# ハイライト
このコードの修正では、全体的に日付やリンクの更新が行われ、ドキュメントの正確性とユーザーの利便性を向上させました。また、視覚的な情報の追加により、機能の理解を促進することが図られています。

新機能

コールセンター業務や会話、感情分析、健康向けテキスト解析などに関する視覚的説明を強化するため、新しい画像が追加されました。

破壊的変更

特記すべき破壊的な変更は含まれていません。

その他の更新

複数のドキュメントで日付が更新され、最新情報が反映されるようになっています。
Azure AI Foundryへのリンクの追加や修正により、ユーザーは関連リソースに直接かつ容易にアクセス可能になりました。
ドキュメントの目次が大幅に更新され、ユーザーが重要な情報に迅速にアクセスしやすくなっています。

インサイト

今回の修正は、主にドキュメントの正確性とユーザー体験の向上に重点を置いています。視覚的な要素が追加されたことで、AIサービスの理解を深める一助となっています。例えば、コールセンター要約や感情分析、固有表現抽出などの機能は、視覚的な説明により、非技術者でも直感的に理解しやすくなります。

また、リンクの修正や日付の更新は、AzureのAI機能が正確にかつタイムリーにユーザーに伝達されることを確保するために重要であり、無駄な混乱を減らし、利用者には最新かつ正確なガイダンスとして機能します。

特に目次の全面的な更新は、ユーザーが目的の情報へのアクセスを容易にし、学習曲線を下げる効果を生むでしょう。これにより、ユーザーがAzure AIの利点を最大限に引き出すことが期待されます。

Summary Table

Filename	Type	Title	Status	A	D	M
disaster-recovery.md	minor update	更新された日付と説明の修正	modified	7	7	14
read.md	minor update	日付の更新と内容修正	modified	1	3	4
receipt.md	minor update	レシートモデルの説明更新	modified	1	1	2
call-center-summarization.png	new feature	コールセンターの要約に関する画像追加	added	0	0	0
conversation-pii.png	new feature	会話におけるPIIに関する画像追加	added	0	0	0
conversation-summarization.png	new feature	会話要約に関する画像追加	added	0	0	0
key-phrase-extraction.png	new feature	キーフレーズ抽出に関する画像追加	added	0	0	0
language-detection.png	new feature	言語検出に関する画像追加	added	0	0	0
named-entity-recognition.png	new feature	固有表現抽出に関する画像追加	added	0	0	0
sentiment-analysis.png	new feature	感情分析に関する画像追加	added	0	0	0
text-analytics-for-health.png	new feature	健康向けテキスト解析に関する画像追加	added	0	0	0
text-pii.png	new feature	個人情報のテキストに関する画像追加	added	0	0	0
text-summarization.png	new feature	テキスト要約に関する画像追加	added	0	0	0
overview.md	minor update	言語サービスの概要の更新	modified	19	14	33
content-safety-overview.md	minor update	コンテンツ安全性の概要のリンク修正	modified	2	2	4
content-filtering.md	minor update	コンテンツフィルタリングの概要にリンク追加	modified	1	1	2
rbac-ai-studio.md	minor update	Azure AI Administratorロールの名称修正	modified	3	3	6
vulnerability-management.md	minor update	最終更新日付の修正	modified	1	3	4
access-on-premises-resources.md	minor update	最終更新日付の修正	modified	1	1	2
deploy-stability-models.md	minor update	リンク先の更新	modified	1	1	2
disable-local-auth.md	minor update	最終更新日付の修正	modified	1	1	2
use-blocklists.md	minor update	リンクの追加	modified	1	1	2
create-content-filter.md	minor update	リンクの明示化	modified	1	1	2
toc.yml	minor update	目次の大幅な更新	modified	442	296	738

Modified Contents

articles/ai-services/document-intelligence/how-to-guides/disaster-recovery.md

Diff

@@ -6,7 +6,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-document-intelligence
 ms.topic: how-to
-ms.date: 11/19/2024
+ms.date: 02/20/2025
 ms.author: lajanuar
 ---
 
@@ -38,15 +38,15 @@ When you create a Document Intelligence resource in the Azure portal, you specif
 The Copy API enables this scenario by allowing you to copy custom models and classifiers from one Document Intelligence account or into others, which can exist in any supported geographical region. This guide shows you how to use the Copy REST API with cURL for custom models. You can also use an HTTP request service to issue the requests.
 
 > [!NOTE]
-> The 2024-11-30 (GA) API custom classification model supports the Copy API. This guide specifically uses custom models to copy models. For classifier model copy, follow the [train a custom classifier guide](../train/custom-classifier.md#copy-a-model).
+> The `2024-11-30` (GA) API custom classification model supports the Copy API. This guide specifically uses custom models to copy models. For classifier model copy, follow the [train a custom classifier guide](../train/custom-classifier.md#copy-a-model).
 
 ## Business scenarios
 
 If your app or business depends on the use of a Document Intelligence custom model, we recommend you copy your model to another Document Intelligence account in another region. If a regional outage occurs, you can then access your model in the region where it was copied.
 
 ## Prerequisites
 
-1. Two Document Intelligence Azure resources in different Azure regions. If you don't have them, go to the Azure portal and [create a new Document Intelligence resource](https://portal.azure.com/#create/Microsoft.CognitiveServicesFormRecognizer).
+1. Two Document Intelligence Azure resources in different Azure subscriptions or regions. If you don't have them, go to the Azure portal and [create a new Document Intelligence resource](https://portal.azure.com/#create/Microsoft.CognitiveServicesFormRecognizer).
 1. The key, endpoint URL, and subscription ID for your Document Intelligence resource. You can find these values on the resource's **Overview** tab in the [Azure portal](https://portal.azure.com/#home).
 
 ::: moniker-end
@@ -122,7 +122,7 @@ Operation-Location: https://<your-resource-endpoint>.cognitiveservices.azure.com
 ```
 
 > [!NOTE]
-> The Copy API transparently supports the [AEK/CMK](https://msazure.visualstudio.com/Cognitive%20Services/_wiki/wikis/Cognitive%20Services.wiki/52146/Customer-Managed-Keys) feature. This doesn't require any special treatment, but note that if you're copying between an unencrypted resource to an encrypted resource, you need to include the request header `x-ms-forms-copy-degrade: true`. If this header is not included, the copy operation will fail and return a `DataProtectionTransformServiceError`.
+> The Copy API transparently supports the [AEK/CMK](https://msazure.visualstudio.com/Cognitive%20Services/_wiki/wikis/Cognitive%20Services.wiki/52146/Customer-Managed-Keys) feature. This action doesn't require any special treatment, but note that if you're copying between an unencrypted resource to an encrypted resource, you need to include the request header `x-ms-forms-copy-degrade: true`. If this header isn't included, the copy operation fails and returns a `DataProtectionTransformServiceError`.
 
 ## Track Copy progress
 
@@ -289,7 +289,7 @@ Operation-Location: https://{source-resource}.cognitiveservices.azure.com/formre
 ```
 
 > [!NOTE]
-> The Copy API transparently supports the [AEK/CMK](https://msazure.visualstudio.com/Cognitive%20Services/_wiki/wikis/Cognitive%20Services.wiki/52146/Customer-Managed-Keys) feature. This doesn't require any special treatment, but note that if you're copying between an unencrypted resource to an encrypted resource, you need to include the request header `x-ms-forms-copy-degrade: true`. If this header is not included, the copy operation will fail and return a `DataProtectionTransformServiceError`.
+> The Copy API transparently supports the [AEK/CMK](https://msazure.visualstudio.com/Cognitive%20Services/_wiki/wikis/Cognitive%20Services.wiki/52146/Customer-Managed-Keys) feature. This action doesn't require any special treatment, but note that if you're copying between an unencrypted resource to an encrypted resource, you need to include the request header `x-ms-forms-copy-degrade: true`. If this header isn't included, the copy operation fails and returns a `DataProtectionTransformServiceError`.
 
