minor tweaks

Minor cleanup
Fid http URL for test
2026-06-16 21:04:09 +08:00 · 2026-01-23 10:16:31 -08:00 · 2026-01-23 07:48:31 -08:00 · 2026-01-23 07:05:02 -08:00 · 2026-01-22 22:09:33 -08:00 · 2026-01-22 21:27:53 -08:00
722 changed files with 22944 additions and 38088 deletions
@@ -105,7 +105,7 @@ After completing migration, verify these specific items:
 1. **Compilation**: Execute `dotnet build` on all modified projects - zero errors required
 2. **Namespace Updates**: Confirm all `using Microsoft.SemanticKernel.Agents` statements are replaced
 3. **Method Calls**: Verify all `InvokeAsync` calls are changed to `RunAsync`
-4. **Return Types**: Confirm handling of `AgentResponse` instead of `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>`
+4. **Return Types**: Confirm handling of `AgentRunResponse` instead of `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>`
 5. **Thread Creation**: Validate all thread creation uses `agent.GetNewThread()` pattern
 6. **Tool Registration**: Ensure `[KernelFunction]` attributes are removed and `AIFunctionFactory.Create()` is used
 7. **Options Configuration**: Verify `AgentRunOptions` or `ChatClientAgentRunOptions` replaces `AgentInvokeOptions`
@@ -119,7 +119,7 @@ Agent Framework provides functionality for creating and managing AI agents throu
 Key API differences:
 - Agent creation: Remove Kernel dependency, use direct client-based creation
 - Method names: `InvokeAsync` → `RunAsync`, `InvokeStreamingAsync` → `RunStreamingAsync`
- Return types: `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` → `AgentResponse`
+- Return types: `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` → `AgentRunResponse`
 - Thread creation: Provider-specific constructors → `agent.GetNewThread()`
 - Tool registration: `KernelPlugin` system → Direct `AIFunction` registration
 - Options: `AgentInvokeOptions` → Provider-specific run options (e.g., `ChatClientAgentRunOptions`)
@@ -166,8 +166,8 @@ Replace these method calls:
 | `thread.DeleteAsync()` | Provider-specific cleanup | Use provider client directly |

 Return type changes:
- `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` → `AgentResponse`
- `IAsyncEnumerable<StreamingChatMessageContent>` → `IAsyncEnumerable<AgentResponseUpdate>`
+- `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` → `AgentRunResponse`
+- `IAsyncEnumerable<StreamingChatMessageContent>` → `IAsyncEnumerable<AgentRunResponseUpdate>`
 </api_changes>

 <configuration_changes>
@@ -191,8 +191,8 @@ Agent Framework changes these behaviors compared to Semantic Kernel Agents:
 1. **Thread Management**: Agent Framework automatically manages thread state. Semantic Kernel required manual thread updates in some scenarios (e.g., OpenAI Responses).

 2. **Return Types**:
-   - Non-streaming: Returns single `AgentResponse` instead of `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>`
-   - Streaming: Returns `IAsyncEnumerable<AgentResponseUpdate>` instead of `IAsyncEnumerable<StreamingChatMessageContent>`
+   - Non-streaming: Returns single `AgentRunResponse` instead of `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>`
+   - Streaming: Returns `IAsyncEnumerable<AgentRunResponseUpdate>` instead of `IAsyncEnumerable<StreamingChatMessageContent>`

 3. **Tool Registration**: Agent Framework uses direct function registration without requiring `[KernelFunction]` attributes.

@@ -397,7 +397,7 @@ await foreach (AgentResponseItem<ChatMessageContent> item in agent.InvokeAsync(u

 **With this Agent Framework non-streaming pattern:**
 ```csharp
-AgentResponse result = await agent.RunAsync(userInput, thread, options);
+AgentRunResponse result = await agent.RunAsync(userInput, thread, options);
 Console.WriteLine(result);
 ```

@@ -411,7 +411,7 @@ await foreach (StreamingChatMessageContent update in agent.InvokeStreamingAsync(

 **With this Agent Framework streaming pattern:**
 ```csharp
-await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(userInput, thread, options))
+await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(userInput, thread, options))
 {
    Console.Write(update);
 }
@@ -420,8 +420,8 @@ await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(userInput,
 **Required changes:**
 1. Replace `agent.InvokeAsync()` with `agent.RunAsync()`
 2. Replace `agent.InvokeStreamingAsync()` with `agent.RunStreamingAsync()`
-3. Change return type handling from `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` to `AgentResponse`
-4. Change streaming type from `StreamingChatMessageContent` to `AgentResponseUpdate`
+3. Change return type handling from `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` to `AgentRunResponse`
+4. Change streaming type from `StreamingChatMessageContent` to `AgentRunResponseUpdate`
 5. Remove `await foreach` for non-streaming calls
 6. Access message content directly from result object instead of iterating
 </api_changes>
@@ -661,7 +661,7 @@ await foreach (var result in agent.InvokeAsync(input, thread, options))
 ```csharp
 ChatClientAgentRunOptions options = new(new ChatOptions { MaxOutputTokens = 1000 });

-AgentResponse result = await agent.RunAsync(input, thread, options);
+AgentRunResponse result = await agent.RunAsync(input, thread, options);
 Console.WriteLine(result);

 // Access underlying content when needed:
@@ -689,7 +689,7 @@ await foreach (var result in agent.InvokeAsync(input, thread, options))

 **With this Agent Framework non-streaming usage pattern:**
 ```csharp
-AgentResponse result = await agent.RunAsync(input, thread, options);
+AgentRunResponse result = await agent.RunAsync(input, thread, options);
 Console.WriteLine($"Tokens: {result.Usage.TotalTokenCount}");
 ```

@@ -709,7 +709,7 @@ await foreach (StreamingChatMessageContent response in agent.InvokeStreamingAsyn

 **With this Agent Framework streaming usage pattern:**
 ```csharp
-await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(input, thread, options))
+await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(input, thread, options))
 {
    if (update.Contents.OfType<UsageContent>().FirstOrDefault() is { } usageContent)
    {
@@ -29,4 +29,3 @@ jobs:
          token: ${{ secrets.GITHUB_TOKEN }}
          timeout: 3600
          interval: 30
-          ignored: CodeQL
@@ -97,7 +97,7 @@ jobs:
        id: azure-functions-setup
      - name: Test with pytest
        timeout-minutes: 10
-        run: uv run poe all-tests -n logical --dist loadfile --dist worksteal --timeout 600 --retries 3 --retry-delay 10
+        run: uv run poe all-tests -n logical --dist loadfile --dist worksteal --timeout 300 --retries 3 --retry-delay 10
        working-directory: ./python
      - name: Test core samples
        timeout-minutes: 10
@@ -226,4 +226,3 @@ local.settings.json

 # Database files
 *.db
-python/dotnet-ref
@@ -163,8 +163,8 @@ foreach (var update in response.Messages)
 ### Option 2 Run: Container with Primary and Secondary Properties, RunStreaming: Stream of Primary + Secondary

 Run returns a new response type that has separate properties for the Primary Content and the Secondary Updates leading up to it.
-The Primary content is available in the `AgentResponse.Messages` property while Secondary updates are in a new `AgentResponse.Updates` property.
-`AgentResponse.Text` returns the Primary content text.
+The Primary content is available in the `AgentRunResponse.Messages` property while Secondary updates are in a new `AgentRunResponse.Updates` property.
+`AgentRunResponse.Text` returns the Primary content text.

 Since streaming would still need to return an `IAsyncEnumerable` of updates, the design would differ from non-streaming.
 With non-streaming Primary and Secondary content is split into separate lists, while with streaming it's combined in one stream.
@@ -232,24 +232,24 @@ await foreach (var update in responses)
 ```csharp
 class Agent
 {
-    public abstract Task<AgentResponse> RunAsync(
+    public abstract Task<AgentRunResponse> RunAsync(
        IReadOnlyCollection<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
        CancellationToken cancellationToken = default);

-    public abstract IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
+    public abstract IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
        IReadOnlyCollection<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
        CancellationToken cancellationToken = default);
 }

-class AgentResponse : ChatResponse
+class AgentRunResponse : ChatResponse
 {
 }

-public class AgentResponseUpdate : ChatResponseUpdate
+public class AgentRunResponseUpdate : ChatResponseUpdate
 {
 }
 ```
@@ -265,20 +265,20 @@ The new types could also exclude properties that make less sense for agents, lik
 ```csharp
 class Agent
 {
-    public abstract Task<AgentResponse> RunAsync(
+    public abstract Task<AgentRunResponse> RunAsync(
        IReadOnlyCollection<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
        CancellationToken cancellationToken = default);

-    public abstract IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
+    public abstract IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
        IReadOnlyCollection<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
        CancellationToken cancellationToken = default);
 }

-class AgentResponse // Compare with ChatResponse
+class AgentRunResponse // Compare with ChatResponse
 {
    public string Text { get; } // Aggregation of TextContent from messages.

@@ -294,12 +294,12 @@ class AgentResponse // Compare with ChatResponse
    public AdditionalPropertiesDictionary? AdditionalProperties { get; set; }
 }

-// Not Included in AgentResponse compared to ChatResponse
+// Not Included in AgentRunResponse compared to ChatResponse
 public ChatFinishReason? FinishReason { get; set; }
 public string? ConversationId { get; set; }
 public string? ModelId { get; set; }

-public class AgentResponseUpdate // Compare with ChatResponseUpdate
+public class AgentRunResponseUpdate // Compare with ChatResponseUpdate
 {
    public string Text { get; } // Aggregation of TextContent from Contents.

@@ -317,7 +317,7 @@ public class AgentResponseUpdate // Compare with ChatResponseUpdate
    public AdditionalPropertiesDictionary? AdditionalProperties { get; set; }
 }

-// Not Included in AgentResponseUpdate compared to ChatResponseUpdate
+// Not Included in AgentRunResponseUpdate compared to ChatResponseUpdate
 public ChatFinishReason? FinishReason { get; set; }
 public string? ConversationId { get; set; }
 public string? ModelId { get; set; }
@@ -360,7 +360,7 @@ public class ChatFinishReason
 ### Option 2: Add another property on responses for AgentRun

 ```csharp
-class AgentResponse
+class AgentRunResponse
 {
    ...
    public AgentRun RunReference { get; set; } // Reference to long running process
@@ -368,7 +368,7 @@ class AgentResponse
 }


-public class AgentResponseUpdate
+public class AgentRunResponseUpdate
 {
    ...
    public AgentRun RunReference { get; set; } // Reference to long running process
@@ -424,7 +424,7 @@ Note that where an agent doesn't support structured output, it may also be possi
 See [Structured Outputs Support](#structured-outputs-support) for a comparison on what other agent frameworks and protocols support.

 To support a good user experience for structured outputs, I'm proposing that we follow the pattern used by MEAI.
-We would add a generic version of `AgentResponse<T>`, that allows us to get the agent result already deserialized into our preferred type.
+We would add a generic version of `AgentRunResponse<T>`, that allows us to get the agent result already deserialized into our preferred type.
 This would be coupled with generic overload extension methods for Run that automatically builds a schema from the supplied type and updates
 the run options.

@@ -438,14 +438,14 @@ class Movie
    public int ReleaseYear { get; set; }
 }

-AgentResponse<Movie[]> response = agent.RunAsync<Movie[]>("What are the top 3 children's movies of the 80s.");
+AgentRunResponse<Movie[]> response = agent.RunAsync<Movie[]>("What are the top 3 children's movies of the 80s.");
 Movie[] movies = response.Result
 ```

 If we only support requesting a schema at agent creation time or where an agent has a built in schema, the following would be the preferred approach:

 ```csharp
-AgentResponse response = agent.RunAsync("What are the top 3 children's movies of the 80s.");
+AgentRunResponse response = agent.RunAsync("What are the top 3 children's movies of the 80s.");
 Movie[] movies = response.TryParseStructuredOutput<Movie[]>();
 ```

@@ -463,7 +463,7 @@ Option 2 chosen so that we can vary Agent responses independently of Chat Client
 ### StructuredOutputs Decision

 We will not support structured output per run request, but individual agents are free to allow this on the concrete implementation or at construction time.
-We will however add support for easily extracting a structured output type from the `AgentResponse`.
+We will however add support for easily extracting a structured output type from the `AgentRunResponse`.

 ## Addendum 1: AIContext Derived Types for different response types / Gap Analysis (Work in progress)

@@ -54,7 +54,7 @@ The table below represents the majority of the naming changes discussed in issue
 | *Mcp* & *Http* | *MCP* & *HTTP* | accepted | Acronyms should be uppercased in class names, according to PEP 8. | None |
 | `agent.run_streaming` | `agent.run_stream` | accepted | Shorter and more closely aligns with AutoGen and Semantic Kernel names for the same methods. | None |
 | `workflow.run_streaming` | `workflow.run_stream` | accepted | In sync with `agent.run_stream` and shorter and more closely aligns with AutoGen and Semantic Kernel names for the same methods. | None |
-| AgentResponse & AgentResponseUpdate | AgentResponse & AgentResponseUpdate | rejected | Rejected, because it is the response to a run invocation and AgentResponse is too generic. | None |
+| AgentRunResponse & AgentRunResponseUpdate | AgentResponse & AgentResponseUpdate | rejected | Rejected, because it is the response to a run invocation and AgentResponse is too generic. | None |
 | *Content | * | rejected | Rejected other content type renames (removing `Content` suffix) because it would reduce clarity and discoverability. | Item was also considered, but rejected as it is very similar to Content, but would be inconsistent with dotnet. |
 | ChatResponse & ChatResponseUpdate | Response & ResponseUpdate | rejected | Rejected, because Response is too generic. | None |

@@ -161,11 +161,11 @@ while (response.ApprovalRequests.Count > 0)
    response = await agent.RunAsync(messages, thread);
 }

-class AgentResponse
+class AgentRunResponse
 {
    ...

-    // A new property on AgentResponse to aggregate the ApprovalRequestContent items from
+    // A new property on AgentRunResponse to aggregate the ApprovalRequestContent items from
    // the response messages (Similar to the Text property).
    public IEnumerable<ApprovalRequestContent> ApprovalRequests { get; set; }

@@ -251,11 +251,11 @@ while (response.UserInputRequests.Any())
    response = await agent.RunAsync(messages, thread);
 }

-class AgentResponse
+class AgentRunResponse
 {
    ...

-    // A new property on AgentResponse to aggregate the UserInputRequestContent items from
+    // A new property on AgentRunResponse to aggregate the UserInputRequestContent items from
    // the response messages (Similar to the Text property).
    public IReadOnlyList<UserInputRequestContent> UserInputRequests { get; set; }

@@ -366,11 +366,11 @@ while (response.UserInputRequests.Any())
    response = await agent.RunAsync(messages, thread);
 }

-class AgentResponse
+class AgentRunResponse
 {
    ...

-    // A new property on AgentResponse to aggregate the UserInputRequestContent items from
+    // A new property on AgentRunResponse to aggregate the UserInputRequestContent items from
    // the response messages (Similar to the Text property).
    public IEnumerable<UserInputRequestContent> UserInputRequests { get; set; }

@@ -115,7 +115,7 @@ public class AIAgent
        }
    }

-    public async Task<AgentResponse> RunAsync(
+    public async Task<AgentRunResponse> RunAsync(
        IReadOnlyCollection<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
@@ -135,7 +135,7 @@ public class AIAgent
        return context.Response ?? throw new InvalidOperationException("Agent execution did not produce a response");
    }

-    protected abstract Task<AgentResponse> ExecuteCoreLogicAsync(
+    protected abstract Task<AgentRunResponse> ExecuteCoreLogicAsync(
        IReadOnlyCollection<ChatMessage> messages,
        AgentThread? thread,
        AgentRunOptions? options,
@@ -190,7 +190,7 @@ internal sealed class GuardrailCallbackAgent : DelegatingAIAgent

    public GuardrailCallbackAgent(AIAgent innerAgent) : base(innerAgent) { }

-    public override async Task<AgentResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
+    public override async Task<AgentRunResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
    {
        var filteredMessages = this.FilterMessages(messages);
        Console.WriteLine($"Guardrail Middleware - Filtered messages: {new ChatResponse(filteredMessages).Text}");
@@ -202,14 +202,14 @@ internal sealed class GuardrailCallbackAgent : DelegatingAIAgent
        return response;
    }

-    public override async IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default)
+    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default)
    {
        var filteredMessages = this.FilterMessages(messages);
        await foreach (var update in this.InnerAgent.RunStreamingAsync(filteredMessages, thread, options, cancellationToken))
        {
            if (update.Text != null)
            {
-                yield return new AgentResponseUpdate(update.Role, this.FilterContent(update.Text));
+                yield return new AgentRunResponseUpdate(update.Role, this.FilterContent(update.Text));
            }
            else
            {
@@ -252,7 +252,7 @@ internal sealed class RunningCallbackHandlerAgent : DelegatingAIAgent
        this._func = func;
    }

-    public override async Task<AgentResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
+    public override async Task<AgentRunResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
    {
        var context = new AgentInvokeCallbackContext(this, messages, thread, options, isStreaming: false, cancellationToken);

@@ -469,7 +469,7 @@ public sealed class CallbackEnabledAgent : DelegatingAIAgent
        this._callbacksProcessor = callbackMiddlewareProcessor ?? new();
    }

-    public override async Task<AgentResponse> RunAsync(
+    public override async Task<AgentRunResponse> RunAsync(
        IEnumerable<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
@@ -541,7 +541,7 @@ public abstract class AgentContext
 public class AgentRunContext : AgentContext
 {
    public IList<ChatMessage> Messages { get; set; }
-    public AgentResponse? Response { get; set; }
+    public AgentRunResponse? Response { get; set; }
    public AgentThread? Thread { get; }

    public AgentRunContext(AIAgent agent, IList<ChatMessage> messages, AgentThread? thread, AgentRunOptions? options)
@@ -687,7 +687,7 @@ This section considers different options for exposing the `RunId`, `Status`, and
 #### 4.1. As AIContent

 The `AsyncRunContent` class will represent a long-running operation initiated and managed by an agent/LLM.
-Items of this content type will be returned in a chat message as part of the `AgentResponse` or `ChatResponse`
+Items of this content type will be returned in a chat message as part of the `AgentRunResponse` or `ChatResponse`
 response to represent the long-running operation.

