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

Author: paulth1

.openpublishing.redirection.json

@@ -6,6 +6,11 @@
       "redirect_document_id": false
     },
     {
+      "source_path": "articles/ai-foundry/how-to/develop/vscode.md",
+      "redirect_url": "/azure/ai-foundry/how-to/develop/get-started-projects-vs-code",
+      "redirect_document_id": false
+    },
+        {
       "source_path": "articles/ai-foundry/azure-openai-in-azure-ai-foundry.md",
       "redirect_url": "/azure/ai-foundry/what-is-azure-ai-foundry",
       "redirect_document_id": false

articles/ai-foundry/agents/concepts/model-region-support.md

@@ -7,7 +7,7 @@ author: aahill
 ms.author: aahi
 ms.service: azure-ai-agent-service
 ms.topic: conceptual
-ms.date: 08/01/2025
+ms.date: 08/04/2025
 ms.custom: azure-ai-agents, references_regions
 ---
 
@@ -26,6 +26,7 @@ Azure AI Foundry Agent Service supports the following Azure OpenAI models in the
 
 > [!NOTE]
 > * [Hub based projects](../../what-is-azure-ai-foundry.md#project-types) are limited to the following models: gpt-4o, gpt-4o-mini, gpt-4, gpt-35-turbo
+> * For information on class A subnet support, see the setup guide on [GitHub](https://github.com/azure-ai-foundry/foundry-samples/tree/main/samples/microsoft/infrastructure-setup/15-private-network-standard-agent-setup).
 > * The [file search tool](../how-to/tools/file-search.md) is currently unavailable in the following regions:
 >     * Italy north
 >     * Brazil south 
@@ -41,9 +42,11 @@ Azure AI Foundry Agent Service supports the following Azure OpenAI models in the
 | eastus           | ✅                         | ✅                         | ✅                         | ✅                              | ✅                  | ✅                              |
 | eastus2          | ✅                         | ✅                         | ✅                         | ✅                              | ✅                  | ✅                              |
 | francecentral    | ✅                         | ✅                         | ✅                         | ✅                              | ✅                  | ✅                              |
+| germanywestcentral| ✅                        | ✅                         | ✅                         | ✅                              | ✅                  | ✅                              |
 | italynorth       |  -                          |  -                         | ✅                         | ✅                              |  -                   | -                               |
 | japaneast        | ✅                         | ✅                         | ✅                         | ✅                              | ✅                  | ✅                              |
 | norwayeast       | ✅                         | ✅                         | ✅                         | ✅                              | ✅                  | ✅                              |
+| southcentralus   | ✅                         | ✅                         | ✅                         | ✅                              | ✅                  | ✅                              |
 | southindia       | ✅                         | ✅                         | ✅                         | ✅                              | ✅                  | ✅                              |
 | swedencentral    | ✅                         | ✅                         | ✅                         | ✅                              | ✅                  | ✅                              |
 | switzerlandnorth | ✅                         | ✅                         | ✅                         | ✅                              | ✅                  | ✅                              |
@@ -61,8 +64,10 @@ Azure AI Foundry Agent Service supports the following Azure OpenAI models in the
 | eastus             | ✅                       | ✅                       | ✅                       | ✅                            |
 | eastus2            | ✅                       | ✅                       | ✅                       | ✅                            |
 | francecentral      | ✅                       | ✅                       | ✅                       | ✅                            |
+| germanywestcentral|  ✅                       | ✅                       | ✅                       | ✅                            |
 | italynorth         | ✅                       | ✅                       | ✅                       | ✅                            |
 | japaneast          | ✅                       | ✅                       | ✅                       | ✅                            |
+| southcentralus     | ✅                       | ✅                       | ✅                       | ✅                            |
 | southeastasia      | ✅                       | ✅                       | ✅                       | ✅                            |
 | southindia         | ✅                       | ✅                       | ✅                       | ✅                            |
 | swedencentral      | ✅                       | ✅                       | ✅                       | ✅                            |
@@ -82,6 +87,7 @@ Azure AI Foundry Agent Service supports the following Azure OpenAI models in the
 | francecentral    | -                            | -                  | -                  | ✅                  | -                       | ✅           | -                       | ✅               | ✅                  | ✅                  |
 | japaneast        | -                            | -                  | -                  | ✅                  | -                       | -           | -                       | -               | -                  | ✅                  |
 | norwayeast       | ✅                            | -                  | -                  | ✅                  | -                       | -           | -                       | -               | -                  | -                  |  
+| southcentralus   | ✅                           | ✅                | ✅                 | ✅                  | ✅                     | ✅          | ✅                      | -             | -                  | ✅                |
 | southindia       | -                            | -                  | -                  | ✅                  | -                       | -           | -                       | -               | ✅                  | ✅                  |  
 | swedencentral    | -                            | ✅                  | ✅                  | ✅                  | ✅                       | ✅           | ✅                       | ✅               | ✅                  | ✅                  |  
 | switzerlandnorth | -                            | -                  | -                  | ✅                  | -                       | ✅           | -                       | ✅               | -                  | ✅                  |  
@@ -100,7 +106,9 @@ Azure AI Foundry Agent Service supports the following Azure OpenAI models in the
 | eastus           | ✅                  | ✅                  | ✅                  | ✅                       | ✅           | ✅                       | ✅               | ✅                  | ✅                  |
 | eastus2          | ✅                  | ✅                  | ✅                  | ✅                       | ✅           | ✅                       | ✅               | ✅                  | ✅                  |
 | francecentral    | ✅                  | ✅                  | -                  | ✅                       | ✅           | -                       | ✅               | -                  | ✅                  |
+| germanywestcentral|  ✅                | ✅                  | ✅                  |  -                      |✅             | -                      | ✅                | ✅                |              |
 | japaneast        | ✅                  | ✅                  | ✅                  | ✅                       | -           | ✅                       | -               | -                  | ✅                  |
+| southcentralus   | -                   | ✅                  | ✅                  | ✅                       | ✅          | ✅                      | ✅                 | ✅                | ✅                  | 
 | southeastasia    | -                   | ✅                  | ✅                  | ✅                       | -           | -                       | -               | -                  | -                  |                    
 | southindia       | ✅                  | ✅                  | ✅                  | ✅                       | ✅           | -                       | ✅               | ✅                  | ✅                  |  
 | swedencentral    | ✅                  | ✅                  | ✅                  | ✅                       | ✅           | ✅                       | ✅               | ✅                  | ✅                  |  