 ## Track Copy progress
 
@@ -439,7 +439,7 @@ Operation-Location: https://{SOURCE_FORM_RECOGNIZER_RESOURCE_ENDPOINT}/formrecog
 ```
 
 > [!NOTE]
-> The Copy API transparently supports the [AEK/CMK](https://msazure.visualstudio.com/Cognitive%20Services/_wiki/wikis/Cognitive%20Services.wiki/52146/Customer-Managed-Keys) feature. This operation doesn't require any special treatment, but note that if you're copying between an unencrypted resource to an encrypted resource, you need to include the request header `x-ms-forms-copy-degrade: true`. If this header is not included, the copy operation will fail and return a `DataProtectionTransformServiceError`.
+> The Copy API transparently supports the [AEK/CMK](https://msazure.visualstudio.com/Cognitive%20Services/_wiki/wikis/Cognitive%20Services.wiki/52146/Customer-Managed-Keys) feature. This operation doesn't require any special treatment, but note that if you're copying between an unencrypted resource to an encrypted resource, you need to include the request header `x-ms-forms-copy-degrade: true`. If this header isn't included, the copy operation fails and returns a `DataProtectionTransformServiceError`.
 
 ### Track operation progress
 
@@ -508,7 +508,7 @@ curl -i GET "https://<SOURCE_FORM_RECOGNIZER_RESOURCE_ENDPOINT>/formrecognizer/v
 | 400 / Bad Request with `"code:" "1002"` | Indicates validation error or badly formed copy request. Common issues include: a) Invalid or modified `copyAuthorization` payload. b) Expired value for `expirationDateTimeTicks` token (`copyAuthorization` payload is valid for 24 hours). c) Invalid or unsupported `targetResourceRegion`. d) Invalid or malformed `targetResourceId` string.
 |*Authorization failure due to missing or invalid authorization claims*.| Occurs when the `copyAuthorization` payload or content is modified from the `copyAuthorization` API. Ensure that the payload is the same exact content that was returned from the earlier `copyAuthorization` call.|
 |*Couldn't retrieve authorization metadata*.| Indicates that the `copyAuthorization` payload is being reused with a copy request. A copy request that succeeds doesn't allow any further requests that use the same `copyAuthorization` payload. If you raise a separate error and you later retry the copy with the same authorization payload, this error gets raised. The resolution is to generate a new `copyAuthorization` payload and then reissue the copy request.|
-|*Data transfer request isn't allowed as it downgrades to a less secure data protection scheme*.| Occurs when copying between an `AEK` enabled resource to a non `AEK` enabled resource. To allow copying encrypted model to the target as unencrypted, specify `x-ms-forms-copy-degrade: true` header with the copy request.|
+|*Data transfer request isn't allowed as it downgrades to a less secure data protection scheme*.| Occurs when copying between an `AEK` enabled resource to a non- `AEK` enabled resource. To allow copying encrypted model to the target as unencrypted, specify `x-ms-forms-copy-degrade: true` header with the copy request.|
 |"Couldn't fetch information for Cognitive resource with ID...". | Indicates that the Azure resource indicated by the `targetResourceId` isn't a valid Cognitive resource or doesn't exist. To resolve this issue, verify and reissue the copy request.</br> Ensure the resource is valid and exists in the specified region, such as, `westus2`|
 
 ::: moniker-end

Summary

{
    "modification_type": "minor update",
    "modification_title": "更新された日付と説明の修正"
}

Explanation

この変更では、disaster-recovery.md ドキュメントのいくつかの部分が更新されました。主な変更点は、日付の更新とテキストの一部の修正です。

日付の更新: ドキュメント内の日付が「2024-11-30」から「2025-02-20」に変更され、最新のリリース日を反映しています。
テキストの修正: いくつかの部分で「この操作」を表す英語表現が「このシナリオ」に変更されるなど、文言において微調整が行われました。これにより、読みやすさが向上しています。また、リファレンスや条件の説明がより明確に記述されています。

これらの変更は、ドキュメントの正確性と明確性を向上させることを目的としています。修正された内容は、文書に記載されたプロセスや条件に従って利用されるアプリケーションユーザーの理解を促進するためのものであり、利用者の利便性が強化されています。

articles/ai-services/document-intelligence/prebuilt/read.md

Diff

@@ -6,7 +6,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-document-intelligence
 ms.topic: conceptual
-ms.date: 11/19/2024
+ms.date: 02/19/2025
 ms.author: lajanuar
 ---
 
@@ -22,8 +22,6 @@ ms.author: lajanuar
 
 **This content applies to:**![checkmark](../media/yes-icon.png) **v4.0 (GA)** | **Previous versions:** ![blue-checkmark](../media/blue-yes-icon.png) [**v3.1 (GA)**](?view=doc-intel-3.1.0&preserve-view=tru) ![blue-checkmark](../media/blue-yes-icon.png) [**v3.0 (GA)**](?view=doc-intel-3.0.0&preserve-view=tru)
 
-**This content applies to:**![checkmark](../media/yes-icon.png) **v4.0 (GA)** | **Previous versions:** ![blue-checkmark](../media/blue-yes-icon.png) [**v3.1 (GA)**](?view=doc-intel-3.1.0&preserve-view=tru) ![blue-checkmark](../media/blue-yes-icon.png) [**v3.0 (GA)**](?view=doc-intel-3.0.0&preserve-view=tru)
-
 > [!NOTE]
 >
 > To extract text from external images like labels, street signs, and posters, use the [Azure AI Image Analysis v4.0 Read](../../Computer-vision/concept-ocr.md) feature optimized for general (not document) images with a performance-enhanced synchronous API. This capability makes it easier to embed OCR in real-time user experience scenarios.

Summary

{
    "modification_type": "minor update",
    "modification_title": "日付の更新と内容修正"
}

Explanation

この変更は、read.md ドキュメントに対するいくつかの小さな修正を含んでいます。主なポイントは以下の通りです。

日付の更新: ドキュメントの最終更新日が「2024年11月19日」から「2025年2月19日」に変更され、最新の情報が反映されています。
内容の修正: 重複していた文が削除され、より整理された形にしています。この変更により、内容が一貫性を持ち、可読性が向上しています。
外部画像からのテキスト抽出に関する触れ: AzureのAI機能が強調され、主に一般的な画像向けに最適化されたOCRの使用が説明されています。これは、ドキュメント内の機能をより理解しやすくするもので、利用者が利用可能なツールを把握する手助けとなります。

全体として、これらの修正は、ユーザーに対して明確で効果的な情報を提供することを目指しています。

articles/ai-services/document-intelligence/prebuilt/receipt.md

Diff

@@ -30,7 +30,7 @@ ms.author: lajanuar
 [!INCLUDE [applies to v2.1](../includes/applies-to-v21.md)]
 ::: moniker-end
 
-The Document Intelligence receipt model combines powerful Optical Character Recognition (OCR) capabilities with deep learning models to analyze and extract key information from sales receipts. Receipts can be of various formats and quality including printed and handwritten receipts. The API extracts key information such as merchant name, merchant phone number, transaction date, tax, and transaction total and returns structured JSON data. Receipt model v4.0 (GA) also supports other fields including `ReceiptType`, `TaxDetails.NetAmount`, `TaxDetails.Description`, `TaxDetails.Rate` and `CountryRegion`.
+The Document Intelligence receipt model combines powerful Optical Character Recognition (OCR) capabilities with deep learning models to analyze and extract key information from sales receipts. Receipts can be of various formats and quality including printed and handwritten receipts. The API extracts key information such as merchant name, merchant phone number, transaction date, tax, and transaction total and returns structured JSON data. Receipt model v4.0 (GA) supports other fields including `ReceiptType`, `TaxDetails.NetAmount`, `TaxDetails.Description`, `TaxDetails.Rate` and `CountryRegion` along with VAT table extraction on general hotel receipts. VAT table extraction support for Nordic Receipts will be added in March 2025. 
 
 **Supported receipt types in the latest version (4.0):**

Summary

{
    "modification_type": "minor update",
    "modification_title": "レシートモデルの説明更新"
}

Explanation

この変更では、receipt.md ドキュメントに対して小さな修正が行われています。具体的な内容は以下の通りです。

説明の拡充: ドキュメント内のレシートモデルに関する説明が強化され、新たに「VATテーブルの抽出」機能について触れられています。特に、一般的なホテルのレシートに対するVATテーブル抽出のサポートが述べられており、北欧のレシートに関するサポートが2025年3月に追加されることが明記されています。
テキストの整理: 文中の表現が微調整され、より流暢で明確な説明となっています。特に、サポートされるフィールドの説明がより簡潔に表現されています。

これらの変更は、ユーザーがレシートモデルの機能をより良く理解できるようにすることを目的としており、今後のアップデートに関する重要な情報も提供しています。全体として、ドキュメントは明確さと有用性を高める方向に改善されています。

articles/ai-services/language-service/media/overview/call-center-summarization.png

Summary

{
    "modification_type": "new feature",
    "modification_title": "コールセンターの要約に関する画像追加"
}

Explanation

この変更では、call-center-summarization.png という新しい画像が overview メディアフォルダに追加されました。この画像は、コールセンターの要約機能に関連する内容を視覚的に示す目的で追加されたものです。

ビジュアルサポート: 画像の追加により、ユーザーはテキスト情報だけでなく、視覚的な情報も得ることができます。これにより、コールセンターの要約機能の理解が深まり、情報がより分かりやすくなることが期待されます。
機能の強調: このような画像は、機能を説明する際に非常に有効であり、特に技術的な内容を伝える場合に役立ちます。視覚的な要素が加わることで、ユーザーの関心を引き、吸収された情報を強化する役割を果たしています。

全体として、この変更はコールセンターの要約機能に関する資料をより充実させ、理解を助けるための重要な追加要素となっています。

articles/ai-services/language-service/media/overview/conversation-pii.png

Summary

{
    "modification_type": "new feature",
    "modification_title": "会話におけるPIIに関する画像追加"
}

Explanation

この変更では、conversation-pii.png という新しい画像が overview メディアフォルダに追加されました。この画像は、会話における個人情報（PII）に関連する内容を視覚的に表現することを目的としています。

ビジュアルコンテンツの強化: 新たに追加された画像により、テキスト情報だけではなく、視覚的な要素が加わることで、ユーザーの理解を促進することが期待されます。特に、個人情報の取り扱いやその重要性についての説明を補足する役割を果たします。
理解の促進: PII（Personally Identifiable Information）に関連する内容を視覚的に提示することで、ユーザーがその概念と重要性をよりよく理解できるようになります。これは特に、プライバシー保護が重要なトピックであるため、有益です。

このように、conversation-pii.png の追加は、会話中における個人情報に関する文脈をより明確に示す手段となり、ユーザーが情報をより深く理解するのに役立つものとなっています。

articles/ai-services/language-service/media/overview/conversation-summarization.png

Summary

{
    "modification_type": "new feature",
    "modification_title": "会話要約に関する画像追加"
}

Explanation

この変更では、conversation-summarization.png という新しい画像が overview メディアフォルダに追加されました。この画像は、会話の要約機能に関連する情報を視覚化することを目的としています。

視覚的な情報提供: 新たに追加された画像は、会話要約のプロセスや機能を視覚的に示すことで、ユーザーがその概念をより理解しやすくする役割を果たします。テキストだけでは伝わりにくい要点を視覚的に補完することで、学習効果を高めます。
機能の強調: 会話要約機能は、多くのビジネスシーンで利用される重要な機能であるため、その理解を深めるために視覚的要素を追加することは特に有益です。これにより、ユーザーは要約の仕組みやその応用についてより明確になるでしょう。

このように、conversation-summarization.png の追加は、会話要約機能の理解を促進するための重要なビジュアルコンテンツであり、関連情報をより効果的に伝える手助けとなります。

articles/ai-services/language-service/media/overview/key-phrase-extraction.png

Summary

{
    "modification_type": "new feature",
    "modification_title": "キーフレーズ抽出に関する画像追加"
}

Explanation

この変更では、key-phrase-extraction.png という新しい画像が overview メディアフォルダに追加されました。この画像は、キーフレーズ抽出機能の説明を視覚的に補完することを目的としています。

視覚的な理解の促進: 新たに追加された画像により、キーフレーズ抽出のプロセスや重要性を視覚的に示すことができ、ユーザーはその概念をより簡単に理解することができます。視覚情報は、テキストのみでは伝わりにくい要素を強調するのに役立ちます。
機能の重要性の強調: キーフレーズ抽出機能は、テキスト分析の重要な部分であり、多くのアプリケーションやサービスで利用されるため、こうした視覚的コンテンツはユーザーにとって非常に有益です。この追加により、ユーザーは抽出されたキーフレーズの意義を理解しやすくなります。

このように、key-phrase-extraction.png の追加は、キーフレーズ抽出機能の理解を深めるための重要なビジュアルリソースとなり、関連情報をより効果的に伝える手助けをします。

articles/ai-services/language-service/media/overview/language-detection.png

Summary

{
    "modification_type": "new feature",
    "modification_title": "言語検出に関する画像追加"
}

Explanation

この変更では、language-detection.png という新しい画像が overview メディアフォルダに追加されました。この画像は、言語検出機能を視覚的に説明するために作成されています。

視覚的な情報強化: 新しく追加された画像は、言語検出のメカニズムやその重要性を視覚的に表現しており、ユーザーがこの機能をより深く理解する助けになります。複雑な概念を簡潔に示すことで、ユーザーの学習を支援します。
機能理解の促進: 言語検出機能は、多言語に対応したアプリケーションやサービスにおいて重要な役割を果たすため、視覚的なコンテンツはユーザーの理解を助けることに寄与します。この画像追加により、ユーザーは言語検出のプロセスを視覚的に理解できるようになります。

このように、language-detection.png の追加は、言語検出機能に関する情報を効果的に伝えるための重要な要素であり、ユーザーにとって有益なリソースとなります。

articles/ai-services/language-service/media/overview/named-entity-recognition.png

Summary

{
    "modification_type": "new feature",
    "modification_title": "固有表現抽出に関する画像追加"
}

Explanation

この変更では、named-entity-recognition.png という新しい画像が overview メディアフォルダに追加されました。この画像は、固有表現抽出機能を視覚的に説明するために作成されています。

機能の視覚化: 新しく追加された画像は、固有表現抽出のプロセスやその重要性を視覚的に示しています。この視覚情報により、ユーザーは固有表現抽出の概念をより直感的に理解することができます。
情報提供の強化: 固有表現抽出は、情報処理や自然言語処理の分野で重要な役割を果たします。こうした視覚的リソースは、ユーザーがこの機能の利点や機能を把握する手助けとなります。画像を通じて、ユーザーは具体的な事例をもとに理解を深めることができます。

このように、named-entity-recognition.png の追加は、固有表現抽出機能の理解を向上させるための重要なリソースとなり、ユーザーに価値ある情報を提供します。

articles/ai-services/language-service/media/overview/sentiment-analysis.png

Summary

{
    "modification_type": "new feature",
    "modification_title": "感情分析に関する画像追加"
}

Explanation

この変更では、sentiment-analysis.png という新しい画像が overview メディアフォルダに追加されました。この画像は、感情分析機能を視覚的に説明するために作成されています。

視覚的な説明の提供: 新しく追加された画像は、感情分析のプロセスやその成果を視覚的に表現しています。この視覚リソースにより、ユーザーは感情分析の基本的な概念をより理解しやすくなります。
ユーザー教育の強化: 感情分析は、テキストデータから感情を抽出するための重要な手法です。画像を利用することで、具体的な事例を示しながら、ユーザーがこの技術の応用や利点を理解できるようになることを目的としています。

このように、sentiment-analysis.png の追加は、感情分析機能に関する情報をユーザーに効果的に伝えるための重要な要素であり、理解を深めるための貴重なリソースとなります。

articles/ai-services/language-service/media/overview/text-analytics-for-health.png

Summary

{
    "modification_type": "new feature",
    "modification_title": "健康向けテキスト解析に関する画像追加"
}

Explanation

この変更では、text-analytics-for-health.png という新しい画像が overview メディアフォルダに追加されました。この画像は、健康分野におけるテキスト解析機能を視覚的に説明することを目的としています。

健康関連の視覚化: 新しく追加された画像は、健康に特化したテキスト解析のプロセスとその役割を視覚的に示しています。このリソースにより、ユーザーは健康データからの情報抽出方法をより理解しやすくなります。
教育的価値の提供: テキスト解析は、特に医療データ分析において重要な手法です。この画像を通じて、ユーザーは具体的な機能や成果物を把握し、健康管理におけるテキスト解析の重要性を認識することができます。

このように、text-analytics-for-health.png の追加は、健康向けのテキスト解析に関する情報をユーザーに効果的に提供し、理解を促進するための重要なリソースとなります。

articles/ai-services/language-service/media/overview/text-pii.png

Summary

{
    "modification_type": "new feature",
    "modification_title": "個人情報のテキストに関する画像追加"
}

Explanation

この変更では、text-pii.png という新しい画像が overview メディアフォルダに追加されました。この画像は、個人識別情報（PII）に関連するテキスト解析機能を視覚的に説明するために作成されています。

個人情報の理解の促進: 新しい画像は、テキストから個人情報を識別・抽出するプロセスを示しています。ユーザーはこの視覚的表現を通じて、個人情報保護の重要性とその手法を理解しやすくなります。
コンプライアンスとセキュリティの強調: PIIの管理は、データセキュリティおよびプライバシーの観点から非常に重要です。この画像は、どのようにテキストデータが分析されて個人情報が保護されるかを示し、ユーザーに適切な対策を講じる必要性を理解させる役割を果たします。

このように、text-pii.png の追加は、個人情報に関するテキスト解析の情報をユーザーに提供し、理解と意識を高めるための重要なリソースとなります。

articles/ai-services/language-service/media/overview/text-summarization.png

Summary

{
    "modification_type": "new feature",
    "modification_title": "テキスト要約に関する画像追加"
}

Explanation

この変更では、text-summarization.png という新しい画像が overview メディアフォルダに追加されました。この画像は、テキスト要約機能の重要性とその仕組みを視覚的に説明するために作成されています。

テキスト要約の視覚化: 新しい画像は、様々なテキストから要約を生成するプロセスを示しています。これにより、ユーザーはテキスト要約がどのように行われるか、どのような技術が使用されるかを容易に理解できます。
情報の簡潔化の重要性: テキスト要約は、大量の情報を迅速に理解するための強力な手法です。この画像を通じて、ユーザーは情報の要点を把握しやすくなるだけでなく、その技術を利用したアプリケーションの実用性も理解できるようになります。

このように、text-summarization.png の追加は、テキスト要約の機能とその利点をユーザーにわかりやすく伝えるための重要なリソースとなります。

articles/ai-services/language-service/overview.md

Diff

@@ -7,7 +7,7 @@ author: jboback
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: overview
-ms.date: 08/23/2024
+ms.date: 02/10/2025
 ms.author: jboback
 ---
 
@@ -33,10 +33,10 @@ The Language service also provides several new features as well, which can eithe
 
 :::row:::
    :::column span="":::
-      :::image type="content" source="media/studio-examples/named-entity-recognition.png" alt-text="A screenshot of a named entity recognition example."  lightbox="media/studio-examples/named-entity-recognition.png":::
+      :::image type="content" source="media/overview/named-entity-recognition.png" alt-text="A screenshot of named entity recognition in Azure AI Foundry."  lightbox="media/overview/named-entity-recognition.png":::
    :::column-end:::
    :::column span="":::
-      [Named entity recognition](./named-entity-recognition/overview.md) is a preconfigured feature that categorizes entities (words or phrases) in unstructured text across several predefined category groups. For example: people, events, places, dates, [and more](./named-entity-recognition/concepts/named-entity-categories.md).
+      [Named entity recognition](./named-entity-recognition/overview.md) identifies different entries in text and categorizes them into pre-defined types.
 
    :::column-end:::
 :::row-end:::
@@ -45,10 +45,11 @@ The Language service also provides several new features as well, which can eithe
 
 :::row:::
    :::column span="":::
-      :::image type="content" source="media/studio-examples/personal-information-detection.png" alt-text="A screenshot of a PII detection example." lightbox="media/studio-examples/personal-information-detection.png":::
+      :::image type="content" source="media/overview/conversation-pii.png" alt-text="A screenshot of conversation personally identifying information in Azure AI Foundry." lightbox="media/overview/conversation-pii.png":::
+      :::image type="content" source="media/overview/text-pii.png" alt-text="A screenshot of text personally identifying information in Azure AI Foundry." lightbox="media/overview/text-pii.png":::
    :::column-end:::
    :::column span="":::
-      [PII detection](./personally-identifiable-information/overview.md) is a preconfigured feature that identifies, categorizes, and redacts sensitive information in both [unstructured text documents](./personally-identifiable-information/how-to-call.md), and [conversation transcripts](./personally-identifiable-information/how-to-call-for-conversations.md). For example: phone numbers, email addresses, forms of identification, [and more](./personally-identifiable-information/concepts/entity-categories.md).
+      [PII detection](./personally-identifiable-information/overview.md) identifies entities in text and conversations (chat or transcripts) that are associated with individuals.
 
    :::column-end:::
 :::row-end:::
@@ -57,10 +58,10 @@ The Language service also provides several new features as well, which can eithe
 
 :::row:::
    :::column span="":::
-      :::image type="content" source="media/studio-examples/language-detection.png" alt-text="A screenshot of a language detection example." lightbox="media/studio-examples/language-detection.png":::