 The `AsyncRunContent` class has two properties: `RunId` and `Status`. The `RunId` identifies the 
@@ -1162,29 +1162,29 @@ For cancellation and deletion of long-running operations, new methods will be ad
 public abstract class AIAgent
 {
    // Existing methods...
-    public Task<AgentResponse> RunAsync(string message, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) { ... }
-    public IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(string message, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) { ... }
+    public Task<AgentRunResponse> RunAsync(string message, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) { ... }
+    public IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(string message, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) { ... }

    // New methods for uncommon operations
-    public virtual Task<AgentResponse?> CancelRunAsync(string id, AgentCancelRunOptions? options = null, CancellationToken cancellationToken = default)
+    public virtual Task<AgentRunResponse?> CancelRunAsync(string id, AgentCancelRunOptions? options = null, CancellationToken cancellationToken = default)
    {
-        return Task.FromResult<AgentResponse?>(null);
+        return Task.FromResult<AgentRunResponse?>(null);
    }

-    public virtual Task<AgentResponse?> DeleteRunAsync(string id, AgentDeleteRunOptions? options = null, CancellationToken cancellationToken = default)
+    public virtual Task<AgentRunResponse?> DeleteRunAsync(string id, AgentDeleteRunOptions? options = null, CancellationToken cancellationToken = default)
    {
-        return Task.FromResult<AgentResponse?>(null);
+        return Task.FromResult<AgentRunResponse?>(null);
    }
 }

 // Agent that supports update and cancellation
 public class CustomAgent : AIAgent
 {
-    public override async Task<AgentResponse?> CancelRunAsync(string id, AgentCancelRunOptions? options = null, CancellationToken cancellationToken = default)
+    public override async Task<AgentRunResponse?> CancelRunAsync(string id, AgentCancelRunOptions? options = null, CancellationToken cancellationToken = default)
    {
        var response = await this._client.CancelRunAsync(id, options?.Thread?.ConversationId);

-        return ConvertToAgentResponse(response); 
+        return ConvertToAgentRunResponse(response); 
    }

    // No overload for DeleteRunAsync as it's not supported by the underlying API
@@ -1195,7 +1195,7 @@ AIAgent agent = new CustomAgent();

 AgentThread thread = agent.GetNewThread();

-AgentResponse response = await agent.RunAsync("What is the capital of France?");
+AgentRunResponse response = await agent.RunAsync("What is the capital of France?");

 response = await agent.CancelRunAsync(response.ResponseId, new AgentCancelRunOptions { Thread = thread });
 ```
@@ -1251,10 +1251,10 @@ public class AgentRunOptions
 AIAgent agent = ...; // Get an instance of an AIAgent

 // Start a long-running execution for the prompt if supported by the underlying API
-AgentResponse response = await agent.RunAsync("<prompt>", new AgentRunOptions { AllowLongRunningResponses = true });
+AgentRunResponse response = await agent.RunAsync("<prompt>", new AgentRunOptions { AllowLongRunningResponses = true });

 // Start a quick prompt
-AgentResponse response = await agent.RunAsync("<prompt>");
+AgentRunResponse response = await agent.RunAsync("<prompt>");
 ```

 **Pros:** 
@@ -1279,7 +1279,7 @@ Below are the details of the option selected for chat clients that is also selec
 #### 3.1 Continuation Token of a Custom Type

 This option suggests using `ContinuationToken` to encapsulate all properties representing a long-running operation. The continuation token will be returned by agents in the 
-`ContinuationToken` property of the `AgentResponse` and `AgentResponseUpdate` responses to indicate that the response is part of a long-running operation. A null value 
+`ContinuationToken` property of the `AgentRunResponse` and `AgentRunResponseUpdate` responses to indicate that the response is part of a long-running operation. A null value 
 of the property will indicate that the response is not part of a long-running operation or the long-running operation has been completed. Callers will set the token in the
 `ContinuationToken` property of the `AgentRunOptions` class in follow-up calls to the `Run{Streaming}Async` methods to indicate that they want to "continue" the long-running
 operation identified by the token.
@@ -1313,18 +1313,18 @@ public class AgentRunOptions
    public ResponseContinuationToken? ContinuationToken { get; set; }
 }

-public class AgentResponse
+public class AgentRunResponse
 {
    public ResponseContinuationToken? ContinuationToken { get; }
 }
 
-public class AgentResponseUpdate
+public class AgentRunResponseUpdate
 {
    public ResponseContinuationToken? ContinuationToken { get; }
 }

 // Usage example
-AgentResponse response = await agent.RunAsync("What is the capital of France?");
+AgentRunResponse response = await agent.RunAsync("What is the capital of France?");

 AgentRunOptions options = new() { ContinuationToken = response.ContinuationToken };

@@ -36,7 +36,7 @@ Chosen option: "Current approach with internal event types and framework-native

 - Protects consumers from protocol changes by keeping AG-UI events internal
 - Maintains framework abstractions through conversion at boundaries
- Uses existing framework types (AgentResponseUpdate, ChatMessage) for public API
+- Uses existing framework types (AgentRunResponseUpdate, ChatMessage) for public API
 - Focuses on core text streaming functionality
 - Leverages existing properties (ConversationId, ResponseId, ErrorContent) instead of custom types
 - Provides bidirectional client and server support
@@ -69,7 +69,7 @@ Chosen option: "Current approach with internal event types and framework-native

 3. **Agent Factory Pattern** - `MapAGUIAgent` uses factory function `(messages) => AIAgent` to allow request-specific agent configuration supporting multi-tenancy

-4. **Bidirectional Conversion Architecture** - Symmetric conversion logic in shared namespace compiled into both packages for server (`AgentResponseUpdate` → AG-UI events) and client (AG-UI events → `AgentResponseUpdate`)
+4. **Bidirectional Conversion Architecture** - Symmetric conversion logic in shared namespace compiled into both packages for server (`AgentRunResponseUpdate` → AG-UI events) and client (AG-UI events → `AgentRunResponseUpdate`)

 5. **Thread Management** - `AGUIAgentThread` stores only `ThreadId` with thread ID communicated via `ConversationId`; applications manage persistence for parity with other implementations and to be compliant with the protocol. Future extensions will support having the server manage the conversation.

