Merge pull request #977 from mrbullwinkle/mrb_10_22_2024_global_batch_ga

prmerger-automator[bot] · web-flow · commit ae79efa069a0 · 2024-10-23T15:57:04.000Z
[Azure OpenAI] Global Batch GA
diff --git a/articles/ai-services/openai/how-to/batch.md b/articles/ai-services/openai/how-to/batch.md
@@ -13,7 +13,7 @@ recommendations: false
 zone_pivot_groups: openai-fine-tuning-batch
 ---
 
-# Getting started with Azure OpenAI global batch deployments (preview)
+# Getting started with Azure OpenAI global batch deployments
 
 The Azure OpenAI Batch API is designed to handle large-scale and high-volume processing tasks efficiently. Process asynchronous groups of requests with separate quota, with 24-hour target turnaround, at [50% less cost than global standard](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/). With batch processing, rather than send one request at a time you send a large number of requests in a single file. Global batch requests have a separate enqueued token quota avoiding any disruption of your online workloads.  
 
@@ -65,7 +65,12 @@ Refer to the [models page](../concepts/models.md) for the most up-to-date inform
 
 ### API support
 
-API support was first added with `2024-07-01-preview`. Use `2024-10-01-preview` to take advantage of the latest features.
+|   | API Version   |
+|---|---|
+|**Latest GA API release:**| `2024-10-21`|
+|**Latest Preview API release:**| `2024-10-01-preview`|
+
+Support first added in: `2024-07-01-preview`
 
 ### Feature support
 
@@ -75,7 +80,7 @@ The following aren't currently supported:
 - Integration with Azure OpenAI On Your Data feature.
 
 > [!NOTE]
-> Structured outputs is now supported with Global Batch when used in conjunction with API version `2024-08-01-preview` or later. Use `2024-10-01-preview` for the latest features.
+> Structured outputs is now supported with Global Batch.
 
 ### Global batch deployment
 
diff --git a/articles/ai-services/openai/includes/batch/batch-python.md b/articles/ai-services/openai/includes/batch/batch-python.md
@@ -94,7 +94,7 @@ token_provider = get_bearer_token_provider(
 client = AzureOpenAI(
   azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT"), 
   azure_ad_token_provider=token_provider,
-  api_version="2024-10-01-preview"
+  api_version="2024-10-21"
 )
 
 # Upload a file with a purpose of "batch"
@@ -117,7 +117,7 @@ from openai import AzureOpenAI
     
 client = AzureOpenAI(
     api_key=os.getenv("AZURE_OPENAI_API_KEY"),  
-    api_version="2024-10-01-preview",
+    api_version="2024-10-21",
     azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
     )
 
diff --git a/articles/ai-services/openai/includes/batch/batch-rest.md b/articles/ai-services/openai/includes/batch/batch-rest.md
@@ -73,7 +73,7 @@ Once your input file is prepared, you first need to upload the file to then be a
 [!INCLUDE [Azure key vault](~/reusable-content/ce-skilling/azure/includes/ai-services/security/azure-key-vault.md)]
 
 ```http
-curl -X POST https://YOUR_RESOURCE_NAME.openai.azure.com/openai/files?api-version=2024-10-01-preview \
+curl -X POST https://YOUR_RESOURCE_NAME.openai.azure.com/openai/files?api-version=2024-10-21 \
   -H "Content-Type: multipart/form-data" \
   -H "api-key: $AZURE_OPENAI_API_KEY" \
   -F "purpose=batch" \
@@ -103,7 +103,7 @@ The above code assumes a particular file path for your test.jsonl file. Adjust t
 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:
 
 ```http
-curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/files/{file-id}?api-version=2024-10-01-preview \
+curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/files/{file-id}?api-version=2024-10-21 \
   -H "api-key: $AZURE_OPENAI_API_KEY"
 ```
 
@@ -127,7 +127,7 @@ curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/files/{file-id}?api-vers
 Once your file has uploaded successfully you can submit the file for batch processing.
 
 ```http
-curl -X POST https://YOUR_RESOURCE_NAME.openai.azure.com/openai/batches?api-version=2024-10-01-preview \
+curl -X POST https://YOUR_RESOURCE_NAME.openai.azure.com/openai/batches?api-version=2024-10-21 \
   -H "api-key: $AZURE_OPENAI_API_KEY" \
   -H "Content-Type: application/json" \
   -d '{
@@ -176,7 +176,7 @@ curl -X POST https://YOUR_RESOURCE_NAME.openai.azure.com/openai/batches?api-vers
 Once you have created batch job successfully you can monitor its progress either in the Studio or programatically. When checking batch job progress we recommend waiting at least 60 seconds in between each status call.
 
 ```http
-curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/batches/{batch_id}?api-version=2024-10-01-preview \
+curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/batches/{batch_id}?api-version=2024-10-21 \
   -H "api-key: $AZURE_OPENAI_API_KEY" 
 ```
 