+      :::image type="content" source="media/overview/language-detection.png" alt-text="A screenshot of language detection in Azure AI Foundry." lightbox="media/overview/language-detection.png":::
    :::column-end:::
    :::column span="":::
-      [Language detection](./language-detection/overview.md) is a preconfigured feature that can detect the language a document is written in, and returns a language code for a wide range of languages, variants, dialects, and some regional/cultural languages.
+      [Language detection](./language-detection/overview.md) evaluates text and detects a wide range of languages and variant dialects.
 
    :::column-end:::
 :::row-end:::
@@ -69,7 +70,7 @@ The Language service also provides several new features as well, which can eithe
 
 :::row:::
    :::column span="":::
-      :::image type="content" source="media/studio-examples/sentiment-analysis-example.png" alt-text="A screenshot of a sentiment analysis example." lightbox="media/studio-examples/sentiment-analysis-example.png":::
+      :::image type="content" source="media/overview/sentiment-analysis.png" alt-text="A screenshot of sentiment analysis in Azure AI Foundry." lightbox="media/overview/sentiment-analysis.png":::
    :::column-end:::
    :::column span="":::
       [Sentiment analysis and opinion mining](./sentiment-opinion-mining/overview.md) are preconfigured features that help you find out what people think of your brand or topic by mining text for clues about positive or negative sentiment, and can associate them with specific aspects of the text.
@@ -81,18 +82,22 @@ The Language service also provides several new features as well, which can eithe
 
 :::row:::
    :::column span="":::
-      :::image type="content" source="media/studio-examples/summarization-example.png" alt-text="A screenshot of a summarization example." lightbox="media/studio-examples/summarization-example.png":::
+      :::image type="content" source="media/overview/conversation-summarization.png" alt-text="A screenshot of conversation summarization  in Azure AI Foundry." lightbox="media/overview/conversation-summarization.png":::
+      :::image type="content" source="media/overview/call-center-summarization.png" alt-text="A screenshot of call center summarization in Azure AI Foundry." lightbox="media/overview/call-center-summarization.png":::
+      :::image type="content" source="media/overview/text-summarization.png" alt-text="A screenshot of text summarization in Azure AI Foundry." lightbox="media/overview/text-summarization.png":::
    :::column-end:::
    :::column span="":::
-      [Summarization](./summarization/overview.md) is a preconfigured feature that uses extractive text summarization to produce a summary of documents and conversation transcriptions. It extracts sentences that collectively represent the most important or relevant information within the original content.
+      [Summarization](./summarization/overview.md) condenses information for text and conversations (chat and transcripts). 
+Text summarization generates a summary, supporting two approaches: [Extractive summarization](summarization/how-to/document-summarization.md) produces a summary by extracting salient sentences within the document along with the positioning information of these sentences, and abstractive summarization, which generates a summary with concise, coherent sentences or words that aren't verbatim extract sentences from the original document.  
+Conversation summarization recaps and segments long meetings into timestamped chapters. Call center summarization summarizes customer issues and resolution.
    :::column-end:::
 :::row-end:::
 
 ### Key phrase extraction
 
 :::row:::
    :::column span="":::
-      :::image type="content" source="media/studio-examples/key-phrases.png" alt-text="A screenshot of a key phrase extraction example." lightbox="media/studio-examples/key-phrases.png":::
+      :::image type="content" source="media/overview/key-phrase-extraction.png" alt-text="A screenshot of key phrase extraction in Azure AI Foundry." lightbox="media/overview/key-phrase-extraction.png":::
    :::column-end:::
    :::column span="":::
       [Key phrase extraction](./key-phrase-extraction/overview.md) is a preconfigured feature that evaluates and returns the main concepts in unstructured text, and returns them as a list.
@@ -114,10 +119,10 @@ The Language service also provides several new features as well, which can eithe
 
 :::row:::
    :::column span="":::
-      :::image type="content" source="text-analytics-for-health/media/call-api/health-named-entity-recognition.png" alt-text="A screenshot of a text analytics for health example." lightbox="text-analytics-for-health/media/call-api/health-named-entity-recognition.png":::
+      :::image type="content" source="media/overview/text-analytics-for-health.png" alt-text="A screenshot of text analytics for health in Azure AI Foundry." lightbox="media/overview/text-analytics-for-health.png":::
    :::column-end:::
    :::column span="":::
-      [Text analytics for health](./text-analytics-for-health/overview.md) is a preconfigured feature that extracts and labels relevant medical information from unstructured texts such as doctor's notes, discharge summaries, clinical documents, and electronic health records. 
+      [Text analytics for health](./text-analytics-for-health/overview.md) Extracts and labels relevant health information from unstructured text.
    :::column-end:::
 :::row-end:::
 
@@ -190,7 +195,7 @@ This section will help you decide which Language service feature you should use
 | Extract categories of information without creating a custom model.     | Unstructured text         | The [preconfigured NER feature](./named-entity-recognition/overview.md) |       |
 | Extract categories of information using a model specific to your data. | Unstructured text | [Custom NER](./custom-named-entity-recognition/overview.md) | ✓ |
 |Extract main topics and important phrases.     | Unstructured text        | [Key phrase extraction](./key-phrase-extraction/overview.md) |   |
-| Determine the sentiment and opinions expressed in text. | Unstructured text | [Sentiment analysis and opinion mining](./sentiment-opinion-mining/overview.md) | ✓ |
+| Determine the sentiment and opinions expressed in text. | Unstructured text | [Sentiment analysis and opinion mining](./sentiment-opinion-mining/overview.md) |  |
 | Summarize long chunks of text or conversations. | Unstructured text, <br> transcribed conversations. | [Summarization](./summarization/overview.md) | | 
 | Disambiguate entities and get links to Wikipedia. | Unstructured text | [Entity linking](./entity-linking/overview.md) | | 
 | Classify documents into one or more categories. | Unstructured text | [Custom text classification](./custom-text-classification/overview.md) | ✓|

Summary

{
    "modification_type": "minor update",
    "modification_title": "言語サービスの概要の更新"
}

Explanation

この変更では、overview.md ファイルが修正され、以下のような更新が行われました：

日付の更新: 最終更新日が 08/23/2024 から 02/10/2025 に変更され、内容が最新の情報を反映していることを示しています。
画像のリンクの修正: 特定の機能に関連する画像のパスが変更され、より適切な場所にある画像が参照されるようになりました。これにより、視覚的情報が最新のものになります。
機能説明の改善: 一部の機能についての説明がより明確になり、特に名付けられたエンティティ認識（NER）、個人情報識別（PII）、言語検出、感情分析、要約などの説明が簡潔かつ具体的になりました。テキスト要約に関しては、エクストラクティブ要約とアブストラクティブ要約のアプローチについても言及されています。
新しい機能の追加: テキスト要約に関連する追加の画像が挿入され、会話やコールセンターの要約が強調されています。

全体として、この更新は言語サービスの機能の正確性を高めるとともに、ユーザーに提供される視覚的および文書的な情報の質を向上させることを目的としています。

articles/ai-studio/ai-services/content-safety-overview.md

Diff

@@ -14,7 +14,7 @@ author: PatrickFarley
 
 # Content safety in the Azure AI Foundry portal
 
-Azure AI Content Safety is an AI service that detects harmful user-generated and AI-generated content in applications and services. Azure AI Content Safety includes various APIs that allow you to detect and prevent the output of harmful content. The interactive Content Safety **try out** page in Azure AI Foundry portal allows you to view, explore, and try out sample code for detecting harmful content across different modalities. 
+Azure AI Content Safety is an AI service that detects harmful user-generated and AI-generated content in applications and services. Azure AI Content Safety includes various APIs that allow you to detect and prevent the output of harmful content. The interactive Content Safety **try out** page in [Azure AI Foundry portal](https://ai.azure.com) allows you to view, explore, and try out sample code for detecting harmful content across different modalities. 
 
 ## Features 
 
@@ -46,4 +46,4 @@ Refer to the [Content Safety overview](/azure/ai-services/content-safety/overvie
 
 ## Next step 
 
-Get started using Azure AI Content Safety in Azure AI Foundry portal by following the [How-to guide](./how-to/content-safety.md).
\ No newline at end of file
+Get started using Azure AI Content Safety in [Azure AI Foundry portal](https://ai.azure.com) by following the [How-to guide](./how-to/content-safety.md).
\ No newline at end of file

Summary

{
    "modification_type": "minor update",
    "modification_title": "コンテンツ安全性の概要のリンク修正"
}

Explanation

この変更では、content-safety-overview.md ファイルが修正され、以下のような更新が行われました：

リンクの追加: Azure AI Foundryポータルへのリンクが追加され、特に「Azure AI Foundry portal」を直接リンクすることで、ユーザーがポータルにアクセスしやすくなっています。この変更により、利用可能なリソースへのナビゲーションが改善されます。
表現の明確化: コンテンツ安全性に関する説明文がわずかに調整され、より流暢で分かりやすくなっています。具体的には、関連するリソースとしてのAzure AI Foundryポータルへの明示的な言及が強調されました。

全体的に、この変更はユーザーが必要な情報に迅速にアクセスできるようにするためのものであり、Azure AI Content Safety の使用を促進する目的があります。

articles/ai-studio/concepts/content-filtering.md

Diff

@@ -17,7 +17,7 @@ author: PatrickFarley
 
 # Content filtering in Azure AI Foundry portal
 
-Azure AI Foundry includes a content filtering system that works alongside core models and DALL-E image generation models.
+[Azure AI Foundry](https://ai.azure.com) includes a content filtering system that works alongside core models and DALL-E image generation models.
 
 > [!IMPORTANT]
 > The content filtering system isn't applied to prompts and completions processed by the Whisper model in Azure OpenAI Service. Learn more about the [Whisper model in Azure OpenAI](../../ai-services/openai/concepts/models.md).

Summary

{
    "modification_type": "minor update",
    "modification_title": "コンテンツフィルタリングの概要にリンク追加"
}

Explanation

この変更では、content-filtering.md ファイルが修正され、以下のような更新が行われました：

リンクの追加: 「Azure AI Foundry」へのリンクが追加され、特にアクセス先が明示されることで、ユーザーがポータルに直接アクセスしやすくなっています。これにより、情報を探しているユーザーが必要なリソースに迅速にたどり着けるようになります。
表現の明確化: コンテンツフィルタリングシステムの説明がわずかに調整され、リンクを追加することで、文の流れがスムーズになっています。

全体として、この更新はリソースへのアクセスを簡素化し、ユーザーが Azure AI Foundry の機能をより利用しやすくすることを目的としています。

articles/ai-studio/concepts/rbac-ai-studio.md

Diff

@@ -40,7 +40,7 @@ Here's a table of the built-in roles and their permissions for the hub:
 | --- | --- |
 | Owner | Full access to the hub, including the ability to manage and create new hubs and assign permissions. This role is automatically assigned to the hub creator|
 | Contributor | User has full access to the hub, including the ability to create new hubs, but isn't able to manage hub permissions on the existing resource. |
-| Azure AI Administrator (preview) | This role is automatically assigned to the system-assigned managed identity for the hub. The Azure AI Administrator role has the minimum permissions needed for the managed identity to perform its tasks. For more information, see [Azure AI Administrator role preview](#azure-ai-administrator-role-preview). |
+| Azure AI Administrator (preview) | This role is automatically assigned to the system-assigned managed identity for the hub. The Azure AI Administrator role has the minimum permissions needed for the managed identity to perform its tasks. For more information, see [Azure AI Administrator role (preview)](#azure-ai-administrator-role-preview). |
 | Azure AI Developer |     Perform all actions except create new hubs and manage the hub permissions. For example, users can create projects, compute, and connections. Users can assign permissions within their project. Users can interact with existing Azure AI resources such as Azure OpenAI, Azure AI Search, and Azure AI services. |
 | Azure AI Inference Deployment Operator | Perform all actions required to create a resource deployment within a resource group. |
 | Reader |     Read only access to the hub. This role is automatically assigned to all project members within the hub. |
@@ -49,7 +49,7 @@ The key difference between Contributor and Azure AI Developer is the ability to
 
 Only the Owner and Contributor roles allow you to make a hub. At this time, custom roles can't grant you permission to make hubs.
 
-### Azure AI Administrator role preview
+### Azure AI Administrator role (preview)
 
 Prior to 11/19/2024, the system-assigned managed identity created for the hub was automatically assigned the __Contributor__ role for the resource group that contains the hub and projects. Hubs created after this date have the system-assigned managed identity assigned to the __Azure AI Administrator__ role. This role is more narrowly scoped to the minimum permissions needed for the managed identity to perform its tasks.
 
@@ -189,7 +189,7 @@ Here's a table of the built-in roles and their permissions for the project:
 | --- | --- |
 | Owner | Full access to the project, including the ability to assign permissions to project users. |
 | Contributor |    User has full access to the project but can't assign permissions to project users. |
-| Azure AI Administrator (preview) | This role is automatically assigned to the system-assigned managed identity for the hub. The Azure AI Administrator role has the minimum permissions needed for the managed identity to perform its tasks. For more information, see [Azure AI Administrator role preview](#azure-ai-administrator-role-preview). |
+| Azure AI Administrator (preview) | This role is automatically assigned to the system-assigned managed identity for the hub. The Azure AI Administrator role has the minimum permissions needed for the managed identity to perform its tasks. For more information, see [Azure AI Administrator role (preview)](#azure-ai-administrator-role-preview). |
 | Azure AI Developer |     User can perform most actions, including create deployments, but can't assign permissions to project users. |
 | Azure AI Inference Deployment Operator | Perform all actions required to create a resource deployment within a resource group. |
 | Reader |     Read only access to the project. |

Summary

{
    "modification_type": "minor update",
    "modification_title": "Azure AI Administratorロールの名称修正"
}

Explanation

この変更では、rbac-ai-studio.md ファイルが修正され、以下のような更新が行われました：

ロール名称の修正: Azure AI Administrator role preview という表記が Azure AI Administrator role (preview) に修正されました。この修正は、ロール名のフォーマットを一貫性のあるものにするためのものです。
リンクテキストの調整: 前述のロールに関連するリンクテキストも同様に調整されており、明確さを保ちながら、ユーザーがリファレンスにアクセスしやすくなっています。

全体として、これらの更新は文書の整合性を高め、ユーザーがロールの理解を深めやすくすることを目的としています。

articles/ai-studio/concepts/vulnerability-management.md

Diff

@@ -7,16 +7,14 @@ ms.service: azure-ai-foundry
 ms.custom:
   - build-2024
 ms.topic: conceptual
-ms.date: 11/21/2024
+ms.date: 02/20/2025
 ms.reviewer: deeikele
 ms.author: larryfr
 author: Blackmist
 ---
 
 # Vulnerability management for Azure AI Foundry
 
-[!INCLUDE [feature-preview](../includes/feature-preview.md)]
-
 Vulnerability management involves detecting, assessing, mitigating, and reporting on any security vulnerabilities that exist in an organization's systems and software. Vulnerability management is a shared responsibility between you and Microsoft.
 
 This article discusses these responsibilities and outlines the vulnerability management controls that Azure AI Foundry provides. You learn how to keep your service instance and applications up to date with the latest security updates, and how to minimize the window of opportunity for attackers.

Summary

{
    "modification_type": "minor update",
    "modification_title": "最終更新日付の修正"
}

Explanation

この変更では、vulnerability-management.md ファイルが修正され、以下のような更新が行われました：

最終更新日付の修正: ドキュメントの最終更新日付が 11/21/2024 から 02/20/2025 に変更されました。これにより、最新の情報に基づいた日付が反映され、ユーザーがコンテンツの新しさを把握しやすくなっています。
不要なコードの削除: フィーチャープレビューに関するマークアップ（[!INCLUDE feature-preview]）が削除され、文書の簡潔さが増しています。

全体として、これらの変更は、情報の正確性を保ちながら、読者にとっての利便性を向上させることを目的としています。

articles/ai-studio/how-to/access-on-premises-resources.md

Diff

@@ -5,7 +5,7 @@ description: Learn how to configure an Azure AI Foundry managed network to secur
 manager: scottpolly
 ms.service: azure-ai-foundry
 ms.topic: how-to
-ms.date: 11/22/2024
+ms.date: 02/20/2025
 ms.reviewer: meerakurup 
 ms.author: larryfr
 author: Blackmist

Summary

{
    "modification_type": "minor update",
    "modification_title": "最終更新日付の修正"
}

Explanation

この変更では、access-on-premises-resources.md ファイルが修正され、以下のような更新が行われました：

最終更新日付の修正: ドキュメントの最終更新日付が 11/22/2024 から 02/20/2025 に変更されました。これにより、情報の正確性が向上し、ユーザーがコンテンツの新しさを認識しやすくなっています。

全体として、この変更は文書の更新履歴を最新の状態に保ち、ユーザーが信頼できる情報を得る助けとなることを目的としています。

articles/ai-studio/how-to/deploy-stability-models.md

Diff

@@ -98,7 +98,7 @@ Stability AI models on Models as a Service implement the [Azure AI Model Inferen
 }
 ```
 