@@ -1,368 +0,0 @@
---
-status: proposed
-contact: dmytrostruk
-date: 2025-12-12
-deciders: dmytrostruk, markwallace-microsoft, eavanvalkenburg, giles17
---
-
-# Create/Get Agent API
-
-## Context and Problem Statement
-
-There is a misalignment between the create/get agent API in the .NET and Python implementations.
-
-In .NET, the `CreateAIAgent` method can create either a local instance of an agent or a remote instance if the backend provider supports it. For remote agents, once the agent is created, you can retrieve an existing remote agent by using the `GetAIAgent` method. If a backend provider doesn't support remote agents, `CreateAIAgent` just initializes a new local agent instance and `GetAIAgent` is not available. There is also a `BuildAIAgent` method, which is an extension for the `ChatClientBuilder` class from `Microsoft.Extensions.AI`. It builds pipelines of `IChatClient` instances with an `IServiceProvider`. This functionality does not exist in Python, so `BuildAIAgent` is out of scope.
-
-In Python, there is only one `create_agent` method, which always creates a local instance of the agent. If the backend provider supports remote agents, the remote agent is created only on the first `agent.run()` invocation.
-
-Below is a short summary of different providers and their APIs in .NET:
-
-| Package | Method | Behavior | Python support |
-|---|---|---|---|
-| Microsoft.Agents.AI | `CreateAIAgent` (based on `IChatClient`) | Creates a local instance of `ChatClientAgent`. | Yes (`create_agent` in `BaseChatClient`). |
-| Microsoft.Agents.AI.Anthropic | `CreateAIAgent` (based on `IBetaService` and `IAnthropicClient`) | Creates a local instance of `ChatClientAgent`. | Yes (`AnthropicClient` inherits `BaseChatClient`, which exposes `create_agent`). |
-| Microsoft.Agents.AI.AzureAI (V2) | `GetAIAgent` (based on `AIProjectClient` with `AgentReference`) | Creates a local instance of `ChatClientAgent`. | Partial (Python uses `create_agent` from `BaseChatClient`). |
-| Microsoft.Agents.AI.AzureAI (V2) | `GetAIAgent`/`GetAIAgentAsync` (with `Name`/`ChatClientAgentOptions`) | Fetches `AgentRecord` via HTTP, then creates a local `ChatClientAgent` instance. | No |
-| Microsoft.Agents.AI.AzureAI (V2) | `CreateAIAgent`/`CreateAIAgentAsync` (based on `AIProjectClient`) | Creates a remote agent first, then wraps it into a local `ChatClientAgent` instance. | No |
-| Microsoft.Agents.AI.AzureAI.Persistent (V1) | `GetAIAgent` (based on `PersistentAgentsClient` with `PersistentAgent`) | Creates a local instance of `ChatClientAgent`. | Partial (Python uses `create_agent` from `BaseChatClient`). |
-| Microsoft.Agents.AI.AzureAI.Persistent (V1) | `GetAIAgent`/`GetAIAgentAsync` (with `AgentId`) | Fetches `PersistentAgent` via HTTP, then creates a local `ChatClientAgent` instance. | No |
-| Microsoft.Agents.AI.AzureAI.Persistent (V1) | `CreateAIAgent`/`CreateAIAgentAsync` | Creates a remote agent first, then wraps it into a local `ChatClientAgent` instance. | No |
-| Microsoft.Agents.AI.OpenAI | `GetAIAgent` (based on `AssistantClient` with `Assistant`) | Creates a local instance of `ChatClientAgent`. | Partial (Python uses `create_agent` from `BaseChatClient`). |
-| Microsoft.Agents.AI.OpenAI | `GetAIAgent`/`GetAIAgentAsync` (with `AgentId`) | Fetches `Assistant` via HTTP, then creates a local `ChatClientAgent` instance. | No |
-| Microsoft.Agents.AI.OpenAI | `CreateAIAgent`/`CreateAIAgentAsync` (based on `AssistantClient`) | Creates a remote agent first, then wraps it into a local `ChatClientAgent` instance. | No |
-| Microsoft.Agents.AI.OpenAI | `CreateAIAgent` (based on `ChatClient`) | Creates a local instance of `ChatClientAgent`. | Yes (`create_agent` in `BaseChatClient`). |
-| Microsoft.Agents.AI.OpenAI | `CreateAIAgent` (based on `OpenAIResponseClient`) | Creates a local instance of `ChatClientAgent`. | Yes (`create_agent` in `BaseChatClient`). |
-
-Another difference between Python and .NET implementation is that in .NET `CreateAIAgent`/`GetAIAgent` methods are implemented as extension methods based on underlying SDK client, like `AIProjectClient` from Azure AI or `AssistantClient` from OpenAI:
-
-```csharp
-// Definition
-public static ChatClientAgent CreateAIAgent(
-    this AIProjectClient aiProjectClient,
-    string name,
-    string model,
-    string instructions,
-    string? description = null,
-    IList<AITool>? tools = null,
-    Func<IChatClient, IChatClient>? clientFactory = null,
-    IServiceProvider? services = null,
-    CancellationToken cancellationToken = default)
-{ }
-
-// Usage
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential()); // Initialization of underlying SDK client
-
-var newAgent = await aiProjectClient.CreateAIAgentAsync(name: AgentName, model: deploymentName, instructions: AgentInstructions, tools: [tool]); // ChatClientAgent creation from underlying SDK client
-
-// Alternative usage (same as extension method, just explicit syntax)
-var newAgent = await AzureAIProjectChatClientExtensions.CreateAIAgentAsync(
-    aiProjectClient,
-    name: AgentName,
-    model: deploymentName,
-    instructions: AgentInstructions,
-    tools: [tool]);
-```
-
-Python doesn't support extension methods. Currently `create_agent` method is defined on `BaseChatClient`, but this method only creates a local instance of `ChatAgent` and it can't create remote agents for providers that support it for a couple of reasons:
-
- It's defined as non-async.
- `BaseChatClient` implementation is stateful for providers like Azure AI or OpenAI Assistants. The implementation stores agent/assistant metadata like `AgentId` and `AgentName`, so currently it's not possible to create different instances of `ChatAgent` from a single `BaseChatClient` in case if the implementation is stateful.
-
-## Decision Drivers
-
- API should be aligned between .NET and Python.
- API should be intuitive and consistent between backend providers in .NET and Python.
-
-## Considered Options
-
-Add missing implementations on the Python side. This should include the following:
-
-### agent-framework-azure-ai (both V1 and V2)
-
- Add a `get_agent` method that accepts an underlying SDK agent instance and creates a local instance of `ChatAgent`.
- Add a `get_agent` method that accepts an agent identifier, performs an additional HTTP request to fetch agent data, and then creates a local instance of `ChatAgent`.
- Override the `create_agent` method from `BaseChatClient` to create a remote agent instance and wrap it into a local `ChatAgent`.
-
-.NET:
-
-```csharp
-var agent1 = new AIProjectClient(...).GetAIAgent(agentInstanceFromSdkType); // Creates a local ChatClientAgent instance from Azure.AI.Projects.OpenAI.AgentReference 
-var agent2 = new AIProjectClient(...).GetAIAgent(agentName); // Fetches agent data, creates a local ChatClientAgent instance
-var agent3 = new AIProjectClient(...).CreateAIAgent(...); // Creates a remote agent, returns a local ChatClientAgent instance
-```
-
-### agent-framework-core (OpenAI Assistants)
-
- Add a `get_agent` method that accepts an underlying SDK agent instance and creates a local instance of `ChatAgent`.
- Add a `get_agent` method that accepts an agent name, performs an additional HTTP request to fetch agent data, and then creates a local instance of `ChatAgent`.
- Override the `create_agent` method from `BaseChatClient` to create a remote agent instance and wrap it into a local `ChatAgent`.
-
-.NET:
-
-```csharp
-var agent1 = new AssistantClient(...).GetAIAgent(agentInstanceFromSdkType); // Creates a local ChatClientAgent instance from OpenAI.Assistants.Assistant
-var agent2 = new AssistantClient(...).GetAIAgent(agentId); // Fetches agent data, creates a local ChatClientAgent instance
-var agent3 = new AssistantClient(...).CreateAIAgent(...); // Creates a remote agent, returns a local ChatClientAgent instance
-```
-
-### Possible Python implementations
-
-Methods like `create_agent` and `get_agent` should be implemented separately or defined on some stateless component that will allow to create multiple agents from the same instance/place.
-
-Possible options:
-
-#### Option 1: Module-level functions
-
-Implement free functions in the provider package that accept the underlying SDK client as the first argument (similar to .NET extension methods, but expressed in Python).
-
-Example:
-
-```python
-from agent_framework.azure import create_agent, get_agent
-
-ai_project_client = AIProjectClient(...)
-
-# Creates a remote agent first, then returns a local ChatAgent wrapper
-created_agent = await create_agent(
-    ai_project_client,
-    name="",
-    instructions="",
-    tools=[tool],
-)
-
-# Gets an existing remote agent and returns a local ChatAgent wrapper
-first_agent = await get_agent(ai_project_client, agent_id=agent_id)
-
-# Wraps an SDK agent instance (no extra HTTP call)
-second_agent = get_agent(ai_project_client, agent_reference)
-```
-
-Pros:
-
- Naturally supports async `create_agent` / `get_agent`.
- Supports multiple agents per SDK client.
- Closest conceptual match to .NET extension methods while staying Pythonic.
-
-Cons:
-
- Discoverability is lower (users need to know where the functions live).
- Verbose when creating multiple agents (client must be passed every time):
-
-  ```python
-  agent1 = await azure_agents.create_agent(client, name="Agent1", ...)
-  agent2 = await azure_agents.create_agent(client, name="Agent2", ...)
-  ```
-
-#### Option 2: Provider object
-
-Introduce a dedicated provider type that is constructed from the underlying SDK client, and exposes async `create_agent` / `get_agent` methods.
-
-Example:
-
-```python
-from agent_framework.azure import AzureAIAgentProvider
-
-ai_project_client = AIProjectClient(...)
-provider = AzureAIAgentProvider(ai_project_client)
-
-agent = await provider.create_agent(
-    name="",
-    instructions="",
-    tools=[tool],
-)
-
-agent = await provider.get_agent(agent_id=agent_id)
-agent = provider.get_agent(agent_reference=agent_reference)
-```
-
-Pros:
-
- High discoverability and clear grouping of related behavior.
- Keeps SDK clients unchanged and supports multiple agents per SDK client.
- Concise when creating multiple agents (client passed once):
-
-  ```python
-  provider = AzureAIAgentProvider(ai_project_client)
-  agent1 = await provider.create_agent(name="Agent1", ...)
-  agent2 = await provider.create_agent(name="Agent2", ...)
-  ```
-
-Cons:
-
- Adds a new public concept/type for users to learn.
-
-#### Option 3: Inheritance (SDK client subclass)
-
-Create a subclass of the underlying SDK client and add `create_agent` / `get_agent` methods.
-
-Example:
-
-```python
-class ExtendedAIProjectClient(AIProjectClient):
-    async def create_agent(self, *, name: str, model: str, instructions: str, **kwargs) -> ChatAgent:
-        ...
-
-    async def get_agent(self, *, agent_id: str | None = None, sdk_agent=None, **kwargs) -> ChatAgent:
-        ...
-
-client = ExtendedAIProjectClient(...)
-agent = await client.create_agent(name="", instructions="")
-```
-
-Pros:
-
- Discoverable and ergonomic call sites.
- Mirrors the .NET “methods on the client” feeling.
-
-Cons:
-
- Many SDK clients are not designed for inheritance; SDK upgrades can break subclasses.
- Users must opt into subclass everywhere.
- Typing/initialization can be tricky if the SDK client has non-trivial constructors.
-
-#### Option 4: Monkey patching
-
-Attach `create_agent` / `get_agent` methods to an SDK client class (or instance) at runtime.
-
-Example:
-
-```python
-def _create_agent(self, *, name: str, model: str, instructions: str, **kwargs) -> ChatAgent:
-    ...
-
-AIProjectClient.create_agent = _create_agent  # monkey patch
-```
-
-Pros:
-
- Produces “extension method-like” call sites without wrappers or subclasses.
-
-Cons:
-
- Fragile across SDK updates and difficult to type-check.
- Surprising behavior (global side effects), potential conflicts across packages.
- Harder to support/debug, especially in larger apps and test suites.
-
-## Decision Outcome
-
-Implement `create_agent`/`get_agent`/`as_agent` API via **Option 2: Provider object**.
-
-### Rationale
-
-| Aspect | Option 1 (Functions) | Option 2 (Provider) |
-|--------|----------------------|---------------------|
-| Multiple implementations | One package may contain V1, V2, and other agent types. Function names like `create_agent` become ambiguous - which agent type does it create? | Each provider class is explicit: `AzureAIAgentsProvider` vs `AzureAIProjectAgentProvider` |
-| Discoverability | Users must know to import specific functions from the package | IDE autocomplete on provider instance shows all available methods |
-| Client reuse | SDK client must be passed to every function call: `create_agent(client, ...)`, `get_agent(client, ...)` | SDK client passed once at construction: `provider = Provider(client)` |
-
-**Option 1 example:**
-```python
-from agent_framework.azure import create_agent, get_agent
-agent1 = await create_agent(client, name="Agent1", ...)  # Which agent type, V1 or V2?
-agent2 = await create_agent(client, name="Agent2", ...)  # Repetitive client passing
-```
-
-**Option 2 example:**
-```python
-from agent_framework.azure import AzureAIProjectAgentProvider
-provider = AzureAIProjectAgentProvider(client)  # Clear which service, client passed once
-agent1 = await provider.create_agent(name="Agent1", ...)
-agent2 = await provider.create_agent(name="Agent2", ...)
-```
-
-### Method Naming
-
-| Operation | Python | .NET | Async |
-|-----------|--------|------|-------|
-| Create on service | `create_agent()` | `CreateAIAgent()` | Yes |
-| Get from service | `get_agent(id=...)` | `GetAIAgent(agentId)` | Yes |
-| Wrap SDK object | `as_agent(reference)` | `AsAIAgent(agentInstance)` | No |
-
-The method names (`create_agent`, `get_agent`) do not explicitly mention "service" or "remote" because:
- In Python, the provider class name explicitly identifies the service (`AzureAIAgentsProvider`, `OpenAIAssistantProvider`), making additional qualifiers in method names redundant.
- In .NET, these are extension methods on `AIProjectClient` or `AssistantClient`, which already imply service operations.
-
-### Provider Class Naming
-
-| Package | Provider Class | SDK Client | Service |
-|---------|---------------|------------|---------|
-| `agent_framework.azure` | `AzureAIProjectAgentProvider` | `AIProjectClient` | Azure AI Agent Service, based on Responses API (V2) |
-| `agent_framework.azure` | `AzureAIAgentsProvider` | `AgentsClient` | Azure AI Agent Service (V1) |
-| `agent_framework.openai` | `OpenAIAssistantProvider` | `AsyncOpenAI` | OpenAI Assistants API |
-
-> **Note:** Azure AI naming is temporary. Final naming will be updated according to Azure AI / Microsoft Foundry renaming decisions.
-
-### Usage Examples
-
-#### Azure AI Agent Service V2 (based on Responses API)
-
-```python
-from agent_framework.azure import AzureAIProjectAgentProvider
-from azure.ai.projects import AIProjectClient
-
-client = AIProjectClient(endpoint, credential)
-provider = AzureAIProjectAgentProvider(client)
-
-# Create new agent on service
-agent = await provider.create_agent(name="MyAgent", model="gpt-4", instructions="...")
-
-# Get existing agent by name
-agent = await provider.get_agent(agent_name="MyAgent")
-
-# Wrap already-fetched SDK object (no HTTP calls)
-agent_ref = await client.agents.get("MyAgent")
-agent = provider.as_agent(agent_ref)
-```
-
-#### Azure AI Persistent Agents V1
-
-```python
-from agent_framework.azure import AzureAIAgentsProvider
-from azure.ai.agents import AgentsClient
-
-client = AgentsClient(endpoint, credential)
-provider = AzureAIAgentsProvider(client)
-
-agent = await provider.create_agent(name="MyAgent", model="gpt-4", instructions="...")
-agent = await provider.get_agent(agent_id="persistent-agent-456")
-agent = provider.as_agent(persistent_agent)
-```
-
-#### OpenAI Assistants
-
-```python
-from agent_framework.openai import OpenAIAssistantProvider
-from openai import OpenAI
-
-client = OpenAI()
-provider = OpenAIAssistantProvider(client)
-
-agent = await provider.create_agent(name="MyAssistant", model="gpt-4", instructions="...")
-agent = await provider.get_agent(assistant_id="asst_123")
-agent = provider.as_agent(assistant)
-```
-
-#### Local-Only Agents (No Provider)
-
-Current method `create_agent` (python) / `CreateAIAgent` (.NET) can be renamed to `as_agent` (python) / `AsAIAgent` (.NET) to emphasize the conversion logic rather than creation/initialization logic and to avoid collision with `create_agent` method for remote calls.
-
-```python
-from agent_framework import ChatAgent
-from agent_framework.openai import OpenAIChatClient
-
-# Convert chat client to ChatAgent (no remote service involved)
-client = OpenAIChatClient(model="gpt-4")
-agent = client.as_agent(name="LocalAgent", instructions="...") # instead of create_agent
-```
-
-### Adding New Agent Types
-
-Python:
-
-1. Create provider class in appropriate package.
-2. Implement `create_agent`, `get_agent`, `as_agent` as applicable.
-
-.NET:
-
-1. Create static class for extension methods.
-2. Implement `CreateAIAgentAsync`, `GetAIAgentAsync`, `AsAIAgent` as applicable.
@@ -1,129 +0,0 @@
---
-# These are optional elements. Feel free to remove any of them.
-status: proposed
-contact: eavanvalkenburg
-date: 2026-01-08
-deciders: eavanvalkenburg, markwallace-microsoft,  sphenry, alliscode, johanst, brettcannon
-consulted: taochenosu, moonbox3, dmytrostruk, giles17
---
-
-# Leveraging TypedDict and Generic Options in Python Chat Clients
-
-## Context and Problem Statement
-
-The Agent Framework Python SDK provides multiple chat client implementations for different providers (OpenAI, Anthropic, Azure AI, Bedrock, Ollama, etc.). Each provider has unique configuration options beyond the common parameters defined in `ChatOptions`. Currently, developers using these clients lack type safety and IDE autocompletion for provider-specific options, leading to runtime errors and a poor developer experience.
-
-How can we provide type-safe, discoverable options for each chat client while maintaining a consistent API across all implementations?
-
-## Decision Drivers
-
- **Type Safety**: Developers should get compile-time/static analysis errors when using invalid options
- **IDE Support**: Full autocompletion and inline documentation for all available options
- **Extensibility**: Users should be able to define custom options that extend provider-specific options
- **Consistency**: All chat clients should follow the same pattern for options handling
- **Provider Flexibility**: Each provider can expose its unique options without affecting the common interface
-
-## Considered Options
-
- **Option 1: Status Quo - Class `ChatOptions` with `**kwargs`**
- **Option 2: TypedDict with Generic Type Parameters**
-
-### Option 1: Status Quo - Class `ChatOptions` with `**kwargs`
-
-The current approach uses a base `ChatOptions` Class with common parameters, and provider-specific options are passed via `**kwargs` or loosely typed dictionaries.
-
-```python
-# Current usage - no type safety for provider-specific options
-response = await client.get_response(
-    messages=messages,
-    temperature=0.7,
-    top_k=40,
-    random=42, # No validation
-)
-```
-
-**Pros:**
- Simple implementation
- Maximum flexibility
-
-**Cons:**
- No type checking for provider-specific options
- No IDE autocompletion for available options
- Runtime errors for typos or invalid options
- Documentation must be consulted for each provider
-
-### Option 2: TypedDict with Generic Type Parameters (Chosen)
-
-Each chat client is parameterized with a TypeVar bound to a provider-specific `TypedDict` that extends `ChatOptions`. This enables full type safety and IDE support.
-
-```python
-# Provider-specific TypedDict
-class AnthropicChatOptions(ChatOptions, total=False):
-    """Anthropic-specific chat options."""
-    top_k: int
-    thinking: ThinkingConfig
-    # ... other Anthropic-specific options
-
-# Generic chat client
-class AnthropicChatClient(ChatClientBase[TAnthropicChatOptions]):
-    ...
-
-client = AnthropicChatClient(...)
-
-# Usage with full type safety
-response = await client.get_response(
-    messages=messages,
-    options={
-        "temperature": 0.7,
-        "top_k": 40,
-        "random": 42,  # fails type checking and IDE would flag this
-    }
-)
-
-# Users can extend for custom options
-class MyAnthropicOptions(AnthropicChatOptions, total=False):
-    custom_field: str
-
-
-client = AnthropicChatClient[MyAnthropicOptions](...)
-
-# Usage of custom options with full type safety
-response = await client.get_response(
-    messages=messages,
-    options={
-        "temperature": 0.7,
-        "top_k": 40,
-        "custom_field": "value",
-    }
-)
-
-```
-
-**Pros:**
- Full type safety with static analysis
- IDE autocompletion for all options
- Compile-time error detection
- Self-documenting through type hints
- Users can extend options for their specific needs or advances in models
-
-**Cons:**
- More complex implementation
- Some type: ignore comments needed for TypedDict field overrides
- Minor: Requires TypeVar with default (Python 3.13+ or typing_extensions)
-
-> [NOTE!]
-> In .NET this is already achieved through overloads on the `GetResponseAsync` method for each provider-specific options class, e.g., `AnthropicChatOptions`, `OpenAIChatOptions`, etc. So this does not apply to .NET.
-
-### Implementation Details
-
-1. **Base Protocol**: `ChatClientProtocol[TOptions]` is generic over options type, with default set to `ChatOptions` (the new TypedDict)
-2. **Provider TypedDicts**: Each provider defines its options extending `ChatOptions`
-    They can even override fields with type=None to indicate they are not supported.
-3. **TypeVar Pattern**: `TProviderOptions = TypeVar("TProviderOptions", bound=TypedDict, default=ProviderChatOptions, contravariant=True)`
-4. **Option Translation**: Common options are kept in place,and explicitly documented in the Options class how they are used. (e.g., `user` → `metadata.user_id`) in `_prepare_options` (for Anthropic) to preserve easy use of common options.
-
-## Decision Outcome
-
-Chosen option: **"Option 2: TypedDict with Generic Type Parameters"**, because it provides full type safety, excellent IDE support with autocompletion, and allows users to extend provider-specific options for their use cases. Extended this Generic to ChatAgents in order to also properly type the options used in agent construction and run methods.
-
-See [typed_options.py](../../python/samples/getting_started/chat_client/typed_options.py) for a complete example demonstrating the usage of typed options with custom extensions.
@@ -1,258 +0,0 @@
---
-status: Accepted
-contact: eavanvalkenburg
-date: 2026-01-06
-deciders: markwallace-microsoft, dmytrostruk, taochenosu, alliscode, moonbox3, sphenry
-consulted: sergeymenshykh, rbarreto, dmytrostruk, westey-m
-informed:
---
-
-# Simplify Python Get Response API into a single method
-
-## Context and Problem Statement
-
-Currently chat clients must implement two separate methods to get responses, one for streaming and one for non-streaming. This adds complexity to the client implementations and increases the maintenance burden. This was likely done because the .NET version cannot do proper typing with a single method, in Python this is possible and this for instance is also how the OpenAI python client works, this would then also make it simpler to work with the Python version because there is only one method to learn about instead of two.
-
-## Implications of this change
-
-### Current Architecture Overview
-
-The current design has **two separate methods** at each layer:
-
-| Layer | Non-streaming | Streaming |
-|-------|---------------|-----------|
-| **Protocol** | `get_response()` → `ChatResponse` | `get_streaming_response()` → `AsyncIterable[ChatResponseUpdate]` |
-| **BaseChatClient** | `get_response()` (public) | `get_streaming_response()` (public) |
-| **Implementation** | `_inner_get_response()` (private) | `_inner_get_streaming_response()` (private) |
-
-### Key Usage Areas Identified
-
-#### 1. **ChatAgent** (_agents.py)
- `run()` → calls `self.chat_client.get_response()`
- `run_stream()` → calls `self.chat_client.get_streaming_response()`
-
-These are parallel methods on the agent, so consolidating the client methods would **not break** the agent API. You could keep `agent.run()` and `agent.run_stream()` unchanged while internally calling `get_response(stream=True/False)`.
-
-#### 2. **Function Invocation Decorator** (_tools.py)
-This is **the most impacted area**. Currently:
- `_handle_function_calls_response()` decorates `get_response`
- `_handle_function_calls_streaming_response()` decorates `get_streaming_response`
- The `use_function_invocation` class decorator wraps **both methods separately**
-
-**Impact**: The decorator logic is almost identical (~200 lines each) with small differences:
- Non-streaming collects response, returns it
- Streaming yields updates, returns async iterable
-
-With a unified method, you'd need **one decorator** that:
- Checks the `stream` parameter
- Uses `@overload` to determine return type
- Handles both paths with conditional logic
- The new decorator could be applied just on the method, instead of the whole class.
-
-This would **reduce code duplication** but add complexity to a single function.
-
-#### 3. **Observability/Instrumentation** (observability.py)
-Same pattern as function invocation:
- `_trace_get_response()` wraps `get_response`
- `_trace_get_streaming_response()` wraps `get_streaming_response`
- `use_instrumentation` decorator applies both
-
-**Impact**: Would need consolidation into a single tracing wrapper.
-
-#### 4. **Chat Middleware** (_middleware.py)
-The `use_chat_middleware` decorator also wraps both methods separately with similar logic.
-
-#### 5. **AG-UI Client** (_client.py)
-Wraps both methods to unwrap server function calls:
-```python
-original_get_streaming_response = chat_client.get_streaming_response
-original_get_response = chat_client.get_response
-```
-
-#### 6. **Provider Implementations** (all subpackages)
-All subclasses implement both `_inner_*` methods, except:
- OpenAI Assistants Client (and similar clients, such as Foundry Agents V1) - it implements `_inner_get_response` by calling `_inner_get_streaming_response`
-
-### Implications of Consolidation
-
-| Aspect | Impact |
-|--------|--------|
-| **Type Safety** | Overloads work well: `@overload` with `Literal[True]` → `AsyncIterable`, `Literal[False]` → `ChatResponse`. Runtime return type based on `stream` param. |
-| **Breaking Change** | **Major breaking change** for anyone implementing custom chat clients. They'd need to update from 2 methods to 1 (or 2 inner methods to 1). |
-| **Decorator Complexity** | All 3 decorator systems (function invocation, middleware, observability) would need refactoring to handle both paths in one wrapper. |
-| **Code Reduction** | Significant reduction in _tools.py (~200 lines of near-duplicate code) and other decorators. |
-| **Samples/Tests** | Many samples call `get_streaming_response()` directly - would need updates. |
-| **Protocol Simplification** | `ChatClientProtocol` goes from 2 methods + 1 property to 1 method + 1 property. |
-
-### Recommendation
-
-The consolidation makes sense architecturally, but consider:
-
-1. **The overload pattern with `stream: bool`** works well in Python typing:
-   ```python
-   @overload
-   async def get_response(self, messages, *, stream: Literal[True] = True, ...) -> AsyncIterable[ChatResponseUpdate]: ...
-   @overload
-   async def get_response(self, messages, *, stream: Literal[False] = False, ...) -> ChatResponse: ...
-   ```
-
-2. **The decorator complexity** is the biggest concern. The current approach of separate decorators for separate methods is cleaner than conditional logic inside one wrapper.
-
-## Decision Drivers
-
- Reduce code needed to implement a Chat Client, simplify the public API for chat clients
- Reduce code duplication in decorators and middleware
- Maintain type safety and clarity in method signatures
-
-## Considered Options
-
-1. Status quo: Keep separate methods for streaming and non-streaming
-2. Consolidate into a single `get_response` method with a `stream` parameter
-3. Option 2 plus merging `agent.run` and `agent.run_stream` into a single method with a `stream` parameter as well
-
-## Option 1: Status Quo
- Good: Clear separation of streaming vs non-streaming logic
- Good: Aligned with .NET design, although it is already `run` for Python and `RunAsync` for .NET
- Bad: Code duplication in decorators and middleware
- Bad: More complex client implementations
-
-## Option 2: Consolidate into Single Method
- Good: Simplified public API for chat clients
- Good: Reduced code duplication in decorators
- Good: Smaller API footprint for users to get familiar with
- Good: People using OpenAI directly already expect this pattern
- Bad: Increased complexity in decorators and middleware
- Bad: Less alignment with .NET design (`get_response(stream=True)` vs `GetStreamingResponseAsync`)
-
-## Option 3: Consolidate + Merge Agent and Workflow Methods
- Good: Further simplifies agent and workflow implementation
- Good: Single method for all chat interactions
- Good: Smaller API footprint for users to get familiar with
- Good: People using OpenAI directly already expect this pattern
- Good: Workflows internally already use a single method (_run_workflow_with_tracing), so would eliminate public API duplication as well, with hardly any code changes
- Bad: More breaking changes for agent users
- Bad: Increased complexity in agent implementation
- Bad: More extensive misalignment with .NET design (`run(stream=True)` vs `RunStreamingAsync` in addition to `get_response` change)
-
-## Misc
-
-Smaller questions to consider:
- Should default be `stream=False` or `stream=True`? (Current is False)
-    - Default to `False` makes it simpler for new users, as non-streaming is easier to handle.
-    - Default to `False` aligns with existing behavior.
-    - Streaming tends to be faster, so defaulting to `True` could improve performance for common use cases.
-    - Should this differ between ChatClient, Agent and Workflows? (e.g., Agent and Workflow defaults to streaming, ChatClient to non-streaming)
-
-## Decision Outcome
-
-Chosen Option: **Option 3: Consolidate + Merge Agent and Workflow Methods**
-
-Since this is the most pythonic option and it reduces the API surface and code duplication the most, we will go with this option.
-We will keep the default of `stream=False` for all methods to maintain backward compatibility and simplicity for new users.
-
-# Appendix
-## Code Samples for Consolidated Method
-
-### Python - Option 3: Direct ChatClient + Agent with Single Method
-
-```python
-# Copyright (c) Microsoft. All rights reserved.
-
-import asyncio
-from random import randint
-from typing import Annotated
-
-from agent_framework import ChatAgent
-from agent_framework.openai import OpenAIChatClient
-from pydantic import Field
-
-
-def get_weather(
-    location: Annotated[str, Field(description="The location to get the weather for.")],
-) -> str:
-    """Get the weather for a given location."""
-    conditions = ["sunny", "cloudy", "rainy", "stormy"]
-    return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
-
-
-async def main() -> None:
-    # Example 1: Direct ChatClient usage with single method
-    client = OpenAIChatClient()
-    message = "What's the weather in Amsterdam and in Paris?"
-
-    # Non-streaming usage
-    print(f"User: {message}")
-    response = await client.get_response(message, tools=get_weather)
-    print(f"Assistant: {response.text}")
-
-    # Streaming usage - same method, different parameter
-    print(f"\nUser: {message}")
-    print("Assistant: ", end="")
-    async for chunk in client.get_response(message, tools=get_weather, stream=True):
-        if chunk.text:
-            print(chunk.text, end="")
-    print("")
-
-    # Example 2: Agent usage with single method
-    agent = ChatAgent(
-        chat_client=client,
-        tools=get_weather,
-        name="WeatherAgent",
-        instructions="You are a weather assistant.",
-    )
-    thread = agent.get_new_thread()
-
-    # Non-streaming agent
-    print(f"\nUser: {message}")
-    result = await agent.run(message, thread=thread) # default would be stream=False
-    print(f"{agent.name}: {result.text}")
-
-    # Streaming agent - same method, different parameter
-    print(f"\nUser: {message}")
-    print(f"{agent.name}: ", end="")
-    async for update in agent.run(message, thread=thread, stream=True):
-        if update.text:
-            print(update.text, end="")
-    print("")
-
-
-if __name__ == "__main__":
-    asyncio.run(main())
-```
-
-### .NET - Current pattern for comparison
-
-```csharp
-// Copyright (c) Microsoft. All rights reserved.
-
-using Azure.AI.OpenAI;
-using Azure.Identity;
-using Microsoft.Agents.AI;
-using OpenAI.Chat;
-
-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";
-
-AIAgent agent = new AzureOpenAIClient(
-    new Uri(endpoint),
-    new AzureCliCredential())
-    .GetChatClient(deploymentName)
-    .CreateAIAgent(
-        instructions: "You are good at telling jokes about pirates.",
-        name: "PirateJoker");
-
-// Non-streaming: Returns a string directly
-Console.WriteLine("=== Non-streaming ===");
-string result = await agent.RunAsync("Tell me a joke about a pirate.");
-Console.WriteLine(result);
-
-// Streaming: Returns IAsyncEnumerable<AgentUpdate>
-Console.WriteLine("\n=== Streaming ===");
-await foreach (AgentUpdate update in agent.RunStreamingAsync("Tell me a joke about a pirate."))
-{
-    Console.Write(update);
-}
-Console.WriteLine();
-
-```
@@ -125,7 +125,7 @@ The proposed solution is to add helper methods which allow developers to either
 - [Foundry SDK] Create a `PersistentAgentsClient`
 - [Foundry SDK] Create a `PersistentAgent` using the `PersistentAgentsClient`
 - [Foundry SDK] Retrieve an `AIAgent` using the `PersistentAgentsClient`
- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentResponse` 
+- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentRunResponse` 
 - [Foundry SDK] Clean up the agent


