Merge pull request #6413 from MicrosoftDocs/main

Auto Publish – main to live - 2025-08-06 17:07 UTC

Author: learn-build-service-prod[bot]

.openpublishing.redirection.json

@@ -5,6 +5,11 @@
       "redirect_url": "/azure/ai-foundry/how-to/connections-add",
       "redirect_document_id": false
     },
+    {
+      "source_path": "articles/ai-foundry/how-to/develop/connections-add-sdk.md",
+      "redirect_url": "/azure/ai-foundry/how-to/connections-add?pivots=hub-project",
+      "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",

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

@@ -146,112 +146,161 @@ This ensures proper resource management and prevents unnecessary resource consum
 
 :::zone pivot="csharp" 
 
-## Create a client and agent
+## Create a project client
 
-First, set up the configuration using `appsettings.json`, create a `PersistentAgentsClient`, and then create a `PersistentAgent` with the Code Interpreter tool enabled.
+Create a client object, which will contain the project endpoint for connecting to your AI project and other resources.
 
 ```csharp
 using Azure;
 using Azure.AI.Agents.Persistent;
 using Azure.Identity;
-using Microsoft.Extensions.Configuration;
-using System.Diagnostics;
 
-IConfigurationRoot configuration = new ConfigurationBuilder()
-    .SetBasePath(AppContext.BaseDirectory)
-    .AddJsonFile("appsettings.json", optional: false, reloadOnChange: true)
-    .Build();
+var projectEndpoint = System.Environment.GetEnvironmentVariable("ProjectEndpoint");
+var projectEndpoint = System.Environment.GetEnvironmentVariable("ModelDeploymentName");
+var projectEndpoint = System.Environment.GetEnvironmentVariable("BingConnectionId");
 
-var projectEndpoint = configuration["ProjectEndpoint"];
-var modelDeploymentName = configuration["ModelDeploymentName"];
+// Create the Agent Client
+PersistentAgentsClient agentClient = new(projectEndpoint, new DefaultAzureCredential());
+```
+
+## Create an Agent with the Grounding with Bing search tool enabled
 
-PersistentAgentsClient client = new(projectEndpoint, new DefaultAzureCredential());
+To make the Grounding with Bing search tool available to your agent, use a connection to initialize the tool and attach it to the agent. You can find your connection in the **connected resources** section of your project in the [Azure AI Foundry portal](https://ai.azure.com/?cid=learnDocs).
 
-PersistentAgent agent = client.Administration.CreateAgent(
+```csharp
+
+BingGroundingToolDefinition bingGroundingTool = new(
+    new BingGroundingSearchToolParameters(
+        [new BingGroundingSearchConfiguration(bingConnectionId)]
+    )
+);
+
+// Create the Agent
+PersistentAgent agent = agentClient.Administration.CreateAgent(
     model: modelDeploymentName,
-    name: "My Friendly Test Agent",
-    instructions: "You politely help with math questions. Use the code interpreter tool when asked to visualize numbers.",
-    tools: [new CodeInterpreterToolDefinition()]
+    name: "my-agent",
+    instructions: "Use the bing grounding tool to answer questions.",
+    tools: [bingGroundingTool]
 );
 ```
 
-## Create a thread and add a message
-
-Next, create a `PersistentAgentThread` for the conversation and add the initial user message.
+## Create a thread and run
 
 ```csharp
-PersistentAgentThread thread = client.Threads.CreateThread();
+PersistentAgentThread thread = agentClient.Threads.CreateThread();
 
-client.Messages.CreateMessage(
+// Create message and run the agent
+PersistentThreadMessage message = agentClient.Messages.CreateMessage(
     thread.Id,
     MessageRole.User,
-    "Hi, Agent! Draw a graph for a line with a slope of 4 and y-intercept of 9.");
+    "How does wikipedia explain Euler's Identity?");
+ThreadRun run = agentClient.Runs.CreateRun(thread, agent);
+
 ```
 
-## Create and monitor a run
+## Wait for the agent to complete and print the output
 
