Merge branch 'main' into peibekwe/workflow-unit-tests

dotnet/samples/03-workflows/Concurrent/Concurrent/Concurrent.csproj

@@ -9,7 +9,7 @@
   </PropertyGroup>
 
   <ItemGroup>
-    <PackageReference Include="Azure.AI.Projects" />
+    <PackageReference Include="Azure.AI.OpenAI" />
     <PackageReference Include="Azure.Identity" />
     <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
   </ItemGroup>

dotnet/samples/03-workflows/Concurrent/Concurrent/Program.cs

@@ -1,7 +1,6 @@
 // Copyright (c) Microsoft. All rights reserved.
 
-using System.Text;
-using Azure.AI.Projects;
+using Azure.AI.OpenAI;
 using Azure.Identity;
 using Microsoft.Agents.AI;
 using Microsoft.Agents.AI.Workflows;
@@ -32,26 +31,22 @@ public static class Program
 {
     private static async Task Main()
     {
-        // Set up the Azure AI Project client
-        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 chatClient = new AIProjectClient(new Uri(endpoint), new AzureCliCredential())
-                            .ProjectOpenAIClient.GetChatClient(deploymentName).AsIChatClient();
+        // Set up the Azure OpenAI client
+        var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+        var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+        var chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential()).GetChatClient(deploymentName).AsIChatClient();
 
         // Create the executors
-        var physicist = new ChatClientAgent(
+        ChatClientAgent physicist = new(
             chatClient,
             name: "Physicist",
             instructions: "You are an expert in physics. You answer questions from a physics perspective."
-        ).BindAsExecutor(new AIAgentHostOptions { ForwardIncomingMessages = false });
-
-        var chemist = new ChatClientAgent(
+        );
+        ChatClientAgent chemist = new(
             chatClient,
             name: "Chemist",
             instructions: "You are an expert in chemistry. You answer questions from a chemistry perspective."
-        ).BindAsExecutor(new AIAgentHostOptions { ForwardIncomingMessages = false });
-
+        );
         var startExecutor = new ConcurrentStartExecutor();
         var aggregationExecutor = new ConcurrentAggregationExecutor();
 
@@ -66,30 +61,11 @@ public static class Program
         await using StreamingRun run = await InProcessExecution.RunStreamingAsync(workflow, input: "What is temperature?");
         await foreach (WorkflowEvent evt in run.WatchStreamAsync())
         {
-            switch (evt)
+            if (evt is WorkflowOutputEvent output)
             {
-                case WorkflowOutputEvent workflowOutput:
-                    Console.WriteLine($"Workflow completed with results:\n{workflowOutput.Data}");
-                    break;
-
-                case WorkflowErrorEvent workflowError:
-                    WriteError(workflowError.Exception?.ToString() ?? "Unknown workflow error occurred");
-                    break;
-
-                case ExecutorFailedEvent executorFailed:
-                    WriteError($"Executor '{executorFailed.ExecutorId}' failed with {(
-                        executorFailed.Data == null ? "unknown error" : $"exception {executorFailed.Data}"
-                        )}.");
-                    break;
+                Console.WriteLine($"Workflow completed with results:\n{output.Data}");
             }
         }
-
-        void WriteError(string error)
-        {
-            Console.ForegroundColor = ConsoleColor.Red;
-            Console.Write(error);
-            Console.ResetColor();
-        }
     }
 }
 
@@ -116,7 +92,7 @@ internal sealed partial class ConcurrentStartExecutor() :
         // the message but will not start processing until they receive a turn token.
         await context.SendMessageAsync(new ChatMessage(ChatRole.User, message), cancellationToken: cancellationToken);
         // Broadcast the turn token to kick off the agents.
-        await context.SendMessageAsync(new TurnToken(emitEvents: false), cancellationToken: cancellationToken);
+        await context.SendMessageAsync(new TurnToken(emitEvents: true), cancellationToken: cancellationToken);
     }
 }
 
@@ -140,19 +116,11 @@ internal sealed partial class ConcurrentAggregationExecutor() :
     public override async ValueTask HandleAsync(List<ChatMessage> message, IWorkflowContext context, CancellationToken cancellationToken = default)
     {
         this._messages.AddRange(message);
-    }
 