@@ -156,7 +156,7 @@ await persistentAgentsClient.Administration.DeleteAgentAsync(agent.Id);

 - [Foundry SDK] Create a `PersistentAgentsClient`
 - [Foundry SDK] Create a `AIAgent` using the `PersistentAgentsClient`
- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentResponse` 
+- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentRunResponse` 
 - [Foundry SDK] Clean up the agent

 ```csharp
@@ -184,7 +184,7 @@ await persistentAgentsClient.Administration.DeleteAgentAsync(agent.Id);
 - [Foundry SDK] Create a `PersistentAgentsClient`
 - [Foundry SDK] Create a `AIAgent` using the `PersistentAgentsClient`
 - [Agent Framework SDK] Optionally create an `AgentThread` for the agent run
- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentResponse` 
+- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentRunResponse` 
 - [Foundry SDK] Clean up the agent and the agent thread

 ```csharp
@@ -227,7 +227,7 @@ await persistentAgentsClient.Administration.DeleteAgentAsync(agent.Id);
 - [Foundry SDK] Create a `PersistentAgentsClient`
 - [Foundry SDK] Create multiple `AIAgent` instances using the `PersistentAgentsClient`
 - [Agent Framework SDK] Create a `SequentialOrchestration` and add all of the agents to it
- [Agent Framework SDK] Invoke the `SequentialOrchestration` instance and access response from the `AgentResponse` 
+- [Agent Framework SDK] Invoke the `SequentialOrchestration` instance and access response from the `AgentRunResponse` 
 - [Foundry SDK] Clean up the agents

 ```csharp
@@ -281,7 +281,7 @@ SequentialOrchestration orchestration =
 // Run the orchestration
 string input = "An eco-friendly stainless steel water bottle that keeps drinks cold for 24 hours";
 Console.WriteLine($"\n# INPUT: {input}\n");
-AgentResponse result = await orchestration.RunAsync(input);
+AgentRunResponse result = await orchestration.RunAsync(input);
 Console.WriteLine($"\n# RESULT: {result}");

 // Cleanup
@@ -112,14 +112,14 @@
    <PackageVersion Include="Microsoft.Bot.ObjectModel.PowerFx" Version="1.2025.1106.1" />
    <PackageVersion Include="Microsoft.PowerFx.Interpreter" Version="1.5.0-build.20251008-1002" />
    <!-- Durable Task -->
-    <PackageVersion Include="Microsoft.DurableTask.Client" Version="1.18.0" />
-    <PackageVersion Include="Microsoft.DurableTask.Client.AzureManaged" Version="1.18.0" />
-    <PackageVersion Include="Microsoft.DurableTask.Worker" Version="1.18.0" />
-    <PackageVersion Include="Microsoft.DurableTask.Worker.AzureManaged" Version="1.18.0" />
+    <PackageVersion Include="Microsoft.DurableTask.Client" Version="1.19.1" />
+    <PackageVersion Include="Microsoft.DurableTask.Client.AzureManaged" Version="1.19.0" />
+    <PackageVersion Include="Microsoft.DurableTask.Worker" Version="1.19.0" />
+    <PackageVersion Include="Microsoft.DurableTask.Worker.AzureManaged" Version="1.19.0" />
    <!-- Azure Functions -->
    <PackageVersion Include="Microsoft.Azure.Functions.Worker" Version="2.50.0" />
    <PackageVersion Include="Microsoft.Azure.Functions.Worker.ApplicationInsights" Version="2.50.0" />
-    <PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" Version="1.11.0" />
+    <PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" Version="1.13.1" />
    <PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" Version="1.0.1" />
    <PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Http" Version="3.3.0" />
    <PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" Version="2.1.0" />
@@ -34,6 +34,13 @@
    <Project Path="samples/AzureFunctions/06_LongRunningTools/06_LongRunningTools.csproj" />
    <Project Path="samples/AzureFunctions/07_AgentAsMcpTool/07_AgentAsMcpTool.csproj" />
    <Project Path="samples/AzureFunctions/08_ReliableStreaming/08_ReliableStreaming.csproj" />
+    <Project Path="samples/AzureFunctions/09_Workflow/09_Workflow.csproj" />
+    <Project Path="samples/AzureFunctions/10_WorkflowConcurrent/10_WorkflowConcurrent.csproj" />
+    <Project Path="samples/AzureFunctions/11_WorkflowSharedState/11_WorkflowSharedState.csproj" />
+    <Project Path="samples/AzureFunctions/12_ConditionalEdges/12_ConditionalEdges.csproj" />
+  </Folder>
+  <Folder Name="/Samples/DurableWorkflows/">
+    <Project Path="samples/DurableWorkflows/01_ExecutorsAndEdges/01_ExecutorsAndEdges.csproj" />
  </Folder>
  <Folder Name="/Samples/GettingStarted/">
    <File Path="samples/GettingStarted/README.md" />
@@ -3,10 +3,14 @@
  <packageSources>
    <clear />
    <add key="nuget.org" value="https://api.nuget.org/v3/index.json" />
+    <add key="LocalNugetSource" value="C:\LocalNugetSource" />
  </packageSources>
  <packageSourceMapping>
    <packageSource key="nuget.org">
      <package pattern="*" />
    </packageSource>
+    <packageSource key="LocalNugetSource">
+      <package pattern="*" />
+    </packageSource>
  </packageSourceMapping>
 </configuration>
@@ -42,7 +42,7 @@ public static class Program
        // Create the Host agent
        var hostAgent = new HostClientAgent(loggerFactory);
        await hostAgent.InitializeAgentAsync(modelId, apiKey, agentUrls!.Split(";"));
-        AgentThread thread = await hostAgent.Agent!.GetNewThreadAsync(cancellationToken);
+        AgentThread thread = hostAgent.Agent!.GetNewThread();
        try
        {
            while (true)
@@ -88,7 +88,7 @@ public static class Program
            description: "AG-UI Client Agent",
            tools: [changeBackground, readClientClimateSensors]);

-        AgentThread thread = await agent.GetNewThreadAsync(cancellationToken);
+        AgentThread thread = agent.GetNewThread();
        List<ChatMessage> messages = [new(ChatRole.System, "You are a helpful assistant.")];
        try
        {
@@ -114,7 +114,7 @@ public static class Program
                bool isFirstUpdate = true;
                string? threadId = null;
                var updates = new List<ChatResponseUpdate>();
-                await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread, cancellationToken: cancellationToken))
+                await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread, cancellationToken: cancellationToken))
                {
                    // Use AsChatResponseUpdate to access ChatResponseUpdate properties
                    ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();
@@ -19,12 +19,12 @@ internal sealed class AgenticUIAgent : DelegatingAIAgent
        this._jsonSerializerOptions = jsonSerializerOptions;
    }

-    protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
+    protected override Task<AgentRunResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
    {
-        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
+        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken).ToAgentRunResponseAsync(cancellationToken);
    }

-    protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
+    protected override async IAsyncEnumerable<AgentRunResponseUpdate> RunCoreStreamingAsync(
        IEnumerable<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
@@ -69,7 +69,7 @@ internal sealed class AgenticUIAgent : DelegatingAIAgent

            yield return update;

-            yield return new AgentResponseUpdate(
+            yield return new AgentRunResponseUpdate(
                new ChatResponseUpdate(role: ChatRole.System, stateEventsToEmit)
                {
                    MessageId = "delta_" + Guid.NewGuid().ToString("N"),
@@ -20,12 +20,12 @@ internal sealed class PredictiveStateUpdatesAgent : DelegatingAIAgent
        this._jsonSerializerOptions = jsonSerializerOptions;
    }

-    protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
+    protected override Task<AgentRunResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
    {
-        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
+        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken).ToAgentRunResponseAsync(cancellationToken);
    }

-    protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
+    protected override async IAsyncEnumerable<AgentRunResponseUpdate> RunCoreStreamingAsync(
        IEnumerable<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
@@ -79,7 +79,7 @@ internal sealed class PredictiveStateUpdatesAgent : DelegatingAIAgent
                        stateUpdate,
                        this._jsonSerializerOptions.GetTypeInfo(typeof(DocumentState)));

-                    yield return new AgentResponseUpdate(
+                    yield return new AgentRunResponseUpdate(
                        new ChatResponseUpdate(role: ChatRole.Assistant, [new DataContent(stateBytes, "application/json")])
                        {
                            MessageId = "snapshot" + Guid.NewGuid().ToString("N"),
@@ -19,12 +19,12 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
        this._jsonSerializerOptions = jsonSerializerOptions;
    }

-    protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
+    protected override Task<AgentRunResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
    {
-        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
+        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken).ToAgentRunResponseAsync(cancellationToken);
    }

-    protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
+    protected override async IAsyncEnumerable<AgentRunResponseUpdate> RunCoreStreamingAsync(
        IEnumerable<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
@@ -63,7 +63,7 @@ internal sealed class SharedStateAgent : DelegatingAIAgent

        var firstRunMessages = messages.Append(stateUpdateMessage);

-        var allUpdates = new List<AgentResponseUpdate>();
+        var allUpdates = new List<AgentRunResponseUpdate>();
        await foreach (var update in this.InnerAgent.RunStreamingAsync(firstRunMessages, thread, firstRunOptions, cancellationToken).ConfigureAwait(false))
        {
            allUpdates.Add(update);
@@ -76,14 +76,14 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
            }
        }

-        var response = allUpdates.ToAgentResponse();
+        var response = allUpdates.ToAgentRunResponse();

        if (response.TryDeserialize(this._jsonSerializerOptions, out JsonElement stateSnapshot))
        {
            byte[] stateBytes = JsonSerializer.SerializeToUtf8Bytes(
                stateSnapshot,
                this._jsonSerializerOptions.GetTypeInfo(typeof(JsonElement)));
-            yield return new AgentResponseUpdate
+            yield return new AgentRunResponseUpdate
            {
                Contents = [new DataContent(stateBytes, "application/json")]
            };
@@ -151,9 +151,9 @@ AIAgent agent = chatClient.CreateAIAgent(
    tools: []);

 bool isFirstUpdate = true;
-AgentResponseUpdate? currentUpdate = null;
+AgentRunResponseUpdate? currentUpdate = null;

-await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread))
+await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread))
 {
    // First update indicates run started
    if (isFirstUpdate)
@@ -190,19 +190,19 @@ if (currentUpdate != null)
 The `RunStreamingAsync` method:
 1. Sends messages to the server via HTTP POST
 2. Receives server-sent events (SSE) stream
-3. Parses events into `AgentResponseUpdate` objects
+3. Parses events into `AgentRunResponseUpdate` objects
 4. Yields updates as they arrive for real-time display

 ## Key Concepts

 - **Thread**: Represents a conversation context that persists across multiple runs (accessed via `ConversationId` property)
 - **Run**: A single execution of the agent for a given set of messages (identified by `ResponseId` property)
- **AgentResponseUpdate**: Contains the response data with:
+- **AgentRunResponseUpdate**: Contains the response data with:
  - `ResponseId`: The unique run identifier
  - `ConversationId`: The thread/conversation identifier
  - `Contents`: Collection of content items (TextContent, ErrorContent, etc.)
 - **Run Lifecycle**: 
-  - The **first** `AgentResponseUpdate` in a run indicates the run has started
+  - The **first** `AgentRunResponseUpdate` in a run indicates the run has started
  - Subsequent updates contain streaming content as the agent processes
-  - The **last** `AgentResponseUpdate` in a run indicates the run has finished
+  - The **last** `AgentRunResponseUpdate` in a run indicates the run has finished
  - If an error occurs, the update will contain `ErrorContent`
@@ -25,7 +25,7 @@ internal sealed class A2AAgentClient : AgentClientBase
        this._uri = baseUri;
    }

-    public override async IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
+    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
        string agentName,
        IList<ChatMessage> messages,
        string? threadId = null,
@@ -37,7 +37,7 @@ internal sealed class A2AAgentClient : AgentClientBase
        var contextId = threadId ?? Guid.NewGuid().ToString("N");

        // Convert and send messages via A2A without try-catch in yield method
-        var results = new List<AgentResponseUpdate>();
+        var results = new List<AgentRunResponseUpdate>();

        try
        {
@@ -60,7 +60,7 @@ internal sealed class A2AAgentClient : AgentClientBase
                var responseMessage = message.ToChatMessage();
                if (responseMessage is { Contents.Count: > 0 })
                {
-                    results.Add(new AgentResponseUpdate(responseMessage.Role, responseMessage.Contents)
+                    results.Add(new AgentRunResponseUpdate(responseMessage.Role, responseMessage.Contents)
                    {
                        MessageId = message.MessageId,
                        CreatedAt = DateTimeOffset.UtcNow
@@ -90,7 +90,7 @@ internal sealed class A2AAgentClient : AgentClientBase
                                RawRepresentation = artifact,
                            };

-                            results.Add(new AgentResponseUpdate(chatMessage.Role, chatMessage.Contents)
+                            results.Add(new AgentRunResponseUpdate(chatMessage.Role, chatMessage.Contents)
                            {
                                MessageId = agentTask.Id,
                                CreatedAt = DateTimeOffset.UtcNow
@@ -108,7 +108,7 @@ internal sealed class A2AAgentClient : AgentClientBase
        {
            this._logger.LogError(ex, "Error running agent {AgentName} via A2A", agentName);

-            results.Add(new AgentResponseUpdate(ChatRole.Assistant, $"Error: {ex.Message}")
+            results.Add(new AgentRunResponseUpdate(ChatRole.Assistant, $"Error: {ex.Message}")
            {
                MessageId = Guid.NewGuid().ToString("N"),
                CreatedAt = DateTimeOffset.UtcNow
@@ -19,7 +19,7 @@ internal abstract class AgentClientBase
    /// <param name="threadId">Optional thread identifier for conversation continuity.</param>
    /// <param name="cancellationToken">Cancellation token.</param>
    /// <returns>An asynchronous enumerable of agent response updates.</returns>
-    public abstract IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
+    public abstract IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
        string agentName,
        IList<ChatMessage> messages,
        string? threadId = null,
@@ -16,7 +16,7 @@ namespace AgentWebChat.Web;
 /// </summary>
 internal sealed class OpenAIChatCompletionsAgentClient(HttpClient httpClient) : AgentClientBase
 {
-    public override async IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
+    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
        string agentName,
        IList<ChatMessage> messages,
        string? threadId = null,
@@ -31,7 +31,7 @@ internal sealed class OpenAIChatCompletionsAgentClient(HttpClient httpClient) :
        var openAiClient = new ChatClient(model: "myModel!", credential: new ApiKeyCredential("dummy-key"), options: options).AsIChatClient();
        await foreach (var update in openAiClient.GetStreamingResponseAsync(messages, cancellationToken: cancellationToken))
        {
-            yield return new AgentResponseUpdate(update);
+            yield return new AgentRunResponseUpdate(update);
        }
    }
 }
@@ -15,7 +15,7 @@ namespace AgentWebChat.Web;
 /// </summary>
 internal sealed class OpenAIResponsesAgentClient(HttpClient httpClient) : AgentClientBase
 {
-    public override async IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
+    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
        string agentName,
        IList<ChatMessage> messages,
        string? threadId = null,
@@ -35,7 +35,7 @@ internal sealed class OpenAIResponsesAgentClient(HttpClient httpClient) : AgentC

        await foreach (var update in openAiClient.GetStreamingResponseAsync(messages, chatOptions, cancellationToken: cancellationToken))
        {
-            yield return new AgentResponseUpdate(update);
+            yield return new AgentRunResponseUpdate(update);
        }
    }
 }
@@ -8,3 +8,6 @@ dotnet_diagnostic.DURABLE0003.severity = none
 dotnet_diagnostic.DURABLE0004.severity = none
 dotnet_diagnostic.DURABLE0005.severity = none
 dotnet_diagnostic.DURABLE0006.severity = none
+
+# CA1812: Internal classes are instantiated via dependency injection or reflection in samples
+dotnet_diagnostic.CA1812.severity = none
@@ -6,8 +6,8 @@
    <ImplicitUsings>enable</ImplicitUsings>
    <Nullable>enable</Nullable>
    <!-- The Functions build tools don't like namespaces that start with a number -->
-    <AssemblyName>SingleAgent</AssemblyName>
-    <RootNamespace>SingleAgent</RootNamespace>
+    <AssemblyName>Workflow</AssemblyName>
+    <RootNamespace>Workflow</RootNamespace>
  </PropertyGroup>

  <ItemGroup>
@@ -5,4 +5,4 @@
 POST {{authority}}/api/agents/Joker/run
 Content-Type: text/plain

-Tell me a joke about a pirate.
+Hello world
@@ -19,13 +19,13 @@ public static class FunctionTriggers
    public static async Task<string> RunOrchestrationAsync([OrchestrationTrigger] TaskOrchestrationContext context)
    {
        DurableAIAgent writer = context.GetAgent("WriterAgent");
-        AgentThread writerThread = await writer.GetNewThreadAsync();
+        AgentThread writerThread = writer.GetNewThread();

-        AgentResponse<TextResponse> initial = await writer.RunAsync<TextResponse>(
+        AgentRunResponse<TextResponse> initial = await writer.RunAsync<TextResponse>(
            message: "Write a concise inspirational sentence about learning.",
            thread: writerThread);

-        AgentResponse<TextResponse> refined = await writer.RunAsync<TextResponse>(
+        AgentRunResponse<TextResponse> refined = await writer.RunAsync<TextResponse>(
            message: $"Improve this further while keeping it under 25 words: {initial.Result.Text}",
            thread: writerThread);

@@ -26,9 +26,9 @@ public static class FunctionsTriggers
        DurableAIAgent chemist = context.GetAgent("ChemistAgent");

        // Start both agent runs concurrently
-        Task<AgentResponse<TextResponse>> physicistTask = physicist.RunAsync<TextResponse>(prompt);
+        Task<AgentRunResponse<TextResponse>> physicistTask = physicist.RunAsync<TextResponse>(prompt);

-        Task<AgentResponse<TextResponse>> chemistTask = chemist.RunAsync<TextResponse>(prompt);
+        Task<AgentRunResponse<TextResponse>> chemistTask = chemist.RunAsync<TextResponse>(prompt);

        // Wait for both tasks to complete using Task.WhenAll
        await Task.WhenAll(physicistTask, chemistTask);
@@ -21,10 +21,10 @@ public static class FunctionTriggers

        // Get the spam detection agent
        DurableAIAgent spamDetectionAgent = context.GetAgent("SpamDetectionAgent");
-        AgentThread spamThread = await spamDetectionAgent.GetNewThreadAsync();
+        AgentThread spamThread = spamDetectionAgent.GetNewThread();

        // Step 1: Check if the email is spam
-        AgentResponse<DetectionResult> spamDetectionResponse = await spamDetectionAgent.RunAsync<DetectionResult>(
+        AgentRunResponse<DetectionResult> spamDetectionResponse = await spamDetectionAgent.RunAsync<DetectionResult>(
            message:
                $"""
                Analyze this email for spam content and return a JSON response with 'is_spam' (boolean) and 'reason' (string) fields:
@@ -43,9 +43,9 @@ public static class FunctionTriggers

        // Generate and send response for legitimate email
        DurableAIAgent emailAssistantAgent = context.GetAgent("EmailAssistantAgent");
-        AgentThread emailThread = await emailAssistantAgent.GetNewThreadAsync();
+        AgentThread emailThread = emailAssistantAgent.GetNewThread();

-        AgentResponse<EmailResponse> emailAssistantResponse = await emailAssistantAgent.RunAsync<EmailResponse>(
+        AgentRunResponse<EmailResponse> emailAssistantResponse = await emailAssistantAgent.RunAsync<EmailResponse>(
            message:
                $"""
                    Draft a professional response to this email. Return a JSON response with a 'response' field containing the reply:
@@ -24,13 +24,13 @@ public static class FunctionTriggers

        // Get the writer agent
        DurableAIAgent writerAgent = context.GetAgent("WriterAgent");
-        AgentThread writerThread = await writerAgent.GetNewThreadAsync();
+        AgentThread writerThread = writerAgent.GetNewThread();

        // Set initial status
        context.SetCustomStatus($"Starting content generation for topic: {input.Topic}");

        // Step 1: Generate initial content
-        AgentResponse<GeneratedContent> writerResponse = await writerAgent.RunAsync<GeneratedContent>(
+        AgentRunResponse<GeneratedContent> writerResponse = await writerAgent.RunAsync<GeneratedContent>(
            message: $"Write a short article about '{input.Topic}'.",
            thread: writerThread);
        GeneratedContent content = writerResponse.Result;
@@ -20,13 +20,13 @@ public static class FunctionTriggers

        // Get the writer agent
        DurableAIAgent writerAgent = context.GetAgent("Writer");
-        AgentThread writerThread = await writerAgent.GetNewThreadAsync();
+        AgentThread writerThread = writerAgent.GetNewThread();

        // Set initial status
        context.SetCustomStatus($"Starting content generation for topic: {input.Topic}");

        // Step 1: Generate initial content
-        AgentResponse<GeneratedContent> writerResponse = await writerAgent.RunAsync<GeneratedContent>(
+        AgentRunResponse<GeneratedContent> writerResponse = await writerAgent.RunAsync<GeneratedContent>(
            message: $"Write a short article about '{input.Topic}'.",
            thread: writerThread);
        GeneratedContent content = writerResponse.Result;
@@ -95,7 +95,7 @@ public sealed class FunctionTriggers
        AIAgent agentProxy = durableClient.AsDurableAgentProxy(context, "TravelPlanner");

        // Create a new agent thread
-        AgentThread thread = await agentProxy.GetNewThreadAsync(cancellationToken);
+        AgentThread thread = agentProxy.GetNewThread();
        string agentSessionId = thread.GetService<AgentSessionId>().ToString();

        this._logger.LogInformation("Creating new agent session: {AgentSessionId}", agentSessionId);
@@ -196,7 +196,7 @@ The `id` field is the Redis stream entry ID - use it as the `cursor` parameter t

 2. **Agent invoked**: The durable entity (`AgentEntity`) is signaled to run the travel planner agent. This is fire-and-forget from the HTTP request's perspective.

-3. **Responses captured**: As the agent generates responses, `RedisStreamResponseHandler` (implementing `IAgentResponseHandler`) extracts the text from each `AgentResponseUpdate` and publishes it to a Redis Stream keyed by session ID.
+3. **Responses captured**: As the agent generates responses, `RedisStreamResponseHandler` (implementing `IAgentResponseHandler`) extracts the text from each `AgentRunResponseUpdate` and publishes it to a Redis Stream keyed by session ID.

 4. **Client polls Redis**: The HTTP response streams events by polling the Redis Stream. For SSE format, each event includes the Redis entry ID as the `id` field.

@@ -29,7 +29,7 @@ public readonly record struct StreamChunk(string EntryId, string? Text, bool IsD
 /// </para>
 /// <para>
 /// Each agent session gets its own Redis Stream, keyed by session ID. The stream entries
-/// contain text chunks extracted from <see cref="AgentResponseUpdate"/> objects.
+/// contain text chunks extracted from <see cref="AgentRunResponseUpdate"/> objects.
 /// </para>
 /// </remarks>
 public sealed class RedisStreamResponseHandler : IAgentResponseHandler
@@ -53,7 +53,7 @@ public sealed class RedisStreamResponseHandler : IAgentResponseHandler

    /// <inheritdoc/>
    public async ValueTask OnStreamingResponseUpdateAsync(
-        IAsyncEnumerable<AgentResponseUpdate> messageStream,
+        IAsyncEnumerable<AgentRunResponseUpdate> messageStream,
        CancellationToken cancellationToken)
    {
        // Get the current session ID from the DurableAgentContext
@@ -73,7 +73,7 @@ public sealed class RedisStreamResponseHandler : IAgentResponseHandler
        IDatabase db = this._redis.GetDatabase();
        int sequenceNumber = 0;

-        await foreach (AgentResponseUpdate update in messageStream.WithCancellation(cancellationToken))