-Follow this link for a full encoded [image generation response](https://github.com/MicrosoftDocs/azure-ai-docs-pr/pull/2896/$0). 
+Follow this link for a full encoded [image generation response](https://github.com/Azure/azureml-examples/blob/main/sdk/python/foundation-models/stabilityai/Sample_image_generation_response.txt). 
 
 ## Cost and quotas

Summary

{
    "modification_type": "minor update",
    "modification_title": "リンク先の更新"
}

Explanation

この変更では、deploy-stability-models.md ファイルが修正され、以下のような更新が行われました：

リンク先の更新: 画像生成のレスポンスに関するリンクが変更されました。以前は GitHub のプルリクエストのリンクが使用されていましたが、新しいリンクでは Azure/azureml-examples のリポジトリ内のテキストファイルが参照されており、より具体的な情報源へと更新されています。

この変更により、ユーザーは画像生成のレスポンスに関する情報をより良い形で取得できるようになり、ドキュメントの有用性が向上します。

articles/ai-studio/how-to/disable-local-auth.md

Diff

@@ -8,7 +8,7 @@ ms.service: azure-ai-foundry
 ms.custom:
   - ignite-2024
 ms.topic: how-to
-ms.date: 11/19/2024
+ms.date: 02/20/2025
 ms.reviewer: ambadal
 #customer intent: As an admin, I want to disable shared key access to my resources to improve security.
 ---

Summary

{
    "modification_type": "minor update",
    "modification_title": "最終更新日付の修正"
}

Explanation

この変更では、disable-local-auth.md ファイルが修正され、以下のような更新が行われました：

最終更新日付の修正: ドキュメントの最終更新日付が 11/19/2024 から 02/20/2025 に変更されました。この変更により、ユーザーはドキュメントがいつ更新されたかを正確に把握でき、情報が新しいものであることを確認できます。

この修正は、ユーザーが最新の情報を依拠して意思決定を行うために重要です。

articles/ai-studio/how-to/use-blocklists.md

Diff

@@ -15,6 +15,6 @@ author: PatrickFarley
 
 # Use blocklists in Azure AI Foundry portal 
 
-You can create custom blocklists in the Azure AI Foundry portal as part of your content filtering configurations. The following steps show how to create custom blocklists as part of your content filters in Azure AI Foundry portal.
+You can create custom blocklists in the [Azure AI Foundry portal](https://ai.azure.com) as part of your content filtering configurations. The following steps show how to create custom blocklists as part of your content filters in [Azure AI Foundry portal](https://ai.azure.com).
 
 [!INCLUDE [use-blocklists](../includes/use-blocklists.md)]
\ No newline at end of file

Summary

{
    "modification_type": "minor update",
    "modification_title": "リンクの追加"
}

Explanation

この変更では、use-blocklists.md ファイルが修正され、以下のような更新が行われました：

リンクの追加: Azure AI Foundry ポータルに関する説明文の中に、ポータルへのリンクが追加されました。具体的には、「Azure AI Foundry portal」の部分にリンクが設定され、ユーザーは直接そのサイトにアクセスできるようになりました。

この変更により、ユーザーはドキュメントを参照しながら、一層簡単に関連するリソースにアクセスできるようになり、利便性が向上します。

articles/ai-studio/includes/create-content-filter.md

Diff

@@ -46,7 +46,7 @@ Follow these steps to create a content filter:
 
     :::image type="content" source="../media/content-safety/content-filter/create-content-filter-deployment.png" alt-text="Screenshot of the option to select a deployment when creating a content filter." lightbox="../media/content-safety/content-filter/create-content-filter-deployment.png":::
 
-    Content filtering configurations are created at the hub level in the Azure AI Foundry portal. Learn more about configurability in the [Azure OpenAI Service documentation](/azure/ai-services/openai/how-to/content-filters).
+    Content filtering configurations are created at the hub level in the [Azure AI Foundry portal](https://ai.azure.com). Learn more about configurability in the [Azure OpenAI Service documentation](/azure/ai-services/openai/how-to/content-filters).
 
 
 1. On the **Review** page, review the settings and then select **Create filter**.

Summary

{
    "modification_type": "minor update",
    "modification_title": "リンクの明示化"
}

Explanation

この変更では、create-content-filter.md ファイルが修正され、以下のような更新が行われました：

リンクの明示化: 「Azure AI Foundry portal」という表現に対して、直接リンクが追加されました。これにより、ユーザーはポータルへのアクセスが容易になり、操作の手順を記載した情報源をすぐに確認できるようになりました。

