fixing merge conflict

Author: ShawnJackson

articles/ai-foundry/agents/how-to/tools/model-context-protocol.md

@@ -58,7 +58,7 @@ For more information on using MCP, see:
 
    1. `server_url`: The URL of the MCP server; for example, `https://api.githubcopilot.com/mcp/`.
    2. `server_label`: A unique identifier of this MCP server to the agent; for example, `github`.
-   3. `allowed_tools`: An optional list of tools that you want to allow without approval.
+   3. `allowed_tools`: An optional list of tools that this agent can access and use.
 
 1. Create a run and pass additional information about the `mcp` tool in `tool_resources` with headers:
 

articles/ai-foundry/includes/get-started-fdp.md

@@ -10,7 +10,7 @@ ms.custom:
   - include file
   - build-aifnd
   - build-2025
-  - update-code
+  - update-code-2
 ---
 
 In this quickstart, you use [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs) to:

articles/ai-services/language-service/whats-new.md

@@ -6,34 +6,48 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: whats-new
-ms.date: 06/02/2025
+ms.date: 07/09/2025
 ms.author: lajanuar
 ---
 
 # What's new in Azure AI Language?
 
 Azure AI Language is updated on an ongoing basis. Bookmark this page to stay up to date with release notes, feature enhancements, and our newest documentation.
 
+## June 2025
+
+* A new version of the Conversational Language Understanding (CLU) training configuration, aimed at minimizing overpredictions of the [None intent](conversational-language-understanding/concepts/none-intent.md)—particularly in multilingual contexts—is now supported in [REST API version 2025-15-05-preview](/rest/api/language/analyze-conversations/analyze-conversations?view=rest-language-2025-05-15-preview&preserve-view=true).
+
+* The [Build your conversational agent](https://github.com/Azure-Samples/Azure-Language-OpenAI-Conversational-Agent-Accelerator) accelerator project is updated to include a new routing strategy—**TRIAGE_AGENT**. This strategy uses an agent hosted on Azure AI Foundry Agent Service. It utilizes Conversational Language Understanding (CLU) and Custom Question Answering (CQA) as tools to triage user intent for downstream agent routing. Additionally, these tools help deliver precise answers to specific questions. For more information, *see* [TechCommunity Blog Post](https://techcommunity.microsoft.com/blog/azure-ai-services-blog/announcing-azure-ai-language-new-features-to-accelerate-your-agent-development/4415216)
+
+* The following [.NET SDKs](/dotnet/api/overview/azure/ai.textanalytics-readme?view=azure-dotnet&preserve-view=true) are now available, and support the latest REST API version **2025-15-05-preview**:
+
+  * [Azure.AI.Language.Text 1.0.0-beta.3](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/cognitivelanguage/Azure.AI.Language.Conversations/CHANGELOG.md) provides inference capabilities for a wide range of language processing tasks. These tasks include language detection, sentiment analysis, key phrase extraction, and named entity recognition (NER). The capabilities also cover personally identifiable information (PII) entity recognition, entity linking, text analytics for healthcare, custom NER, and custom text classification. In addition, both extractive and abstractive text summarization are supported.
+
+  * [Azure.AI.Language.Conversation 2.0.0-beta.3](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/cognitivelanguage/Azure.AI.Language.Conversations/CHANGELOG.md) provides inference capabilities for conversational PII, conversational language understanding (CLU), and conversation summarization.
+
+* The Text PII GPU container is now available for integration. You can access it on the [Microsoft Artifact Registry](https://mcr.microsoft.com/artifact/mar/azure-cognitive-services/textanalytics/pii/) using the tag `gpu`.
+
 ## May 2025
 