+        await foreach (AgentRunResponseUpdate update in messageStream.WithCancellation(cancellationToken))
        {
            // Extract just the text content - this avoids serialization round-trip issues
            string text = update.Text;
@@ -112,7 +112,7 @@ public sealed class RedisStreamResponseHandler : IAgentResponseHandler
    }

    /// <inheritdoc/>
-    public ValueTask OnAgentResponseAsync(AgentResponse message, CancellationToken cancellationToken)
+    public ValueTask OnAgentResponseAsync(AgentRunResponse message, CancellationToken cancellationToken)
    {
        // This handler is optimized for streaming responses.
        // For non-streaming responses, we don't need to store in Redis since
@@ -0,0 +1,44 @@
+<Project Sdk="Microsoft.NET.Sdk">
+  <PropertyGroup>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+    <AzureFunctionsVersion>v4</AzureFunctionsVersion>
+    <OutputType>Exe</OutputType>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+    <!-- The Functions build tools don't like namespaces that start with a number -->
+    <AssemblyName>SingleAgent</AssemblyName>
+    <RootNamespace>SingleAgent</RootNamespace>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <FrameworkReference Include="Microsoft.AspNetCore.App" />
+  </ItemGroup>
+
+  <!-- Azure Functions packages -->
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Azure.Functions.Worker" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
+  <!--
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
+    <PackageReference Include="Microsoft.Agents.AI.OpenAI" />
+  </ItemGroup>
+  -->
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Workflows\Microsoft.Agents.AI.Workflows.csproj" />
+  </ItemGroup>
+</Project>
@@ -0,0 +1,67 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using Microsoft.Agents.AI.Workflows;
+
+namespace SingleAgent;
+
+/// <summary>
+/// Parses an Order ID from a string input and returns an Order object populated.
+/// </summary>
+internal sealed class OrderLookup() : Executor<string, Order>("OrderLookup")
+{
+    public override async ValueTask<Order> HandleAsync(string message, IWorkflowContext context, CancellationToken cancellationToken = default)
+    {
+        // Populate Order information from OrderId.
+        return new Order(message, 100.0m);
+    }
+}
+
+/// <summary>
+/// Enriches an Order object with additional information.
+/// </summary>
+internal sealed class OrderEnrich() : Executor<Order, Order>("EnrichOrder")
+{
+    public override async ValueTask<Order> HandleAsync(Order message, IWorkflowContext context, CancellationToken cancellationToken = default)
+    {
+        if (message.Customer is null)
+        {
+            // populate customer information for the order from database.
+            message.Customer = new Customer(1, "Jerry");
+        }
+
+        return message;
+    }
+}
+
+internal sealed class PaymentProcessor() : Executor<Order, Order>("ProcessPayment")
+{
+    public override async ValueTask<Order> HandleAsync(Order message, IWorkflowContext context, CancellationToken cancellationToken = default)
+    {
+        message.PaymentReferenceNumber = Guid.NewGuid().ToString()[^4..];
+
+        return message;
+    }
+}
+
+internal sealed class OrderCancel() : Executor<Order, string>("OrderCancel")
+{
+    public override async ValueTask<string> HandleAsync(Order message, IWorkflowContext context, CancellationToken cancellationToken = default)
+    {
+        return $"Order {message.Id} cancelled at {DateTime.UtcNow:g} UTC.";
+    }
+}
+
+internal sealed class Order
+{
+    public Order(string id, decimal amount)
+    {
+        this.Id = id;
+        this.Amount = amount;
+    }
+    public string Id { get; }
+    public decimal Amount { get; }
+    public Customer? Customer { get; set; }
+    public string? PaymentReferenceNumber { get; set; }
+}
+
+public sealed record Customer(int Id, string Name);
@@ -0,0 +1,40 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using Microsoft.Agents.AI.Hosting.AzureFunctions;
+using Microsoft.Agents.AI.Workflows;
+using Microsoft.Azure.Functions.Worker.Builder;
+using Microsoft.Extensions.Hosting;
+using SingleAgent;
+
+Func<string, string> orderParserFunc = input =>
+{
+    // We accept both short ordereId(Ex:12345) and long order reference number(MSFT12345)
+    // OrderId is the last 5 digigs of order reference number.
+    const int OrderIdPartLength = 5;
+    if (input.Length > OrderIdPartLength)
+    {
+        return input[^OrderIdPartLength..];
+    }
+
+    return input;
+};
+var orderParserExecutor = orderParserFunc.BindAsExecutor("ParseOrderId");
+
+OrderLookup orderLookupExecutor = new();
+OrderEnrich orderEnricherExeecutor = new();
+PaymentProcessor paymentProcessorExecutor = new();
+
+Workflow fulfillOrder = new WorkflowBuilder(orderParserExecutor)
+    .WithName("FulfillOrder")
+    .WithDescription("Looks up an order by ID and run payment processing")
+    .AddEdge(orderParserExecutor, orderLookupExecutor)
+    .AddEdge(orderLookupExecutor, orderEnricherExeecutor)
+    .AddEdge(orderEnricherExeecutor, paymentProcessorExecutor)
+    .Build();
+
+var host = FunctionsApplication.CreateBuilder(args)
+    .ConfigureFunctionsWebApplication()
+    .ConfigureDurableOptions(options => options.Workflows.AddWorkflow(fulfillOrder, enableMcpToolTrigger: true))
+    .Build();
+
+host.Run();
@@ -0,0 +1,89 @@
+# Single Agent Sample
+
+This sample demonstrates how to use the Durable Agent Framework (DAFx) to create a simple Azure Functions app that hosts a single AI agent and provides direct HTTP API access for interactive conversations.
+
+## Key Concepts Demonstrated
+
+- Using the Microsoft Agent Framework to define a simple AI agent with a name and instructions.
+- Registering agents with the Function app and running them using HTTP.
+- Conversation management (via session IDs) for isolated interactions.
+
+## Environment Setup
+
+See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
+
+## Running the Sample
+
+With the environment setup and function app running, you can test the sample by sending an HTTP request to the agent endpoint.
+
+You can use the `demo.http` file to send a message to the agent, or a command line tool like `curl` as shown below:
+
+Bash (Linux/macOS/WSL):
+
+```bash
+curl -X POST http://localhost:7071/api/agents/Joker/run \
+    -H "Content-Type: text/plain" \
+    -d "Tell me a joke about a pirate."
+```
+
+PowerShell:
+
+```powershell
+Invoke-RestMethod -Method Post `
+    -Uri http://localhost:7071/api/agents/Joker/run `
+    -ContentType text/plain `
+    -Body "Tell me a joke about a pirate."
+```
+
+You can also send JSON requests:
+
+```bash
+curl -X POST http://localhost:7071/api/agents/Joker/run \
+    -H "Content-Type: application/json" \
+    -H "Accept: application/json" \
+    -d '{"message": "Tell me a joke about a pirate."}'
+```
+
+To continue a conversation, include the `thread_id` in the query string or JSON body:
+
+```bash
+curl -X POST "http://localhost:7071/api/agents/Joker/run?thread_id=your-thread-id" \
+    -H "Content-Type: application/json" \
+    -H "Accept: application/json" \
+    -d '{"message": "Tell me another one."}'
+```
+
+The response from the agent will be displayed in the terminal where you ran `func start`. The expected `text/plain` output will look something like:
+
+```text
+Why don't pirates ever learn the alphabet? Because they always get stuck at "C"!
+```
+
+The expected `application/json` output will look something like:
+
+```json
+{
+  "status": 200,
+  "thread_id": "ee6e47a0-f24b-40b1-ade8-16fcebb9eb40",
+  "response": {
+    "Messages": [
+      {
+        "AuthorName": "Joker",
+        "CreatedAt": "2025-11-11T12:00:00.0000000Z",
+        "Role": "assistant",
+        "Contents": [
+          {
+            "Type": "text",
+            "Text": "Why don't pirates ever learn the alphabet? Because they always get stuck at 'C'!"
+          }
+        ]
+      }
+    ],
+    "Usage": {
+      "InputTokenCount": 78,
+      "OutputTokenCount": 36,
+      "TotalTokenCount": 114
+    }
+  }
+}
+```
@@ -0,0 +1,14 @@
+# Default endpoint address for local testing
+@authority=http://localhost:7071
+
+### Look up a long order reference id
+POST {{authority}}/api/workflows/FulfillOrder/run
+Content-Type: text/plain
+
+QWERTY80853
+
+### Look up a short order id
+POST {{authority}}/api/workflows/CancelOrder/run
+Content-Type: text/plain
+
+12345
@@ -0,0 +1,20 @@
+{
+  "version": "2.0",
+  "logging": {
+    "logLevel": {
+      "Microsoft.Agents.AI.DurableTask": "Information",
+      "Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
+      "DurableTask": "Information",
+      "Microsoft.DurableTask": "Information"
+    }
+  },
+  "extensions": {
+    "durableTask": {
+      "hubName": "default",
+      "storageProvider": {
+        "type": "AzureManaged",
+        "connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
+      }
+    }
+  }
+}
@@ -0,0 +1,48 @@
+<Project Sdk="Microsoft.NET.Sdk">
+  <PropertyGroup>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+    <AzureFunctionsVersion>v4</AzureFunctionsVersion>
+    <OutputType>Exe</OutputType>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+    <!-- The Functions build tools don't like namespaces that start with a number -->
+    <AssemblyName>SingleAgent</AssemblyName>
+    <RootNamespace>SingleAgent</RootNamespace>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <FrameworkReference Include="Microsoft.AspNetCore.App" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <None Include="local.settings.json" />
+  </ItemGroup>
+
+  <!-- Azure Functions packages -->
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Azure.Functions.Worker" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
+  <!--
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
+    <PackageReference Include="Microsoft.Agents.AI.OpenAI" />
+  </ItemGroup>
+  -->
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Workflows\Microsoft.Agents.AI.Workflows.csproj" />
+  </ItemGroup>
+</Project>
@@ -0,0 +1,30 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using Microsoft.Agents.AI.Workflows;
+
+namespace SingleAgent;
+
+internal sealed class PrepareQuery() : Executor<string, string>("PrepareQuery")
+{
+    public override ValueTask<string> HandleAsync(string message, IWorkflowContext context, CancellationToken cancellationToken = default)
+    {
+        // do some initial parsing and validation of the message.
+        // Return a polished version ith additional metadta.
+        if (!message.StartsWith("Query for the agent:", StringComparison.OrdinalIgnoreCase))
+        {
+            message = "Query for the agent: " + message;
+        }
+
+        return ValueTask.FromResult(message);
+    }
+}
+
+internal sealed class ResultAggregator() : Executor<string[], string>("ResultAggregator")
+{
+    public override ValueTask<string> HandleAsync(string[] message, IWorkflowContext context, CancellationToken cancellationToken = default)
+    {
+        // Aggregate all responses from parallel executors.
+        string aggregatedResponse = string.Join("\n---\n", message);
+        return ValueTask.FromResult($"Aggregated {message.Length} responses:\n{aggregatedResponse}");
+    }
+}
@@ -0,0 +1,48 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using Azure;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.Hosting.AzureFunctions;
+using Microsoft.Agents.AI.Workflows;
+using Microsoft.Azure.Functions.Worker.Builder;
+using Microsoft.Extensions.AI;
+using Microsoft.Extensions.Hosting;
+using OpenAI.Chat;
+using SingleAgent;
+
+// Get the Azure OpenAI endpoint and deployment name from environment variables.
+string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
+    ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
+    ?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
+
+// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
+string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
+    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
+    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+
+AIAgent physicist = client.GetChatClient(deploymentName).CreateAIAgent("You are an expert in physics. You answer questions from a physics perspective.", "Physicist");
+AIAgent chemist = client.GetChatClient(deploymentName).CreateAIAgent("You are an expert in chemistry. You answer questions from a chemistry perspective.", "Chemist");
+
+var startExecutor = new PrepareQuery();
+var aggregationExecutor = new ResultAggregator();
+
+var workflow = new WorkflowBuilder(startExecutor)
+    .WithName("ExpertReview")
+    .AddFanOutEdge(startExecutor, [physicist, chemist])
+    .AddFanInEdge([physicist, chemist], aggregationExecutor)
+    .Build();
+
+var host = FunctionsApplication.CreateBuilder(args)
+    .ConfigureFunctionsWebApplication()
+    .ConfigureDurableOptions(options =>
+    {
+        // Configure workflows
+        options.Workflows.AddWorkflow(workflow);
+    })
+    .Build();
+
+host.Run();
@@ -0,0 +1,89 @@
+# Single Agent Sample
+
+This sample demonstrates how to use the Durable Agent Framework (DAFx) to create a simple Azure Functions app that hosts a single AI agent and provides direct HTTP API access for interactive conversations.
+
+## Key Concepts Demonstrated
+
+- Using the Microsoft Agent Framework to define a simple AI agent with a name and instructions.
+- Registering agents with the Function app and running them using HTTP.
+- Conversation management (via session IDs) for isolated interactions.
+
+## Environment Setup
+
+See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
+
+## Running the Sample
+
+With the environment setup and function app running, you can test the sample by sending an HTTP request to the agent endpoint.
+
+You can use the `demo.http` file to send a message to the agent, or a command line tool like `curl` as shown below:
+
+Bash (Linux/macOS/WSL):
+
+```bash
+curl -X POST http://localhost:7071/api/agents/Joker/run \
+    -H "Content-Type: text/plain" \
+    -d "Tell me a joke about a pirate."
+```
+
+PowerShell:
+
+```powershell
+Invoke-RestMethod -Method Post `
+    -Uri http://localhost:7071/api/agents/Joker/run `
+    -ContentType text/plain `
+    -Body "Tell me a joke about a pirate."
+```
+
+You can also send JSON requests:
+
+```bash
+curl -X POST http://localhost:7071/api/agents/Joker/run \
+    -H "Content-Type: application/json" \
+    -H "Accept: application/json" \
+    -d '{"message": "Tell me a joke about a pirate."}'
+```
+
+To continue a conversation, include the `thread_id` in the query string or JSON body:
+
+```bash
+curl -X POST "http://localhost:7071/api/agents/Joker/run?thread_id=your-thread-id" \
+    -H "Content-Type: application/json" \
+    -H "Accept: application/json" \
+    -d '{"message": "Tell me another one."}'
+```
+
+The response from the agent will be displayed in the terminal where you ran `func start`. The expected `text/plain` output will look something like:
+
+```text
+Why don't pirates ever learn the alphabet? Because they always get stuck at "C"!
+```
+
+The expected `application/json` output will look something like:
+
+```json
+{
+  "status": 200,
+  "thread_id": "ee6e47a0-f24b-40b1-ade8-16fcebb9eb40",
+  "response": {
+    "Messages": [
+      {
+        "AuthorName": "Joker",
+        "CreatedAt": "2025-11-11T12:00:00.0000000Z",
+        "Role": "assistant",
+        "Contents": [
+          {
+            "Type": "text",
+            "Text": "Why don't pirates ever learn the alphabet? Because they always get stuck at 'C'!"
+          }
+        ]
+      }
+    ],
+    "Usage": {
+      "InputTokenCount": 78,
+      "OutputTokenCount": 36,
+      "TotalTokenCount": 114
+    }
+  }
+}
+```
@@ -0,0 +1,8 @@
+# Default endpoint address for local testing
+@authority=http://localhost:7071
+
+### Start the workflow
+POST {{authority}}/api/workflows/ExpertReview/run
+Content-Type: text/plain
+
+What is temperature?
@@ -0,0 +1,20 @@
+{
+  "version": "2.0",
+  "logging": {
+    "logLevel": {
+      "Microsoft.Agents.AI.DurableTask": "Information",
+      "Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
+      "DurableTask": "Information",
+      "Microsoft.DurableTask": "Information"
+    }
+  },
+  "extensions": {
+    "durableTask": {
+      "hubName": "default",
+      "storageProvider": {
+        "type": "AzureManaged",
+        "connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
+      }
+    }
+  }
+}
@@ -0,0 +1,48 @@
+<Project Sdk="Microsoft.NET.Sdk">
+  <PropertyGroup>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+    <AzureFunctionsVersion>v4</AzureFunctionsVersion>
+    <OutputType>Exe</OutputType>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+    <!-- The Functions build tools don't like namespaces that start with a number -->
+    <AssemblyName>SingleAgent</AssemblyName>
+    <RootNamespace>SingleAgent</RootNamespace>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <FrameworkReference Include="Microsoft.AspNetCore.App" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <None Include="local.settings.json" />
+  </ItemGroup>
+
+  <!-- Azure Functions packages -->
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Azure.Functions.Worker" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
+  <!--
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
+    <PackageReference Include="Microsoft.Agents.AI.OpenAI" />
+  </ItemGroup>
+  -->
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Workflows\Microsoft.Agents.AI.Workflows.csproj" />
+  </ItemGroup>
+</Project>
@@ -0,0 +1,86 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to use durable state management in Azure Functions workflows.
+// The OrderIdParserExecutor writes a value to shared state, and the EmailSenderExecutor reads it back.
+// The state is persisted durably using Durable Entities behind the scenes.
+
+using Microsoft.Agents.AI.Workflows;
+
+namespace SingleAgent;
+
+/// <summary>
+/// Constants for shared state scopes used across executors.
+/// </summary>
+internal static class SharedStateConstants
+{
+    public const string MessageScope = "MessageState";
+    public const string ProcessedMessageKey = "ProcessedMessage";
+}
+
+public sealed class Order
+{
+    public Order(string id, decimal amount)
+    {
+        this.Id = id;
+        this.Amount = amount;
+    }
+    public string Id { get; }
+    public decimal Amount { get; }
+    public string? PaymentReferenceNumber { get; set; }
+}
+
+/// <summary>
+/// First executor that processes a message and stores the result in shared state.
+/// </summary>
+internal sealed class OrderIdParserExecutor() : Executor<string, Order>("OrderIdParserExecutor")
+{
+    public override async ValueTask<Order> HandleAsync(string message, IWorkflowContext context, CancellationToken cancellationToken = default)
+    {
+        // Process the message
+        string processedMessage = $"Processed: {message}";
+
+        // Store the processed message in shared state for the next executor
+        await context.QueueStateUpdateAsync(
+            SharedStateConstants.ProcessedMessageKey,
+            processedMessage,
+            SharedStateConstants.MessageScope,
+            cancellationToken);
+
+        return GetOrder(message);
+    }
+
+    private static Order GetOrder(string id)
+    {
+        // Simulate fetching order details
+        return new Order(id, 100.0m);
+    }
+}
+
+/// <summary>
+/// Second executor that reads the shared state and appends to the message.
+/// </summary>
+internal sealed class EmailSenderExecutor() : Executor<Order, string>("EmailSenderExecutor")
+{
+    public override async ValueTask<string> HandleAsync(Order message, IWorkflowContext context, CancellationToken cancellationToken = default)
+    {
+        // Read the processed message from shared state (written by OrderIdParserExecutor)
+        string? storedMessage = await context.ReadStateAsync<string>(
+            SharedStateConstants.ProcessedMessageKey,
+            SharedStateConstants.MessageScope,
+            cancellationToken);
+
+        return storedMessage is not null
+            ? $"From state: [{storedMessage}] | Input: [{message.Id}]"
+            : $"No state found | Input: [{message.Id}]";
+    }
+}
+
+internal sealed class PaymentProcesserExecutor() : Executor<Order, Order>("PaymentProcesserExecutor")
+{
+    public override async ValueTask<Order> HandleAsync(Order message, IWorkflowContext context, CancellationToken cancellationToken = default)
+    {
+        // Call payment gateway.
+        message.PaymentReferenceNumber = Guid.NewGuid().ToString().Substring(0, 4);
+        return message;
+    }
+}
@@ -0,0 +1,23 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using Microsoft.Agents.AI.Hosting.AzureFunctions;
+using Microsoft.Agents.AI.Workflows;
+using Microsoft.Azure.Functions.Worker.Builder;
+using Microsoft.Extensions.Hosting;
+using SingleAgent;
+
+// Set up an AI agent following the standard Microsoft Agent Framework pattern.
+
+OrderIdParserExecutor orderParser = new();
+PaymentProcesserExecutor paymentProcessor = new();
+EmailSenderExecutor emailSender = new();
+
+WorkflowBuilder builder = new(orderParser);
+builder.AddEdge(orderParser, paymentProcessor);
+builder.AddEdge(paymentProcessor, emailSender).WithOutputFrom(emailSender);
+var workflow = builder.WithName("ProcessOrder").Build();
+
+FunctionsApplication.CreateBuilder(args)
+    .ConfigureFunctionsWebApplication()
+    .ConfigureDurableOptions(options => options.Workflows.AddWorkflow(workflow))
+    .Build().Run();
@@ -0,0 +1,89 @@
+# Single Agent Sample
+
+This sample demonstrates how to use the Durable Agent Framework (DAFx) to create a simple Azure Functions app that hosts a single AI agent and provides direct HTTP API access for interactive conversations.
+
+## Key Concepts Demonstrated
+
+- Using the Microsoft Agent Framework to define a simple AI agent with a name and instructions.
+- Registering agents with the Function app and running them using HTTP.
+- Conversation management (via session IDs) for isolated interactions.
+
+## Environment Setup
+
+See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
+
+## Running the Sample
+
+With the environment setup and function app running, you can test the sample by sending an HTTP request to the agent endpoint.
+
+You can use the `demo.http` file to send a message to the agent, or a command line tool like `curl` as shown below:
+
+Bash (Linux/macOS/WSL):
+
+```bash
+curl -X POST http://localhost:7071/api/agents/Joker/run \
+    -H "Content-Type: text/plain" \
+    -d "Tell me a joke about a pirate."
+```
+
+PowerShell:
+
+```powershell
+Invoke-RestMethod -Method Post `
+    -Uri http://localhost:7071/api/agents/Joker/run `
+    -ContentType text/plain `
+    -Body "Tell me a joke about a pirate."
+```
+
+You can also send JSON requests:
+
+```bash
+curl -X POST http://localhost:7071/api/agents/Joker/run \
+    -H "Content-Type: application/json" \
+    -H "Accept: application/json" \
+    -d '{"message": "Tell me a joke about a pirate."}'
+```
+
+To continue a conversation, include the `thread_id` in the query string or JSON body:
+
+```bash
+curl -X POST "http://localhost:7071/api/agents/Joker/run?thread_id=your-thread-id" \
+    -H "Content-Type: application/json" \
+    -H "Accept: application/json" \
+    -d '{"message": "Tell me another one."}'
+```
+
+The response from the agent will be displayed in the terminal where you ran `func start`. The expected `text/plain` output will look something like:
+
+```text
+Why don't pirates ever learn the alphabet? Because they always get stuck at "C"!
+```
+
+The expected `application/json` output will look something like:
+
+```json
+{
+  "status": 200,
+  "thread_id": "ee6e47a0-f24b-40b1-ade8-16fcebb9eb40",
+  "response": {
+    "Messages": [
+      {
+        "AuthorName": "Joker",
+        "CreatedAt": "2025-11-11T12:00:00.0000000Z",
+        "Role": "assistant",
+        "Contents": [
+          {
+            "Type": "text",
+            "Text": "Why don't pirates ever learn the alphabet? Because they always get stuck at 'C'!"
+          }
+        ]
+      }
+    ],
+    "Usage": {
+      "InputTokenCount": 78,
+      "OutputTokenCount": 36,
+      "TotalTokenCount": 114
+    }
+  }
+}
+```
@@ -0,0 +1,14 @@
+# Default endpoint address for local testing
+@authority=http://localhost:7071
+
+### Start the workflow
+POST {{authority}}/api/workflows/ProcessOrder/run
+Content-Type: text/plain
+
+123
+
+### Start second workflow
+POST {{authority}}/api/workflows/ProcessOrder/run
+Content-Type: text/plain
+
+456
@@ -0,0 +1,20 @@
+{
+  "version": "2.0",
+  "logging": {
+    "logLevel": {
+      "Microsoft.Agents.AI.DurableTask": "Information",
+      "Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
+      "DurableTask": "Information",
+      "Microsoft.DurableTask": "Information"
+    }
+  },
+  "extensions": {
+    "durableTask": {
+      "hubName": "default",
+      "storageProvider": {
+        "type": "AzureManaged",
+        "connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
+      }
+    }
+  }
+}
@@ -0,0 +1,51 @@
+<Project Sdk="Microsoft.NET.Sdk">
