Merge branch 'main' into qna-broken-links

Author: laujan

.github/policies/disallow-edits.yml

@@ -28,15 +28,17 @@ configuration:
               matchAny: true
               pattern: articles/ai-foundry/responsible-ai/*
           - not:
-              activitySenderHasAssociation:
-                association: Member
+              or:
+                - activitySenderHasAssociation:
+                    association: Member
+                - isActivitySender:
+                    user: learn-build-service-prod[bot]
         then:
           - addReply:
               reply: >-
                 @${issueAuthor} - Pull requests that modify files in this folder aren't accepted from public contributors.
           - closePullRequest
 
-
       - description: \@mention specific people when a PR is opened in the "ai-foundry/responsible-ai" folder.
         if:
           - payloadType: Pull_Request

articles/ai-foundry/.openpublishing.redirection.ai-studio.json

@@ -1203,6 +1203,11 @@
           "redirect_url": "/azure/ai-foundry/how-to/develop/trace-application#visualize-your-traces",
           "redirect_document_id": false
         },
+        {
+          "source_path_from_root": "/articles/ai-foundry/agents/index.yml",
+          "redirect_url": "/azure/ai-foundry/",
+          "redirect_document_id": false
+        },
         {
           "source_path_from_root": "/articles/ai-foundry/how-to/online-evaluation.md",
           "redirect_url": "/azure/ai-foundry/how-to/monitor-applications",

articles/ai-foundry/agents/how-to/connected-agents.md

@@ -109,7 +109,7 @@ Checks the contract against internal standards or uploaded guidelines to identif
 ## Use the .NET SDK 
 
 > [!NOTE]
-> This shows a synchronous usage. You can find an asynchronous example on [GitHub](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/ai/Azure.AI.Projects/samples/Sample24_Agent_Connected_Agent.md) 
+> This shows a synchronous usage. You can find an asynchronous example on [GitHub](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/ai/Azure.AI.Agents.Persistent/samples/Sample23_PersistentAgents_Connected_Agent.md) 
 
 To enable your Agent to use a connected agent, you use `ConnectedAgentToolDefinition` along with the agent ID, name, and a description.
 

articles/ai-foundry/agents/how-to/tools/deep-research-samples.md

@@ -50,14 +50,14 @@ Use this article to learn how to use the Deep Research tool with the Azure AI Pr
 
     Save this endpoint to an environment variable named `BING_RESOURCE_NAME`. 
 
-* The names of your `o3-deep-research-model` deployment name and Azure OpenAI GPT model deployment name. You can find them in **Models + Endpoints** in the left navigation menu. 
+* The deployment names of your `o3-deep-research-model` and `gpt-4o` models. You can find them in **Models + Endpoints** in the left navigation menu.
 
-    :::image type="content" source="../../media/tools/deep-research/model-deployments.png" alt-text="A screenshot showing the model deployment screen the AI Foundry portal." lightbox="../../media/tools/deep-research/model-deployments.png":::
+   :::image type="content" source="../../media/tools/deep-research/model-deployments.png" alt-text="A screenshot showing the model deployment screen the AI Foundry portal." lightbox="../../media/tools/deep-research/model-deployments.png":::
     
-    Save the name of your `o3-deep-research-model` deployment name as an environment variable named `DEEP_RESEARCH_MODEL_DEPLOYMENT_NAME` and Azure OpenAI GPT model deployment name as an environment variable named `MODEL_DEPLOYMENT_NAME`. 
+    Save the name of your `o3-deep-research` deployment name as an environment variable named `DEEP_RESEARCH_MODEL_DEPLOYMENT_NAME` and the `gpt-4o` deployment name as an environment variable named `MODEL_DEPLOYMENT_NAME`.
 
 > [!NOTE]
-> Limitation: The Deep Research tool is currently recommended only in nonstreaming scenarios. Using it with streaming can work, but it might occasionally time out and is therefore not recommended.
+> Other GPT-series models including GPT-4o-mini and the GPT-4.1 series are not supported for scope clarification.
 
