azure-ai-translation-text-py

# 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 Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications. Covers: Azure AI Text Translation SDK for Python, Environment Variables, Or use custom endpoint, Authentication, API Key with Region.