fix: address review comments

README.md

@@ -120,38 +120,38 @@ if __name__ == "__main__":
 ```
 
 ### Basic Agent - .NET
-Create a simple Agent, using Microsoft Foundry with token-based auth, that writes a haiku about the Microsoft Agent Framework
-
-```c#
-// dotnet add package Microsoft.Agents.AI.Foundry
-// Use `az login` to authenticate with Azure CLI
-using Azure.AI.Projects;
-using Azure.Identity;
-using System;
-using Azure.AI.Projects;
-using Azure.Identity;
-
-var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
-
-var agent = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
-    .AsAIAgent(model: deploymentName, name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
-
-Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
-```
 
 Create a simple Agent, using OpenAI Responses, that writes a haiku about the Microsoft Agent Framework
 
 ```c#
-// dotnet add package Microsoft.Agents.AI.OpenAI
-using System;
+// dotnet add package Microsoft.Agents.AI.OpenAI --prerelease
+using Microsoft.Agents.AI;
 using OpenAI;
 using OpenAI.Responses;
 
 // Replace the <apikey> with your OpenAI API key.
 var agent = new OpenAIClient("<apikey>")
-    .GetResponsesClient()
-    .AsAIAgent(model: "gpt-5.4-mini", name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
+    .GetResponsesClient("gpt-4o-mini")
+    .AsAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
+
+Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
+```
+
+Create a simple Agent, using Microsoft Foundry with token-based auth, that writes a haiku about the Microsoft Agent Framework
+
+```c#
+// dotnet add package Microsoft.Agents.AI.AzureAI --prerelease
+// dotnet add package Azure.Identity
+// Use `az login` to authenticate with Azure CLI
+using Azure.AI.Projects;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+var agent = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
+    .AsAIAgent(model: deploymentName, name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
 
 Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
 ```
@@ -207,9 +207,4 @@ The samples typically read configuration from environment variables. Common requ
 
 ## Important Notes
 
-> [!IMPORTANT]
-> If you use Microsoft Agent Framework to build applications that operate with any third-party servers, agents, code, or non-Azure Direct models (“Third-Party Systems”), you do so at your own risk. Third-Party Systems are Non-Microsoft Products under the Microsoft Product Terms and are governed by their own third-party license terms. You are responsible for any usage and associated costs.
->
->We recommend reviewing all data being shared with and received from Third-Party Systems and being cognizant of third-party practices for handling, sharing, retention and location of data. It is your responsibility to manage whether your data will flow outside of your organization’s Azure compliance and geographic boundaries and any related implications, and that appropriate permissions, boundaries and approvals are provisioned.
-> 
->You are responsible for carefully reviewing and testing applications you build using Microsoft Agent Framework in the context of your specific use cases, and making all appropriate decisions and customizations. This includes implementing your own responsible AI mitigations such as metaprompt, content filters, or other safety systems, and ensuring your applications meet appropriate quality, reliability, security, and trustworthiness standards. See also: [Transparency FAQ](./TRANSPARENCY_FAQ.md)
+If you use the Microsoft Agent Framework to build applications that operate with third-party servers or agents, you do so at your own risk. We recommend reviewing all data being shared with third-party servers or agents and being cognizant of third-party practices for retention and location of data. It is your responsibility to manage whether your data will flow outside of your organization's Azure compliance and geographic boundaries and any related implications.

dotnet/samples/03-workflows/_StartHere/04_MultiModelService/04_MultiModelService.csproj

@@ -10,7 +10,7 @@
 
   <ItemGroup>
     <PackageReference Include="Anthropic" />
-    <PackageReference Include="Google.GenAI" />
+    <PackageReference Include="AWSSDK.Extensions.Bedrock.MEAI" />
     <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
   </ItemGroup>
 

dotnet/samples/03-workflows/_StartHere/04_MultiModelService/Program.cs

@@ -1,6 +1,6 @@
 // Copyright (c) Microsoft. All rights reserved.
 
-using Google.GenAI;
+using Amazon.BedrockRuntime;
 using Microsoft.Agents.AI;
 using Microsoft.Agents.AI.Workflows;
 using Microsoft.Extensions.AI;
@@ -9,20 +9,22 @@ using Microsoft.Extensions.AI;
 const string Topic = "Goldendoodles make the best pets.";
 
 // Create the IChatClients to talk to different services.
-IChatClient google = new Client(vertexAI: false, apiKey: Environment.GetEnvironmentVariable("GOOGLE_GENAI_API_KEY"))
-    .AsIChatClient("gemini-2.5-flash");
+IChatClient aws = new AmazonBedrockRuntimeClient(
+    Environment.GetEnvironmentVariable("BEDROCK_ACCESS_KEY"!),
+    Environment.GetEnvironmentVariable("BEDROCK_SECRET_KEY")!,
+    Amazon.RegionEndpoint.USEast1)
+    .AsIChatClient("amazon.nova-pro-v1:0");
 
 IChatClient anthropic = new Anthropic.AnthropicClient(
     new() { ApiKey = Environment.GetEnvironmentVariable("ANTHROPIC_API_KEY") })
     .AsIChatClient("claude-sonnet-4-20250514");
 
 IChatClient openai = new OpenAI.OpenAIClient(
-    Environment.GetEnvironmentVariable("OPENAI_API_KEY"))
-    .GetResponsesClient()
-    .AsIChatClient("gpt-4o-mini");
+    Environment.GetEnvironmentVariable("OPENAI_API_KEY")!).GetChatClient("gpt-4o-mini")
+    .AsIChatClient();
 
 // Define our agents.
-AIAgent researcher = new ChatClientAgent(google,
+AIAgent researcher = new ChatClientAgent(aws,
     instructions: """
         Write a short essay on topic specified by the user. The essay should be three to five paragraphs, written at a
         high school reading level, and include relevant background information, key claims, and notable perspectives.
@@ -58,12 +60,6 @@ AIAgent workflowAgent = AgentWorkflowBuilder.BuildSequential(researcher, factChe
 string? lastAuthor = null;
 await foreach (var update in workflowAgent.RunStreamingAsync(Topic))
 {
-    // Skip WorkflowEvent-only updates
-    if ((update.Contents == null || update.Contents.Count == 0) && update.RawRepresentation is WorkflowEvent)
-    {
-        continue;
-    }
-
     if (lastAuthor != update.AuthorName)
     {
         lastAuthor = update.AuthorName;

dotnet/src/Microsoft.Agents.AI.Workflows/Execution/StreamingRunEventStream.cs

@@ -287,6 +287,10 @@ internal sealed class StreamingRunEventStream : IRunEventStream
         {
             // Discard each event (including InternalCompletionSignals)
         }
+
+        // After clearing, signal the run loop to continue if needed
+        // The run loop will send a new completion signal when it finishes processing from the restored state
+        this.SignalInput();
     }
 
     public async ValueTask StopAsync()

dotnet/src/Microsoft.Agents.AI.Workflows/InProc/InProcessRunnerContext.cs

@@ -419,12 +419,6 @@ internal sealed class InProcessRunnerContext : IRunnerContext
                                                       .Select(id => this.EnsureExecutorAsync(id, tracer: null).AsTask())
                                                       .ToArray();
 
-        // Discard queued external deliveries from the superseded timeline so a runtime
-        // restore cannot apply stale responses after importing the checkpoint state.
-        while (this._queuedExternalDeliveries.TryDequeue(out _))
-        {
-        }
-
         this._nextStep = new StepContext();
         this._nextStep.ImportMessages(importedState.QueuedMessages);
 

dotnet/tests/Microsoft.Agents.AI.Workflows.UnitTests/CheckpointResumeTests.cs

@@ -279,48 +279,6 @@ public class CheckpointResumeTests
             "the workflow should be able to continue after the runtime restore replay");
     }
 
-    /// <summary>
-    /// Verifies that restoring a live run clears any queued external responses from the
-    /// superseded timeline before importing checkpoint state.
-    /// </summary>
-    [Fact]
-    internal async Task Checkpoint_Restore_ClearsQueuedExternalResponsesBeforeImportAsync()
-    {
-        Workflow workflow = CreateSimpleRequestWorkflow();
-        CheckpointManager checkpointManager = CheckpointManager.CreateInMemory();
-        InProcessExecutionEnvironment env = ExecutionEnvironment.InProcess_Lockstep.ToWorkflowExecutionEnvironment();
-
-        await using StreamingRun run = await env.WithCheckpointing(checkpointManager)
-                                                .RunStreamingAsync(workflow, "Hello");
-
-        (ExternalRequest pendingRequest, CheckpointInfo checkpoint) = await CapturePendingRequestAndCheckpointAsync(run);
-
-        await run.SendResponseAsync(pendingRequest.CreateResponse("World"));
-        await run.RestoreCheckpointAsync(checkpoint);
-
-        List<WorkflowEvent> restoredEvents = await ReadToHaltAsync(run);
-        ExternalRequest replayedRequest = restoredEvents.OfType<RequestInfoEvent>()
-                                                        .Select(evt => evt.Request)
-                                                        .Should()
-                                                        .ContainSingle("the restored run should still be waiting for the checkpointed request")
-                                                        .Subject;
-
-        restoredEvents.OfType<WorkflowErrorEvent>().Should().BeEmpty(
-            "a queued response from the superseded timeline should not be processed after restore");
-        RunStatus statusAfterRestore = await run.GetStatusAsync();
-        statusAfterRestore.Should().Be(RunStatus.PendingRequests,
-            "the restored run should remain pending until a post-restore response is sent");
-
-        await run.SendResponseAsync(replayedRequest.CreateResponse("Again"));
-
-        List<WorkflowEvent> completionEvents = await ReadToHaltAsync(run);
-        completionEvents.OfType<WorkflowErrorEvent>().Should().BeEmpty(
-            "the restored request should complete cleanly once a new response is provided");
-        RunStatus finalStatus = await run.GetStatusAsync();
-        finalStatus.Should().Be(RunStatus.Idle,
-            "the workflow should finish once the replayed request receives a fresh response");
-    }
-
     /// <summary>
     /// Verifies that a resumed parent workflow re-emits pending requests that originated in a subworkflow.
     /// </summary>