 **2025-05-15-preview release**. The [latest API preview version](/rest/api/language/operation-groups?view=rest-language-2025-05-15-preview&preserve-view=true) includes updates for named entity recognition (NER) and PII detection:
 * New entity type support for `DateOfBirth`, `BankAccountNumber`, `PassportNumber`, and `DriversLicenseNumber`.
 * Improved AI quality for `PhoneNumber` entity type.
-  
+
 **New agent templates**. Azure AI Language now supports the following agent templates:
 *  [Intent routing](../agents/concepts/agent-catalog.md): Detects user intent and provides precise answers, ideal for deterministic intent routing, and exact question answering with human oversight.
 *   [Exact question answering](../agents/concepts/agent-catalog.md): Delivers consistent, accurate responses to high-value predefined questions through deterministic methods.
-  
+
 **PII detection enhancements**. Azure AI Language introduces new customization and entity subtype features for PII detection:
 *  [Customize PII detection using your own regex](personally-identifiable-information/how-to/adapt-to-domain-pii.md#customizing-pii-detection-using-your-own-regex-only-available-for-text-pii-container) (Text PII container only).
 *  [Specify values to exclude from PII output](personally-identifiable-information/how-to/adapt-to-domain-pii.md#customizing-pii-output-by-specifying-values-to-exclude).
 *  [Use entity synonyms for tailored PII detection](personally-identifiable-information/how-to/adapt-to-domain-pii.md#api-schema-for-the-entitysynoyms-parameter).
-  
+
 **Enhanced CLU and CQA Capabilities in Azure AI Foundry**. Azure AI Foundry now offers enhanced capabilities for fine-tuning with custom conversational language understanding (CLU) and conversational question-and-answer (CQA) AI features:
-*	CLU and CQA authoring tools are now available in Azure AI Foundry.
-*	CLU offers a quick deploy option powered by large language models (LLMs) for rapid deployment.
-*	CQA incorporates the QnA Maker scoring algorithm for more accurate responses.
-*	CQA enables exact match answering for precise query resolutions.
+*    CLU and CQA authoring tools are now available in Azure AI Foundry.
+*    CLU offers a quick deploy option powered by large language models (LLMs) for rapid deployment.
+*    CQA incorporates the QnA Maker scoring algorithm for more accurate responses.
+*    CQA enables exact match answering for precise query resolutions.
 
 **For more updates, see our latest [TechCommunity Blog Post](https://techcommunity.microsoft.com/blog/azure-ai-services-blog/announcing-azure-ai-language-new-features-to-accelerate-your-agent-development/4415216)**.
 

articles/machine-learning/how-to-deploy-mlflow-models-online-endpoints.md

@@ -10,7 +10,7 @@ ms.author: mopeakande
 ms.reviewer: fasantia
 ms.date: 03/31/2025
 ms.topic: how-to
-ms.custom: deploy, mlflow, devplatv2, no-code-deployment, devx-track-azurecli, cliv2, update-code1
+ms.custom: deploy, mlflow, devplatv2, no-code-deployment, devx-track-azurecli, cliv2, update-code2
 # customer intent: As a developer, I want to see how to deploy an MLflow model to an online endpoint so that I can use the model to make predictions in real time.
 ---
 

articles/machine-learning/how-to-package-models-moe.md

@@ -9,7 +9,7 @@ ms.service: azure-machine-learning
 ms.subservice: mlops
 ms.date: 12/08/2023
 ms.topic: how-to
-ms.custom: update-code
+ms.custom: update-code-2
 ---
 
 # Deploy model packages to online endpoints (preview)

articles/machine-learning/how-to-package-models.md

@@ -7,7 +7,7 @@ ms.author: mopeakande
 ms.reviewer: fasantia
 ms.service: azure-machine-learning
 ms.subservice: mlops
-ms.custom: devx-track-python, update-code
+ms.custom: devx-track-python, update-code-2
 ms.date: 12/08/2023
 ms.topic: how-to
 ---

articles/machine-learning/how-to-use-batch-scoring-pipeline.md

@@ -15,7 +15,7 @@ ms.custom:
   - devplatv2
   - event-tier1-build-2023
   - ignite-2023
-  - update-code3
+  - update-code-4
 ---
 
 # How to deploy a pipeline to perform batch scoring with preprocessing