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

@@ -275,11 +275,11 @@ To create a multi-agent setup, follow these steps:
 1. Create a thread and add a message to it.
 
     ```python
-    thread = project_client.agents.create_thread()
+    thread = project_client.agents.threads.create()
     print(f"Created thread, ID: {thread.id}")
 
     # Create message to thread
-    message = project_client.agents.create_message(
+    message = project_client.agents.messages.create(
         thread_id=thread.id,
         role=MessageRole.USER,
         content="What is the stock price of Microsoft?",
@@ -293,7 +293,7 @@ To create a multi-agent setup, follow these steps:
     ```python
 
     # Create and process Agent run in thread with tools
-    run = project_client.agents.create_and_process_run(thread_id=thread.id, agent_id=agent.id)
+    run = project_client.agents.runs.create_and_process(thread_id=thread.id, agent_id=agent.id)
     print(f"Run finished with status: {run.status}")
 
     if run.status == "failed":
@@ -312,7 +312,7 @@ To create a multi-agent setup, follow these steps:
 
     ```python
     # Print the Agent's response message with optional citation
-    response_message = project_client.agents.list_messages(thread_id=thread.id).get_last_message_by_role(
+    response_message = project_client.agents.messages.list(thread_id=thread.id).get_last_message_by_role(
         MessageRole.AGENT
     )
     if response_message:

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

@@ -89,7 +89,7 @@ When you add the Grounding with Bing Search tool to your agent, you can pass the
 According to Grounding with Bing's [terms of use and use and display requirements](https://www.microsoft.com/en-us/bing/apis/grounding-legal#use-and-display-requirements), you need to display both website URLs and Bing search query URLs in your custom interface. You can find website URLs through `annotations` parameter in API response and Bing search query URLs through `runstep` details. To render the webpage, we recommend you replace the endpoint of Bing search query URLs with `www.bing.com` and your Bing search query URL would look like "https://www.bing.com/search?q={search query}"
 
 ```python
-run_steps = project_client.agents.list_run_steps(run_id=run.id, thread_id=thread.id)
+run_steps = project_client.agents.runs_steps.list(run_id=run.id, thread_id=thread.id)
 run_steps_data = run_steps['data']
 print(f"Last run step detail: {run_steps_data}")
 ```

articles/ai-foundry/agents/how-to/tools/code-interpreter-samples.md

@@ -66,7 +66,7 @@ project_client = AIProjectClient(
 The sample uploads a data file for analysis:
 
 ```python
-file = project_client.agents.upload_file_and_poll(
+file = project_client.agents.files.upload_and_poll(
     file_path="nifty_500_quarterly_results.csv", 
     purpose=FilePurpose.AGENTS
 )
@@ -122,7 +122,7 @@ messages = project_client.agents.messages.list(thread_id=thread.id)
 for image_content in messages.image_contents:
     file_id = image_content.image_file.file_id
     file_name = f"{file_id}_image_file.png"
-    project_client.agents.save_file(file_id=file_id, file_name=file_name)
+    project_client.agents.files.save(file_id=file_id, file_name=file_name)
 
 # Process file path annotations
 for file_path_annotation in messages.file_path_annotations:
@@ -136,7 +136,7 @@ for file_path_annotation in messages.file_path_annotations:
 After completing the interaction, the code properly cleans up resources:
 
