azure-ai-translation-ts
Build translation applications using Azure Translation SDKs for JavaScript (@azure-rest/ai-translation-text, @azure-rest/ai-translation-document). Use when implementing text translation, transliteration, language detection, or batch document translation.
- License 许可
- MIT
- 所属仓库
- microsoft/skills
- 最近更新
- 2026-11-12
- Stars
- ★ 3.2k
- Forks
- 365
01 前言 Front Matter
- name
- azure-ai-translation-ts
- license
- MIT
- metadata
- { "author": "Microsoft", "package": "@azure-rest/ai-translation-text, @azure-rest/ai-translation-document", "version": "1.0.0" }
- description
- Build translation applications using Azure Translation SDKs for JavaScript (@azure-rest/ai-translation-text, @azure-rest/ai-translation-document). Use when implementing text translation, transliteration, language detection, or batch document translation.
02 资源文件 7
- 参考文档references/data-grid-visual.md6.5 KB
- 参考文档references/data-table.md5.6 KB
- 参考文档references/flint-authoring.md12.1 KB
- 参考文档references/formatting.md6.4 KB
- 参考文档references/multi-data-input.md4.8 KB
- 参考文档references/vega-lite-visual.md4.7 KB
- 参考文档references/visual-container.md3.7 KB
03 SKILL.md 正文
Azure Translation SDKs for TypeScript
Text and document translation with REST-style clients.
Installation
# Text translation
npm install @azure-rest/ai-translation-text @azure/identity
# Document translation
npm install @azure-rest/ai-translation-document @azure/identity
Environment Variables
TRANSLATOR_ENDPOINT=https://api.cognitive.microsofttranslator.com
TRANSLATOR_SUBSCRIPTION_KEY=<your-api-key>
TRANSLATOR_REGION=<your-region> # e.g., westus, eastus
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production
Text Translation Client
Authentication
import TextTranslationClient, { TranslatorCredential } from "@azure-rest/ai-translation-text";
// API Key + Region
const credential: TranslatorCredential = {
key: process.env.TRANSLATOR_SUBSCRIPTION_KEY!,
region: process.env.TRANSLATOR_REGION!,
};
const client = TextTranslationClient(process.env.TRANSLATOR_ENDPOINT!, credential);
// Or just credential (uses global endpoint)
const client2 = TextTranslationClient(credential);
Translate Text
import TextTranslationClient, { isUnexpected } from "@azure-rest/ai-translation-text";
const response = await client.path("/translate").post({
body: {
inputs: [
{
text: "Hello, how are you?",
language: "en", // source (optional, auto-detect)
targets: [
{ language: "es" },
{ language: "fr" },
],
},
],
},
});
if (isUnexpected(response)) {
throw response.body.error;
}
for (const result of response.body.value) {
for (const translation of result.translations) {
console.log(`${translation.language}: ${translation.text}`);
}
}
Translate with Options
const response = await client.path("/translate").post({
body: {
inputs: [
{
text: "Hello world",
language: "en",
textType: "Plain", // or "Html"
targets: [
{
language: "de",
profanityAction: "NoAction", // "Marked" | "Deleted"
tone: "formal", // LLM-specific
},
],
},
],
},
});
Get Supported Languages
const response = await client.path("/languages").get();
if (isUnexpected(response)) {
throw response.body.error;
}
// Translation languages
for (const [code, lang] of Object.entries(response.body.translation || {})) {
console.log(`${code}: ${lang.name} (${lang.nativeName})`);
}
Transliterate
const response = await client.path("/transliterate").post({
body: { inputs: [{ text: "这是个测试" }] },
queryParameters: {
language: "zh-Hans",
fromScript: "Hans",
toScript: "Latn",
},
});
if (!isUnexpected(response)) {
for (const t of response.body.value) {
console.log(`${t.script}: ${t.text}`); // Latn: zhè shì gè cè shì
}
}
Detect Language
const response = await client.path("/detect").post({
body: { inputs: [{ text: "Bonjour le monde" }] },
});
if (!isUnexpected(response)) {
for (const result of response.body.value) {
console.log(`Language: ${result.language}, Score: ${result.score}`);
}
}
Document Translation Client
Authentication
import DocumentTranslationClient from "@azure-rest/ai-translation-document";
import { DefaultAzureCredential, ManagedIdentityCredential } from "@azure/identity";
const endpoint = "https://<translator>.cognitiveservices.azure.com";
// 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();
// TokenCredential
const client = DocumentTranslationClient(endpoint, credential);
// API Key
const client2 = DocumentTranslationClient(endpoint, { key: "<api-key>" });