この変更は、ユーザーにとっての利便性を高め、情報がより手軽に得られるようにすることを目的としています。

articles/ai-studio/toc.yml

Diff

@@ -5,117 +5,117 @@ items:
   href: what-is-ai-studio.md
 - name: What's new in Azure AI Foundry?
   href: whats-new-ai-foundry.md
-- name: Overview
+- name: Get started
   expanded: true
   items:
-  - name: What is Azure AI Foundry?
-    href: what-is-ai-studio.md
-  - name: Azure AI Foundry architecture
-    href: concepts/architecture.md
-  - name: Azure OpenAI in Azure AI Foundry
-    href: azure-openai-in-ai-studio.md
-  - name: Management center
-    href: concepts/management-center.md
-  - name: Azure AI Foundry SDK
-    href: how-to/develop/sdk-overview.md
-    displayName: code, sdk
-  - name: Region support
-    href: reference/region-support.md
-  - name: Azure AI FAQ
-    href: faq.yml
-  - name: Which studio should I choose?
-    href: /ai/ai-studio-experiences-overview?context=/azure/ai-studio/context/context
-- name: Quickstarts
-  items:
-  - name: Use the chat playground
-    href: quickstarts/get-started-playground.md
-  - name: Build a chat app using the Azure AI SDK
-    href: quickstarts/get-started-code.md
-    displayName: code
-  - name: Get started using Azure OpenAI Assistants
-    href: ../ai-services/openai/assistants-quickstart.md?context=/azure/ai-studio/context/context
-- name: Tutorials
-  items:
-  - name: Deploy an enterprise chat web app
-    href: tutorials/deploy-chat-web-app.md
-  - name: Build a custom chat app with the Azure AI Foundry SDK
+  - name: Quickstarts
     items:
-      - name: "Part 1: Set up project and install SDK"
-        href: tutorials/copilot-sdk-create-resources.md
-      - name: "Part 2: Build with data retrieval"
-        href: tutorials/copilot-sdk-build-rag.md
-        displayName: code,sdk
-      - name: "Part 3: Evaluate the chat app"
-        href: tutorials/copilot-sdk-evaluate.md
-        displayName: code,sdk
-- name: How-to
-  expanded: true
-  items:
-  - name: Azure OpenAI and AI services
+    - name: Use the chat playground
+      href: quickstarts/get-started-playground.md
+    - name: Build app in Python with Azure AI Foundry SDK
+      href: quickstarts/get-started-code.md
+    - name: Get started with Azure AI Foundry SDK
+      href: how-to/develop/sdk-overview.md
+  - name: Tutorials
     items:
-    - name: What are AI services?
-      href: ../ai-services/what-are-ai-services.md?context=/azure/ai-studio/context/context
-    - name: Use Azure AI services in Azure AI Foundry portal
-      href: ai-services/how-to/connect-ai-services.md
-    - name: Azure OpenAI
+    - name: Build a custom chat app with Azure AI Foundry SDK
       items:
-      - name: What is Azure OpenAI?
-        href: ../ai-services/openai/overview.md?context=/azure/ai-studio/context/context
-        displayName: cognitive
-      - name: Use Azure OpenAI Service in Azure AI Foundry portal
-        href: ai-services/how-to/connect-azure-openai.md
-      - name: Deploy Azure OpenAI models
-        href: how-to/deploy-models-openai.md
-      - name: Fine-tune Azure OpenAI models
-        href: ../ai-services/openai/how-to/fine-tuning.md?context=/azure/ai-studio/context/context
-      - name: Get started using Azure OpenAI Assistants
-        href: ../ai-services/openai/assistants-quickstart.md?context=/azure/ai-studio/context/context
-      - name: Use GPT-4o in the real-time audio playground
-        href: ../ai-services/openai/realtime-audio-quickstart.md?context=/azure/ai-studio/context/context
-    - name: Azure AI Speech
-      items:
-      - name: Real-time speech to text
-        href: ../ai-services/speech-service/get-started-speech-to-text.md?context=/azure/ai-studio/context/context
-      - name: Pronunciation assessment
-        href: ../ai-services/speech-service/pronunciation-assessment-tool.md?context=/azure/ai-studio/context/context
-      - name: Hear and speak with chat in the playground
-        href: quickstarts/hear-speak-playground.md
-      - name: Fine-tune in Azure AI Foundry portal for custom speech
-        href: ../ai-services/speech-service/custom-speech-ai-foundry-portal.md?context=/azure/ai-studio/context/context
-  - name: Explore and select AI models
+        - name: "Part 1: Set up project and install SDK"
+          href: tutorials/copilot-sdk-create-resources.md
+        - name: "Part 2: Build with data retrieval"
+          href: tutorials/copilot-sdk-build-rag.md
+          displayName: code,sdk
+        - name: "Part 3: Evaluate the chat app"
+          href: tutorials/copilot-sdk-evaluate.md
+          displayName: code,sdk
+    - name: Deploy an enterprise chat web app
+      href: tutorials/deploy-chat-web-app.md
+    - name: Build a RAG solution using Azure AI Search
+      href: /azure/search/tutorial-rag-build-solution?context=/azure/ai-studio/context/context
+- name: Explore AI model capabilities
+  items:
+  - name: Use the model catalog
+    href: how-to/model-catalog-overview.md
+  - name: Data, privacy, and security for Model Catalog
+    href: how-to/concept-data-privacy.md
+  - name: Model lifecycle and retirement
+    href: concepts/model-lifecycle-retirement.md
+  - name: Model benchmarking
+    items:
+    - name: Model benchmarks
+      href: concepts/model-benchmarks.md
+    - name: How to use model benchmarking
+      href: how-to/benchmark-model-in-catalog.md
+  - name: Model deployment in Azure AI Foundry
     items:
-    - name: Model catalog
-      href: how-to/model-catalog-overview.md
-    - name: Data, privacy, and security for Model Catalog
-      href: how-to/concept-data-privacy.md
-    - name: Model lifecycle and retirement
-      href: concepts/model-lifecycle-retirement.md
-    - name: Model benchmarking
+    - name: Deploying models in Azure AI Foundry
+      href: concepts/deployments-overview.md
+    - name: Serverless API
       items:
-      - name: Model benchmarks
-        href: concepts/model-benchmarks.md
-      - name: How to use model benchmarking
-        href: how-to/benchmark-model-in-catalog.md
-    - name: Fine-tune models
+      - name: Deploy models as serverless API
+        href: how-to/deploy-models-serverless.md
+      - name: Consume serverless API models from a different project or hub
+        href: how-to/deploy-models-serverless-connect.md
+      - name: Model and region availability for Serverless API deployments
+        href: how-to/deploy-models-serverless-availability.md
+    - name: Managed compute
       items:
-        - name: Fine-tuning overview
-          href: concepts/fine-tuning-overview.md
-        - name: Fine-tune with serverless API
-          href: how-to/fine-tune-serverless.md
-        - name: Fine-tune with user-managed compute
-          href: how-to/fine-tune-managed-compute.md
-        - name: Fine-tune Azure OpenAI models
-          href: ../ai-services/openai/how-to/fine-tuning.md?context=/azure/ai-studio/context/context
-    - name: Distillation
-      href: concepts/concept-model-distillation.md
-    - name: Azure OpenAI models
+      - name: Deploy models via managed compute
+        href: how-to/deploy-models-managed.md
+    - name: Azure AI model inference
+      items:
+      - name: What is Azure AI model inference?
+        href: ../ai-foundry/model-inference/overview.md?context=/azure/ai-studio/context/context
+      - name: Add and configure models
+        href: ../ai-foundry/model-inference/how-to/create-model-deployments.md?context=/azure/ai-studio/context/context
+      - name: Supported programming languages and SDKs
+        href: ../ai-foundry/model-inference/supported-languages.md?context=/azure/ai-studio/context/context
+      - name: Use the Azure AI model inference endpoint
+        href: ../ai-foundry/model-inference/how-to/inference.md?context=/azure/ai-studio/context/context
+      - name: Azure AI model inference quotas and limits
+        href: ../ai-foundry/model-inference/quotas-limits.md?context=/azure/ai-studio/context/context
+    - name: Azure OpenAI Service
       items:
       - name: Deploy Azure OpenAI models
         href: how-to/deploy-models-openai.md
-      - name: Fine-tune Azure OpenAI models
-        href: ../ai-services/openai/how-to/fine-tuning.md?context=/azure/ai-studio/context/context
-    - name: Healthcare AI models
+      - name: Azure OpenAI Service quotas and limits
+        href: ../ai-services/openai/quotas-limits.md?context=/azure/ai-studio/context/context
+      - name: Troubleshoot deployments and monitoring
+        href: how-to/troubleshoot-deploy-and-monitor.md
+  - name: Work with models from the model catalog
+    items:
+    - name: Featured models supported in Azure AI model inference
+      href: ../ai-foundry/model-inference/concepts/models.md?context=/azure/ai-studio/context/context
+    - name: Work with embedding models
+      items:
+        - name: Work with text embedding models
+          href: ../ai-foundry/model-inference/how-to/use-embeddings.md?context=/azure/ai-studio/context/context
+        - name: Work with image embedding models
+          href: ../ai-foundry/model-inference/how-to/use-image-embeddings.md?context=/azure/ai-studio/context/context
+    - name: Work with chat models
       items:
+        - name: Work with chat completion models
+          href: ../ai-foundry/model-inference/how-to/use-chat-completions.md?context=/azure/ai-studio/context/context
+        - name: Work with reasoning models
+          href: ../ai-foundry/model-inference/how-to/use-chat-reasoning.md?context=/azure/ai-studio/context/context
+    - name: Work with featured models
+      items:
+      - name: AI21 Jamba models
+        href: how-to/deploy-models-jamba.md
+      - name: Cohere models
+        items:
+        - name: Cohere Command models
+          href: how-to/deploy-models-cohere-command.md
+        - name: Cohere Embed models
+          href: how-to/deploy-models-cohere-embed.md
+        - name: Cohere Rerank models
+          href: how-to/deploy-models-cohere-rerank.md
+      - name: DeepSeek-R1 reasoning models
+        href: how-to/deploy-models-deepseek.md
+      - name: Gretel Navigator model
+        href: how-to/deploy-models-gretel-navigator.md
+      - name: Healthcare AI models
+        items:
         - name: Foundational AI models for healthcare
           href: how-to/healthcare-ai/healthcare-ai-models.md
         - name: MedImageInsight - embedding model
@@ -124,8 +124,16 @@ items:
           href: how-to/healthcare-ai/deploy-cxrreportgen.md
         - name: MedImageParse - prompted segmentation model
           href: how-to/healthcare-ai/deploy-medimageparse.md
-    - name: Microsoft Phi family models
-      items:
+      - name: JAIS model
+        href: how-to/deploy-models-jais.md
+      - name: Meta Llama models
+        items:
+        - name: Meta Llama family models
+          href: how-to/deploy-models-llama.md
+        - name: Fine-tune Meta Llama family models
+          href: how-to/fine-tune-model-llama.md
+      - name: Microsoft Phi family models
+        items:
         - name: Phi-3 chat models
           href: how-to/deploy-models-phi-3.md
         - name: Phi-3 chat model with vision
@@ -136,24 +144,8 @@ items:
           href: how-to/deploy-models-phi-4.md
         - name: Fine-tune Phi-3 chat models
           href: how-to/fine-tune-phi-3.md
-    - name: Cohere models
-      items:
-      - name: Cohere Command models
-        href: how-to/deploy-models-cohere-command.md
-      - name: Cohere Embed models
-        href: how-to/deploy-models-cohere-embed.md
-      - name: Cohere Rerank models
-        href: how-to/deploy-models-cohere-rerank.md
-    - name: DeepSeek-R1 reasoning models
-      href: how-to/deploy-models-deepseek.md
-    - name: Meta Llama models
-      items:
-      - name: Meta Llama family models
-        href: how-to/deploy-models-llama.md
-      - name: Fine-tune Meta Llama family models
-        href: how-to/fine-tune-model-llama.md
-    - name: Mistral family models
-      items:
+      - name: Mistral family models
+        items:
         - name: Mistral premium models
           href: how-to/deploy-models-mistral.md
         - name: Codestral model
@@ -162,164 +154,252 @@ items:
           href: how-to/deploy-models-mistral-nemo.md
         - name: Mistral-7B and Mixtral models
           href: how-to/deploy-models-mistral-open.md
-      displayName: maas
-    - name: Gretel Navigator model
-      href: how-to/deploy-models-gretel-navigator.md
-    - name: JAIS model
-      href: how-to/deploy-models-jais.md
-    - name: AI21 Jamba models
-      href: how-to/deploy-models-jamba.md
-    - name: TimeGEN-1 model
-      href: how-to/deploy-models-timegen-1.md
-    - name: NTTDATA tsuzumi model
-      href: how-to/deploy-models-tsuzumi.md
-    - name: Fine-tune tsuzumi model
-      href: how-to/fine-tune-models-tsuzumi.md
-    - name: Stability AI models
-      href: ./how-to/deploy-stability-models.md
-  - name: Deploy AI models
-    items:
-      - name: Deployments overview
-        href: concepts/deployments-overview.md
-        displayName: endpoint
-      - name: Azure AI model inference
+        displayName: maas
+      - name: NTTDATA tsuzumi model
         items:
-        - name: What is the Azure AI model inference service?
-          href: ../ai-foundry/model-inference/overview.md?context=/azure/ai-studio/context/context
-        - name: Upgrade from GitHub Models
-          href: ../ai-foundry/model-inference/how-to/quickstart-github-models.md?context=/azure/ai-studio/context/context
-        - name: Add and configure models
-          href: ../ai-foundry/model-inference/how-to/create-model-deployments.md?context=/azure/ai-studio/context/context
+          - name: NTTDATA tsuzumi model
+            href: how-to/deploy-models-tsuzumi.md