 ## Create an agent with the Deep Research tool
 
@@ -197,6 +197,9 @@ with project_client:
         print("Deleted agent")
 ```
 
+> [!NOTE]
+> Limitation: The Deep Research tool is currently recommended only in nonstreaming scenarios. Using it with streaming can work, but it might occasionally time out and is therefore not recommended.
+
 ## Next steps
 
 * [Reference documentation](https://aka.ms/azsdk/azure-ai-projects/python/reference)

articles/ai-foundry/agents/how-to/tools/deep-research.md

@@ -47,11 +47,14 @@ The Deep Research tool is supported in the following regions where the deep rese
 |---------|---------|
 | ✔️ | ✔️ | 
 
-## GPT model for clarifying research scope
+## GPT-4o model for clarifying research scope
 
-The Deep Research tool uses a GPT model to clarify the question contained in the user prompt, gather additional context if needed, and precisely scope the research task. This model is deployed during configuration of the Deep Research tool and can be one of the GPT-series models including GPT-4o, **except** the GPT-4.1 family, The 4.1 family is not supported by the Agents service.
+The Deep Research tool uses the `gpt-4o` model to clarify the question contained in the user prompt, gather additional context if needed, and precisely scope the research task. This model is deployed during configuration of the Deep Research tool. 
 
-## Deep research model for deep analysis
+> [!NOTE]
+> Other GPT-series models including GPT-4o-mini and the GPT-4.1 series are not supported for scope clarification.
+
+## Deep research model for analysis
 
 - **Model name**: `o3-deep-research`
 - **Deployment type**: Global Standard
@@ -64,7 +67,7 @@ The Deep Research tool uses a GPT model to clarify the question contained in the
 - [Grounding with Bing Search tool](./bing-grounding.md) resource for connecting to your Azure AI Foundry project.
 - [Model deployments](../../../model-inference/how-to/create-model-deployments.md) for the following models
     - `o3-deep-research` version `2025-06-26`. This model is available in `West US` and `Norway East`.
-    - Any Azure OpenAI GPT model like `gpt-4o` for intent clarification. Deploy in the same regions.
+    - The `gpt-4o` model for intent clarification. Deploy this model in the same region.
 
 ## Research tool setup 
 

articles/ai-foundry/agents/how-to/tools/file-search.md

@@ -6,7 +6,7 @@ services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-agent-service
 ms.topic: how-to
-ms.date: 12/11/2024
+ms.date: 07/17/2025
 author: aahill
 ms.author: aahi
 ms.custom: azure-ai-agents
@@ -26,17 +26,13 @@ File search augments agents with knowledge from outside its model, such as propr
 
 ### File sources  
 - Upload local files 
-- Azure Blob Storage 
-
-### Supported file types
-
-- [Supported file types](#supported-file-types)
+- Azure Blob Storage
 
 ### Usage support
 
 |Azure AI foundry support  | Python SDK |	C# SDK | JavaScript SDK | REST API | Basic agent setup | Standard agent setup |
 |---------|---------|---------|---------|---------|---------|---------|
-| ✔️  | ✔️ | ✔️ | ✔️ | ✔️ | File upload only | File upload and using  BYO blob storage | 
+| ✔️  | ✔️ | ✔️ | ✔️ | ✔️ | File upload only | File upload and using  bring-your-own blob storage | 
 
 ## Dependency on agent setup
 
@@ -49,9 +45,8 @@ The file search tool has the same functionality as Azure OpenAI Assistants. Micr
 The file search tool uses the Azure AI Search and Azure Blob Storage resources you connected during agent setup. 
 - Uploaded files get stored in your connected Azure Blob Storage account 
 - Vector stores get created using your connected Azure AI Search resource 
-<br> </br>
 
-For both agent setups, Azure OpenAI handles the entire ingestion process, which includes:
+For both agent setups, the service handles the entire ingestion process, which includes:
 - Automatically parsing and chunking documents
 - Generating and storing embeddings
 - Utilizing both vector and keyword searches to retrieve relevant content for user queries. 
@@ -169,9 +164,9 @@ vector_store = project_client.agents.create_vector_store_and_poll(
 
 Vector stores created using thread helpers (like `tool_resources.file_search.vector_stores` in Threads or `message.attachments` in Messages) have a default expiration policy of seven days after they were last active (defined as the last time the vector store was part of a run).
 
-When a vector store expires, the runs on that thread fail.  To fix this issue, you can recreate a new vector_store with the same files and reattach it to the thread.
+When a vector store expires, the runs on that thread fail. To fix this issue, you can recreate a new vector_store with the same files and reattach it to the thread.
 
-### Supported file types
+## Supported file types
 
 > [!NOTE]
 > For text/ MIME types, the encoding must be either utf-8, utf-16, or ASCII.

articles/ai-foundry/agents/how-to/tools/logic-apps.md

@@ -6,7 +6,7 @@ services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-agent-service
 ms.topic: how-to
-ms.date: 07/11/2025
+ms.date: 07/16/2025
 author: aahill
 ms.author: aahi
 ms.reviewer: umangsehgal
@@ -74,7 +74,7 @@ project_client = AIProjectClient(
 
 ## Register the Logic App
 
-Register the Logic App by providing its name and trigger details. You can find code for `AzureLogicAppTool` on[GitHub](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-agents/samples/utils/user_functions.py).
+Register the Logic App by providing its name and trigger details. You can find code for `AzureLogicAppTool` on [GitHub](https://github.com/azure-ai-foundry/foundry-samples/blob/main/samples/microsoft/python/getting-started-agents/logic_apps/user_logic_apps.py).
 
 ```python
 from user_logic_apps import AzureLogicAppTool