+  <PropertyGroup>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+    <AzureFunctionsVersion>v4</AzureFunctionsVersion>
+    <OutputType>Exe</OutputType>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+    <!-- The Functions build tools don't like namespaces that start with a number -->
+    <AssemblyName>SingleAgent</AssemblyName>
+    <RootNamespace>SingleAgent</RootNamespace>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <FrameworkReference Include="Microsoft.AspNetCore.App" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <None Include="local.settings.json">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+      <CopyToPublishDirectory>Never</CopyToPublishDirectory>
+    </None>
+  </ItemGroup>
+
+  <!-- Azure Functions packages -->
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Azure.Functions.Worker" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
+  <!--
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
+    <PackageReference Include="Microsoft.Agents.AI.OpenAI" />
+  </ItemGroup>
+  -->
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Workflows\Microsoft.Agents.AI.Workflows.csproj" />
+  </ItemGroup>
+</Project>
@@ -0,0 +1,98 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to use durable state management in Azure Functions workflows.
+// The OrderIdParser writes a value to shared state, and the FraudValidation reads it back.
+// The state is persisted durably using Durable Entities behind the scenes.
+
+using Microsoft.Agents.AI.Workflows;
+
+namespace SingleAgent;
+
+/// <summary>
+/// Constants for shared state scopes used across executors.
+/// </summary>
+internal static class SharedStateConstants
+{
+    public const string MessageScope = "MessageState";
+    public const string ProcessedMessageKey = "ProcessedMessage";
+}
+
+internal sealed class Order
+{
+    public Order(string id, decimal amount)
+    {
+        this.Id = id;
+        this.Amount = amount;
+    }
+    public string Id { get; }
+    public decimal Amount { get; }
+    public Customer? Customer { get; set; }
+    public string? PaymentReferenceNumber { get; set; }
+}
+
+public sealed record Customer(int Id, string Name, bool IsBlocked);
+
+internal sealed class OrderIdParser() : Executor<string, Order>("OrderIdParser")
+{
+    public override async ValueTask<Order> HandleAsync(string message, IWorkflowContext context, CancellationToken cancellationToken = default)
+    {
+        return GetOrder(message);
+    }
+
+    private static Order GetOrder(string id)
+    {
+        // Simulate fetching order details
+        return new Order(id, 100.0m);
+    }
+}
+
+internal sealed class OrderEnrich() : Executor<Order, Order>("EnrichOrder")
+{
+    public override async ValueTask<Order> HandleAsync(Order message, IWorkflowContext context, CancellationToken cancellationToken = default)
+    {
+        message.Customer = GetCustomerForOrder(message.Id);
+        return message;
+    }
+
+    private static Customer GetCustomerForOrder(string orderId)
+    {
+        if (orderId.Contains('B'))
+        {
+            return new Customer(101, "George", true);
+        }
+
+        return new Customer(201, "Jerry", false);
+    }
+}
+
+internal sealed class PaymentProcesser() : Executor<Order, Order>("PaymentProcesser")
+{
+    public override async ValueTask<Order> HandleAsync(Order message, IWorkflowContext context, CancellationToken cancellationToken = default)
+    {
+        // Call payment gateway.
+        message.PaymentReferenceNumber = Guid.NewGuid().ToString().Substring(0, 4);
+        return message;
+    }
+}
+
+internal sealed class NotifyFraud() : Executor<Order, string>("NotifyFraud")
+{
+    public override async ValueTask<string> HandleAsync(Order message, IWorkflowContext context, CancellationToken cancellationToken = default)
+    {
+        // Notify fraud team.
+        return $"Order {message.Id} flagged as fraudulent for customer {message.Customer?.Name}.";
+    }
+}
+
+internal static class OrderRouteConditions
+{
+    /// <summary>
+    /// Returns a condition that evaluates to true when the customer is blocked.
+    /// </summary>
+    internal static Func<Order?, bool> WhenBlocked() => order => order?.Customer?.IsBlocked == true;
+
+    /// <summary>
+    /// Returns a condition that evaluates to true when the customer is not blocked.
+    /// </summary>
+    internal static Func<Order?, bool> WhenNotBlocked() => order => order?.Customer?.IsBlocked == false;
+}
@@ -0,0 +1,26 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using Microsoft.Agents.AI.Hosting.AzureFunctions;
+using Microsoft.Agents.AI.Workflows;
+using Microsoft.Azure.Functions.Worker.Builder;
+using Microsoft.Extensions.Hosting;
+using SingleAgent;
+
+OrderIdParser orderParser = new();
+OrderEnrich orderEnrich = new();
+PaymentProcesser paymentProcessor = new();
+NotifyFraud notifyFraud = new();
+
+WorkflowBuilder builder = new(orderParser);
+builder
+    .AddEdge(orderParser, orderEnrich)
+    .AddEdge(orderEnrich, notifyFraud, condition: OrderRouteConditions.WhenBlocked())
+    .AddEdge(orderEnrich, paymentProcessor, condition: OrderRouteConditions.WhenNotBlocked());
+
+var workflow = builder.WithName("AuditOrder").Build();
+
+FunctionsApplication.CreateBuilder(args)
+    .ConfigureFunctionsWebApplication()
+    .ConfigureDurableOptions(options => options.Workflows.AddWorkflow(workflow, enableMcpToolTrigger: true))
+    .Build()
+    .Run();
@@ -0,0 +1,89 @@
+# Single Agent Sample
+
+This sample demonstrates how to use the Durable Agent Framework (DAFx) to create a simple Azure Functions app that hosts a single AI agent and provides direct HTTP API access for interactive conversations.
+
+## Key Concepts Demonstrated
+
+- Using the Microsoft Agent Framework to define a simple AI agent with a name and instructions.
+- Registering agents with the Function app and running them using HTTP.
+- Conversation management (via session IDs) for isolated interactions.
+
+## Environment Setup
+
+See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
+
+## Running the Sample
+
+With the environment setup and function app running, you can test the sample by sending an HTTP request to the agent endpoint.
+
+You can use the `demo.http` file to send a message to the agent, or a command line tool like `curl` as shown below:
+
+Bash (Linux/macOS/WSL):
+
+```bash
+curl -X POST http://localhost:7071/api/agents/Joker/run \
+    -H "Content-Type: text/plain" \
+    -d "Tell me a joke about a pirate."
+```
+
+PowerShell:
+
+```powershell
+Invoke-RestMethod -Method Post `
+    -Uri http://localhost:7071/api/agents/Joker/run `
+    -ContentType text/plain `
+    -Body "Tell me a joke about a pirate."
+```
+
+You can also send JSON requests:
+
+```bash
+curl -X POST http://localhost:7071/api/agents/Joker/run \
+    -H "Content-Type: application/json" \
+    -H "Accept: application/json" \
+    -d '{"message": "Tell me a joke about a pirate."}'
+```
+
+To continue a conversation, include the `thread_id` in the query string or JSON body:
+
+```bash
+curl -X POST "http://localhost:7071/api/agents/Joker/run?thread_id=your-thread-id" \
+    -H "Content-Type: application/json" \
+    -H "Accept: application/json" \
+    -d '{"message": "Tell me another one."}'
+```
+
+The response from the agent will be displayed in the terminal where you ran `func start`. The expected `text/plain` output will look something like:
+
+```text
+Why don't pirates ever learn the alphabet? Because they always get stuck at "C"!
+```
+
+The expected `application/json` output will look something like:
+
+```json
+{
+  "status": 200,
+  "thread_id": "ee6e47a0-f24b-40b1-ade8-16fcebb9eb40",
+  "response": {
+    "Messages": [
+      {
+        "AuthorName": "Joker",
+        "CreatedAt": "2025-11-11T12:00:00.0000000Z",
+        "Role": "assistant",
+        "Contents": [
+          {
+            "Type": "text",
+            "Text": "Why don't pirates ever learn the alphabet? Because they always get stuck at 'C'!"
+          }
+        ]
+      }
+    ],
+    "Usage": {
+      "InputTokenCount": 78,
+      "OutputTokenCount": 36,
+      "TotalTokenCount": 114
+    }
+  }
+}
+```
@@ -0,0 +1,14 @@
+# Default endpoint address for local testing
+@authority=http://localhost:7071
+
+### Start the workflow
+POST {{authority}}/api/workflows/AuditOrder/run
+Content-Type: text/plain
+
+B123
+
+### Start second workflow
+POST {{authority}}/api/workflows/AuditOrder/run
+Content-Type: text/plain
+
+456
@@ -0,0 +1,20 @@
+{
+  "version": "2.0",
+  "logging": {
+    "logLevel": {
+      "Microsoft.Agents.AI.DurableTask": "Information",
+      "Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
+      "DurableTask": "Information",
+      "Microsoft.DurableTask": "Information"
+    }
+  },
+  "extensions": {
+    "durableTask": {
+      "hubName": "default",
+      "storageProvider": {
+        "type": "AzureManaged",
+        "connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
+      }
+    }
+  }
+}
@@ -0,0 +1,22 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Microsoft.DurableTask.Client.AzureManaged" />
+    <PackageReference Include="Microsoft.DurableTask.Worker.AzureManaged" />
+    <PackageReference Include="Microsoft.Extensions.Hosting" />
+  </ItemGroup>
+  
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Workflows\Microsoft.Agents.AI.Workflows.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,63 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using Microsoft.Agents.AI.Workflows;
+
+namespace WorkflowExecutorsAndEdgesSample;
+
+/// <summary>
+/// This sample introduces the concepts of executors and edges in a workflow.
+///
+/// Workflows are built from executors (processing units) connected by edges (data flow paths).
+/// In this example, we create a simple text processing pipeline that:
+/// 1. Takes input text and converts it to uppercase using an UppercaseExecutor
+/// 2. Takes the uppercase text and reverses it using a ReverseTextExecutor
+///
+/// The executors are connected sequentially, so data flows from one to the next in order.
+/// For input "Hello, World!", the workflow produces "!DLROW ,OLLEH".
+/// </summary>
+public static class Program
+{
+    private static async Task Main()
+    {
+        // Create the executors
+        Func<string, string> uppercaseFunc = s => s.ToUpperInvariant();
+        var uppercase = uppercaseFunc.BindAsExecutor("UppercaseExecutor");
+
+        ReverseTextExecutor reverse = new();
+
+        // Build the workflow by connecting executors sequentially
+        WorkflowBuilder builder = new(uppercase);
+        builder.AddEdge(uppercase, reverse).WithOutputFrom(reverse);
+        var workflow = builder.Build();
+
+        // Execute the workflow with input data
+        await using Run run = await InProcessExecution.RunAsync(workflow, "Hello, World!");
+        foreach (WorkflowEvent evt in run.NewEvents)
+        {
+            if (evt is ExecutorCompletedEvent executorComplete)
+            {
+                Console.WriteLine($"{executorComplete.ExecutorId}: {executorComplete.Data}");
+            }
+        }
+    }
+}
+
+/// <summary>
+/// Second executor: reverses the input text and completes the workflow.
+/// </summary>
+internal sealed class ReverseTextExecutor() : Executor<string, string>("ReverseTextExecutor")
+{
+    /// <summary>
+    /// Processes the input message by reversing the text.
+    /// </summary>
+    /// <param name="message">The input text to reverse</param>
+    /// <param name="context">Workflow context for accessing workflow services and adding events</param>
+    /// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests.
+    /// The default is <see cref="CancellationToken.None"/>.</param>
+    /// <returns>The input text reversed</returns>
+    public override ValueTask<string> HandleAsync(string message, IWorkflowContext context, CancellationToken cancellationToken = default)
+    {
+        // Because we do not suppress it, the returned result will be yielded as an output from this executor.
+        return ValueTask.FromResult(string.Concat(message.Reverse()));
+    }
+}
@@ -16,10 +16,10 @@ AgentCard agentCard = await agentCardResolver.GetAgentCardAsync();
 // Create an instance of the AIAgent for an existing A2A agent specified by the agent card.
 AIAgent agent = agentCard.GetAIAgent();

-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();

 // Start the initial run with a long-running task.
-AgentResponse response = await agent.RunAsync("Conduct a comprehensive analysis of quantum computing applications in cryptography, including recent breakthroughs, implementation challenges, and future roadmap. Please include diagrams and visual representations to illustrate complex concepts.", thread);
+AgentRunResponse response = await agent.RunAsync("Conduct a comprehensive analysis of quantum computing applications in cryptography, including recent breakthroughs, implementation challenges, and future roadmap. Please include diagrams and visual representations to illustrate complex concepts.", thread);

 // Poll until the response is complete.
 while (response.ContinuationToken is { } token)
@@ -212,7 +212,7 @@ dotnet run

 1. `AGUIAgent` sends HTTP POST request to server
 2. Server responds with SSE stream
-3. Client parses events into `AgentResponseUpdate` objects
+3. Client parses events into `AgentRunResponseUpdate` objects
 4. Updates are displayed based on content type
 5. `ConversationId` maintains conversation context

@@ -20,7 +20,7 @@ AIAgent agent = chatClient.CreateAIAgent(
    name: "agui-client",
    description: "AG-UI Client Agent");

-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();
 List<ChatMessage> messages =
 [
    new(ChatRole.System, "You are a helpful assistant.")
@@ -51,7 +51,7 @@ try
        bool isFirstUpdate = true;
        string? threadId = null;

-        await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread))
+        await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread))
        {
            ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();

@@ -20,7 +20,7 @@ AIAgent agent = chatClient.CreateAIAgent(
    name: "agui-client",
    description: "AG-UI Client Agent");

-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();
 List<ChatMessage> messages =
 [
    new(ChatRole.System, "You are a helpful assistant.")
@@ -51,7 +51,7 @@ try
        bool isFirstUpdate = true;
        string? threadId = null;

-        await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread))
+        await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread))
        {
            ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();

@@ -33,7 +33,7 @@ AIAgent agent = chatClient.CreateAIAgent(
    description: "AG-UI Client Agent",
    tools: frontendTools);

-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();
 List<ChatMessage> messages =
 [
    new(ChatRole.System, "You are a helpful assistant.")
@@ -64,7 +64,7 @@ try
        bool isFirstUpdate = true;
        string? threadId = null;

-        await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread))
+        await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread))
        {
            ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();

@@ -51,8 +51,8 @@ while ((input = Console.ReadLine()) != null && !input.Equals("exit", StringCompa
    {
        approvalResponses.Clear();

-        List<AgentResponseUpdate> chatResponseUpdates = [];
-        await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread, cancellationToken: default))
+        List<AgentRunResponseUpdate> chatResponseUpdates = [];
+        await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread, cancellationToken: default))
        {
            chatResponseUpdates.Add(update);
            foreach (AIContent content in update.Contents)
@@ -111,7 +111,7 @@ while ((input = Console.ReadLine()) != null && !input.Equals("exit", StringCompa
            }
        }

-        AgentResponse response = chatResponseUpdates.ToAgentResponse();
+        AgentRunResponse response = chatResponseUpdates.ToAgentRunResponse();
        messages.AddRange(response.Messages);
        foreach (AIContent approvalResponse in approvalResponses)
        {
@@ -22,17 +22,17 @@ internal sealed class ServerFunctionApprovalClientAgent : DelegatingAIAgent
        this._jsonSerializerOptions = jsonSerializerOptions;
    }

-    protected override Task<AgentResponse> RunCoreAsync(
+    protected override Task<AgentRunResponse> RunCoreAsync(
        IEnumerable<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
        CancellationToken cancellationToken = default)
    {
        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken)
-            .ToAgentResponseAsync(cancellationToken);
+            .ToAgentRunResponseAsync(cancellationToken);
    }

-    protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
+    protected override async IAsyncEnumerable<AgentRunResponseUpdate> RunCoreStreamingAsync(
        IEnumerable<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
@@ -166,8 +166,8 @@ internal sealed class ServerFunctionApprovalClientAgent : DelegatingAIAgent
        return result ?? messages;
    }

-    private static AgentResponseUpdate ProcessIncomingServerApprovalRequests(
-        AgentResponseUpdate update,
+    private static AgentRunResponseUpdate ProcessIncomingServerApprovalRequests(
+        AgentRunResponseUpdate update,
        JsonSerializerOptions jsonSerializerOptions)
    {
        IList<AIContent>? updatedContents = null;
@@ -215,7 +215,7 @@ internal sealed class ServerFunctionApprovalClientAgent : DelegatingAIAgent
        if (updatedContents is not null)
        {
            var chatUpdate = update.AsChatResponseUpdate();
-            return new AgentResponseUpdate(new ChatResponseUpdate()
+            return new AgentRunResponseUpdate(new ChatResponseUpdate()
            {
                Role = chatUpdate.Role,
                Contents = updatedContents,
@@ -22,17 +22,17 @@ internal sealed class ServerFunctionApprovalAgent : DelegatingAIAgent
        this._jsonSerializerOptions = jsonSerializerOptions;
    }

-    protected override Task<AgentResponse> RunCoreAsync(
+    protected override Task<AgentRunResponse> RunCoreAsync(
        IEnumerable<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
        CancellationToken cancellationToken = default)
    {
        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken)
-            .ToAgentResponseAsync(cancellationToken);
+            .ToAgentRunResponseAsync(cancellationToken);
    }

-    protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
+    protected override async IAsyncEnumerable<AgentRunResponseUpdate> RunCoreStreamingAsync(
        IEnumerable<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
@@ -172,8 +172,8 @@ internal sealed class ServerFunctionApprovalAgent : DelegatingAIAgent
        return result ?? messages;
    }

-    private static AgentResponseUpdate ProcessOutgoingApprovalRequests(
-        AgentResponseUpdate update,
+    private static AgentRunResponseUpdate ProcessOutgoingApprovalRequests(
+        AgentRunResponseUpdate update,
        JsonSerializerOptions jsonSerializerOptions)
    {
        IList<AIContent>? updatedContents = null;
@@ -207,7 +207,7 @@ internal sealed class ServerFunctionApprovalAgent : DelegatingAIAgent
        {
            var chatUpdate = update.AsChatResponseUpdate();
            // Yield a tool call update that represents the approval request
-            return new AgentResponseUpdate(new ChatResponseUpdate()
+            return new AgentRunResponseUpdate(new ChatResponseUpdate()
            {
                Role = chatUpdate.Role,
                Contents = updatedContents,
@@ -30,7 +30,7 @@ JsonSerializerOptions jsonOptions = new(JsonSerializerDefaults.Web)
 };
 StatefulAgent<AgentState> agent = new(baseAgent, jsonOptions, new AgentState());

-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();
 List<ChatMessage> messages =
 [
    new(ChatRole.System, "You are a helpful recipe assistant.")
@@ -70,7 +70,7 @@ try

        Console.WriteLine();

-        await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread))
+        await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread))
        {
            ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();

@@ -35,18 +35,18 @@ internal sealed class StatefulAgent<TState> : DelegatingAIAgent
    }

    /// <inheritdoc />
-    protected override Task<AgentResponse> RunCoreAsync(
+    protected override Task<AgentRunResponse> RunCoreAsync(
        IEnumerable<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
        CancellationToken cancellationToken = default)
    {
        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken)
-            .ToAgentResponseAsync(cancellationToken);
+            .ToAgentRunResponseAsync(cancellationToken);
    }

    /// <inheritdoc />
-    protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
+    protected override async IAsyncEnumerable<AgentRunResponseUpdate> RunCoreStreamingAsync(
        IEnumerable<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
@@ -64,7 +64,7 @@ internal sealed class StatefulAgent<TState> : DelegatingAIAgent
        messagesWithState.Add(stateMessage);

        // Stream the response and update state when received
-        await foreach (AgentResponseUpdate update in this.InnerAgent.RunStreamingAsync(messagesWithState, thread, options, cancellationToken))
+        await foreach (AgentRunResponseUpdate update in this.InnerAgent.RunStreamingAsync(messagesWithState, thread, options, cancellationToken))
        {
            // Check if this update contains a state snapshot
            foreach (AIContent content in update.Contents)
@@ -17,17 +17,17 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
        this._jsonSerializerOptions = jsonSerializerOptions;
    }

-    protected override Task<AgentResponse> RunCoreAsync(
+    protected override Task<AgentRunResponse> RunCoreAsync(
        IEnumerable<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
        CancellationToken cancellationToken = default)
    {
        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken)
-            .ToAgentResponseAsync(cancellationToken);
+            .ToAgentRunResponseAsync(cancellationToken);
    }

-    protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
+    protected override async IAsyncEnumerable<AgentRunResponseUpdate> RunCoreStreamingAsync(
        IEnumerable<ChatMessage> messages,
        AgentThread? thread = null,
        AgentRunOptions? options = null,
@@ -91,7 +91,7 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
        var firstRunMessages = messages.Append(stateUpdateMessage);

        // Collect all updates from first run
-        var allUpdates = new List<AgentResponseUpdate>();
+        var allUpdates = new List<AgentRunResponseUpdate>();
        await foreach (var update in this.InnerAgent.RunStreamingAsync(firstRunMessages, thread, firstRunOptions, cancellationToken).ConfigureAwait(false))
        {
            allUpdates.Add(update);
@@ -104,7 +104,7 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
            }
        }

-        var response = allUpdates.ToAgentResponse();
+        var response = allUpdates.ToAgentRunResponse();

        // Try to deserialize the structured state response
        if (response.TryDeserialize(this._jsonSerializerOptions, out JsonElement stateSnapshot))
@@ -113,7 +113,7 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
            byte[] stateBytes = JsonSerializer.SerializeToUtf8Bytes(
                stateSnapshot,
                this._jsonSerializerOptions.GetTypeInfo(typeof(JsonElement)));
-            yield return new AgentResponseUpdate
+            yield return new AgentRunResponseUpdate
            {
                Contents = [new DataContent(stateBytes, "application/json")]
            };
@@ -128,7 +128,7 @@ var agent = new ChatClientAgent(instrumentedChatClient,
    .UseOpenTelemetry(SourceName, configure: (cfg) => cfg.EnableSensitiveData = true) // enable telemetry at the agent level
    .Build();

-var thread = await agent.GetNewThreadAsync();
+var thread = agent.GetNewThread();

 appLogger.LogInformation("Agent created successfully with ID: {AgentId}", agent.Id);

@@ -14,5 +14,5 @@ A2ACardResolver agentCardResolver = new(new Uri(a2aAgentHost));
 AIAgent agent = await agentCardResolver.GetAIAgentAsync();

 // Invoke the agent and output the text result.
-AgentResponse response = await agent.RunAsync("Tell me a joke about a pirate.");
+AgentRunResponse response = await agent.RunAsync("Tell me a joke about a pirate.");
 Console.WriteLine(response);
@@ -29,6 +29,6 @@ A2AClient a2aClient = new(new Uri("https://your-a2a-agent-host/echo"));
 AIAgent agent = a2aClient.GetAIAgent();

 // Run the agent
-AgentResponse response = await agent.RunAsync("Tell me a joke about a pirate.");
+AgentRunResponse response = await agent.RunAsync("Tell me a joke about a pirate.");
 Console.WriteLine(response);
 ```
@@ -31,7 +31,7 @@ AIAgent agent2 = await persistentAgentsClient.CreateAIAgentAsync(
    instructions: JokerInstructions);

