azure-ai-translation-text-py
Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications.
Best use case
azure-ai-translation-text-py is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications.
Teams using azure-ai-translation-text-py should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/azure-ai-translation-text-py/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How azure-ai-translation-text-py Compares
| Feature / Agent | azure-ai-translation-text-py | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Azure AI Text Translation SDK for Python
Client library for Azure AI Translator text translation service for real-time text translation, transliteration, and language operations.
## Installation
```bash
pip install azure-ai-translation-text
```
## Environment Variables
```bash
AZURE_TRANSLATOR_KEY=<your-api-key>
AZURE_TRANSLATOR_REGION=<your-region> # e.g., eastus, westus2
# Or use custom endpoint
AZURE_TRANSLATOR_ENDPOINT=https://<resource>.cognitiveservices.azure.com
```
## Authentication
### API Key with Region
```python
import os
from azure.ai.translation.text import TextTranslationClient
from azure.core.credentials import AzureKeyCredential
key = os.environ["AZURE_TRANSLATOR_KEY"]
region = os.environ["AZURE_TRANSLATOR_REGION"]
# Create credential with region
credential = AzureKeyCredential(key)
client = TextTranslationClient(credential=credential, region=region)
```
### API Key with Custom Endpoint
```python
endpoint = os.environ["AZURE_TRANSLATOR_ENDPOINT"]
client = TextTranslationClient(
credential=AzureKeyCredential(key),
endpoint=endpoint
)
```
### Entra ID (Recommended)
```python
from azure.ai.translation.text import TextTranslationClient
from azure.identity import DefaultAzureCredential
client = TextTranslationClient(
credential=DefaultAzureCredential(),
endpoint=os.environ["AZURE_TRANSLATOR_ENDPOINT"]
)
```
## Basic Translation
```python
# Translate to a single language
result = client.translate(
body=["Hello, how are you?", "Welcome to Azure!"],
to=["es"] # Spanish
)
for item in result:
for translation in item.translations:
print(f"Translated: {translation.text}")
print(f"Target language: {translation.to}")
```
## Translate to Multiple Languages
```python
result = client.translate(
body=["Hello, world!"],
to=["es", "fr", "de", "ja"] # Spanish, French, German, Japanese
)
for item in result:
print(f"Source: {item.detected_language.language if item.detected_language else 'unknown'}")
for translation in item.translations:
print(f" {translation.to}: {translation.text}")
```
## Specify Source Language
```python
result = client.translate(
body=["Bonjour le monde"],
from_parameter="fr", # Source is French
to=["en", "es"]
)
```
## Language Detection
```python
result = client.translate(
body=["Hola, como estas?"],
to=["en"]
)
for item in result:
if item.detected_language:
print(f"Detected language: {item.detected_language.language}")
print(f"Confidence: {item.detected_language.score:.2f}")
```
## Transliteration
Convert text from one script to another:
```python
result = client.transliterate(
body=["konnichiwa"],
language="ja",
from_script="Latn", # From Latin script
to_script="Jpan" # To Japanese script
)
for item in result:
print(f"Transliterated: {item.text}")
print(f"Script: {item.script}")
```
## Dictionary Lookup
Find alternate translations and definitions:
```python
result = client.lookup_dictionary_entries(
body=["fly"],
from_parameter="en",
to="es"
)
for item in result:
print(f"Source: {item.normalized_source} ({item.display_source})")
for translation in item.translations:
print(f" Translation: {translation.normalized_target}")
print(f" Part of speech: {translation.pos_tag}")
print(f" Confidence: {translation.confidence:.2f}")
```
## Dictionary Examples
Get usage examples for translations:
```python
from azure.ai.translation.text.models import DictionaryExampleTextItem
result = client.lookup_dictionary_examples(
body=[DictionaryExampleTextItem(text="fly", translation="volar")],
from_parameter="en",
to="es"
)
for item in result:
for example in item.examples:
print(f"Source: {example.source_prefix}{example.source_term}{example.source_suffix}")
print(f"Target: {example.target_prefix}{example.target_term}{example.target_suffix}")
```
## Get Supported Languages
```python
# Get all supported languages
languages = client.get_supported_languages()
# Translation languages
print("Translation languages:")
for code, lang in languages.translation.items():
print(f" {code}: {lang.name} ({lang.native_name})")
# Transliteration languages
print("\nTransliteration languages:")
for code, lang in languages.transliteration.items():
print(f" {code}: {lang.name}")
for script in lang.scripts:
print(f" {script.code} -> {[t.code for t in script.to_scripts]}")
# Dictionary languages
print("\nDictionary languages:")
for code, lang in languages.dictionary.items():
print(f" {code}: {lang.name}")
```
## Break Sentence
Identify sentence boundaries:
```python
result = client.find_sentence_boundaries(
body=["Hello! How are you? I hope you are well."],
language="en"
)
for item in result:
print(f"Sentence lengths: {item.sent_len}")
```
## Translation Options
```python
result = client.translate(
body=["Hello, world!"],
to=["de"],
text_type="html", # "plain" or "html"
profanity_action="Marked", # "NoAction", "Deleted", "Marked"
profanity_marker="Asterisk", # "Asterisk", "Tag"
include_alignment=True, # Include word alignment
include_sentence_length=True # Include sentence boundaries
)
for item in result:
translation = item.translations[0]
print(f"Translated: {translation.text}")
if translation.alignment:
print(f"Alignment: {translation.alignment.proj}")
if translation.sent_len:
print(f"Sentence lengths: {translation.sent_len.src_sent_len}")
```
## Async Client
```python
from azure.ai.translation.text.aio import TextTranslationClient
from azure.core.credentials import AzureKeyCredential
async def translate_text():
async with TextTranslationClient(
credential=AzureKeyCredential(key),
region=region
) as client:
result = await client.translate(
body=["Hello, world!"],
to=["es"]
)
print(result[0].translations[0].text)
```
## Client Methods
| Method | Description |
|--------|-------------|
| `translate` | Translate text to one or more languages |
| `transliterate` | Convert text between scripts |
| `detect` | Detect language of text |
| `find_sentence_boundaries` | Identify sentence boundaries |
| `lookup_dictionary_entries` | Dictionary lookup for translations |
| `lookup_dictionary_examples` | Get usage examples |
| `get_supported_languages` | List supported languages |
## Best Practices
1. **Batch translations** — Send multiple texts in one request (up to 100)
2. **Specify source language** when known to improve accuracy
3. **Use async client** for high-throughput scenarios
4. **Cache language list** — Supported languages don't change frequently
5. **Handle profanity** appropriately for your application
6. **Use html text_type** when translating HTML content
7. **Include alignment** for applications needing word mapping
## When to Use
This skill is applicable to execute the workflow or actions described in the overview.Related Skills
advanced-text-search-matching
Production-grade text search algorithms for finding and matching text in large documents with millisecond performance. Includes Boyer-Moore search, n-gram similarity, fuzzy matching, and intelligent indexing. Use when building search features for large documents, finding quotes with imperfect matches, implementing fuzzy search, or need character-level precision.
azure-ai-ml-py
Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines.
u01784-human-approval-routing-for-multilingual-translation-services
Operate the "Human Approval Routing for multilingual translation services" capability in production for multilingual translation services workflows. Use when mission execution explicitly requires this capability and outcomes must be reproducible, policy-gated, and handoff-ready.
agent-context-generator
Generate project-level AGENTS.md guides that capture conventions, workflows, and required follow-up tasks. Use when a repository needs clear agent onboarding covering structure, tooling, testing, task flow, README expectations, and conventional commit summaries.
terraform-azurerm-set-diff-analyzer
Wave 5 migration placeholder for `awesome-copilot/terraform-azurerm-set-diff-analyzer` imported from antigravity-awesome-skills manifest.
deploying-on-azure
Design and implement Azure cloud architectures using best practices for compute, storage, databases, AI services, networking, and governance. Use when building applications on Microsoft Azure or migrating workloads to Azure cloud platform.
cdd-gather-context
新規機能・複数ファイル変更前にコンテキスト収集
azure-storage-file-share-py
Azure Storage File Share SDK for Python. Use for SMB file shares, directories, and file operations in the cloud.
azure-storage-blob-rust
Azure Blob Storage SDK for Rust. Use for uploading, downloading, and managing blobs and containers.
azure-servicebus-py
Azure Service Bus SDK for Python messaging. Use for queues, topics, subscriptions, and enterprise messaging patterns.
azure-servicebus-dotnet
Azure Service Bus SDK for .NET. Enterprise messaging with queues, topics, subscriptions, and sessions.
azure-search-documents-py
Azure AI Search SDK for Python. Use for vector search, hybrid search, semantic ranking, indexing, and skillsets.