azure-ai-contentsafety-ts
microsoft/skills
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。
...展开全部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 | 低 | 审查或允许但带有警告 |
| 4 | 中 | 屏蔽或要求人工审查 |
| 6 | 高 | 立即屏蔽 |
输出类型:
FourSeverityLevels(默认):返回 0, 2, 4, 6EightSeverityLevels: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
- 始终使用 isUnexpected() - 用于错误处理的类型守卫
- 设置适当的阈值 - 不同类别可能需要不同的严重程度阈值
- 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
- 记录审核决策 - 保留合规性的审计轨迹
- 处理边缘情况 - 空文本、超长文本、不支持的图像格式
---
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
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