 // You can then invoke the agent like any other AIAgent.
-AgentThread thread = await agent1.GetNewThreadAsync();
+AgentThread thread = agent1.GetNewThread();
 Console.WriteLine(await agent1.RunAsync("Tell me a joke about a pirate.", thread));

 // Cleanup for sample purposes.
@@ -40,7 +40,7 @@ var latestAgentVersion = jokerAgentLatest.GetService<AgentVersion>()!;
 Console.WriteLine($"Latest agent version id: {latestAgentVersion.Id}");

 // Once you have the AIAgent, you can invoke it like any other AIAgent.
-AgentThread thread = await jokerAgentLatest.GetNewThreadAsync();
+AgentThread thread = jokerAgentLatest.GetNewThread();
 Console.WriteLine(await jokerAgentLatest.RunAsync("Tell me a joke about a pirate.", thread));

 // This will use the same thread to continue the conversation.
@@ -28,16 +28,16 @@ namespace SampleApp
    {
        public override string? Name => "UpperCaseParrotAgent";

-        public override ValueTask<AgentThread> GetNewThreadAsync(CancellationToken cancellationToken = default)
-            => new(new CustomAgentThread());
+        public override AgentThread GetNewThread()
+            => new CustomAgentThread();

-        public override ValueTask<AgentThread> DeserializeThreadAsync(JsonElement serializedThread, JsonSerializerOptions? jsonSerializerOptions = null, CancellationToken cancellationToken = default)
-            => new(new CustomAgentThread(serializedThread, jsonSerializerOptions));
+        public override AgentThread DeserializeThread(JsonElement serializedThread, JsonSerializerOptions? jsonSerializerOptions = null)
+            => new CustomAgentThread(serializedThread, jsonSerializerOptions);

-        protected override async Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
+        protected override async Task<AgentRunResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
        {
            // Create a thread if the user didn't supply one.
-            thread ??= await this.GetNewThreadAsync(cancellationToken);
+            thread ??= this.GetNewThread();

            if (thread is not CustomAgentThread typedThread)
            {
@@ -58,7 +58,7 @@ namespace SampleApp
            };
            await typedThread.MessageStore.InvokedAsync(invokedContext, cancellationToken);

-            return new AgentResponse
+            return new AgentRunResponse
            {
                AgentId = this.Id,
                ResponseId = Guid.NewGuid().ToString("N"),
@@ -66,10 +66,10 @@ namespace SampleApp
            };
        }

-        protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default)
+        protected override async IAsyncEnumerable<AgentRunResponseUpdate> RunCoreStreamingAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default)
        {
            // Create a thread if the user didn't supply one.
-            thread ??= await this.GetNewThreadAsync(cancellationToken);
+            thread ??= this.GetNewThread();

            if (thread is not CustomAgentThread typedThread)
            {
@@ -92,7 +92,7 @@ namespace SampleApp

            foreach (var message in responseMessages)
            {
-                yield return new AgentResponseUpdate
+                yield return new AgentRunResponseUpdate
                {
                    AgentId = this.Id,
                    AuthorName = message.AuthorName,
@@ -22,7 +22,7 @@ ChatClientAgent agentGenAI = new(
    name: JokerName,
    instructions: JokerInstructions);

-AgentResponse response = await agentGenAI.RunAsync("Tell me a joke about a pirate.");
+AgentRunResponse response = await agentGenAI.RunAsync("Tell me a joke about a pirate.");
 Console.WriteLine($"Google GenAI client based agent response:\n{response}");

 // Using a community driven Mscc.GenerativeAI.Microsoft package
@@ -33,7 +33,7 @@ AIAgent agent2 = await assistantClient.CreateAIAgentAsync(
    instructions: JokerInstructions);

 // You can invoke the agent like any other AIAgent.
-AgentThread thread = await agent1.GetNewThreadAsync();
+AgentThread thread = agent1.GetNewThread();
 Console.WriteLine(await agent1.RunAsync("Tell me a joke about a pirate.", thread));

