Merge branch 'main' into release-agents-foundry

Author: v-alje

.openpublishing.redirection.json

@@ -39,6 +39,11 @@
       "source_path_from_root": "/articles/ai-services/openai/how-to/use-your-data-securely.md",
       "redirect_url": "/azure/ai-services/openai/how-to/on-your-data-configuration",
       "redirect_document_id": false
+    },
+    {
+      "source_path_from_root": "/articles/ai-services/openai/references/azure-machine-learning.md",
+      "redirect_url": "/azure/ai-services/openai/concepts/use-your-data",
+      "redirect_document_id": false
     }
   ]
 }

articles/ai-foundry/model-inference/reference/reference-model-inference-api.md

@@ -5,7 +5,7 @@ description: Learn about how to use the Azure AI Model Inference API
 manager: scottpolly
 ms.service: azure-ai-studio
 ms.topic: conceptual
-ms.date: 5/21/2024
+ms.date: 01/31/2025
 ms.reviewer: fasantia 
 reviewer: santiagxf
 ms.author: mopeakande

articles/ai-services/cognitive-services-virtual-networks.md

@@ -8,7 +8,7 @@ manager: nitinme
 ms.service: azure-ai-services
 ms.custom: devx-track-azurepowershell, devx-track-azurecli
 ms.topic: how-to
-ms.date: 06/13/2024
+ms.date: 01/31/2025
 ms.author: aahi
 ---
 

articles/ai-services/commitment-tier.md

@@ -9,7 +9,7 @@ ms.custom:
   - ignite-2023
 ms.service: azure-ai-services
 ms.topic: conceptual
-ms.date: 01/22/2024
+ms.date: 01/31/2025
 ---
 
 # Purchase commitment tier pricing

articles/ai-services/containers/azure-kubernetes-recipe.md

@@ -7,7 +7,7 @@ author: aahill
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: conceptual
-ms.date: 02/26/2024
+ms.date: 01/31/2025
 ms.author: aahi
 ms.custom: devx-track-azurecli
 ms.devlang: azurecli
@@ -74,7 +74,7 @@ To deploy the container to the Azure Kubernetes Service, the container images ne
     az acr create --resource-group cogserv-container-rg --name pattyregistry --sku Basic
     ```
 
-    Save the results to get the **loginServer** property. This will be part of the hosted container's address, used later in the `language.yml` file.
+    Save the results to get the **loginServer** property. This is part of the hosted container's address, used later in the `language.yml` file.
 
     ```azurecli-interactive
     az acr create --resource-group cogserv-container-rg --name pattyregistry --sku Basic
@@ -101,7 +101,7 @@ To deploy the container to the Azure Kubernetes Service, the container images ne
     }
     ```
 
-1. Sign in to your container registry. You need to login before you can push images to your registry.
+1. Sign in to your container registry. You need to log in before you can push images to your registry.
 
     ```azurecli-interactive
     az acr login --name pattyregistry
@@ -125,13 +125,13 @@ To deploy the container to the Azure Kubernetes Service, the container images ne
 
     To track the version on your container registry, add the tag with a version format, such as `v1`.
 
-1. Push the image to your container registry. This may take a few minutes.
+1. Push the image to your container registry. This can take a few minutes.
 
     ```console
     docker push pattyregistry.azurecr.io/language-frontend:v1
     ```
 
-    If you get an `unauthorized: authentication required` error, login with the `az acr login --name <your-container-registry-name>` command. 
+    If you get an `unauthorized: authentication required` error, sign in with the `az acr login --name <your-container-registry-name>` command. 
 
     When the process is done, the results should be similar to:
 
@@ -148,7 +148,7 @@ To deploy the container to the Azure Kubernetes Service, the container images ne
 
 ## Get language detection Docker image
 
-1. Pull the latest version of the Docker image to the local machine. This may take a few minutes. If there is a newer version of this container, change the value from `1.1.006770001-amd64-preview` to the newer version.
+1. Pull the latest version of the Docker image to the local machine. This can take a few minutes. If there is a newer version of this container, change the value from `1.1.006770001-amd64-preview` to the newer version.
 
