Merge pull request #779 from MicrosoftDocs/main

10/11 11:00 AM IST Publishing

Author: Saisang

articles/ai-services/.openpublishing.redirection.ai-services.json

@@ -484,6 +484,11 @@
       "source_path_from_root": "/articles/ai-services/language-service/summarization/custom/quickstart.md",
       "redirect_url": "/azure/ai-services//language-service/summarization/overview",
       "redirect_document_id": false
-    }
+    },
+    {
+      "source_path_from_root": "/articles/ai-services/speech-service/video-translation-studio.md",
+      "redirect_url": "/azure/ai-services/speech-service/video-translation-get-started",
+      "redirect_document_id": true
+   }
   ]
-}
+}

articles/ai-services/language-service/personally-identifiable-information/how-to/use-containers.md

@@ -1,7 +1,7 @@
 ---
-title: Use personally identifiable information Docker containers on-premises
+title: Use personally identifiable information (PII) detection Docker containers on-premises
 titleSuffix: Azure AI services
-description: Use Docker containers for the Personally Identifiable Information API to determine the language of written text, on-premises.
+description: Use Docker containers for the Personally Identifiable Information (PII) detection API to determine the language of written text, on-premises.
 #services: cognitive-services
 author: jboback
 manager: nitinme
@@ -16,7 +16,7 @@ keywords: on-premises, Docker, container
 # Install and run Personally Identifiable Information (PII) Detection containers
 
 > [!NOTE]
-> The data limits for the PII container are 5120 characters and 10 documents max.
+> The data limits in a single synchronous API call for the PII container are 5120 characters per document and up to 10 documents per call.
 
 Containers enable you to host the PII detection API on your own infrastructure. If you have security or data governance requirements that can't be fulfilled by calling PII detection remotely, then containers might be a good option.
 

articles/ai-services/openai/concepts/model-retirements.md

@@ -102,7 +102,8 @@ These models are currently available for use in Azure OpenAI Service.
 | `gpt-4` | 1106-preview | To be upgraded to `gpt-4` version: `turbo-2024-04-09`, starting no sooner than January 27, 2025 **<sup>1</sup>** | `gpt-4o`|
 | `gpt-4` | 0125-preview |To be upgraded to `gpt-4` version: `turbo-2024-04-09`, starting no sooner than January 27, 2025 **<sup>1</sup>**  | `gpt-4o` |
 | `gpt-4` | vision-preview | To be upgraded to `gpt-4` version: `turbo-2024-04-09`, starting no sooner than January 27, 2025  **<sup>1</sup>** | `gpt-4o`|
-| `gpt-4o` | 2024-05-13 | No earlier than March 20, 2025 <br><br>Deployments set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `2024-08-06`, starting on December 5, 2024. | |
+| `gpt-4o` | 2024-05-13 | No earlier than May 20, 2025 <br><br>Deployments set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `2024-08-06`, starting on December 5, 2024. | |
+| `gpt-4o-mini` | 2024-07-18 | No earlier than July 18, 2025  | |
 | `gpt-3.5-turbo-instruct` | 0914 | No earlier than Sep 14, 2025 |  |
 | `text-embedding-ada-002` | 2 | No earlier than April 3, 2025 | `text-embedding-3-small` or `text-embedding-3-large` |
 | `text-embedding-ada-002` | 1 | No earlier than April 3, 2025 | `text-embedding-3-small` or `text-embedding-3-large` |
@@ -119,8 +120,7 @@ These models are currently available for use in Azure OpenAI Service.
 | Model | Current default version | New default version | Default upgrade date |
 |---|---|---|---|
 | `gpt-35-turbo` | 0301 | 0125 | Deployments of versions `0301`, `0613`, and `1106` set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `0125`, starting on November 13, 2024.|
-
-
+|  `gpt-4o` | 2024-05-13 | 2024-08-06 | Deployments set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `2024-08-06`, starting on December 5, 2024. |
 
 ## Deprecated models
 

articles/ai-services/openai/how-to/batch.md

@@ -6,7 +6,7 @@ manager: nitinme
 ms.service: azure-ai-openai
 ms.custom: 
 ms.topic: how-to
-ms.date: 10/02/2024
+ms.date: 10/11/2024
 author: mrbullwinkle
 ms.author: mbullwin
 recommendations: false
@@ -65,9 +65,9 @@ The following models support global batch:
 
 Refer to the [models page](../concepts/models.md) for the most up-to-date information on regions/models where global batch is currently supported.
 
-### API Versions
+### API support
 
-- `2024-07-01-preview`
+API support was first added with `2024-07-01-preview`. 
 
 ### Not supported
 
@@ -224,8 +224,7 @@ When a job failure occurs, you'll find details about the failure in the `errors`
 
 ### Known issues
 
-- Resources deployed with Azure CLI won't work out-of-box with Azure OpenAI global batch. This is due to an issue where resources deployed using this method have endpoint subdomains that don't follow the `https://your-resource-name.openai.azure.com` pattern. A workaround for this issue is to deploy a new Azure OpenAI resource using one of the other common deployment methods which will properly handle the subdomain setup as part of the deployment process. 
-
+- Resources deployed with Azure CLI won't work out-of-box with Azure OpenAI global batch. This is due to an issue where resources deployed using this method have endpoint subdomains that don't follow the `https://your-resource-name.openai.azure.com` pattern. A workaround for this issue is to deploy a new Azure OpenAI resource using one of the other common deployment methods which will properly handle the subdomain setup as part of the deployment process.
 
 ## See also
 

articles/ai-services/openai/includes/batch/batch-python.md

@@ -104,34 +104,11 @@ file_id = file.id
   "filename": "test.jsonl",
   "object": "file",
   "purpose": "batch",
-  "status": "pending",
+  "status": null,
   "status_details": null
 }
 ```
 
-## Track file upload status
-
-Depending on the size of your upload file it might take some time before it's fully uploaded and processed. To check on your file upload status run:
-
-```python
-# Wait until the uploaded file is in processed state
-import time
-import datetime 
-
-status = "pending"
-while status != "processed":
-    time.sleep(15)
-    file_response = client.files.retrieve(file_id)
-    status = file_response.status
-    print(f"{datetime.datetime.now()} File Id: {file_id}, Status: {status}")
-```
-
-**Output:**
-
-```output
-2024-07-31 21:42:53.663655 File Id: file-9f3a81d899b4442f98b640e4bc3535dd, Status: processed
-```
-
 ## Create batch job
 
 Once your file has uploaded successfully by reaching a status of `processed` you can submit the file for batch processing.