-Then, create a `ThreadRun` for the thread and agent. Poll the run's status until it completes or requires action.
+First, wait for the agent to complete the run by polling its status. Observe that the model uses the Grounding with Bing Search tool to provide a response to the user's question.
 
 ```csharp
-ThreadRun run = client.Runs.CreateRun(
-    thread.Id,
-    agent.Id,
-    additionalInstructions: "Please address the user as Jane Doe. The user has a premium account.");
-
+// Wait for the agent to finish running
 do
 {
     Thread.Sleep(TimeSpan.FromMilliseconds(500));
-    run = client.Runs.GetRun(thread.Id, run.Id);
+    run = agentClient.Runs.GetRun(thread.Id, run.Id);
 }
 while (run.Status == RunStatus.Queued
-    || run.Status == RunStatus.InProgress
-    || run.Status == RunStatus.RequiresAction);
-```
+    || run.Status == RunStatus.InProgress);
 
-## Process the results and handle files
+// Confirm that the run completed successfully
+if (run.Status != RunStatus.Completed)
+{
+    throw new Exception("Run did not complete successfully, error: " + run.LastError?.Message);
+}
+```
 
-Once the run is finished, retrieve all messages from the thread. Iterate through the messages to display text content and handle any generated image files by saving them locally and opening them.
+Then, retrieve and process the messages from the completed run.
 
 ```csharp
-Pageable<PersistentThreadMessage> messages = client.Messages.GetMessages(
+// Retrieve all messages from the agent client
+Pageable<PersistentThreadMessage> messages = agentClient.Messages.GetMessages(
     threadId: thread.Id,
-    order: ListSortOrder.Ascending);
+    order: ListSortOrder.Ascending
+);
 
+// Process messages in order
 foreach (PersistentThreadMessage threadMessage in messages)
 {
-    foreach (MessageContent content in threadMessage.ContentItems)
+    Console.Write($"{threadMessage.CreatedAt:yyyy-MM-dd HH:mm:ss} - {threadMessage.Role,10}: ");
+    foreach (MessageContent contentItem in threadMessage.ContentItems)
     {
-        switch (content)
+        if (contentItem is MessageTextContent textItem)
         {
-            case MessageTextContent textItem:
-                Console.WriteLine($"[{threadMessage.Role}]: {textItem.Text}");
-                break;
-            case MessageImageFileContent imageFileContent:
-                Console.WriteLine($"[{threadMessage.Role}]: Image content file ID = {imageFileContent.FileId}");
-                BinaryData imageContent = client.Files.GetFileContent(imageFileContent.FileId);
-                string tempFilePath = Path.Combine(AppContext.BaseDirectory, $"{Guid.NewGuid()}.png");
-                File.WriteAllBytes(tempFilePath, imageContent.ToArray());
-                client.Files.DeleteFile(imageFileContent.FileId);
-
-                ProcessStartInfo psi = new()
+            string response = textItem.Text;
+
+            // If we have Text URL citation annotations, reformat the response to show title & URL for citations
+            if (textItem.Annotations != null)
+            {
+                foreach (MessageTextAnnotation annotation in textItem.Annotations)
                 {
-                    FileName = tempFilePath,
-                    UseShellExecute = true
-                };
-                Process.Start(psi);
-                break;
+                    if (annotation is MessageTextUriCitationAnnotation urlAnnotation)
+                    {
+                        response = response.Replace(urlAnnotation.Text, $" [{urlAnnotation.UriCitation.Title}]({urlAnnotation.UriCitation.Uri})");
+                    }
+                }
+            }
+            Console.Write($"Agent response: {response}");
+        }
+        else if (contentItem is MessageImageFileContent imageFileItem)
+        {
+            Console.Write($"<image from ID: {imageFileItem.FileId}");
         }
+        Console.WriteLine();
     }
 }
+
+```
+
+## Optionally output the run steps used by the agent
+
+```csharp
+// Retrieve the run steps used by the agent and print those to the console
+Console.WriteLine("Run Steps used by Agent:");
+Pageable<RunStep> runSteps = agentClient.Runs.GetRunSteps(run);
+
+foreach (var step in runSteps)
+{
+    Console.WriteLine($"Step ID: {step.Id}, Total Tokens: {step.Usage.TotalTokens}, Status: {step.Status}, Type: {step.Type}");
+
+    if (step.StepDetails is RunStepMessageCreationDetails messageCreationDetails)
+    {
+        Console.WriteLine($"   Message Creation Id: {messageCreationDetails.MessageCreation.MessageId}");
+    }
+    else if (step.StepDetails is RunStepToolCallDetails toolCallDetails)
+    {
+        // We know this agent only has the Bing Grounding tool, so we can cast it directly
+        foreach (RunStepBingGroundingToolCall toolCall in toolCallDetails.ToolCalls)
+        {
+            Console.WriteLine($"   Tool Call Details: {toolCall.GetType()}");
+
+            foreach (var result in toolCall.BingGrounding)
+            {
+                Console.WriteLine($"      {result.Key}: {result.Value}");
+            }
+        }
+    }
+}
+
 ```
 
 ## Clean up resources
 
-Finally, delete the thread and the agent to clean up the resources created in this sample.
+Clean up the resources from this sample.
 
