azure-ai-translation-document-py
Lets your agent translate entire documents. Good for translating files like Word or PDF in bulk.
What it does
This service translates entire documents (like Word, PDF, Excel) from one language to another, keeping the original formatting. It's ideal for translating many documents at once.
When to use it
- ✓Translate an entire PDF report to another language.
- ✓Convert multiple presentation files (PPTX) to different languages.
- ✓Translate an Excel spreadsheet (XLSX) with data for analysis into another language.
Example of what to ask your AI
“Translate all documents in the 'originals' folder to Spanish and save them in the 'translated' folder.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
You send the documents you want to translate and specify the target language. The service processes all of them and returns the translated documents in the same format.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill azure-ai-translation-document-pyOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/azure-ai-translation-document-py/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Azure AI Document Translation SDK for Python
Client library for Azure AI Translator document translation service for batch document translation with format preservation.
Installation
pip install azure-ai-translation-document
Environment Variables
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
import os
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)
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
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
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
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
# 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
# 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
# Cancel a running translation
client.cancel_translation(operation_id)
Using Glossary
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(
…
FAQ
What file types can I translate?
You can translate documents like Word (.docx), PDF, Excel (.xlsx), PowerPoint (.pptx), as well as text files (.txt), HTML, CSV, JSON, and others.
Do I need to put the files in a specific place?
Yes, both the original and translated files need to be in Azure Blob Storage containers.
Can I use a glossary for specific terms?
Yes, you can provide a glossary to ensure technical or specific terms are translated consistently.
Details
Original description by the author
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.
Popularity
- GitHub stars
- 48k
- Ranking position
- #2282
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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