Single Document Translation
import DocumentTranslationClient from "@azure-rest/ai-translation-document";
import { writeFile } from "node:fs/promises";
const response = await client.path("/document:translate").post({
queryParameters: {
targetLanguage: "es",
sourceLanguage: "en", // optional
},
contentType: "multipart/form-data",
body: [
{
name: "document",
body: "Hello, this is a test document.",
filename: "test.txt",
contentType: "text/plain",
},
],
}).asNodeStream();
if (response.status === "200") {
await writeFile("translated.txt", response.body);
}
Batch Document Translation
import { ContainerSASPermissions, BlobServiceClient } from "@azure/storage-blob";
// Generate SAS URLs for source and target containers
const sourceSas = await sourceContainer.generateSasUrl({
permissions: ContainerSASPermissions.parse("rl"),
expiresOn: new Date(Date.now() + 24 * 60 * 60 * 1000),
});
const targetSas = await targetContainer.generateSasUrl({
permissions: ContainerSASPermissions.parse("rwl"),
expiresOn: new Date(Date.now() + 24 * 60 * 60 * 1000),
});
// Start batch translation
const response = await client.path("/document/batches").post({
body: {
inputs: [
{
source: { sourceUrl: sourceSas },
targets: [
{ targetUrl: targetSas, language: "fr" },
],
},
],
},
});
// Get operation ID from header
const operationId = new URL(response.headers["operation-location"])
.pathname.split("/").pop();
Get Translation Status
import { isUnexpected, paginate } from "@azure-rest/ai-translation-document";
const statusResponse = await client.path("/document/batches/{id}", operationId).get();
if (!isUnexpected(statusResponse)) {
const status = statusResponse.body;
console.log(`Status: ${status.status}`);
console.log(`Total: ${status.summary.total}`);
console.log(`Success: ${status.summary.success}`);
}
// List documents with pagination
const docsResponse = await client.path("/document/batches/{id}/documents", operationId).get();
const documents = paginate(client, docsResponse);
for await (const doc of documents) {
console.log(`${doc.id}: ${doc.status}`);
}
Get Supported Formats
const response = await client.path("/document/formats").get();
if (!isUnexpected(response)) {
for (const format of response.body.value) {
console.log(`${format.format}: ${format.fileExtensions.join(", ")}`);
}
}
Key Types
// Text Translation
import type {
TranslatorCredential,
TranslatorTokenCredential,
} from "@azure-rest/ai-translation-text";
// Document Translation
import type {
DocumentTranslateParameters,
StartTranslationDetails,
TranslationStatus,
} from "@azure-rest/ai-translation-document";
Best Practices
- Auto-detect source - Omit
languageparameter to auto-detect - Batch requests - Translate multiple texts in one call for efficiency
- Use SAS tokens - For document translation, use time-limited SAS URLs
- Handle errors - Always check
isUnexpected(response)before accessing body - Regional endpoints - Use regional endpoints for lower latency
04 同仓库更多 Skills
skill-creator
Guide for creating effective skills for AI coding agents working with Azure SDKs and Microsoft Foundry services. Use when creating new skills or updating existing skills.
podcast-generation
Generate AI-powered podcast-style audio narratives using Azure OpenAI's GPT Realtime Mini model via WebSocket. Use when building text-to-speech features, audio narrative generation, podcast creation from content, or integrating with Azure OpenAI Realtime API for real audio output. Covers full-stack implementation from React frontend to Python FastAPI backend with WebSocket streaming.
microsoft-docs
Understand Microsoft technologies by querying official documentation. Use whenever the user asks how something works, wants tutorials, needs configuration options, limits, quotas, or best practices for any Microsoft technology (Azure, .NET, M365, Windows, Power Platform, etc.)—even if they don't mention "docs." If the question is about understanding a concept rather than writing code, this is the right skill.
mcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP), Node/TypeScript (MCP SDK), or C#/.NET (Microsoft MCP SDK).
kql
KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.
github-issue-creator
Convert raw notes, error logs, voice dictation, or screenshots into crisp GitHub-flavored markdown issue reports. Use when the user pastes bug info, error messages, or informal descriptions and wants a structured GitHub issue. Supports images/GIFs for visual evidence.