     ```console
     docker pull mcr.microsoft.com/azure-cognitive-services/language:1.1.006770001-amd64-preview
@@ -160,7 +160,7 @@ To deploy the container to the Azure Kubernetes Service, the container images ne
     docker tag mcr.microsoft.com/azure-cognitive-services/language pattiyregistry.azurecr.io/language:1.1.006770001-amd64-preview
     ```
 
-1. Push the image to your container registry. This may take a few minutes.
+1. Push the image to your container registry. This can take a few minutes.
 
     ```console
     docker push pattyregistry.azurecr.io/language:1.1.006770001-amd64-preview
@@ -216,7 +216,7 @@ The following steps are needed to get the required information to connect your c
     az aks create --resource-group cogserv-container-rg --name patty-kube --node-count 2  --service-principal <appId>  --client-secret <client-secret>  --generate-ssh-keys
     ```
 
-    This step may take a few minutes. The result is:
+    This step can take a few minutes. The result is:
 
     ```output
     {
@@ -310,14 +310,14 @@ This section uses the **kubectl** CLI to talk with the Azure Kubernetes Service.
     Language-frontend deployment settings|Purpose|
     |--|--|
     |Line 32<br> `image` property|Image location for the frontend image in your Container Registry<br>`<container-registry-name>.azurecr.io/language-frontend:v1`|
-    |Line 44<br> `name` property|Container Registry secret for the image, referred to as `<client-secret>` in a previous section.|
+    |Line 44<br> `name` property|Container Registry secret for the image. Referred to as `<client-secret>` in a previous section.|
 
 1. Change the language deployment lines of `language.yml` based on the following table to add your own container registry image names, client secret, and Language service settings.
 
     |Language deployment settings|Purpose|
     |--|--|
     |Line 78<br> `image` property|Image location for the language image in your Container Registry<br>`<container-registry-name>.azurecr.io/language:1.1.006770001-amd64-preview`|
-    |Line 95<br> `name` property|Container Registry secret for the image, referred to as `<client-secret>` in a previous section.|
+    |Line 95<br> `name` property|Container Registry secret for the image. Referred to as `<client-secret>` in a previous section.|
     |Line 91<br> `apiKey` property|Your Language service resource key|
     |Line 92<br> `billing` property|The billing endpoint for your Language service resource.<br>`https://westus.api.cognitive.microsoft.com/text/analytics/v2.1`|
 

articles/ai-services/containers/container-faq.yml

@@ -8,7 +8,7 @@ metadata:
   manager: nitinme
   ms.service: azure-ai-services
   ms.topic: faq
-  ms.date: 02/21/2024
+  ms.date: 01/31/2025
   ms.author: aahi
 title: FAQ for Azure AI containers
 summary: |
@@ -82,7 +82,7 @@ sections:
           | `BillingEndpointBusy` | The billing endpoint is currently busy. Check the `Retry-After` value and wait for this period to end before you make more requests. |
           | `ContainerUseUnauthorized` | The provided API key isn't authorized for use with this container. You're likely using a gated container, so make sure your Azure subscription ID is approved by submitting an [online request](https://aka.ms/csgate). |
           | `[ERROR] Failed to download: context deadline exceeded` | The model file download request to our servers timed out. Make sure you have a strong internet connection to download all required files within one hour. Model downloads apply to Text Translation and some Speech service containers. |
-          | `The provided license path was not found. Please ensure a volume is mounted and a directory exists at the location specified by Mounts:License` | **Disconnected containers only.** There is no license file stored locally at the location specified in your docker run command. You might have mounted the license volume incorrectly. Be sure to check your local file system and provide a valid filepath to the desired local storage location for the license file using the -v argument in your docker run command. |
+          | `The provided license path was not found. Please ensure a volume is mounted and a directory exists at the location specified by Mounts:License` | **Disconnected containers only.** There is no license file stored locally at the location specified in your docker run command. You might have mounted the license volume incorrectly. Be sure to check your local file system and provide a valid filepath to the desired local storage location for the license file using the `-v` argument in your docker run command. |
           | `Unknown` | The server is currently unable to process billing requests. |
 