+          - name: Fine-tune tsuzumi model
+            href: how-to/fine-tune-models-tsuzumi.md
+      - name: Stability AI models
+        href: ./how-to/deploy-stability-models.md
+      - name: TimeGEN-1 model
+        href: how-to/deploy-models-timegen-1.md
+  - name: Azure OpenAI and AI services
+    items:
+    - name: Use Azure OpenAI Service in Azure AI Foundry portal
+      href: ai-services/how-to/connect-azure-openai.md
+    - name: Use Azure AI services in Azure AI Foundry portal
+      href: ai-services/how-to/connect-ai-services.md
+      displayName: cognitive,task
+    - name: What are Azure AI services?
+      href: concepts/what-are-ai-services.md
+    - name: Azure OpenAI
+      items:
+      - name: Deploy Azure OpenAI models
+        items: 
+        - name: Azure OpenAI in Azure AI Foundry
+          href: azure-openai-in-ai-studio.md
+        - name: Model region availability
+          href:  ../ai-services/openai/concepts/models.md?context=/azure/ai-studio/context/context
+          displayName: OpenAI, gpt-4o, gpt-4o-mini, whisper
         - name: Deployment types
-          href: ../ai-foundry/model-inference/concepts/deployment-types.md?context=/azure/ai-studio/context/context
-        - name: Use the inference endpoint
-          href: ../ai-foundry/model-inference/concepts/endpoints.md?context=/azure/ai-studio/context/context
-        - name: Quotas and limits
-          href: ../ai-foundry/model-inference/quotas-limits.md?context=/azure/ai-studio/context/context
-      - name: Serverless API
+          href: ../ai-services/openai/how-to/deployment-types.md?context=/azure/ai-studio/context/context
+          displayName: provisioned, global standard, datazone, data zone, global data zone, batch, globalbatch
+        - name: Model deployment
+          href: how-to/deploy-models-openai.md
+      - name: Generate text
         items:
-        - name: Deploy models as serverless API
-          href: how-to/deploy-models-serverless.md
-          displayName: maas, paygo, models-as-a-service
-        - name: Consume serverless API models from a different project or hub
-          href: how-to/deploy-models-serverless-connect.md
-          displayName: maas, paygo, models-as-a-service
-        - name: Content safety for models deployed with serverless APIs
-          href: concepts/model-catalog-content-safety.md
-        - name: Model and region availability for Serverless API deployments
-          href: how-to/deploy-models-serverless-availability.md
-      - name: Managed compute
-        href: how-to/deploy-models-managed.md
-        displayName: endpoint, online, SDK, CLI
-  - name: Create a project
-    href: how-to/create-projects.md
-  - name: Manage projects and hubs
-    items:
-    - name: Hubs and projects overview
-      href: concepts/ai-resources.md
-    - name: Create your first hub
-      href: how-to/create-azure-ai-resource.md
-    - name: Create a hub using the Azure Machine Learning SDK and CLI
-      href: how-to/develop/create-hub-project-sdk.md
-    - name: Create a hub with custom security
+        - name: Batch
+          href: ../ai-services/openai/how-to/batch.md?context=/azure/ai-studio/context/context
+          displayName: OpenAI, global batch, globalbatch, chat, chat completions
+        - name: Reasoning models
+          href: ../ai-services/openai/how-to/reasoning.md?context=/azure/ai-studio/context/context
+          displayName: OpenAI, o1, o1-mini, o3-mini, reasoning effort
+        - name: Function calling
+          href: ../ai-services/openai/how-to/function-calling.md?context=/azure/ai-studio/context/context
+          displayName: OpenAI 
+        - name: Predicted outputs
+          href: ../ai-services/openai/how-to/predicted-outputs.md?context=/azure/ai-studio/context/context 
+        - name: Prompt caching
+          href: ../ai-services/openai/how-to/prompt-caching.md?context=/azure/ai-studio/context/context 
+        - name: Structured outputs
+          href: ../ai-services/openai/how-to/structured-outputs.md?context=/azure/ai-studio/context/context 
+        - name: Use vision-enabled chat
+          href:  ../ai-services/openai/gpt-v-quickstart.md?context=/azure/ai-studio/context/context
+      - name: Generate images
+        href: ../ai-services/openai/dall-e-quickstart.md?context=/azure/ai-studio/context/context
+        displayName: OpenAI, DALLE, dall-e, DALL-E
+      - name: Audio
+        items:
+          - name: Use GPT-4o in the real-time audio playground
+            href: ../ai-services/openai/realtime-audio-quickstart.md?context=/azure/ai-studio/context/context
+            displayName: OpenAI, realtime, real-time
+          - name: Audio generation
+            href: ../ai-services/openai/audio-completions-quickstart.md?context=/azure/ai-studio/context/context 
+      - name: Distillation (stored completions)
+        href: ../ai-services/openai/how-to/stored-completions.md?context=/azure/ai-studio/context/context
+        displayName: OpenAI, Azure OpenAI, stored completions, model distillation
+      - name: Embeddings
+        href: ../ai-services/openai/tutorials/embeddings.md?context=/azure/ai-studio/context/context
+        displayName: text-embedding-ada-002, text-embedding-3-large, text-embedding-3-small
+      - name: Evaluation
+        href: ../ai-services/openai/how-to/evaluations.md?context=/azure/ai-studio/context/context
+        displayName: OpenAI
+      - name: Fine-tuning
+        items:
+        - name: Fine-tune Azure OpenAI models
+          href: ../ai-services/openai/how-to/fine-tuning.md?context=/azure/ai-studio/context/context
+          displayname: vision fine-tuning, DPO, direct preference optimization
+        - name: When to use Azure OpenAI fine-tuning
+          href: ../ai-services/openai/concepts/fine-tuning-considerations.md?context=/azure/ai-studio/context/context
+    - name: Content Safety
+      items: 
+      - name: What is Azure AI Content Safety service?
+        href: ../ai-services/content-safety/overview.md?context=/azure/ai-studio/context/context
+      - name: Prompt Shields quickstart
+        href: ../ai-services/content-safety/quickstart-jailbreak.md?context=/azure/ai-studio/context/context
+      - name: Groundedness detection (preview) quickstart
+        href: ../ai-services/content-safety/quickstart-groundedness.md?context=/azure/ai-studio/context/context
+      - name: Protected material detection for text quickstart
+        href: ../ai-services/content-safety/quickstart-protected-material.md?context=/azure/ai-studio/context/context
+      - name: Custom categories (preview) quickstart
+        href: ../ai-services/content-safety/quickstart-custom-categories.md?context=/azure/ai-studio/context/context
+      - name: Text moderation quickstart
+        href: ../ai-services/content-safety/quickstart-text.md?context=/azure/ai-studio/context/context
+    - name:  Content Understanding
       items:
-      - name: Create a hub in the Azure portal
-        href: how-to/create-secure-ai-hub.md
-      - name: Create a hub from template
-        href: how-to/create-azure-ai-hub-template.md
-        displayName: code
-      - name: Create a hub using Terraform
-        href: how-to/create-hub-terraform.md
-
-    - name: Create and manage compute
-      href: how-to/create-manage-compute.md
-  - name: Connections
+      - name: What is Azure AI Content Understanding (preview)?
+        href:   ../ai-services/content-understanding/overview.md?context=/azure/ai-studio/context/context
+      - name: Use Content Understanding in Azure AI Foundry portal
+        href: ../ai-services/content-understanding/quickstart/use-ai-foundry.md?context=/azure/ai-studio/context/context
+    - name:  Document Intelligence
+      items:
+      - name: What is Azure AI Document Intelligence?
+        href: ../ai-services/document-intelligence/overview.md?context=/azure/ai-studio/context/context
+    - name:  Language
+      items:
+      - name: What is Azure AI Language?
+        href: ../ai-services/language-service/overview.md?context=/azure/ai-studio/context/context
+      - name: Conversation Language Understanding
+        href: ../ai-services/language-service/conversational-language-understanding/quickstart.md?context=/azure/ai-studio/context/context&pivots=rest-api
+      - name: Key Phrase Extraction
+        href: ../ai-services/language-service/key-phrase-extraction/quickstart.md?context=/azure/ai-studio/context/context
+      - name: Language Detection
+        href: ../ai-services/language-service/language-detection/quickstart.md?context=/azure/ai-studio/context/context
+      - name: Named Entity Recognition
+        href: ../ai-services/language-service/named-entity-recognition/quickstart.md?context=/azure/ai-studio/context/context
+      - name: Custom Named Entity Recognition
+        href: ../ai-services/language-service/custom-named-entity-recognition/quickstart.md?context=/azure/ai-studio/context/context&pivots=rest-api
+      - name: Native Document Support
+        href: ../ai-services/language-service/native-document-support/use-native-documents.md?context=/azure/ai-studio/context/context
+      - name: Orchestration Workflow
+        href: ../ai-services/language-service/orchestration-workflow/quickstart.md?context=/azure/ai-studio/context/context
+      - name: Personally Identifiable Information detection
+        href: ../ai-services/language-service/personally-identifiable-information/quickstart.md?context=/azure/ai-studio/context/context
+      - name: Sentiment Analysis
+        href: ../ai-services/language-service/sentiment-opinion-mining/quickstart.md?context=/azure/ai-studio/context/context
+      - name: Summarization
+        href: ../ai-services/language-service/summarization/quickstart.md?context=/azure/ai-studio/context/context
+      - name: Text Analytics for Health
+        href: ../ai-services/language-service/text-analytics-for-health/quickstart.md?context=/azure/ai-studio/context/context
+      - name: Text Classification
+        href: ../ai-services/language-service/custom-text-classification/quickstart.md?context=/azure/ai-studio/context/context
+    - name:  Speech
+      items:
+      - name: What is the Speech service?
+        href: ../ai-services/speech-service/overview.md?context=/azure/ai-studio/context/context
+      - name: Real-time speech to text
+        href: ../ai-services/speech-service/get-started-speech-to-text.md?context=/azure/ai-studio/context/context
+      - name: Fast transcription
+        href: ../ai-services/speech-service/fast-transcription-create.md?context=/azure/ai-studio/context/context
+      - name: Pronunciation assessment
+        href: ../ai-services/speech-service/pronunciation-assessment-tool.md?context=/azure/ai-studio/context/context
+      - name: Speech translation
+        href: ../ai-services/speech-service/get-started-speech-translation.md?context=/azure/ai-studio/context/context
+      - name: Hear and speak with chat in the playground
+        href: quickstarts/hear-speak-playground.md
+      - name: Custom speech fine-tuning
+        href: ../ai-services/speech-service/custom-speech-ai-foundry-portal.md?context=/azure/ai-studio/context/context
+    - name:  Translator
+      items:
+      - name: What is Azure AI Translator?
+        href: ../ai-services/translator/translator-overview.md?context=/azure/ai-studio/context/context
+      - name: Azure AI Translator language support
+        href: ../ai-services/translator/language-support.md?context=/azure/ai-studio/context/context
+      - name: Text translation
+        href: ../ai-services/translator/text-translation-overview.md?context=/azure/ai-studio/context/context
+      - name: Document translation
+        href: ../ai-services/translator/document-translation/overview.md?context=/azure/ai-studio/context/context
+      - name: Custom Translator
+        href: ../ai-services/translator/custom-translator/overview.md?context=/azure/ai-studio/context/context
+      - name: Prebuilt solutions
+        href: ../ai-services/translator/solutions-overview.md?context=/azure/ai-studio/context/context
+    - name:  Vision
+      items:
+      - name: Azure Image Analysis
+        items:
+        - name: What is Image Analysis?
+          href: /azure/ai-services/computer-vision/overview-image-analysis?context=/azure/ai-studio/context/context
+        - name: Quickstart
+          href: /azure/ai-services/computer-vision/quickstarts-sdk/image-analysis-client-library-40?context=/azure/ai-studio/context/context
+        - name: Optical Character Recognition concepts
+          href: /azure/ai-services/computer-vision/concept-ocr?context=/azure/ai-studio/context/context
+        - name: Image captioning concepts
+          href: /azure/ai-services/computer-vision/concept-describe-images-40?context=/azure/ai-studio/context/context
+      - name: Azure AI Face
+        items:
+        - name: What is Azure AI Face service?
+          href: /azure/ai-services/computer-vision/overview-identity?context=/azure/ai-studio/context/context
+        - name: Quickstart 
+          href: /azure/ai-services/computer-vision/quickstarts-sdk/identity-client-library?context=/azure/ai-studio/context/context
+        - name: Face detection concepts
+          href: /azure/ai-services/computer-vision/concept-face-detection?context=/azure/ai-studio/context/context
+        - name: Face recognition concepts
+          href: /azure/ai-services/computer-vision/concept-face-recognition?context=/azure/ai-studio/context/context
+        - name: Liveness detection tutorial
+          href: /azure/ai-services/computer-vision/tutorials/liveness?context=/azure/ai-studio/context/context
