update compatibility

Author: laujan

articles/ai-services/translator/document-translation/quickstarts/includes/sdk/csharp.md

@@ -5,7 +5,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-translator
 ms.topic: include
-ms.date: 06/14/2024
+ms.date: 06/17/2024
 ms.author: lajanuar
 recommendations: false
 ---
@@ -165,7 +165,7 @@ Here's a snippet of the expected output:
 
 ## Synchronous translation code sample
 
-You can download our [document translation sample document](https://raw.githubusercontent.com/Azure-Samples/cognitive-services-REST-api-samples/master/curl/Translator/document-translation-sample.pdf) for this quickstart. The source language is English.
+You can download our [document translation sample document](https://raw.githubusercontent.com/Azure-Samples/cognitive-services-REST-api-samples/master/curl/Translator/document-translation-sample.docx) for this quickstart. The source language is English.
 
 ```csharp
 
@@ -188,7 +188,7 @@ class Program {
     using Stream fileStream = File.OpenRead(filePath);
 
     // MultipartFormFileData (string name, System.IO.Stream content, string contentType);
-    var sourceDocument = new MultipartFormFileData(Path.GetFileName(filePath), fileStream, "text/html");
+    var sourceDocument = new MultipartFormFileData(Path.GetFileName(filePath), fileStream, "application/vnd.openxmlformats-officedocument.wordprocessingml.document");
 
     DocumentTranslateContent content = new DocumentTranslateContent(sourceDocument);
 
@@ -363,7 +363,7 @@ Here's a snippet of the expected output:
 
 ## Synchronous translation code sample
 
-You can download our [document translation sample document](https://raw.githubusercontent.com/Azure-Samples/cognitive-services-REST-api-samples/master/curl/Translator/document-translation-sample.pdf) for this quickstart. The source language is English.
+You can download our [document translation sample document](https://raw.githubusercontent.com/Azure-Samples/cognitive-services-REST-api-samples/master/curl/Translator/document-translation-sample.docx) for this quickstart. The source language is English.
 
 ```csharp
 
@@ -382,11 +382,11 @@ class Program {
 
   try
   {
-    string filePath = @"C:\{folder}\document.txt"
+    string filePath = @"C:\{folder}\document-translation-sample.docx"
     using Stream fileStream = File.OpenRead(filePath);
 
     // MultipartFormFileData (string name, System.IO.Stream content, string contentType);
-    var sourceDocument = new MultipartFormFileData(Path.GetFileName(filePath), fileStream, "text/html");
+    var sourceDocument = new MultipartFormFileData(Path.GetFileName(filePath), fileStream, "application/vnd.openxmlformats-officedocument.wordprocessingml.document");
 
     DocumentTranslateContent content = new DocumentTranslateContent(sourceDocument);
 

articles/ai-services/translator/document-translation/quickstarts/includes/sdk/python.md