@@ -228,7 +228,7 @@ The following status values are possible:
 ## Retrieve batch job output file
 
 ```http
-curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/files/{output_file_id}/content?api-version=2024-10-01-preview \
+curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/files/{output_file_id}/content?api-version=2024-10-21 \
   -H "api-key: $AZURE_OPENAI_API_KEY" > batch_output.jsonl
 ```
 
@@ -239,7 +239,7 @@ curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/files/{output_file_id}/c
 Cancels an in-progress batch. The batch will be in status `cancelling` for up to 10 minutes, before changing to `cancelled`, where it will have partial results (if any) available in the output file.
 
 ```http
-curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/batches/{batch_id}/cancel?api-version=2024-10-01-preview \
+curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/batches/{batch_id}/cancel?api-version=2024-10-21 \
   -H "api-key: $AZURE_OPENAI_API_KEY" 
 ```
 
@@ -248,7 +248,7 @@ curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/batches/{batch_id}/cance
 List all existing batch jobs for a given Azure OpenAI resource.
 
 ```http
-curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/batches?api-version=2024-10-01-preview \
+curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/batches?api-version=2024-10-21 \
   -H "api-key: $AZURE_OPENAI_API_KEY" 
 ```
 
diff --git a/articles/ai-services/openai/includes/batch/batch-studio.md b/articles/ai-services/openai/includes/batch/batch-studio.md
@@ -72,7 +72,7 @@ Once your input file is prepared, you first need to upload the file to then be a
 
 1. Sign in to [AI Studio](https://ai.azure.com).
 2. Select the Azure OpenAI resource where you have a global batch model deployment available.
-3. Select **Batch jobs PREVIEW** > **+Create batch jobs**.
+3. Select **Batch jobs** > **+Create batch jobs**.
 
     :::image type="content" source="../../media/how-to/global-batch/create-batch-job-empty.png" alt-text="Screenshot that shows the batch job creation experience in Azure AI Studio." lightbox="../../media/how-to/global-batch/create-batch-job-empty.png":::
 
diff --git a/articles/ai-services/openai/whats-new.md b/articles/ai-services/openai/whats-new.md
@@ -10,7 +10,7 @@ ms.custom:
   - ignite-2023
   - references_regions
 ms.topic: whats-new
-ms.date: 10/01/2024
+ms.date: 10/22/2024
 recommendations: false
 ---
 
@@ -20,6 +20,30 @@ This article provides a summary of the latest releases and major documentation u
 
 ## October 2024
 
+### Global Batch GA
+
+Azure OpenAI global batch is now generally available.
+
+The Azure OpenAI Batch API is designed to handle large-scale and high-volume processing tasks efficiently. Process asynchronous groups of requests with separate quota, with 24-hour target turnaround, at [50% less cost than global standard](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/). With batch processing, rather than send one request at a time you send a large number of requests in a single file. Global batch requests have a separate enqueued token quota avoiding any disruption of your online workloads.  
+
+Key use cases include:
+
+* **Large-Scale Data Processing:** Quickly analyze extensive datasets in parallel.
+
+* **Content Generation:** Create large volumes of text, such as product descriptions or articles.
+
+* **Document Review and Summarization:** Automate the review and summarization of lengthy documents.
+
+* **Customer Support Automation:** Handle numerous queries simultaneously for faster responses.
+
+* **Data Extraction and Analysis:** Extract and analyze information from vast amounts of unstructured data.
+
+* **Natural Language Processing (NLP) Tasks:** Perform tasks like sentiment analysis or translation on large datasets.
+
+* **Marketing and Personalization:** Generate personalized content and recommendations at scale.
+
+For more information on [getting started with global batch deployments](./how-to/batch.md).
+
 ### o1-preview and o1-mini models limited access
 
 The `o1-preview` and `o1-mini` models are now available for API access and model deployment. **Registration is required, and access will be granted based on Microsoft's eligibility criteria**.

Original file line number	Diff line number	Diff line change
`@@ -94,7 +94,7 @@ token_provider = get_bearer_token_provider(`
`94`	`94`	`client = AzureOpenAI(`
`95`	`95`	`azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT"),`
`96`	`96`	`azure_ad_token_provider=token_provider,`
`97`		`- api_version="2024-10-01-preview"`
	`97`	`+ api_version="2024-10-21"`
`98`	`98`	`)`
`99`	`99`
`100`	`100`	`# Upload a file with a purpose of "batch"`
`@@ -117,7 +117,7 @@ from openai import AzureOpenAI`
`117`	`117`
`118`	`118`	`client = AzureOpenAI(`
`119`	`119`	`api_key=os.getenv("AZURE_OPENAI_API_KEY"),`
`120`		`- api_version="2024-10-01-preview",`
	`120`	`+ api_version="2024-10-21",`
`121`	`121`	`azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")`
`122`	`122`	`)`
`123`	`123`