Merge branch 'main' of https://github.com/MicrosoftDocs/azure-ai-docs-pr into monitoronlineevalsplit

Author: lgayhardt

articles/ai-services/agents/includes/bicep-setup.md

@@ -24,10 +24,18 @@ The following section shows you how to set up the required resources for getting
 
 **Standard Setup**: Agents use customer-owned, single-tenant search and storage resources. With this setup, you have full control and visibility over these resources, but you incur costs based on your usage.
 
+<!--
 | Description   | Resources  | Autodeploy |
 | -----------------------------------------------| -----------------------|----------------------|
 | Deploy a basic agent setup that uses Managed Identity authentication on the AI Services and storage account connections. | AI hub, AI project, AI Services | [![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fazure-quickstart-templates%2Fmaster%2Fquickstarts%2Fmicrosoft.azure-ai-agent-service%2Fbasic-agent-identity%2Fazuredeploy.json) |
 | Deploy a standard agent setup that uses Managed Identity authentication on the AI Services, storage account, and Azure AI Search connections. |AI hub, AI project, storage account, key vault, Azure AI Search, AI Services | [![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fazure-quickstart-templates%2Frefs%2Fheads%2Fmaster%2Fquickstarts%2Fmicrosoft.azure-ai-agent-service%2Fstandard-agent%2Fazuredeploy.json)|
+-->
+
+| Description and Autodeploy  |  Diagram (click to zoom in) |
+| -----------------------------------------------| -----------------------|
+| Deploy a basic agent setup that uses Managed Identity for authentication. Resources for the AI hub, AI project, storage account, and AI Services are created for you. <br><br> The AI Services account is connected to your project and hub, and a gpt-4o-mini model is deployed in the eastus region. A Microsoft-managed key vault is used by default. <br><br> [![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fazure-quickstart-templates%2Fmaster%2Fquickstarts%2Fmicrosoft.azure-ai-agent-service%2Fbasic-agent-identity%2Fazuredeploy.json) |  :::image type="content" source="../media/quickstart/basic-agent-setup-resources.png" alt-text="An architecture diagram for basic agent setup." lightbox="../media/quickstart/basic-agent-setup-resources.png"::: | 
+| Deploy a standard agent setup that uses Managed Identity for authentication. <br><br> Resources for the AI hub, AI project, key vault, storage account, AI Services, and AI Search are created for you. <br><br>The AI Services, AI Search, key vault, and storage account are connected to your project and hub. A gpt-4o-mini model is deployed in eastus region. <br><br> [![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fazure-quickstart-templates%2Frefs%2Fheads%2Fmaster%2Fquickstarts%2Fmicrosoft.azure-ai-agent-service%2Fstandard-agent%2Fazuredeploy.json) | :::image type="content" source="../media/quickstart/standard-agent-setup-resources.png" alt-text="An architecture diagram for standard agent setup." lightbox="../media/quickstart/standard-agent-setup-resources.png"::: |
+
 
 ### [Optional] Model selection in autodeploy template
 You can customize the model used by your agent by editing the model parameters in the autodeploy template. To deploy a different model, you need to update at least the `modelName` and `modelVersion` parameters. 
@@ -64,7 +72,7 @@ If you want to use an existing Azure OpenAI resource, you need to update the `ai
 
 For more information, see [how to use your own resources](../how-to/use-your-own-resources.md).
 
-
+<!--
 ## Basic agent setup resource architecture
 :::image type="content" source="../media/quickstart/basic-agent-setup-resources.png" alt-text="An architecture diagram for basic agent setup." lightbox="../media/quickstart/basic-agent-setup-resources.png":::
 
@@ -73,4 +81,5 @@ Resources for the AI hub, AI project, and AI Services are created for you. A sto
 ## Standard agent setup resource architecture
 :::image type="content" source="../media/quickstart/standard-agent-setup-resources.png" alt-text="An architecture diagram for standard agent setup." lightbox="../media/quickstart/standard-agent-setup-resources.png":::
 
