  isUnexpected,
  AnalyzeTextParameters,
  AnalyzeImageParameters,
  TextCategoriesAnalysisOutput,
  ImageCategoriesAnalysisOutput,
  TextBlocklist,
  TextBlocklistItem
} from "@azure-rest/ai-content-safety";

最佳实践

  1. 始终使用 isUnexpected() - 用于错误处理的类型守卫
  2. 设置适当的阈值 - 不同类别可能需要不同的严重程度阈值
  3. 使用屏蔽列表处理特定领域的术语 - 用自定义规则补充 AI 检测
  4. 记录审核决策 - 保留合规性的审计轨迹
  5. 处理边缘情况 - 空文本、超长文本、不支持的图像格式
在 GitHub 上查看
---
name: azure-ai-contentsafety-ts
description: Analyze text and images for harmful content using Azure AI Content Safety, with customizable blocklists and severity thresholds.
license: MIT
---

# Azure AI Content Safety REST SDK for TypeScript

Analyze text and images for harmful content with customizable blocklists.

## Installation

```bash
npm install @azure-rest/ai-content-safety @azure/identity @azure/core-auth
```

## Environment Variables

```bash
CONTENT_SAFETY_ENDPOINT=https://<resource>.cognitiveservices.azure.com
CONTENT_SAFETY_KEY=<api-key>
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production
```

## Authentication

**Important**: This is a REST client. `ContentSafetyClient` is a **function**, not a class.

### API Key

```typescript
import ContentSafetyClient from "@azure-rest/ai-content-safety";
import { AzureKeyCredential } from "@azure/core-auth";

const client = ContentSafetyClient(
  process.env.CONTENT_SAFETY_ENDPOINT!,
  new AzureKeyCredential(process.env.CONTENT_SAFETY_KEY!)
);
```

### DefaultAzureCredential

```typescript
import ContentSafetyClient from "@azure-rest/ai-content-safety";
import { DefaultAzureCredential, ManagedIdentityCredential } from "@azure/identity";

// Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
const credential = new DefaultAzureCredential({requiredEnvVars: ["AZURE_TOKEN_CREDENTIALS"]});
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/javascript/api/overview/azure/identity-readme?view=azure-node-latest#credential-classes
// const credential = new ManagedIdentityCredential();

const client = ContentSafetyClient(
  process.env.CONTENT_SAFETY_ENDPOINT!,
  credential
);
```

## Analyze Text

```typescript
import ContentSafetyClient, { isUnexpected } from "@azure-rest/ai-content-safety";

const result = await client.path("/text:analyze").post({
  body: {
    text: "Text content to analyze",
    categories: ["Hate", "Sexual", "Violence", "SelfHarm"],
    outputType: "FourSeverityLevels"  // or "EightSeverityLevels"
  }
});

if (isUnexpected(result)) {
  throw result.body;
}

for (const analysis of result.body.categoriesAnalysis) {
  console.log(`${analysis.category}: severity ${analysis.severity}`);
}
```

## Analyze Image

### Base64 Content

```typescript
import { readFileSync } from "node:fs";

const imageBuffer = readFileSync("./image.png");
const base64Image = imageBuffer.toString("base64");

const result = await client.path("/image:analyze").post({
  body: {
    image: { content: base64Image }
  }
});

if (isUnexpected(result)) {
  throw result.body;
}

for (const analysis of result.body.categoriesAnalysis) {
  console.log(`${analysis.category}: severity ${analysis.severity}`);
}
```

### Blob URL

```typescript
const result = await client.path("/image:analyze").post({
  body: {
    image: { blobUrl: "https://storage.blob.core.windows.net/container/image.png" }
  }
});
```

## Blocklist Management

### Create Blocklist

```typescript
const result = await client
  .path("/text/blocklists/{blocklistName}", "my-blocklist")
  .patch({
    contentType: "application/merge-patch+json",
    body: {
      description: "Custom blocklist for prohibited terms"
    }
  });

if (isUnexpected(result)) {
  throw result.body;
}

console.log(`Created: ${result.body.blocklistName}`);
```

### Add Items to Blocklist

```typescript
const result = await client
  .path("/text/blocklists/{blocklistName}:addOrUpdateBlocklistItems", "my-blocklist")
  .post({
    body: {
      blocklistItems: [
        { text: "prohibited-term-1", description: "First blocked term" },
        { text: "prohibited-term-2", description: "Second blocked term" }
      ]
    }
  });

if (isUnexpected(result)) {
  throw result.body;
}

for (const item of result.body.blocklistItems ?? []) {
  console.log(`Added: ${item.blocklistItemId}`);
}
```