 ```python
-project_client.agents.delete_file(file.id)
+project_client.agents.files.delete(file.id)
 project_client.agents.delete_agent(agent.id)
 ```
 

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

@@ -136,7 +136,7 @@ if run.status == "failed":
 project_client.agents.vector_stores.delete(vector_store.id)
 print("Deleted vector store")
 
-project_client.agents.delete_file(file_id=file.id)
+project_client.agents.files.delete(file_id=file.id)
 print("Deleted file")
 
 project_client.agents.delete_agent(agent.id)

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

@@ -98,11 +98,11 @@ Files can also be added to a vector store after it's created by creating vector
 ```python
 
 # create a vector store with no file and wait for it to be processed
-vector_store = project_client.agents.create_vector_store_and_poll(data_sources=[], name="sample_vector_store")
+vector_store = project_client.agents.vector_stores.create_and_poll(data_sources=[], name="sample_vector_store")
 print(f"Created vector store, vector store ID: {vector_store.id}")
 
 # add the file to the vector store or you can supply file ids in the vector store creation
-vector_store_file_batch = project_client.agents.create_vector_store_file_batch_and_poll(
+vector_store_file_batch = project_client.agents.vector_store_file_batches.create_and_poll(
     vector_store_id=vector_store.id, file_ids=[file.id]
 )
 print(f"Created vector store file batch, vector store file batch ID: {vector_store_file_batch.id}")
@@ -112,7 +112,7 @@ print(f"Created vector store file batch, vector store file batch ID: {vector_sto
 Alternatively, you can add several files to a vector store by creating batches of up to 500 files.
 
 ```python
-batch = project_client.agents.create_vector_store_file_batch_and_poll(
+batch = project_client.agents.vector_store_file_batches.create_and_poll(
   vector_store_id=vector_store.id,
   file_ids=[file_1.id, file_2.id, file_3.id, file_4.id, file_5.id]
 )
@@ -144,7 +144,7 @@ print(f"Updated agent, agent ID: {agent.id}")
 
 ## Deleting vector stores
 ```python
-project_client.agents.delete_vector_store(vector_store.id)
+project_client.agents.vector_stores.delete(vector_store.id)
 print("Deleted vector store")
 ```
 
@@ -155,7 +155,7 @@ For basic agent setup, the `file_search` tool uses the `vector_stores`  object a
 To help you manage the costs associated with these vector_store objects, we added support for expiration policies in the `vector_store` object. You can set these policies when creating or updating the `vector_store` object.
 
 ```python
-vector_store = project_client.agents.create_vector_store_and_poll(
+vector_store = project_client.agents.vector_stores.create_and_poll(
   name="Product Documentation",
   file_ids=[file_1.id],
   expires_after={

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

@@ -139,7 +139,7 @@ Create the run, check the output, and examine what tools were called during the
 
 ## Perform cleanup
 
-After the interaction is complete, the script performs cleanup by deleting the created agent resource via `agents_client.delete_agent()` to avoid leaving unused resources. It also fetches and prints the entire message history from the thread by using `agents_client.list_messages()` for review or logging.
+After the interaction is complete, the script performs cleanup by deleting the created agent resource via `agents_client.delete_agent()` to avoid leaving unused resources. It also fetches and prints the entire message history from the thread by using `agents_client.messages.list()` for review or logging.
 
 ```python
         # Delete the agent resource to clean up

articles/ai-foundry/agents/how-to/tools/openapi-spec-samples.md

@@ -155,7 +155,7 @@ Create the run, check the output, and examine what tools were called during the
 
 
 ## Cleanup
-After the interaction is complete, the script performs cleanup by deleting the created agent resource using `agents_client.delete_agent()` to avoid leaving unused resources. It also fetches and prints the entire message history from the thread using `agents_client.list_messages()` for review or logging.
+After the interaction is complete, the script performs cleanup by deleting the created agent resource using `agents_client.delete_agent()` to avoid leaving unused resources. It also fetches and prints the entire message history from the thread using `agents_client.messages.list()` for review or logging.
 
 ```python
         # Delete the agent resource to clean up

articles/ai-foundry/agents/whats-new.md

@@ -7,14 +7,23 @@ author: aahill
 ms.author: aahi
 ms.service: azure-ai-agent-service
 ms.topic: overview
-ms.date: 06/26/2025
+ms.date: 08/04/2025
 ms.custom: azure-ai-agents
 ---
 
 # What's new in Azure AI Foundry Agent Service
 
 This article provides a summary of the latest releases and major documentation updates for Azure AI Foundry Agent Service.
 
+## August 2025
+
+### New regional availability
+
+The Azure AI Foundry Agent Sevice is now available in the following [regions](./concepts/model-region-support.md#available-models):
+* Brazil south
+* Germany west central
+* Italy north
+* South central US
 ## June 2025
 
 ### Deep Research tool