       - question: How do I get support?

articles/ai-services/containers/container-reuse-recipe.md

@@ -7,7 +7,7 @@ author: aahill
 manager: nitinme
 ms.service: azure-ai-services
 ms.topic: how-to
-ms.date: 02/22/2024
+ms.date: 01/31/2025
 ms.author: aahi
 #Customer intent: As a potential customer, I want to know how to configure containers so I can reuse them.
 ---
@@ -23,7 +23,7 @@ Once you have this new layer of container (with settings), and you have tested i
 Any `docker run` examples in this document assume a Windows console with a `^` line continuation character. Consider the following for your own use:
 
 * Do not change the order of the arguments unless you are very familiar with docker containers.
-* If you are using an operating system other than Windows, or a console other than Windows console, use the correct console/terminal, folder syntax for mounts, and line continuation character for your console and system.  Because the Azure AI services container is a Linux operating system, the target mount uses a Linux-style folder syntax.
+* If you are using an operating system other than Windows, or a console other than Windows console, use the correct console/terminal, folder syntax for mounts, and line continuation character for your console and system. Because the Azure AI services container is a Linux operating system, the target mount uses a Linux-style folder syntax.
 * `docker run` examples use the directory off the `c:` drive to avoid any permission conflicts on Windows. If you need to use a specific directory as the input directory, you might need to grant the docker service permission.
 
 ## Store no configuration settings in image
@@ -123,7 +123,7 @@ Follow these steps to use the Dockerfile and place the new image in your private
     az acr login --name <my-registry>
     ```
 
-    You can also sign in with docker login if you are assigned a service principal.
+    You can also sign in with `docker login` if you are assigned a service principal.
 
     ```Bash
     docker login <my-registry>.azurecr.io

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

@@ -43,7 +43,7 @@ Use the table below to find which model versions are supported by each feature:
 | Entity Linking                                      | `latest*`                                      |                                             |
 | Named Entity Recognition (NER)                      | `latest*`                                      | `2023-04-15-preview**`                      |
 | Personally Identifiable Information (PII) detection | `latest*`                                      | `2023-04-15-preview**`                      | 
-| PII detection for conversations                     | `latest*`                                      | `2023-04-15-preview**`                      |
+| PII detection for conversations                     | `latest*`                                      | `2024-11-01-preview**`                      |
 | Question answering                                  | `latest*`                                      |                                             |
 | Text Analytics for health                           | `latest*`                                      | `2022-08-15-preview`, `2023-01-01-preview**`|
 | Key phrase extraction                               | `latest*`                                      |                                             | 

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

@@ -4,7 +4,7 @@ titleSuffix: Azure OpenAI
 description: Learn about the deprecated models in Azure OpenAI.
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 06/14/2024
+ms.date: 01/31/2025
 ms.custom: references_regions, build-2023, build-2023-dataai
 manager: nitinme
 author: mrbullwinkle 

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

@@ -4,7 +4,7 @@ titleSuffix: Azure OpenAI
 description: Learn about the different model capabilities that are available with Azure OpenAI.
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 12/16/2024
+ms.date: 01/30/2025
 ms.custom: references_regions, build-2023, build-2023-dataai, refefences_regions
 manager: nitinme
 author: mrbullwinkle #ChrisHMSFT
@@ -18,7 +18,7 @@ Azure OpenAI Service is powered by a diverse set of models with different capabi
 
