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Azure AI Document Translation SDK for batch translation of documents with format preservation. Use for translating Word, PDF, Excel, PowerPoint, and other document formats at scale.
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Azure AI Document Translation SDK for batch translation of documents with format preservation. Use for translating Word, PDF, Excel, PowerPoint, and other document formats at scale. 📦 Ships with agentic-awesome-skills
</> SKILL.md
azure-ai-translation-document-py.SKILL.md
---
name : azure-ai-translation-document-py
description : Azure AI Document Translation SDK for batch translation of documents with format preservation. Use for translating Word, PDF, Excel, PowerPoint, and other document formats at scale.
risk : unknown
source : community
date_added : '2026-02-27'
---
# Azure AI Document Translation SDK for Python
Client library for Azure AI Translator document translation service for batch document translation with format preservation.
## Installation
```bash
pip install azure-ai-translation-document
```
## Environment Variables
```bash
AZURE_DOCUMENT_TRANSLATION_ENDPOINT=https://<resource>.cognitiveservices.azure.com
AZURE_DOCUMENT_TRANSLATION_KEY=<your-api-key> # If using API key
# Storage for source and target documents
AZURE_SOURCE_CONTAINER_URL=https://<storage>.blob.core.windows.net/<container>?<sas>
AZURE_TARGET_CONTAINER_URL=https://<storage>.blob.core.windows.net/<container>?<sas>
```
## Authentication
### API Key
```python
import os
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from azure.ai.translation.document import DocumentTranslationClient
from azure.core.credentials import AzureKeyCredential
endpoint = os.environ["AZURE_DOCUMENT_TRANSLATION_ENDPOINT"]
key = os.environ["AZURE_DOCUMENT_TRANSLATION_KEY"]
client = DocumentTranslationClient(endpoint, AzureKeyCredential(key))
```
### Entra ID (Recommended)
```python
from azure.ai.translation.document import DocumentTranslationClient
from azure.identity import DefaultAzureCredential
client = DocumentTranslationClient(
endpoint=os.environ["AZURE_DOCUMENT_TRANSLATION_ENDPOINT"],
credential=DefaultAzureCredential()
)
```
## Basic Document Translation
```python
from azure.ai.translation.document import DocumentTranslationInput, TranslationTarget
source_url = os.environ["AZURE_SOURCE_CONTAINER_URL"]
target_url = os.environ["AZURE_TARGET_CONTAINER_URL"]
# Start translation job
poller = client.begin_translation(
inputs=[
DocumentTranslationInput(
source_url=source_url,
targets=[
TranslationTarget(
target_url=target_url,
language="es" # Translate to Spanish
)
]
)
]
)
# Wait for completion
result = poller.result()
print(f"Status: {poller.status()}")
print(f"Documents translated: {poller.details.documents_succeeded_count}")
print(f"Documents failed: {poller.details.documents_failed_count}")
```
## Multiple Target Languages
```python
poller = client.begin_translation(
inputs=[
DocumentTranslationInput(
source_url=source_url,
targets=[
TranslationTarget(target_url=target_url_es, language="es"),
TranslationTarget(target_url=target_url_fr, language="fr"),
TranslationTarget(target_url=target_url_de, language="de")
]
)
]
)
```
## Translate Single Document
```python
from azure.ai.translation.document import SingleDocumentTranslationClient
single_client = SingleDocumentTranslationClient(endpoint, AzureKeyCredential(key))
with open("document.docx", "rb") as f:
document_content = f.read()
result = single_client.translate(
body=document_content,
target_language="es",
content_type="application/vnd.openxmlformats-officedocument.wordprocessingml.document"
)
# Save translated document
with open("document_es.docx", "wb") as f:
f.write(result)
```
## Check Translation Status
```python
# Get all translation operations
operations = client.list_translation_statuses()
for op in operations:
print(f"Operation ID: {op.id}")
print(f"Status: {op.status}")
print(f"Created: {op.created_on}")
print(f"Total documents: {op.documents_total_count}")
print(f"Succeeded: {op.documents_succeeded_count}")
print(f"Failed: {op.documents_failed_count}")
```
## List Document Statuses
```python
# Get status of individual documents in a job
operation_id = poller.id
document_statuses = client.list_document_statuses(operation_id)
for doc in document_statuses:
print(f"Document: {doc.source_document_url}")
print(f" Status: {doc.status}")
print(f" Translated to: {doc.translated_to}")
if doc.error:
print(f" Error: {doc.error.message}")
```
## Cancel Translation
```python
# Cancel a running translation
client.cancel_translation(operation_id)
```
## Using Glossary
```python
from azure.ai.translation.document import TranslationGlossary
poller = client.begin_translation(
inputs=[
DocumentTranslationInput(
source_url=source_url,
targets=[
TranslationTarget(
target_url=target_url,
language="es",
glossaries=[
TranslationGlossary(
glossary_url="https://<storage>.blob.core.windows.net/glossary/terms.csv?<sas>",
file_format="csv"
)
]
)
]
)
]
)
```
## Supported Document Formats
```python
# Get supported formats
formats = client.get_supported_document_formats()
for fmt in formats:
print(f"Format: {fmt.format}")
print(f" Extensions: {fmt.file_extensions}")
print(f" Content types: {fmt.content_types}")
```
## Supported Languages
```python
# Get supported languages
languages = client.get_supported_languages()
for lang in languages:
print(f"Language: {lang.name} ({lang.code})")
```
## Async Client
```python
from azure.ai.translation.document.aio import DocumentTranslationClient
from azure.identity.aio import DefaultAzureCredential
async def translate_documents():
async with DocumentTranslationClient(
endpoint=endpoint,
credential=DefaultAzureCredential()
) as client:
poller = await client.begin_translation(inputs=[...])
result = await poller.result()
```
## Supported Formats
| Category | Formats |
|----------|---------|
| Documents | DOCX, PDF, PPTX, XLSX, HTML, TXT, RTF |
| Structured | CSV, TSV, JSON, XML |
| Localization | XLIFF, XLF, MHTML |
## Storage Requirements
- Source and target containers must be Azure Blob Storage
- Use SAS tokens with appropriate permissions:
- Source: Read, List
- Target: Write, List
## Best Practices
1. **Use SAS tokens** with minimal required permissions
2. **Monitor long-running operations** with `poller.status()`
3. **Handle document-level errors** by iterating document statuses
4. **Use glossaries** for domain-specific terminology
5. **Separate target containers** for each language
6. **Use async client** for multiple concurrent jobs
7. **Check supported formats** before submitting documents
## When to Use
This skill is applicable to execute the workflow or actions described in the overview.
## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
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