mc

Author: v-thepet

.openpublishing.redirection.virtual-desktop.json

@@ -369,6 +369,11 @@
             "source_path_from_root": "/articles/virtual-desktop/publish-applications.md",
             "redirect_url": "/azure/virtual-desktop/publish-applications-stream-remoteapp",
             "redirect_document_id": false
+        },
+        {
+            "source_path_from_root": "/articles/virtual-desktop/autoscale-new-existing-host-pool.md",
+            "redirect_url": "/azure/virtual-desktop/autoscale-scaling-plan",
+            "redirect_document_id": true
         }
     ]
 }

articles/advisor/advisor-reference-reliability-recommendations.md

@@ -4,7 +4,7 @@ description: Full list of available reliability recommendations in Advisor.
 author: mabrahms
 ms.author: v-mabrahms
 ms.topic: article
-ms.date: 09/27/2023
+ms.date: 12/11/2023
 ---
 
 # Reliability recommendations
@@ -544,7 +544,7 @@ Learn more about [Front Door Profile - RenewExpiredBYOC (Renew the expired Azure
 
 Deploying two or more medium or large sized instances ensures business continuity during outages caused by planned or unplanned maintenance.
 
-Learn more about [Application gateway - AppGateway (Upgrade your SKU or add more instances to ensure fault tolerance)](https://aka.ms/aa_gatewayrec_learnmore).
+Learn more about [Improve the reliability of your application by using Azure Advisor - Ensure application gateway fault tolerance)](/azure/advisor/advisor-high-availability-recommendations#ensure-application-gateway-fault-tolerance).
 
 ### Avoid hostname override to ensure site integrity
 

articles/ai-services/computer-vision/how-to/shelf-analyze.md

@@ -36,7 +36,7 @@ To analyze a shelf image, do the following steps:
 1. Copy the following `curl` command into a text editor.
 
     ```bash
-    curl.exe -H "Ocp-Apim-Subscription-Key: <subscriptionKey>" -H "Content-Type: application/json" "https://<endpoint>/computervision/productrecognition/ms-pretrained-product-detection/runs/<your_run_name>?api-version=2023-04-01-preview" -d "{
+    curl -X PUT -H "Ocp-Apim-Subscription-Key: <subscriptionKey>" -H "Content-Type: application/json" "https://<endpoint>/computervision/productrecognition/ms-pretrained-product-detection/runs/<your_run_name>?api-version=2023-04-01-preview" -d "{
         'url':'<your_url_string>'
     }"
     ```

articles/ai-services/computer-vision/how-to/video-retrieval.md

@@ -20,7 +20,7 @@ Azure AI Spatial Analysis Video Retrieval APIs are part of Azure AI Vision and e
 ## Prerequisites
 
 - Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services).
-- Once you have your Azure subscription, [create a Vision resource using the portal](/azure/cognitive-services/cognitive-services-apis-create-account). For this preview, you must create your resource in the East US region.
+- Once you have your Azure subscription, [create a Vision resource using the portal](/azure/cognitive-services/cognitive-services-apis-create-account). For this preview, you must create your resource in the one of the following regions - Australia East, Switzerland North, Sweden Central, or East US.
 - An Azure Storage resource - [Create one](/azure/storage/common/storage-account-create?tabs=azure-portal)
 
 ## Input requirements

articles/ai-services/document-intelligence/index.yml

@@ -12,7 +12,7 @@ metadata:
   ms.topic: landing-page
   author: laujan
   ms.author: lajanuar
-  ms.date: 07/28/2023
+  ms.date: 01/02/2024
   monikerRange: '<=doc-intel-4.0.0'
 # linkListType: architecture | concept | deploy | download | get-started | how-to-guide | learn | overview | quickstart | reference | tutorial | video | whats-new
 # Limits: https://review.learn.microsoft.com/help/contribute/contribute-how-to-write-landing-page?branch=main#limits

articles/ai-services/language-service/concepts/model-lifecycle.md

@@ -8,7 +8,7 @@ manager: nitinme
 ms.service: azure-ai-language
 ms.custom: event-tier1-build-2022
 ms.topic: conceptual
-ms.date: 12/19/2023
+ms.date: 01/16/2024
 ms.author: aahi
 ---
 
@@ -33,8 +33,7 @@ Preview models used for preview features do not maintain a minimum retirement pe
 By default, API and SDK requests will use the latest Generally Available model. You can use an optional parameter to select the version of the model to be used (not recommended).
 
