Azure Document Translation using Access Token Authentication

app.py

# Pre-requisites:
# 1. Create a service princple in Azure AD
# 2. Create a new client secret for it (note down the client-id, tenant-id, and secret-value)
# 3. Go to the Azure portal and find the Translator service among the Azure AI Services.
# 4. In the Access Control (IAM) tab, assign the service principle the "Cognitive Services User" role
# 5. In the Resource management tab, enable a System assigned Identity. 
# 6. under Azure Role Assignment, choose scope: Storage, Resource: your blob storage (where your documents reside), Role: "Storage Blob Data Contributor" 
# 7- Run the code below to get the service to translate all documents in one container to another container

from azure.core.credentials import AccessToken, AzureKeyCredential, TokenCredential
from azure.ai.translation.document import DocumentTranslationClient
from azure.identity import DefaultAzureCredential, InteractiveBrowserCredential
import os

AZURE_CLIENT_ID="<app-registration-client-id>"
AZURE_TENANT_ID="<tenant-id>"
AZURE_CLIENT_SECRET="<app-registration-client-secret-value" #Value

os.environ["AZURE_CLIENT_ID"] = AZURE_CLIENT_ID
os.environ["AZURE_CLIENT_SECRET"] = AZURE_CLIENT_SECRET
os.environ["AZURE_TENANT_ID"] = AZURE_TENANT_ID

# Language all documents will be translated to
TRANSLATE_TO="da"

# Custom credential class to use the token directly
class CustomTokenCredential(TokenCredential):
    def __init__(self, token):
        self.token = token

    def get_token(self, *scopes, **kwargs):
        return AccessToken(self.token, float('inf'))


# Add your endpoint
endpoint = "https://<your-document-translator-single-resource>.cognitiveservices.azure.com/"

credential = DefaultAzureCredential()

#use token authentication
token = credential.get_token("https://cognitiveservices.azure.com/.default").token

custom_credential = CustomTokenCredential(token)
# key_credential = AzureKeyCredential("api key")

# Use the custom credential with the token
document_translation_client = DocumentTranslationClient(endpoint, custom_credential)

source_container_url_en = "https://<blob-storage-account>.blob.core.windows.net/<container>"
target_container_url_da = "https://<blob-storage-account>.blob.core.windows.net/<container>"

poller = document_translation_client.begin_translation(source_container_url_en, target_container_url_da, TRANSLATE_TO)

result = poller.result()

print(f"Status: {poller.status()}")
print(f"Created on: {poller.details.created_on}")
print(f"Last updated on: {poller.details.last_updated_on}")
print(f"Total number of translations on documents: {poller.details.documents_total_count}")

print("\nOf total documents...")
print(f"{poller.details.documents_failed_count} failed")
print(f"{poller.details.documents_succeeded_count} succeeded")

for document in result:
    print(f"Document ID: {document.id}")
    print(f"Document status: {document.status}")
    if document.status == "Succeeded":
        print(f"Source document location: {document.source_document_url}")
        print(f"Translated document location: {document.translated_document_url}")
        print(f"Translated to language: {document.translated_to}\n")
    else:
        print(f"Error Code: {document.error.code}, Message: {document.error.message}\n")