-    protected override ValueTask OnMessageDeliveryFinishedAsync(IWorkflowContext context, CancellationToken cancellationToken = default)
-    {
-        StringBuilder resultBuilder = new();
-        foreach (ChatMessage m in this._messages)
+        if (this._messages.Count == 2)
         {
-            resultBuilder.AppendLine($"{m.AuthorName}: {m.Text}");
-            resultBuilder.AppendLine();
+            var formattedMessages = string.Join(Environment.NewLine, this._messages.Select(m => $"{m.AuthorName}: {m.Text}"));
+            await context.YieldOutputAsync(formattedMessages, cancellationToken);
         }
-
-        this._messages.Clear();
-
-        return context.YieldOutputAsync(resultBuilder.ToString(), cancellationToken);
     }
 }

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

@@ -419,6 +419,12 @@ 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

@@ -279,6 +279,48 @@ 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>

python/samples/02-agents/context_providers/neo4j/README.md

@@ -1,19 +0,0 @@
-# Neo4j Context Providers
-
-Neo4j offers two context providers for the Agent Framework, each serving a different purpose:
-
-| | [Neo4j Memory](../neo4j_memory/README.md) | [Neo4j GraphRAG](../../../05-end-to-end/neo4j_graphrag/README.md) |
-|---|---|---|
-| **What it does** | Read-write memory — stores conversations, builds knowledge graphs, learns from interactions | Read-only retrieval from a pre-existing knowledge base with optional graph traversal |
-| **Data source** | Agent interactions (grows over time) | Pre-loaded documents and indexes |
-| **Python package** | [`neo4j-agent-memory`](https://pypi.org/project/neo4j-agent-memory/) | [`agent-framework-neo4j`](https://pypi.org/project/agent-framework-neo4j/) |
-| **Database setup** | Empty — creates its own schema | Requires pre-indexed documents with vector or fulltext indexes |
-| **Example use case** | "Remember my preferences", "What did we discuss last time?" | "Search our documents", "What risks does Acme Corp face?" |
-
-## Which should I use?
-
-**Use [Neo4j Memory](../neo4j_memory/README.md)** when your agent needs to remember things across sessions — user preferences, past conversations, extracted entities, and reasoning traces. The memory provider writes to the database on every interaction, building a knowledge graph that grows over time.
-
-**Use [Neo4j GraphRAG](../../../05-end-to-end/neo4j_graphrag/README.md)** when your agent needs to search an existing knowledge base — documents, articles, product catalogs — and optionally enrich results by traversing graph relationships. The GraphRAG provider is read-only and does not modify your data.
-
-You can use both together: GraphRAG for domain knowledge retrieval, Memory for personalization and learning.

python/samples/02-agents/context_providers/neo4j_memory/README.md

@@ -1,9 +0,0 @@
-# Neo4j Memory Context Provider
-
-[Neo4j Agent Memory](https://github.com/neo4j-labs/agent-memory) is a graph-native memory system for AI agents that stores conversations, builds knowledge graphs from interactions, and lets agents learn from their own reasoning — all backed by Neo4j.
-
-For full documentation, installation instructions, code examples, and configuration details, see the [Neo4j Memory integration guide on Microsoft Learn](https://learn.microsoft.com/agent-framework/integrations/neo4j-memory).
-
-For a runnable example, see the [retail assistant sample](https://github.com/neo4j-labs/agent-memory/tree/main/examples/microsoft_agent_retail_assistant).
-
-For help choosing between the Memory and GraphRAG providers, see the [Neo4j Context Providers overview](../neo4j/README.md).

python/samples/05-end-to-end/neo4j_graphrag/README.md

@@ -4,8 +4,6 @@ The [Neo4j GraphRAG context provider](https://github.com/neo4j-labs/neo4j-maf-pr
 
 This sample keeps setup lightweight by using a pre-built Neo4j fulltext index plus a graph-enrichment query.
 
-For full documentation, see the [Neo4j GraphRAG integration guide on Microsoft Learn](https://learn.microsoft.com/agent-framework/integrations/neo4j-graphrag).
-
 ## Example
 
 | File | Description |