 > [!NOTE]
-> * If you are using a model version that is not listed in the table, then it was subjected to the expiration policy.
-> * Abstractive document and conversation summarization do not provide model versions other than the latest available.
+> If you are using a model version that is not listed in the table, then it was subjected to the expiration policy.
 
 Use the table below to find which model versions are supported by each feature:
 
@@ -49,7 +48,7 @@ Use the table below to find which model versions are supported by each feature:
 | Question answering                                  | `latest*`                                      |                                             |
 | Text Analytics for health                           | `latest*`                                      | `2022-08-15-preview`, `2023-01-01-preview**`|
 | Key phrase extraction                               | `latest*`                                      |                                             | 
-| Document summarization - extractive only (preview)  |                                                |`2022-08-31-preview**`                       |
+| Summarization                              |  `latest*`                                      |                       |
 
 
 \* Latest Generally Available (GA) model version

articles/ai-services/openai/concepts/models.md

@@ -148,6 +148,9 @@ These models can only be used with Embedding API requests.
 | `text-embedding-ada-002` (version 2) | Australia East <br> Canada East <br> East US <br> East US2 <br> France Central <br> Japan East <br> North Central US <br> Norway East <br> South Central US <br> Sweden Central <br> Switzerland North <br> UK South <br> West Europe <br> West US |8,191 | Sep 2021 | 1,536 |
 | `text-embedding-ada-002` (version 1) | East US <br> South Central US <br> West Europe |2,046 | Sep 2021 | 1,536 |
 
+> [!NOTE]
+> When sending an array of inputs for embedding, the max number of input items in the array per call to the embedding endpoint is 2048.
+
 ### DALL-E models (Preview)
 
 |  Model ID  | Feature Availability | Max Request (characters) |

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

@@ -6,7 +6,7 @@ description: Learn how to generate embeddings with Azure OpenAI
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 11/06/2023
+ms.date: 01/16/2024
 author: mrbullwinkle
 ms.author: mbullwin
 recommendations: false
@@ -126,7 +126,9 @@ return $response.data.embedding
 
 ### Verify inputs don't exceed the maximum length
 
-The maximum length of input text for our latest embedding models is 8192 tokens. You should verify that your inputs don't exceed this limit before making a request.
+- The maximum length of input text for our latest embedding models is 8192 tokens. You should verify that your inputs don't exceed this limit before making a request.
+- If sending an array of inputs in a single embedding request the max array size is 2048.
+
 
 ## Limitations & risks
 

articles/ai-services/openai/how-to/switching-endpoints.md

@@ -7,7 +7,7 @@ ms.author: mbullwin
 ms.service: azure-ai-openai
 ms.custom: devx-track-python
 ms.topic: how-to
-ms.date: 11/22/2023
+ms.date: 01/06/2023
 manager: nitinme
 ---
 
@@ -31,10 +31,11 @@ We recommend using environment variables. If you haven't done this before our [P
 <td>
 
 ```python
+import os
 from openai import OpenAI
 
 client = OpenAI(
-  api_key=os.environ["OPENAI_API_KEY"]  
+    api_key=os.getenv("OPENAI_API_KEY")
 )
 
 
@@ -51,7 +52,7 @@ from openai import AzureOpenAI
 client = AzureOpenAI(
     api_key=os.getenv("AZURE_OPENAI_KEY"),  
     api_version="2023-12-01-preview",
-    azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
+    azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT")
 )
 ```
 
@@ -71,10 +72,11 @@ client = AzureOpenAI(
 <td>
 
 ```python
+import os
 from openai import OpenAI
 
 client = OpenAI(
-  api_key=os.environ["OPENAI_API_KEY"]  
+    api_key=os.getenv("OPENAI_API_KEY")
 )
 
 
@@ -93,7 +95,9 @@ client = OpenAI(
 from azure.identity import DefaultAzureCredential, get_bearer_token_provider
 from openai import AzureOpenAI
 
-token_provider = get_bearer_token_provider(DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default")
+token_provider = get_bearer_token_provider(
+    DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
+)
 
 api_version = "2023-12-01-preview"
 endpoint = "https://my-resource.openai.azure.com"
@@ -126,7 +130,7 @@ OpenAI uses the `model` keyword argument to specify what model to use. Azure Ope
 ```python
 completion = client.completions.create(
     model="gpt-3.5-turbo-instruct",
-    prompt="<prompt>")
+    prompt="<prompt>"
 )
 