-Resources for the AI hub, AI project, key vault, storage account, AI Services, and AI Search are created for you. The AI Services, AI Search, key vault, and storage account are connected to your project and hub. A gpt-4o-mini model is deployed in eastus region using the Azure OpenAI endpoint for your resource.
+Resources for the AI hub, AI project, key vault, storage account, AI Services, and AI Search are created for you. The AI Services, AI Search, key vault, and storage account are connected to your project and hub. A gpt-4o-mini model is deployed in eastus region using the Azure OpenAI endpoint for your resource.
+-->

articles/ai-services/computer-vision/includes/model-customization-deprecation.md

@@ -12,6 +12,6 @@ ms.author: pafarley
 ---
 
 > [!IMPORTANT]
-> This feature is now deprecated. On January 10, 2025, Azure AI Image Analysis 4.0 Custom Image Classification, Custom Object Detection, and Product Recognition preview API will be retired. After this date, API calls to these services will fail.
+> This feature is now deprecated. On March 31, 2025, Azure AI Image Analysis 4.0 Custom Image Classification, Custom Object Detection, and Product Recognition preview API will be retired. After this date, API calls to these services will fail.
 >
 > To maintain a smooth operation of your models, transition to [Azure AI Custom Vision](/azure/ai-services/Custom-Vision-Service/overview), which is now generally available. Custom Vision offers similar functionality to these retiring features.

articles/ai-services/computer-vision/includes/segmentation-deprecation.md

@@ -12,6 +12,6 @@ ms.author: pafarley
 ---
 
 > [!IMPORTANT]
-> This feature is now deprecated. On January 10, 2025, the Azure AI Image Analysis 4.0 Segment API and background removal service will be retired. All requests to this service will fail after this date.
+> This feature is now deprecated. On March 31, 2025, the Azure AI Image Analysis 4.0 Segment API and background removal service will be retired. All requests to this service will fail after this date.
 >
 > To maintain a smooth operation of your models, install the open-source [Florence 2 model](https://huggingface.co/microsoft/Florence-2-large) and use its Region to segmentation feature, which allows for a similar background removal operation.

articles/ai-services/computer-vision/whats-new.md

@@ -11,19 +11,33 @@ ms.custom:
   - ignite-2023
 ms.topic: whats-new
 ms.date: 03/11/2024
-ms.collection: "ce-skilling-fresh-tier2, ce-skilling-ai-copilot"
+ms.collection: ce-skilling-fresh-tier2
 ms.author: pafarley
 ---
 
 # What's new in Azure AI Vision
 
 Learn what's new in Azure AI Vision. Check this page to stay up to date with new features, enhancements, fixes, and documentation updates. 
 
-## September 2024
+## January 2025
 
-### Model customization and Product Recognition deprecation
+### Image Analysis 4.0 Preview API deprecation
 
-On January 10, 2025, the Azure AI Vision Product Recognition and model customization features will be retired. After this date, API calls to these services will fail.
+On March 31, 2025, the Image Analysis 4.0 Preview APIs will be retired. Before that date, you'll need to migrate your Azure Image Analysis workloads to the [Image Analysis 4.0 GA ](/rest/api/computervision/operation-groups?view=rest-computervision-v4.0%20(2024-02-01))API.
+
+We encourage you to make the transition sooner to gain access to improvements such as multimodal embedding, synchronous OCR, people detection, image tagging, smart cropping, caption, dense caption, and image object detection.
+These Image Analysis 4.0 preview APIs will be retired on March 31, 2025:
+- `2022-07-31-preview`
+- `2022-10-12-preview`
+- `2023-02-01-preview`
+- `2023-04-01-preview`
+- `2023-07-01-preview`
+- `v4.0-preview.1`
+
+These features will no longer be available with the retirement of the preview API versions:
+- Model customization
+- Background removal
+- Product recognition
 
 To maintain a smooth operation of your models, transition to [Azure AI Custom Vision](/azure/ai-services/Custom-Vision-Service/overview), which is now generally available. Custom Vision offers similar functionality to these retiring features.
 

articles/ai-services/document-intelligence/language-support/prebuilt.md

@@ -207,7 +207,7 @@ Azure AI Document Intelligence models provide multilingual document processing s
 | • Spanish (`es`) |Spain (`es`)|
 | • Swedish (`sv`) | Sweden (`se`)|
 | • Thai (`th`) | Thailand (`th`)|
-| • Turkish (`tr`) | Turkey (`tr`)|
+| • Turkish (`tr`) | Türkiye (`tr`)|
 | • Ukrainian (`uk`) | Ukraine (`uk`)|
 | • Vietnamese (`vi`) | Vietnam (`vi`)|
 

articles/ai-services/language-service/language-detection/language-support.md

@@ -187,7 +187,7 @@ If you have content expressed in a less frequently used language, you can try La
 | Kannada                               | `kn`        | `Latn`, `Knda` |
 | Malayalam                             | `ml`        | `Latn`, `Mlym` |
 | Marathi	                            | `mr`        | `Latn`, `Deva` |
-| Oriya                                 | `or`        | `Latn`, `Orya` |
+| Odia                                  | `or`        | `Latn`, `Orya` |
 | Punjabi                               | `pa`        | `Latn`, `Guru` |
 | Tamil                                 | `ta`        | `Latn`, `Taml` |
 | Telugu                                | `te`        | `Latn`, `Telu` |

articles/ai-services/metrics-advisor/how-tos/onboard-your-data.md

@@ -115,7 +115,7 @@ Consider the following scenarios:
 