@@ -5,7 +5,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-translator
 ms.topic: include
-ms.date: 05/15/2024
+ms.date: 06/17/2024
 ms.author: lajanuar
 recommendations: false
 ---
@@ -24,16 +24,16 @@ Install the latest version of the Document Translation client library:
   pip install azure-ai-translation-document==1.1.0b1
 ```
 
-### Translate a document or batch files
+### Translate batch files
 
 1. For this project, you need a **source document** uploaded to your **source container**. You can download our [document translation sample document](https://raw.githubusercontent.com/Azure-Samples/cognitive-services-REST-api-samples/master/curl/Translator/document-translation-sample.pdf) for this quickstart. The source language is English.
 
 1. In your Python application file, create variables for your resource key and custom endpoint. For more information, *see* [Retrieve your key and custom domain endpoint](../../../how-to-guides/use-rest-api-programmatically.md#retrieve-your-key-and-custom-domain-endpoint).
 
   ```python
-  key = "<your-key>"
-  endpoint = "<your-custom-endpoint>"
-  
+  key = "{your-api-key}"
+  endpoint = "{your-document-translation-endpoint}"
+
   ```
 
 1. Initialize a `DocumentTranslationClient` object that contains your `endpoint` and `key` parameters.
@@ -60,7 +60,7 @@ Install the latest version of the Document Translation client library:
       * **targetUri** The SAS URI, with a SAS token appended as a query string,for the target container to which the translated documents are written.
       * **targetLanguageCode**. The language code for the translated documents. You can find language codes on our [Language support](../../../../language-support.md) page.
 
-### Code Sample
+## Asynchronous translation code sample
 
 > [!IMPORTANT]
 > Remember to remove the key from your code when you're done, and never post it publicly. For production, use a secure way of storing and accessing your credentials like [Azure Key Vault](../../../../../../key-vault/general/overview.md). For more information, *see* Azure AI services [security](../../../../../../ai-services/security-features.md).
@@ -74,45 +74,45 @@ from azure.core.credentials import AzureKeyCredential
 from azure.ai.translation.document import DocumentTranslationClient
 
 # create variables for your resource key, custom endpoint, sourceUrl, targetUrl, and targetLanguage
-key = "<your-key>"
-endpoint = "<your-custom-endpoint>"
-sourceUri = "<your-container-sourceUrl>"
-targetUri = "<your-container-targetUrl>"
-targetLanguage = "<target-language-code>"
+key = '{your-api-key}'
+endpoint = '{your-document-translation-endpoint}'
+sourceUri = '<your-container-sourceUrl>'
+targetUri = '<your-container-targetUrl>'
+targetLanguage = '<target-language-code>'
 
 
-# initialize a new instance of the DocumentTranslationClient object to interact with the Document Translation feature
+# initialize a new instance of the DocumentTranslationClient object to interact with the asynchronous Document Translation feature
 client = DocumentTranslationClient(endpoint, AzureKeyCredential(key))
 
 # include source and target locations and target language code for the begin translation operation
 poller = client.begin_translation(sourceUri, targetUri, targetLanguage)
 result = poller.result()
 
-print("Status: {}".format(poller.status()))
-print("Created on: {}".format(poller.details.created_on))
-print("Last updated on: {}".format(poller.details.last_updated_on))
+print('Status: {}'.format(poller.status()))
+print('Created on: {}'.format(poller.details.created_on))
+print('Last updated on: {}'.format(poller.details.last_updated_on))
 print(
-    "Total number of translations on documents: {}".format(
+    'Total number of translations on documents: {}'.format(
         poller.details.documents_total_count
     )
 )
 
-print("\nOf total documents...")
-print("{} failed".format(poller.details.documents_failed_count))
-print("{} succeeded".format(poller.details.documents_succeeded_count))
+print('\nOf total documents...')
+print('{} failed'.format(poller.details.documents_failed_count))
+print('{} succeeded'.format(poller.details.documents_succeeded_count))
 
 for document in result:
-    print("Document ID: {}".format(document.id))
-    print("Document status: {}".format(document.status))
-    if document.status == "Succeeded":
-        print("Source document location: {}".format(document.source_document_url))
+    print('Document ID: {}'.format(document.id))
+    print('Document status: {}'.format(document.status))
+    if document.status == 'Succeeded':
+        print('Source document location: {}'.format(document.source_document_url))
         print(
-            "Translated document location: {}".format(document.translated_document_url)
+            'Translated document location: {}'.format(document.translated_document_url)
         )
-        print("Translated to language: {}\n".format(document.translated_to))
+        print('Translated to language: {}\n'.format(document.translated_to))
     else:
         print(
-            "Error Code: {}, Message: {}\n".format(
+            'Error Code: {}, Message: {}\n'.format(
                 document.error.code, document.error.message
             )
         )
@@ -130,4 +130,52 @@ Here's a snippet of the expected output:
 
   :::image type="content" source="../../../../media/quickstarts/python-output-document.png" alt-text="Screenshot of the Python output in the terminal window. ":::
 
-That's it! You just created a program to translate documents in a storage container using the Python client library.
+## Synchronous translation code sample
+
+You can download our [document translation sample document](https://raw.githubusercontent.com/Azure-Samples/cognitive-services-REST-api-samples/master/curl/Translator/document-translation-sample.docx) for this quickstart. The source language is English.
+
+```python
+import os
+from azure.core.credentials import AzureKeyCredential
+from azure.ai.translation.document import SingleDocumentTranslationClient
+from azure.ai.translation.document.models import DocumentTranslateContent
+
+
+def sample_single_document_translation():
+
+    # create variables for your resource api key, document translation endpoint, and target language
+    key = "<your-api-key>"
+    endpoint = "<your-document-translation-endpoint>"
+    target_language = "{target-language-code}"
+
+    # initialize a new instance of the SingleDocumentTranslationClient object to interact with the synchronous Document Translation feature
+    client = SingleDocumentTranslationClient(endpoint, AzureKeyCredential(key))
+
+    # absolute path to your document
+    file_path = "C:/{your-file-path}/document-translation-sample.docx"
+    file_name = os.path.path.basename(file_path)
+    file_type = (
+        "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
+    )
+    print(f"File for translation: {file_name}")
+
+    with open(file_name, "r") as file:
+        file_contents = file.read()
+
+    document_content = (file_name, file_contents, file_type)
+    document_translate_content = DocumentTranslateContent(document=document_content)
+
+    response_stream = client.document_translate(
+        body=document_translate_content, target_language=target_language
+    )
+    translated_response = response_stream.decode("utf-8-sig")  # type: ignore[attr-defined]
+    print(f"Translated response: {translated_response}")
+
+
+if __name__ == "__main__":
+    sample_single_document_translation()
+
+
+```
+
+That's it! You just created a program to translate documents asynchronously and synchronously using the Python client library.