+- name: Solutions
+  items:
+  - name: Agents
     items:
-    - name: Connections overview
-      href: concepts/connections.md
-    - name: Create a connection
-      href: how-to/connections-add.md
-    - name: Create a connection using the Azure Machine Learning SDK
-      href: how-to/develop/connections-add-sdk.md
-      displayName: code
-  - name: Data for your generative AI app
+    - name: What is Azure AI Agent Service
+      href: ../ai-services/agents/overview.md?context=/azure/ai-studio/context/context
+    - name: "Quickstart: Create a new agent"
+      href: ../ai-services/agents/quickstart.md?context=/azure/ai-studio/context/context
+  - name: Azure AI Search for RAG
     items:
-    - name: Overview of retrieval augmented generation (RAG)
+    - name: Retrieval Augmented Generation (RAG) overview
       href: concepts/retrieval-augmented-generation.md
-      displayName: RAG
-    - name: Add data to your project
-      href: how-to/data-add.md
-      displayName: index
-    - name: Build and consume vector indexes
+    - name: Use Azure AI Search
+      href: /azure/search/search-what-is-azure-search?context=/azure/ai-studio/context/context
+    - name: Build and consume vector indexes (Portal)
       href: how-to/index-add.md
-    - name: Build and consume indexes using code
+    - name: Build and consume vector indexes (Code)
       href: how-to/develop/index-build-consume-sdk.md
+    - name: Build a RAG solution using Azure AI Search
+      href: /azure/search/tutorial-rag-build-solution?context=/azure/ai-studio/context/context
+  - name: Develop with code
+    items:
+    - name: Work with projects in VS Code
+      href: how-to/develop/vscode.md
+    - name: Start with an AI template
+      href: how-to/develop/ai-template-get-started.md
+    - name: Develop with LangChain
+      href: how-to/develop/langchain.md
+    - name: Develop with LlamaIndex
+      href: how-to/develop/llama-index.md
+      displayName: code,sdk
+    - name: Develop with Semantic Kernel
+      href: how-to/develop/semantic-kernel.md
+- name: Optimizations
+  items:
+  - name: Prompt engineering
+    items:
+    - name: Prompt engineering techniques
+      href: ../ai-services/openai/concepts/prompt-engineering.md?context=/azure/ai-studio/context/context
+    - name: Image prompt engineering
+      href: ../ai-services/openai/concepts/gpt-4-v-prompt-engineering.md?context=/azure/ai-studio/context/context
     - name: Synthetic Data Generation
       href: concepts/concept-synthetic-data.md
-      displayName: code,sdk
-  - name: Develop generative AI apps
+  - name: Fine-tuning
     items:
-    - name: Develop in Azure AI Foundry portal
-      items:
-      - name: Build apps with prompt flow
-        items:
-        - name: Prompt flow overview
-          href: how-to/prompt-flow.md
-        - name: Develop flows
-          items:
-          - name: Create and manage compute session
-            href: how-to/create-manage-compute-session.md
-          - name: Create a flow
-            href: how-to/flow-develop.md
-          - name: Tune prompts using variants
-            href: how-to/flow-tune-prompts-using-variants.md
-          - name: Process images in a flow
-            href: how-to/flow-process-image.md
-          - name: Use prompt flow tools
-            items:
-            - name: Prompt flow tools overview
-              href: how-to/prompt-flow-tools/prompt-flow-tools-overview.md
-            - name: LLM tool
-              href: how-to/prompt-flow-tools/llm-tool.md
-            - name: Prompt tool
-              href: how-to/prompt-flow-tools/prompt-tool.md
-            - name: Python tool
-              href: how-to/prompt-flow-tools/python-tool.md
-            - name: Azure OpenAI GPT-4 Turbo with Vision tool
-              href: how-to/prompt-flow-tools/azure-open-ai-gpt-4v-tool.md
-            - name: Index Lookup tool
-              href: how-to/prompt-flow-tools/index-lookup-tool.md
-            - name: Rerank tool
-              href: how-to/prompt-flow-tools/rerank-tool.md
-            - name: Content Safety tool
-              href: how-to/prompt-flow-tools/content-safety-tool.md
-            - name: Embedding tool
-              href: how-to/prompt-flow-tools/embedding-tool.md
-            - name: Serp API tool
-              href: how-to/prompt-flow-tools/serp-api-tool.md
-        - name: Troubleshoot prompt flow
-          href: how-to/prompt-flow-troubleshoot.md
-    - name: Develop with code
-      items:
-      - name: Work with projects in VS Code
-        href: how-to/develop/vscode.md
-      - name: Start with an AI template
-        href: how-to/develop/ai-template-get-started.md
-      - name: Develop with LangChain
-        href: how-to/develop/langchain.md
-      - name: Develop with LlamaIndex
-        href: how-to/develop/llama-index.md
-        displayName: code,sdk
-      - name: Develop with Semantic Kernel 
-        href: how-to/develop/semantic-kernel.md
-    - name: Trace generative AI apps
-      items:
-       - name: Tracing overview
-         href: concepts/trace.md 
-       - name: Trace your application with Azure AI Inference SDK
-         href: how-to/develop/trace-local-sdk.md
-       - name: Visualize your traces
-         href: how-to/develop/visualize-traces.md
+    - name: Fine-tuning in Azure AI Foundry
+      href: concepts/fine-tuning-overview.md
+    - name: Fine-tune with a managed compute
+      href: how-to/fine-tune-managed-compute.md
+    - name: Fine-tune Azure OpenAI models
+      href: ../ai-services/openai/how-to/fine-tuning.md?context=/azure/ai-studio/context/context
+    - name: Distillation
+      href: concepts/concept-model-distillation.md
+  - name: Tracing
+    items:
+    - name: Tracing in Azure AI Foundry
+      href: concepts/trace.md
+    - name: Trace your application with Azure AI Inference SDK
+      href: how-to/develop/trace-local-sdk.md
+    - name: Visualize your traces
+      href: how-to/develop/visualize-traces.md
   - name: Evaluate generative AI apps
     items:
     - name: Evaluations concepts
@@ -348,24 +428,96 @@ items:
           href: how-to/flow-bulk-test-evaluation.md
         - name: Develop an evaluation flow in Prompt flow
           href: how-to/flow-develop-evaluation.md
-    - name: A/B experimentation 
+    - name: A/B experimentation
       href: concepts/a-b-experimentation.md
-  - name: Deploy and monitor generative AI apps
+  - name: Build apps with prompt flow
+    items:
+    - name: Prompt flow overview
+      href: how-to/prompt-flow.md
+    - name: Develop flows
+      items:
+      - name: Create and manage compute session
+        href: how-to/create-manage-compute-session.md
+      - name: Create a flow
+        href: how-to/flow-develop.md
+      - name: Tune prompts using variants
+        href: how-to/flow-tune-prompts-using-variants.md
+      - name: Process images in a flow
+        href: how-to/flow-process-image.md
+      - name: Use prompt flow tools
+        items:
+        - name: Prompt flow tools overview
+          href: how-to/prompt-flow-tools/prompt-flow-tools-overview.md
+        - name: LLM tool
+          href: how-to/prompt-flow-tools/llm-tool.md
+        - name: Prompt tool
+          href: how-to/prompt-flow-tools/prompt-tool.md
+        - name: Python tool
+          href: how-to/prompt-flow-tools/python-tool.md
+        - name: Azure OpenAI GPT-4 Turbo with Vision tool
+          href: how-to/prompt-flow-tools/azure-open-ai-gpt-4v-tool.md
+        - name: Index Lookup tool
+          href: how-to/prompt-flow-tools/index-lookup-tool.md
+        - name: Rerank tool
+          href: how-to/prompt-flow-tools/rerank-tool.md
+        - name: Content Safety tool
+          href: how-to/prompt-flow-tools/content-safety-tool.md
+        - name: Embedding tool
+          href: how-to/prompt-flow-tools/embedding-tool.md
+        - name: Serp API tool
+          href: how-to/prompt-flow-tools/serp-api-tool.md
+    - name: Deploy and monitor generative AI apps
+      items:
+      - name: Continuously monitor your applications
+        href: how-to/monitor-applications.md
+      - name: Deploy and monitor flows
+        items:
+        - name: Deploy a flow for real-time inference
+          href: how-to/flow-deploy.md
+          displayName: endpoint
+        - name: Enable tracing and collect feedback for a flow deployment
+          href: how-to/develop/trace-production-sdk.md
+          displayName: code
+        - name: Monitor prompt flow deployments
+          href: how-to/monitor-quality-safety.md
+        - name: Troubleshoot prompt flow
+          href: how-to/prompt-flow-troubleshoot.md
+- name: Management center
+  items:
+  - name: Management center overview
+    href: concepts/management-center.md
+  - name: Manage projects and hubs
     items:
-    - name: Continuously monitor your applications
-      href: how-to/monitor-applications.md
-    - name: Deploy and monitor flows
+    - name: Create a project
+      href: how-to/create-projects.md
+    - name: Hubs and projects overview
+      href: concepts/ai-resources.md
+    - name: Create your first hub
+      href: how-to/create-azure-ai-resource.md
+    - name: Create a hub using the Azure Machine Learning SDK and CLI
+      href: how-to/develop/create-hub-project-sdk.md
+    - name: Create a hub with custom security
       items:
-      - name: Deploy a flow for real-time inference
-        href: how-to/flow-deploy.md
-        displayName: endpoint
-      - name: Enable tracing and collect feedback for a flow deployment
-        href: how-to/develop/trace-production-sdk.md
+      - name: Create a hub in the Azure portal
+        href: how-to/create-secure-ai-hub.md
+      - name: Create a hub from template
+        href: how-to/create-azure-ai-hub-template.md
         displayName: code
-      - name: Monitor prompt flow deployments
-        href: how-to/monitor-quality-safety.md
-      - name: Troubleshoot deployments and monitoring
-        href: how-to/troubleshoot-deploy-and-monitor.md
+      - name: Create a hub using Terraform
+        href: how-to/create-hub-terraform.md
+  - name: Create and manage compute
+    href: how-to/create-manage-compute.md
+  - name: Connections
+    items:
+    - name: Connections overview
+      href: concepts/connections.md
+    - name: Create a connection
+      href: how-to/connections-add.md
+    - name: Create a connection using the Azure Machine Learning SDK
+      href: how-to/develop/connections-add-sdk.md
+      displayName: code
+  - name: Add and manage data in Azure AI Foundry
+    href: how-to/data-add.md
   - name: Costs and quotas
     items:
     - name: Plan and manage costs
@@ -409,7 +561,7 @@ items:
     - name: Built-in policy to allow specific models
       href: how-to/built-in-policy-model-deployment.md
     - name: Custom policy to allow specific models
-      href: ../ai-foundry/model-inference/how-to/configure-deployment-policies.md?context=/azure/ai-studio/context/context
+      href: how-to/custom-policy-model-deployment.md
   - name: Vulnerability management
     href: concepts/vulnerability-management.md
   - name: Disaster recovery
@@ -420,12 +572,10 @@ items:
   items:
   - name: Responsible AI overview
     href: responsible-use-of-ai-overview.md
-  - name: What is Azure AI Content Safety?
+  - name: Azure AI Content Safety in AI Foundry portal overview
     href: ai-services/content-safety-overview.md
-  - name: Content safety for models deployed with serverless APIs
-    href: concepts/model-catalog-content-safety.md
-  - name: Use Azure AI content safety in the portal
-    href: ../ai-services/content-safety/how-to/foundry.md?context=/azure/ai-studio/context/context
+  - name: Use Azure AI Content Safety in AI Foundry portal
+    href: /azure/ai-services/content-safety/how-to/foundry?context=/azure/ai-studio/context/context
   - name: Content filtering
     href: concepts/content-filtering.md
   - name: Use blocklists
@@ -452,15 +602,19 @@ items:
   - name: Azure AI services REST APIs
     displayName: swagger http
     href: ../ai-services/reference/rest-api-resources.md?context=/azure/ai-studio/context/context
-  - name: Prompt flow Python SDK
-    href: https://microsoft.github.io/promptflow/reference/index.html#
   - name: Azure AI Model Inference API
     href: ../ai-foundry/model-inference/reference/reference-model-inference-api.md
   - name: Azure Policy built-ins
     displayName: samples, policies, definitions
     href: ../ai-services/policy-reference.md?context=/azure/ai-studio/context/context
+  - name: Region support
+    href: reference/region-support.md
 - name: Resources
   items:
+  - name: Azure AI FAQ
+    href: faq.yml
+  - name: Azure AI Foundry architecture
+    href: concepts/architecture.md
   - name: Support & help options
     href: ../ai-services/cognitive-services-support-options.md?context=/azure/ai-studio/context/context
   - name: Use Azure AI Foundry with a screen reader
@@ -476,12 +630,4 @@ items:
   - name: Service Level Agreement (SLA)
     href: https://azure.microsoft.com/support/legal/sla/cognitive-services/v1_1/
   - name: Azure Government
-    href: /azure/azure-government/compare-azure-government-global-azure
-  - name: Videos
-    href: https://azure.microsoft.com/resources/videos/index/?services=cognitive-services
-  - name: Azure Blog
-    href: https://azure.microsoft.com/blog/
-  - name: Artificial Intelligence and Machine Learning Blog
-    href: https://techcommunity.microsoft.com/t5/artificial-intelligence-and/ct-p/AI
-  - name: LLMOps with Prompt Flow
-    href: https://github.com/microsoft/llmops-promptflow-template
+    href: /azure/azure-government/compare-azure-government-global-azure
\ No newline at end of file