 * *"My data has already rolled up and the dimension value is represented by: NULL or Empty (Default), NULL only, Others."*
 
-    This option means Metrics Advisor doesn't need to roll up the data because the rows are already summed. For example, if you select *NULL only*, then the second data row in the below example will be seen as an aggregation of all countries and language *EN-US*; the fourth data row which has an empty value for *Country* however will be seen as an ordinary row which might indicate incomplete data.
+    This option means Metrics Advisor doesn't need to roll up the data because the rows are already summed. For example, if you select *NULL only*, then the second data row in the below example will be seen as an aggregation of all countries/regions and language *EN-US*; the fourth data row which has an empty value for *Country* however will be seen as an ordinary row which might indicate incomplete data.
 
     | Country/Region | Language | Income |
     |---------|----------|--------|

articles/ai-services/openai/api-version-deprecation.md

@@ -5,7 +5,7 @@ services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: conceptual 
-ms.date: 01/08/2024
+ms.date: 01/10/2024
 author: mrbullwinkle
 ms.author: mbullwin
 recommendations: false
@@ -25,7 +25,10 @@ This article is to help you understand the support lifecycle for the Azure OpenA
 Azure OpenAI API latest release:
 
 - Inference: [2024-12-01-preview](reference-preview.md)
-- Authoring: [2024-12-01-preview](https://github.com/Azure/azure-rest-api-specs/blob/main/specification/cognitiveservices/data-plane/AzureOpenAI/authoring/preview/2024-10-01-preview/azureopenai.json)
+- Authoring: [2024-10-01-preview](https://github.com/Azure/azure-rest-api-specs/blob/main/specification/cognitiveservices/data-plane/AzureOpenAI/authoring/preview/2024-10-01-preview/azureopenai.json)
+
+> [!IMPORTANT]
+> For features that are part of the dataplane authoring API such as batch, fine-tuning, and assistants files, continue to use API version `2024-10-01-preview` to take advantage of the latest preview features.
 
 This version contains support for the latest Azure OpenAI features including:
 

articles/ai-services/openai/assistants-reference.md

@@ -42,6 +42,62 @@ Create an assistant with a model and instructions.
 | response_format | string or object | Optional | Specifies the format that the model must output. Compatible with GPT-4 Turbo and all GPT-3.5 Turbo models since gpt-3.5-turbo-1106. Setting this parameter to `{ "type": "json_object" }` enables JSON mode, which guarantees the message the model generates is valid JSON. Importantly, when using JSON mode, you must also instruct the model to produce JSON yourself using a system or user message. Without this instruction, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Additionally, the message content may be partially cut off if you use `finish_reason="length"`, which indicates the generation exceeded `max_tokens` or the conversation exceeded the max context length. |
 | tool_resources | object | Optional | A set of resources that are used by the assistant's tools. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs. |
 