 ```csharp
-    client.Threads.DeleteThread(threadId: thread.Id);
-    client.Administration.DeleteAgent(agentId: agent.Id);
+// Delete thread and agent
+agentClient.Threads.DeleteThread(threadId: thread.Id);
+agentClient.Administration.DeleteAgent(agentId: agent.Id);
 ```
 
 :::zone-end

articles/ai-foundry/foundry-local/get-started.md

@@ -84,7 +84,10 @@ foundry model run gpt-oss-20b
 > [!IMPORTANT]
 > Requirements for running GPT-OSS-20B:
 > - Nvidia GPU with 16GB VRAM or more.
-> - Foundry Local version 0.6.0 or above.
+> - Foundry Local version **0.6.87** or above. Any version below this will not support the model. You can check your Foundry Local version by running:
+> ```bash
+> foundry --version
+> ```
 
 ## Explore commands
 

articles/ai-foundry/how-to/connections-add.md

@@ -1,25 +1,25 @@
 ---
 
-title: How to add a new connection in Azure AI Foundry portal
+title: Add a new connection to your project
 titleSuffix: Azure AI Foundry
-description: Learn how to add a new connection in Azure AI Foundry portal.
+description: Learn how to add a new connection to your hub based or Foundry project.
 manager: scottpolly
 ms.service: azure-ai-foundry
 ms.custom:
   - ignite-2023
   - build-2024
   - ignite-2024
 ms.topic: how-to
-ms.date: 07/08/2025
+ms.date: 08/05/2025
 ms.reviewer: sgilley
 ms.author: sgilley
 author: sdgilley
 zone_pivot_groups: project-type
-# Customer Intent: As an admin or developer, I want to understand how to add new connections in Azure AI Foundry portal.
+# Customer Intent: As an admin or developer, I want to understand how to add new connections in my project.
 
 ---
 
-# How to add a new connection in Azure AI Foundry portal
+# Add a new connection to your project
 
 [!INCLUDE [feature-preview](../includes/feature-preview.md)]
 
@@ -77,7 +77,7 @@ To learn more about Agent Knowledge tools, see [Knowledge tool overview](https:/
 
 ::: zone-end
 
-## Create a new connection
+## <a name="create-a-new-connection"></a> Create a new connection in Azure AI Foundry portal
 
 [!INCLUDE [tip-left-pane](../includes/tip-left-pane.md)]
 
@@ -103,6 +103,14 @@ Follow these steps to create a new connection that's only available for the curr
 
 1. After the service is connected, select __Close__.
 
+::: zone pivot="hub-project"
+
+## Create a new connection with Azure Machine Learning SDK
+
+[!INCLUDE [hub-connections](../includes/hub-connections.md)]
+
+::: zone-end 
+
 ## Network isolation
 
 ::: zone pivot="hub-project"