 | Models | Description |
 |--|--|
-| [o1 & o1-mini](#o1-and-o1-mini-models) |[Reasoning models](../how-to/reasoning.md) with advanced problem-solving and increased focus and capability.  |
+| [o-series models](#o-series-models) |[Reasoning models](../how-to/reasoning.md) with advanced problem-solving and increased focus and capability.  |
 | [GPT-4o & GPT-4o mini & GPT-4 Turbo](#gpt-4o-and-gpt-4-turbo) | The latest most capable Azure OpenAI models with multimodal versions, which can accept both text and images as input. |
 | [GPT-4o audio](#gpt-4o-audio) | GPT-4o audio models that support either low-latency, "speech in, speech out" conversational interactions or audio generation. |
 | [GPT-4](#gpt-4) | A set of models that improve on GPT-3.5 and can understand and generate natural language and code. |
@@ -28,30 +28,32 @@ Azure OpenAI Service is powered by a diverse set of models with different capabi
 | [Whisper](#whisper-models) | A series of models in preview that can transcribe and translate speech to text. |
 | [Text to speech](#text-to-speech-models-preview) (Preview) | A series of models in preview that can synthesize text to speech. |
 
-## o1 and o1-mini models
+## o-series models
 
-The Azure OpenAI `o1` and `o1-mini` models are specifically designed to tackle reasoning and problem-solving tasks with increased focus and capability. These models spend more time processing and understanding the user's request, making them exceptionally strong in areas like science, coding, and math compared to previous iterations.
+The Azure OpenAI o<sup>&#42;</sup> series models are specifically designed to tackle reasoning and problem-solving tasks with increased focus and capability. These models spend more time processing and understanding the user's request, making them exceptionally strong in areas like science, coding, and math compared to previous iterations.
 
 |  Model ID  | Description | Max Request (tokens) | Training Data (up to)  |
 |  --- |  :--- |:--- |:---: |
+| `o3-mini` (2025-01-31) | The latest reasoning model, offering [enhanced reasoning abilities](../how-to/reasoning.md). <br> - Structured outputs<br> - Text-only processing <br> - Functions/Tools <br> <br> **Request access: [limited access model application](https://aka.ms/OAI/o1access)** | Input: 200,000 <br> Output: 100,000 | Oct 2023 |  
 | `o1` (2024-12-17) | The most capable model in the o1 series, offering [enhanced reasoning abilities](../how-to/reasoning.md). <br> - Structured outputs<br> - Text, image processing <br> - Functions/Tools <br> <br> **Request access: [limited access model application](https://aka.ms/OAI/o1access)** | Input: 200,000 <br> Output: 100,000 | Oct 2023 |  
 |`o1-preview` (2024-09-12) | Older preview version | Input: 128,000  <br> Output: 32,768 | Oct 2023 |
 | `o1-mini` (2024-09-12) | A faster and more cost-efficient option in the o1 series, ideal for coding tasks requiring speed and lower resource consumption.| Input: 128,000  <br> Output: 65,536 | Oct 2023 |
 
 ### Availability
 
-The `o1` and `o1-mini` models are now available for API access and model deployment. **For access to `o1` registration is required, and access will be granted based on Microsoft's eligibility criteria**. Customers who previously applied and received access to `o1-preview`, don't need to reapply as they are automatically on the wait-list for the latest model.
+**For access to `o3-mini` and `o1` registration is required, and access will be granted based on Microsoft's eligibility criteria**. Customers who previously applied and received access to `o1-preview`, or `o1`  don't need to reapply as they are automatically on the wait-list for the latest models in the o-series.
 
 Request access: [limited access model application](https://aka.ms/OAI/o1access)
 
-Once access has been granted, you will need to create a deployment for each model. If you have an existing `o1-preview` deployment in place upgrade is currently not supported, you will need to create a new deployment.
+Once access has been granted, you will need to create a deployment for each model. 
 
-To learn more about the advanced `o1` series models see, [getting started with o1 series reasoning models](../how-to/reasoning.md).
+To learn more about the advanced `o-series` models see, [getting started with reasoning models](../how-to/reasoning.md).
 
 ### Region availability
 
 | Model | Region |
 |---|---|
+|`o3-mini` | East US2 (Global Standard) <br> Sweden Central (Global Standard) |
 |`o1` | East US2 (Global Standard) <br> Sweden Central (Global Standard) |
 | `o1-preview` | See the [models table](#global-standard-model-availability). |
 | `o1-mini` | See the [models table](#global-provisioned-managed-model-availability). |