+### response_format types
+
+**string**
+
+`auto` is the default value.
+
+**object**
+
+Possible `type` values: `text`, `json_object`, `json_schema`.
+
+***json_schema***
+
+| Name | Type | Description | Default | Required/Optional |
+|---  |---   |---       |--- |--- |
+| `description` | string | A description of what the response format is for, used by the model to determine how to respond in the format. |  | Optional |
+| `name` | string | The name of the response format. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64. |  | Required |
+| `schema` | object | The schema for the response format, described as a JSON Schema object. |  | Optional |
+| `strict` | boolean or null | Whether to enable strict schema adherence when generating the output. If set to true, the model will always follow the exact schema defined in the `schema` field. Only a subset of JSON Schema is supported when `strict` is `true`. | false | Optional |
+
+### tool_resources properties
+
+**code_interpreter**
+
+| Name | Type | Description | Default |
+|---  |---   |---       |--- |
+| `file_ids` | array | A list of file IDs made available to the code_interpreter tool. There can be a maximum of 20 files associated with the tool. | `[]` |
+
+**file_search**
+
+| Name | Type | Description | Required/Optional |
+|---  |---   |---       |--- |
+| `vector_store_ids` | array | The vector store attached to this thread. There can be a maximum of 1 vector store attached to the thread. | Optional | 
+| `vector_stores` | array | A helper to create a vector store with file_ids and attach it to this thread. There can be a maximum of 1 vector store attached to the thread. | Optional |
+
+***vector_stores***
+
+| Name | Type | Description | Required/Optional |
+|---  |---   |---       |--- |
+| `file_ids` | array | A list of file IDs to add to the vector store. There can be a maximum of 10000 files in a vector store. | Optional | 
+| `chunking_strategy` | object | The chunking strategy used to chunk the file(s). If not set, will use the auto strategy. | Optional |
+| `metadata` | map | Set of 16 key-value pairs that can be attached to a vector store. This can be useful for storing additional information about the vector store in a structured format. Keys can be a maximum of 64 characters long and values can be a maximum of 512 characters long. | Optional |
+
+***chunking_strategy***
+
+| Name | Type | Description | Required/optional | 
+|---  |---   |---       |---|
+| `Auto Chunking Strategy` | object | The default strategy. This strategy currently uses a `max_chunk_size_tokens` of `800` and `chunk_overlap_tokens` of `400`. `type` is always `auto` | Required |
+| `Static Chunking Strategy` | object | `type` Always `static`  | Required |
+
+***Static Chunking Strategy***
+
+| Name | Type | Description | Required/Optional |
+|---  |---   |---       |--- |
+| `max_chunk_size_tokens` | integer | The maximum number of tokens in each chunk. The default value is `800`. The minimum value is `100` and the maximum value is `4096`. | Required |
+| `chunk_overlap_tokens` | integer | The number of tokens that overlap between chunks. The default value is `400`. Note that the overlap must not exceed half of `max_chunk_size_tokens`. | Required |
+
 ### Returns
 
 An [assistant](#assistant-object) object.

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

@@ -4,7 +4,7 @@ titleSuffix: Azure OpenAI
 description: Learn about the model deprecations and retirements in Azure OpenAI.
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 12/02/2024
+ms.date: 01/09/2025
 ms.custom: 
 manager: nitinme
 author: mrbullwinkle
@@ -98,15 +98,16 @@ These models are currently available for use in Azure OpenAI Service.
 | `gpt-35-turbo` | 0301 | February 13, 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: `0125`, starting on January 13, 2025.   | `gpt-35-turbo` (0125) <br><br> `gpt-4o-mini`  |
 | `gpt-35-turbo`<br>`gpt-35-turbo-16k` | 0613 | February 13, 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: `0125`, starting on January 13, 2025.  | `gpt-35-turbo` (0125) <br><br> `gpt-4o-mini`|
 | `gpt-35-turbo` | 1106 | No earlier than March 31, 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: `0125`, starting on January 13, 2025. | `gpt-35-turbo` (0125) <br><br> `gpt-4o-mini` |
-| `gpt-35-turbo` | 0125 | No earlier than March 31, 2025 | `gpt-4o-mini` |
+| `gpt-35-turbo` | 0125 | No earlier than May 31, 2025 | `gpt-4o-mini` |
 | `gpt-4`<br>`gpt-4-32k` | 0314 | June 6, 2025 | `gpt-4o` |
 | `gpt-4`<br>`gpt-4-32k` | 0613 | June 6, 2025 | `gpt-4o` |
 | `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 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 February 13, 2025. | |
 | `gpt-4o-mini` | 2024-07-18 | No earlier than July 18, 2025  | |
-| `gpt-3.5-turbo-instruct` | 0914 | No earlier than February 1, 2025 |  |
+| `gpt-3.5-turbo-instruct` | 0914 | No earlier than April 1, 2025 |  |
+| `o1` | 2024-12-17 | No earlier than December 17, 2025 | |
 | `text-embedding-ada-002` | 2 | No earlier than October 3, 2025 | `text-embedding-3-small` or `text-embedding-3-large` |
 | `text-embedding-ada-002` | 1 | No earlier than October 3, 2025 | `text-embedding-3-small` or `text-embedding-3-large` |
 | `text-embedding-3-small` | | No earlier than October 3, 2025 | |
@@ -162,6 +163,12 @@ If you're an existing customer looking for information about these models, see [
 
 ## Retirement and deprecation history
 
+## January 9, 2025
+
+- `o1` added.
+- `gpt-35-turbo instruct` updated to no earlier than April 1, 2025.
+- `gpt-35-turbo` (0125) updated to no earlier than May 31, 2025.
+
 ## December 11, 2024
 
 Embeddings models updated to no earlier than October 3, 2025.