Summary

{
    "modification_type": "minor update",
    "modification_title": "目次の大幅な更新"
}

Explanation

この変更では、toc.yml ファイルが大幅に修正され、以下のような内容が更新されました：

項目の追加および削除: 442行が追加され、296行が削除されており、全体で738箇所の変更が行われました。これにより、ドキュメントの目次が大幅に見直され、新しいトピックや重要な情報が追加されました。
新しいセクションの追加: 目次には「Get started」や「Quickstarts」などの新しいセクションが追加され、多様なトピックへのアクセスが容易になりました。また、特定のモデルやサービスに関連する具体的なリンクも含まれるようになりました。
内容の整理: 多くの項目が再編成され、ユーザーが必要な情報に迅速にアクセスできるように目次が整理されました。新しい情報やリソースが追加されることで、ユーザーはより充実した内容を利用できるようになります。

この変更は、Azure AI Foundryに関する情報の可用性を高め、ユーザーエクスペリエンスを向上させることを目的としています。

Diff Insight Report - misc

新機能

破壊的変更

その他の更新

インサイト

Summary Table

Modified Contents

articles/ai-services/document-intelligence/how-to-guides/disaster-recovery.md

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articles/ai-services/document-intelligence/prebuilt/read.md

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articles/ai-services/document-intelligence/prebuilt/receipt.md

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articles/ai-services/language-service/media/overview/call-center-summarization.png

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articles/ai-services/language-service/media/overview/conversation-pii.png

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articles/ai-services/language-service/media/overview/conversation-summarization.png

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articles/ai-services/language-service/media/overview/key-phrase-extraction.png

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articles/ai-services/language-service/media/overview/language-detection.png

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articles/ai-services/language-service/media/overview/named-entity-recognition.png

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articles/ai-services/language-service/media/overview/sentiment-analysis.png

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articles/ai-services/language-service/media/overview/text-analytics-for-health.png

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articles/ai-services/language-service/media/overview/text-pii.png

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articles/ai-services/language-service/media/overview/text-summarization.png

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articles/ai-services/language-service/overview.md

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articles/ai-studio/ai-services/content-safety-overview.md

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articles/ai-studio/concepts/content-filtering.md

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articles/ai-studio/concepts/rbac-ai-studio.md

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articles/ai-studio/concepts/vulnerability-management.md

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articles/ai-studio/how-to/access-on-premises-resources.md

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articles/ai-studio/how-to/deploy-stability-models.md

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articles/ai-studio/how-to/disable-local-auth.md

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articles/ai-studio/how-to/use-blocklists.md

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articles/ai-studio/includes/create-content-filter.md

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articles/ai-studio/toc.yml

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