 chat_completion = client.chat.completions.create(
@@ -135,8 +139,8 @@ chat_completion = client.chat.completions.create(
 )
 
 embedding = client.embeddings.create(
-    input="<input>",
-    model="text-embedding-ada-002"
+    model="text-embedding-ada-002",
+    input="<input>"
 )
 ```
 
@@ -146,17 +150,17 @@ embedding = client.embeddings.create(
 ```python
 completion = client.completions.create(
     model="gpt-35-turbo-instruct", # This must match the custom deployment name you chose for your model.
-    prompt=<"prompt">
+    prompt="<prompt>"
 )
 
 chat_completion = client.chat.completions.create(
     model="gpt-35-turbo", # model = "deployment_name".
-    messages=<"messages">
+    messages="<messages>"
 )
 
 embedding = client.embeddings.create(
-    input = "<input>",
-    model= "text-embedding-ada-002" # model = "deployment_name".
+    model="text-embedding-ada-002", # model = "deployment_name".
+    input="<input>"
 )
 ```
 
@@ -166,7 +170,7 @@ embedding = client.embeddings.create(
 
 ## Azure OpenAI embeddings multiple input support
 
-OpenAI currently allows a larger number of array inputs with text-embedding-ada-002. Azure OpenAI currently supports input arrays up to 16 for text-embedding-ada-002 Version 2. Both require the max input token limit per API request to remain under 8191 for this model.
+OpenAI and Azure OpenAI currently support input arrays up to 2048 input items for text-embedding-ada-002. Both require the max input token limit per API request to remain under 8191 for this model.
 
 <table>
 <tr>
@@ -179,8 +183,8 @@ OpenAI currently allows a larger number of array inputs with text-embedding-ada-
 inputs = ["A", "B", "C"] 
 
 embedding = client.embeddings.create(
-  input=inputs,
-  model="text-embedding-ada-002"
+    input=inputs,
+    model="text-embedding-ada-002"
 )
 
 
@@ -190,12 +194,12 @@ embedding = client.embeddings.create(
 <td>
 
 ```python
-inputs = ["A", "B", "C"] #max array size=16
+inputs = ["A", "B", "C"] #max array size=2048
 
 embedding = client.embeddings.create(
-  input=inputs,
-  model="text-embedding-ada-002" # This must match the custom deployment name you chose for your model.
-  #engine="text-embedding-ada-002"
+    input=inputs,
+    model="text-embedding-ada-002" # This must match the custom deployment name you chose for your model.
+    # engine="text-embedding-ada-002"
 )
 
 ```

articles/ai-services/openai/how-to/use-blocklists.md

@@ -20,7 +20,7 @@ The configurable content filters are sufficient for most content moderation need
 
 - An Azure subscription. <a href="https://azure.microsoft.com/free/ai-services" target="_blank">Create one for free</a>.
 - Once you have your Azure subscription, create an Azure OpenAI resource in the Azure portal to get your token, key and endpoint. Enter a unique name for your resource, select the subscription you entered on the application form, select a resource group, supported region, and supported pricing tier. Then select **Create**.
-    - The resource takes a few minutes to deploy. After it finishes, sSelect **go to resource**. In the left pane, under **Resource Management**,  select **Subscription Key and Endpoint**. The endpoint and either of the keys are used to call APIs.
+    - The resource takes a few minutes to deploy. After it finishes, select **go to resource**. In the left pane, under **Resource Management**, select **Subscription Key and Endpoint**. The endpoint and either of the keys are used to call APIs.
 - [Azure CLI](/cli/azure/install-azure-cli) installed
 - [cURL](https://curl.haxx.se/) installed
 
@@ -279,4 +279,4 @@ You can also create custom blocklists in the Azure OpenAI Studio as part of your
 
 - Read more about [content filtering categories and severity levels](/azure/ai-services/openai/concepts/content-filter?tabs=python) with Azure OpenAI Service. 
 
-- Learn more about red teaming from our: [Introduction to red teaming large language models (LLMs)](/azure/ai-services/openai/concepts/red-teaming) article. 
+- Learn more about red teaming from our: [Introduction to red teaming large language models (LLMs)](/azure/ai-services/openai/concepts/red-teaming) article.