Merge branch 'main' into release-preview-eval-redteaming

Author: v-alje

articles/ai-services/.openpublishing.redirection.ai-services.json

@@ -925,7 +925,7 @@
     {
       "source_path_from_root": "/articles/ai-services/translator/modifications-deprecations.md",
       "redirect_url": "/azure/ai-services/translator/reference/release-history",
-      "redirect_document_id": true
+      "redirect_document_id": false
     },
     {
       "source_path_from_root": "/articles/ai-services/translator/neural-dictionary.md",
@@ -965,7 +965,7 @@
     {
       "source_path_from_root": "/articles/ai-services/translator/translator-faq.md",
       "redirect_url": "/azure/ai-services/translator/faq",
-      "redirect_document_id": true
+      "redirect_document_id": false
     },
     {
       "source_path_from_root": "/articles/ai-services/translator/word-alignment.md",
@@ -978,13 +978,8 @@
       "redirect_document_id": true
     },
     {
-      "source_path_from_root": "/articles/ai-services/translator/reference/known-issues.md",
+      "source_path_from_root": "/articles/ai-services/translator/known-issues.md",
       "redirect_url": "/azure/ai-services/translator/text-translation/reference/known-issues",
-      "redirect_document_id": true
-    },
-    {
-      "source_path_from_root": "/articles/ai-services/translator/reference/release-history.md",
-      "redirect_url": "/azure/ai-services/translator/text-translation/reference/release-history",
       "redirect_document_id": false
     },
     {
@@ -1058,8 +1053,18 @@
       "redirect_document_id": true
     },
     {
-      "source_path_from_root": "/articles/ai-services/translator/text-translation/reference/release-history.md",
-      "redirect_url": "/azure/ai-services/translator/release-history",
+      "source_path_from_root": "/articles/ai-services/translator/text-translation/reference/known-issues.md",
+      "redirect_url": "/azure/ai-services/translator/reference/known-issues",
+      "redirect_document_id": true
+    },
+    {
+      "source_path_from_root": "/articles/ai-services/translator/release-history.md",
+      "redirect_url": "/azure/ai-services/translator/reference/release-history",
+      "redirect_document_id": true
+    },
+    {
+      "source_path_from_root": "/articles/ai-services/translator/sovereign-clouds.md",
+      "redirect_url": "/azure/ai-services/translator/reference/sovereign-clouds",
       "redirect_document_id": true
     }
   ]

articles/ai-services/agents/how-to/tools/bing-grounding.md

@@ -33,7 +33,12 @@ Developers and end users don't have access to raw content returned from Groundin
 The user query is the message that an end user sends to an agent, such as *"should I take an umbrella with me today? I'm in Seattle."* Instructions are the system message a developer can provide to share context and provide instructions to the AI model on how to use various tools or behave. 
 
 When a user sends a query, the customer's AI model deployment first processes it (using the provided instructions) to later perform a Bing search query (which is [visible to developers](#how-to-display-grounding-with-bing-search-results)). 
-Grounding with Bing returns relevant search results to the customer's model deployment, which then generates the final output. When using Grounding with Bing Search, only the Bing search query and your resource key are sent to Bing, and no end user-specific information is included. Your resource key is sent to Bing solely for billing and rate limiting purposes. The authorization will happen between Grounding with Bing Search service and Azure AI Agent service. Any Bing search query that is generated and sent to Bing for the purposes of grounding is transferred, along with the resource key, outside of the Azure compliance boundary to the Grounding with Bing Search service. Grounding with Bing Search is subject to Bing's terms and do not have the same compliance standards and certifications as the Azure AI Agent Service, as described in the [Grounding with Bing Search Terms of Use](https://www.microsoft.com/bing/apis/grounding-legal). It is your responsibility to assess whether the use of Grounding with Bing Search in your agent meets your needs and requirements.
+Grounding with Bing returns relevant search results to the customer's model deployment, which then generates the final output. 
+
+> [!NOTE]
+> When using Grounding with Bing Search, only the Bing search query and your resource key are sent to Bing, and no end user-specific information is included. Your resource key is sent to Bing solely for billing and rate limiting purposes. 
+
+The authorization will happen between Grounding with Bing Search service and Azure AI Agent service. Any Bing search query that is generated and sent to Bing for the purposes of grounding is transferred, along with the resource key, outside of the Azure compliance boundary to the Grounding with Bing Search service. Grounding with Bing Search is subject to Bing's terms and do not have the same compliance standards and certifications as the Azure AI Agent Service, as described in the [Grounding with Bing Search Terms of Use](https://www.microsoft.com/bing/apis/grounding-legal). It is your responsibility to assess whether the use of Grounding with Bing Search in your agent meets your needs and requirements.
 
 ## Usage support
 
@@ -44,7 +49,7 @@ Grounding with Bing returns relevant search results to the customer's model depl
 ## Setup  
 
 > [!NOTE]
-> 1. Grounding with Bing Search only works with the following Azure OpenAI models: `gpt-3.5-turbo-0125`, `gpt-4-0125-preview`, `gpt-4-turbo-2024-04-09`, `gpt-4o-0513`
+> 1. Grounding with Bing Search works with [all Azure OpenAI models](../../concepts/model-region-support.md) that Azure AI Agent Service supports, except `gpt-4o-mini, 2024-07-18`. 
 
 1. Create an Azure AI Agent by following the steps in the [quickstart](../../quickstart.md).
 

articles/ai-services/agents/how-to/tools/fabric.md

@@ -48,7 +48,7 @@ You need to first build and publish a Fabric data agent and then connect your Fa
 1. Select **Microsoft Fabric** and follow the prompts to add the tool. You can add only one per agent.
 
 1. Click to add new connections. Once you have added a connection, you can directly select from existing list.
-   1. To create a new connection, you need to find `workspace-id` and `artifact-id` in your published Fabric data agent endpoint. Your Fabric data agent endpoint would look like `https://fabric.microsoft.com/groups/<workspace_id>/aiskills/<artifact-id>`
+   1. To create a new connection, you need to find `workspace-id` and `artifact-id` in your published Fabric data agent endpoint. Your Fabric data agent endpoint would look like `https://<environment>.fabric.microsoft.com/groups/<workspace_id>/aiskills/<artifact-id>`
 
    1. Then, you can add both to your connection. Make sure you have checked `is secret` for both of them
 
@@ -325,4 +325,4 @@ curl $AZURE_AI_AGENTS_ENDPOINT/threads/thread_abc123/messages?api-version=2024-1
 
 ## Next steps
 
-[See the full sample for Fabric data agent.](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-projects/samples/agents/sample_agents_fabric.py)
+[See the full sample for Fabric data agent.](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-projects/samples/agents/sample_agents_fabric.py)