### Analyze with Blocklist

```typescript
const result = await client.path("/text:analyze").post({
  body: {
    text: "Text that might contain blocked terms",
    blocklistNames: ["my-blocklist"],
    haltOnBlocklistHit: false
  }
});

if (isUnexpected(result)) {
  throw result.body;
}

// Check blocklist matches
if (result.body.blocklistsMatch) {
  for (const match of result.body.blocklistsMatch) {
    console.log(`Blocked: "${match.blocklistItemText}" from ${match.blocklistName}`);
  }
}
```

### List Blocklists

```typescript
const result = await client.path("/text/blocklists").get();

if (isUnexpected(result)) {
  throw result.body;
}

for (const blocklist of result.body.value ?? []) {
  console.log(`${blocklist.blocklistName}: ${blocklist.description}`);
}
```

### Delete Blocklist

```typescript
await client.path("/text/blocklists/{blocklistName}", "my-blocklist").delete();
```

## Harm Categories

| Category | API Term | Description |
|----------|----------|-------------|
| Hate and Fairness | `Hate` | Discriminatory language targeting identity groups |
| Sexual | `Sexual` | Sexual content, nudity, pornography |
| Violence | `Violence` | Physical harm, weapons, terrorism |
| Self-Harm | `SelfHarm` | Self-injury, suicide, eating disorders |

## Severity Levels

| Level | Risk | Recommended Action |
|-------|------|-------------------|
| 0 | Safe | Allow |
| 2 | Low | Review or allow with warning |
| 4 | Medium | Block or require human review |
| 6 | High | Block immediately |

**Output Types**:
- `FourSeverityLevels` (default): Returns 0, 2, 4, 6
- `EightSeverityLevels`: Returns 0-7

## Content Moderation Helper

```typescript
import ContentSafetyClient, { 
  isUnexpected, 
  TextCategoriesAnalysisOutput 
} from "@azure-rest/ai-content-safety";

interface ModerationResult {
  isAllowed: boolean;
  flaggedCategories: string[];
  maxSeverity: number;
  blocklistMatches: string[];
}

async function moderateContent(
  client: ReturnType<typeof ContentSafetyClient>,
  text: string,
  maxAllowedSeverity = 2,
  blocklistNames: string[] = []
): Promise<ModerationResult> {
  const result = await client.path("/text:analyze").post({
    body: { text, blocklistNames, haltOnBlocklistHit: false }
  });

  if (isUnexpected(result)) {
    throw result.body;
  }

  const flaggedCategories = result.body.categoriesAnalysis
    .filter(c => (c.severity ?? 0) > maxAllowedSeverity)
    .map(c => c.category!);

  const maxSeverity = Math.max(
    ...result.body.categoriesAnalysis.map(c => c.severity ?? 0)
  );

  const blocklistMatches = (result.body.blocklistsMatch ?? [])
    .map(m => m.blocklistItemText!);

  return {
    isAllowed: flaggedCategories.length === 0 && blocklistMatches.length === 0,
    flaggedCategories,
    maxSeverity,
    blocklistMatches
  };
}
```

## API Endpoints

| Operation | Method | Path |
|-----------|--------|------|
| Analyze Text | POST | `/text:analyze` |
| Analyze Image | POST | `/image:analyze` |
| Create/Update Blocklist | PATCH | `/text/blocklists/{blocklistName}` |
| List Blocklists | GET | `/text/blocklists` |
| Delete Blocklist | DELETE | `/text/blocklists/{blocklistName}` |
| Add Blocklist Items | POST | `/text/blocklists/{blocklistName}:addOrUpdateBlocklistItems` |
| List Blocklist Items | GET | `/text/blocklists/{blocklistName}/blocklistItems` |
| Remove Blocklist Items | POST | `/text/blocklists/{blocklistName}:removeBlocklistItems` |

## Key Types

```typescript
import ContentSafetyClient, {
  isUnexpected,
  AnalyzeTextParameters,
  AnalyzeImageParameters,
  TextCategoriesAnalysisOutput,
  ImageCategoriesAnalysisOutput,
  TextBlocklist,
  TextBlocklistItem
} from "@azure-rest/ai-content-safety";
```

## Best Practices

1. **Always use isUnexpected()** - Type guard for error handling
2. **Set appropriate thresholds** - Different categories may need different severity thresholds
3. **Use blocklists for domain-specific terms** - Supplement AI detection with custom rules
4. **Log moderation decisions** - Keep audit trail for compliance
5. **Handle edge cases** - Empty text, very long text, unsupported image formats

所有文件

0 个文件

安装 azure-ai-contentsafety-ts

将技能文件下载并解压到 .claude/skills/ 目录。

下载ZIP

克隆仓库并复制技能文件到您的项目中。

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

复制 复制
快速设置: 将技能文件夹复制到 .claude/skills/ 目录。Claude 将自动检测并使用该技能。

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