 // Cleanup for sample purposes.
@@ -26,12 +26,12 @@ AIAgent agent = new AnthropicClient { APIKey = apiKey }
    .CreateAIAgent(model: model, instructions: AssistantInstructions, name: AssistantName, tools: [tool]);

 // Non-streaming agent interaction with function tools.
-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();
 Console.WriteLine(await agent.RunAsync("What is the weather like in Amsterdam?", thread));

 // Streaming agent interaction with function tools.
-thread = await agent.GetNewThreadAsync();
-await foreach (AgentResponseUpdate update in agent.RunStreamingAsync("What is the weather like in Amsterdam?", thread))
+thread = agent.GetNewThread();
+await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync("What is the weather like in Amsterdam?", thread))
 {
    Console.WriteLine(update);
 }
@@ -34,7 +34,7 @@ AIAgent agent = new AzureOpenAIClient(
    {
        ChatOptions = new() { Instructions = "You are good at telling jokes." },
        Name = "Joker",
-        AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(new ChatHistoryMemoryProvider(
+        AIContextProviderFactory = (ctx) => new ChatHistoryMemoryProvider(
            vectorStore,
            collectionName: "chathistory",
            vectorDimensions: 3072,
@@ -43,18 +43,18 @@ AIAgent agent = new AzureOpenAIClient(
            storageScope: new() { UserId = "UID1", ThreadId = new Guid().ToString() },
            // Configure the scope which would be used to search for relevant prior messages.
            // In this case, we are searching for any messages for the user across all threads.
-            searchScope: new() { UserId = "UID1" }))
+            searchScope: new() { UserId = "UID1" })
    });

 // Start a new thread for the agent conversation.
-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();

 // Run the agent with the thread that stores conversation history in the vector store.
 Console.WriteLine(await agent.RunAsync("I like jokes about Pirates. Tell me a joke about a pirate.", thread));

 // Start a second thread. Since we configured the search scope to be across all threads for the user,
 // the agent should remember that the user likes pirate jokes.
-AgentThread thread2 = await agent.GetNewThreadAsync();
+AgentThread thread2 = agent.GetNewThread();

 // Run the agent with the second thread.
 Console.WriteLine(await agent.RunAsync("Tell me a joke that I might like.", thread2));
@@ -31,16 +31,16 @@ AIAgent agent = new AzureOpenAIClient(
    .CreateAIAgent(new ChatClientAgentOptions()
    {
        ChatOptions = new() { Instructions = "You are a friendly travel assistant. Use known memories about the user when responding, and do not invent details." },
-        AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(ctx.SerializedState.ValueKind is not JsonValueKind.Null and not JsonValueKind.Undefined
+        AIContextProviderFactory = ctx => ctx.SerializedState.ValueKind is not JsonValueKind.Null and not JsonValueKind.Undefined
            // If each thread should have its own Mem0 scope, you can create a new id per thread here:
            // ? new Mem0Provider(mem0HttpClient, new Mem0ProviderScope() { ThreadId = Guid.NewGuid().ToString() })
            // In this case we are storing memories scoped by application and user instead so that memories are retained across threads.
            ? new Mem0Provider(mem0HttpClient, new Mem0ProviderScope() { ApplicationId = "getting-started-agents", UserId = "sample-user" })
            // For cases where we are restoring from serialized state:
-            : new Mem0Provider(mem0HttpClient, ctx.SerializedState, ctx.JsonSerializerOptions))
+            : new Mem0Provider(mem0HttpClient, ctx.SerializedState, ctx.JsonSerializerOptions)
    });

-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();

 // Clear any existing memories for this scope to demonstrate fresh behavior.
 Mem0Provider mem0Provider = thread.GetService<Mem0Provider>()!;
@@ -56,9 +56,9 @@ Console.WriteLine(await agent.RunAsync("What do you already know about my upcomi

 Console.WriteLine("\n>> Serialize and deserialize the thread to demonstrate persisted state\n");
 JsonElement serializedThread = thread.Serialize();
-AgentThread restoredThread = await agent.DeserializeThreadAsync(serializedThread);
+AgentThread restoredThread = agent.DeserializeThread(serializedThread);
 Console.WriteLine(await agent.RunAsync("Can you recap the personal details you remember?", restoredThread));

 Console.WriteLine("\n>> Start a new thread that shares the same Mem0 scope\n");
-AgentThread newThread = await agent.GetNewThreadAsync();
+AgentThread newThread = agent.GetNewThread();
 Console.WriteLine(await agent.RunAsync("Summarize what you already know about me.", newThread));
@@ -33,11 +33,11 @@ ChatClient chatClient = new AzureOpenAIClient(
 AIAgent agent = chatClient.CreateAIAgent(new ChatClientAgentOptions()
 {
    ChatOptions = new() { Instructions = "You are a friendly assistant. Always address the user by their name." },
-    AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(new UserInfoMemory(chatClient.AsIChatClient(), ctx.SerializedState, ctx.JsonSerializerOptions))
+    AIContextProviderFactory = ctx => new UserInfoMemory(chatClient.AsIChatClient(), ctx.SerializedState, ctx.JsonSerializerOptions)
 });

 // Create a new thread for the conversation.
-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();

 Console.WriteLine(">> Use thread with blank memory\n");

@@ -52,7 +52,7 @@ var threadElement = thread.Serialize();
 Console.WriteLine("\n>> Use deserialized thread with previously created memories\n");

 // Later we can deserialize the thread and continue the conversation with the previous memory component state.
-var deserializedThread = await agent.DeserializeThreadAsync(threadElement);
+var deserializedThread = agent.DeserializeThread(threadElement);
 Console.WriteLine(await agent.RunAsync("What is my name and age?", deserializedThread));

 Console.WriteLine("\n>> Read memories from memory component\n");
@@ -68,7 +68,7 @@ Console.WriteLine("\n>> Use new thread with previously created memories\n");

 // It is also possible to set the memories in a memory component on an individual thread.
 // This is useful if we want to start a new thread, but have it share the same memories as a previous thread.
-var newThread = await agent.GetNewThreadAsync();
+var newThread = agent.GetNewThread();
 if (userInfo is not null && newThread.GetService<UserInfoMemory>() is UserInfoMemory newThreadMemory)
 {
    newThreadMemory.UserInfo = userInfo;
@@ -87,10 +87,10 @@ public class OpenAIChatClientAgent : DelegatingAIAgent
    }

    /// <inheritdoc/>
-    protected sealed override Task<AgentResponse> RunCoreAsync(IEnumerable<Microsoft.Extensions.AI.ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
+    protected sealed override Task<AgentRunResponse> RunCoreAsync(IEnumerable<Microsoft.Extensions.AI.ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
        base.RunCoreAsync(messages, thread, options, cancellationToken);

    /// <inheritdoc/>
-    protected override IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(IEnumerable<Microsoft.Extensions.AI.ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
+    protected override IAsyncEnumerable<AgentRunResponseUpdate> RunCoreStreamingAsync(IEnumerable<Microsoft.Extensions.AI.ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
        base.RunCoreStreamingAsync(messages, thread, options, cancellationToken);
 }
@@ -105,10 +105,10 @@ public class OpenAIResponseClientAgent : DelegatingAIAgent
    }

    /// <inheritdoc/>
-    protected sealed override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
+    protected sealed override Task<AgentRunResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
        base.RunCoreAsync(messages, thread, options, cancellationToken);

    /// <inheritdoc/>
-    protected sealed override IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
+    protected sealed override IAsyncEnumerable<AgentRunResponseUpdate> RunCoreStreamingAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default) =>
        base.RunCoreStreamingAsync(messages, thread, options, cancellationToken);
 }
@@ -30,7 +30,7 @@ using JsonDocument createConversationResultAsJson = JsonDocument.Parse(createCon
 string conversationId = createConversationResultAsJson.RootElement.GetProperty("id"u8)!.GetString()!;

 // Create a thread for the conversation - this enables conversation state management for subsequent turns
-AgentThread thread = await agent.GetNewThreadAsync(conversationId);
+AgentThread thread = agent.GetNewThread(conversationId);

 Console.WriteLine("=== Multi-turn Conversation Demo ===\n");

@@ -33,7 +33,7 @@ The `AgentThread` works with `ChatClientAgentRunOptions` to link the agent to a
 ChatClientAgentRunOptions agentRunOptions = new() { ChatOptions = new ChatOptions() { ConversationId = conversationId } };

 // Create a thread for the conversation
-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();

 // First call links the thread to the conversation
 ChatCompletion firstResponse = await agent.RunAsync([firstMessage], thread, agentRunOptions);
@@ -59,7 +59,7 @@ foreach (ClientResult result in getConversationItemsResults.GetRawPages())
 1. **Create an OpenAI Client**: Initialize an `OpenAIClient` with your API key
 2. **Create a Conversation**: Use `ConversationClient` to create a server-side conversation
 3. **Create an Agent**: Initialize an `OpenAIResponseClientAgent` with the desired model and instructions
-4. **Create a Thread**: Call `agent.GetNewThreadAsync()` to create a new conversation thread
+4. **Create a Thread**: Call `agent.GetNewThread()` to create a new conversation thread
 5. **Link Thread to Conversation**: Pass `ChatClientAgentRunOptions` with the `ConversationId` on the first call
 6. **Send Messages**: Subsequent calls to `agent.RunAsync()` only need the thread - context is maintained
 7. **Cleanup**: Delete the conversation when done using `conversationClient.DeleteConversation()`
@@ -62,15 +62,15 @@ AIAgent agent = azureOpenAIClient
    .CreateAIAgent(new ChatClientAgentOptions
    {
        ChatOptions = new() { Instructions = "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available." },
-        AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(new TextSearchProvider(SearchAdapter, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions)),
+        AIContextProviderFactory = ctx => new TextSearchProvider(SearchAdapter, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions),
        // Since we are using ChatCompletion which stores chat history locally, we can also add a message removal policy
        // that removes messages produced by the TextSearchProvider before they are added to the chat history, so that
        // we don't bloat chat history with all the search result messages.
-        ChatMessageStoreFactory = (ctx, ct) => new ValueTask<ChatMessageStore>(new InMemoryChatMessageStore(ctx.SerializedState, ctx.JsonSerializerOptions)
-            .WithAIContextProviderMessageRemoval()),
+        ChatMessageStoreFactory = ctx => new InMemoryChatMessageStore(ctx.SerializedState, ctx.JsonSerializerOptions)
+            .WithAIContextProviderMessageRemoval(),
    });

-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();

 Console.WriteLine(">> Asking about returns\n");
 Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", thread));
@@ -71,10 +71,10 @@ AIAgent agent = azureOpenAIClient
    .CreateAIAgent(new ChatClientAgentOptions
    {
        ChatOptions = new() { Instructions = "You are a helpful support specialist for the Microsoft Agent Framework. Answer questions using the provided context and cite the source document when available. Keep responses brief." },
-        AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(new TextSearchProvider(SearchAdapter, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions))
+        AIContextProviderFactory = ctx => new TextSearchProvider(SearchAdapter, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions)
    });

-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();

 Console.WriteLine(">> Asking about SK threads\n");
 Console.WriteLine(await agent.RunAsync("Hi! How do I create a thread in Semantic Kernel?", thread));
@@ -29,10 +29,10 @@ AIAgent agent = new AzureOpenAIClient(
    .CreateAIAgent(new ChatClientAgentOptions
    {
        ChatOptions = new() { Instructions = "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available." },
-        AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(new TextSearchProvider(MockSearchAsync, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions))
+        AIContextProviderFactory = ctx => new TextSearchProvider(MockSearchAsync, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions)
    });

-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();

 Console.WriteLine(">> Asking about returns\n");
 Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", thread));
@@ -43,7 +43,7 @@ AIAgent agent = await aiProjectClient
        instructions: "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available.",
        tools: [fileSearchTool]);

-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();

 Console.WriteLine(">> Asking about returns\n");
 Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", thread));
@@ -17,12 +17,12 @@ AIAgent agent = new AzureOpenAIClient(
    .CreateAIAgent(instructions: "You are good at telling jokes.", name: "Joker");

 // Invoke the agent with a multi-turn conversation, where the context is preserved in the thread object.
-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();
 Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", thread));
 Console.WriteLine(await agent.RunAsync("Now add some emojis to the joke and tell it in the voice of a pirate's parrot.", thread));

 // Invoke the agent with a multi-turn conversation and streaming, where the context is preserved in the thread object.
-thread = await agent.GetNewThreadAsync();
+thread = agent.GetNewThread();
 await foreach (var update in agent.RunStreamingAsync("Tell me a joke about a pirate.", thread))
 {
    Console.WriteLine(update);
@@ -30,7 +30,7 @@ AIAgent agent = new AzureOpenAIClient(
    .CreateAIAgent(instructions: "You are a helpful assistant", tools: [new ApprovalRequiredAIFunction(AIFunctionFactory.Create(GetWeather))]);

 // Call the agent and check if there are any user input requests to handle.
-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();
 var response = await agent.RunAsync("What is the weather like in Amsterdam?", thread);
 var userInputRequests = response.UserInputRequests.ToList();

@@ -64,4 +64,4 @@ while (userInputRequests.Count > 0)
 Console.WriteLine($"\nAgent: {response}");

 // For streaming use:
-// Console.WriteLine($"\nAgent: {updates.ToAgentResponse()}");
+// Console.WriteLine($"\nAgent: {updates.ToAgentRunResponse()}");
@@ -24,7 +24,7 @@ ChatClient chatClient = new AzureOpenAIClient(
 ChatClientAgent agent = chatClient.CreateAIAgent(name: "HelpfulAssistant", instructions: "You are a helpful assistant.");

 // Set PersonInfo as the type parameter of RunAsync method to specify the expected structured output from the agent and invoke the agent with some unstructured input.
-AgentResponse<PersonInfo> response = await agent.RunAsync<PersonInfo>("Please provide information about John Smith, who is a 35-year-old software engineer.");
+AgentRunResponse<PersonInfo> response = await agent.RunAsync<PersonInfo>("Please provide information about John Smith, who is a 35-year-old software engineer.");

 // Access the structured output via the Result property of the agent response.
 Console.WriteLine("Assistant Output:");
@@ -44,7 +44,7 @@ var updates = agentWithPersonInfo.RunStreamingAsync("Please provide information

 // Assemble all the parts of the streamed output, since we can only deserialize once we have the full json,
 // then deserialize the response into the PersonInfo class.
-PersonInfo personInfo = (await updates.ToAgentResponseAsync()).Deserialize<PersonInfo>(JsonSerializerOptions.Web);
+PersonInfo personInfo = (await updates.ToAgentRunResponseAsync()).Deserialize<PersonInfo>(JsonSerializerOptions.Web);

 Console.WriteLine("Assistant Output:");
 Console.WriteLine($"Name: {personInfo.Name}");
@@ -19,7 +19,7 @@ AIAgent agent = new AzureOpenAIClient(
    .CreateAIAgent(instructions: "You are good at telling jokes.", name: "Joker");

 // Start a new thread for the agent conversation.
-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();

 // Run the agent with a new thread.
 Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", thread));
@@ -35,7 +35,7 @@ await File.WriteAllTextAsync(tempFilePath, JsonSerializer.Serialize(serializedTh
 JsonElement reloadedSerializedThread = JsonElement.Parse(await File.ReadAllTextAsync(tempFilePath));

 // Deserialize the thread state after loading from storage.
-AgentThread resumedThread = await agent.DeserializeThreadAsync(reloadedSerializedThread);
+AgentThread resumedThread = agent.DeserializeThread(reloadedSerializedThread);

 // Run the agent again with the resumed thread.
 Console.WriteLine(await agent.RunAsync("Now tell the same joke in the voice of a pirate, and add some emojis to the joke.", resumedThread));
@@ -31,15 +31,17 @@ AIAgent agent = new AzureOpenAIClient(
    {
        ChatOptions = new() { Instructions = "You are good at telling jokes." },
        Name = "Joker",
-        ChatMessageStoreFactory = (ctx, ct) => new ValueTask<ChatMessageStore>(
+        ChatMessageStoreFactory = ctx =>
+        {
            // Create a new chat message store for this agent that stores the messages in a vector store.
            // Each thread must get its own copy of the VectorChatMessageStore, since the store
            // also contains the id that the thread is stored under.
-            new VectorChatMessageStore(vectorStore, ctx.SerializedState, ctx.JsonSerializerOptions))
+            return new VectorChatMessageStore(vectorStore, ctx.SerializedState, ctx.JsonSerializerOptions);
+        }
    });

 // Start a new thread for the agent conversation.
-AgentThread thread = await agent.GetNewThreadAsync();
+AgentThread thread = agent.GetNewThread();

 // Run the agent with the thread that stores conversation history in the vector store.
 Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", thread));
@@ -56,7 +58,7 @@ Console.WriteLine(JsonSerializer.Serialize(serializedThread, new JsonSerializerO
 // and loaded again later.

 // Deserialize the thread state after loading from storage.
-AgentThread resumedThread = await agent.DeserializeThreadAsync(serializedThread);
+AgentThread resumedThread = agent.DeserializeThread(serializedThread);

 // Run the agent with the thread that stores conversation history in the vector store a second time.
 Console.WriteLine(await agent.RunAsync("Now tell the same joke in the voice of a pirate, and add some emojis to the joke.", resumedThread));
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Shyju Krishnankutty	52da946efd	minor tweaks	2026-01-23 10:16:31 -08:00
Shyju Krishnankutty	859ac0939d	Minor cleanup	2026-01-23 07:48:31 -08:00
Shyju Krishnankutty	c40e5a9020	Fid http URL for test	2026-01-23 07:05:02 -08:00
Shyju Krishnankutty	12256b59aa	Working demos	2026-01-22 22:09:33 -08:00
Shyju Krishnankutty	04fdf25019	Conditional edge routing sample.	2026-01-22 21:27:53 -08:00
Shyju Krishnankutty	29fb22f7d8	Minor cleanup	2026-01-22 17:11:30 -08:00
Shyju Krishnankutty	38fc0b8e08	Remove unused files.	2026-01-22 09:16:11 -08:00
Shyju Krishnankutty	34114f8d7b	Cleanup	2026-01-21 20:19:23 -08:00
Shyju Krishnankutty	38c8f3ec18	minor cleanup.	2026-01-21 17:55:21 -08:00
Shyju Krishnankutty	6a49da6f1c	Minor cleanup. MCP tool works.	2026-01-21 17:39:53 -08:00
Shyju Krishnankutty	d3bfbcbf52	WIP-Run workflow as mcp tool.	2026-01-21 15:28:24 -08:00
Shyju Krishnankutty	588e0bc0b2	WIP	2026-01-21 10:49:10 -08:00
Shyju Krishnankutty	00650f2525	Minor cleanups	2026-01-20 20:20:15 -08:00
Shyju Krishnankutty	530f8b389a	Move relevant stuff to DurableTask project from Hosting.AzureFunctions	2026-01-20 16:22:19 -08:00
Shyju Krishnankutty	8c3182e4e8	Shared state support using durable entity.	2026-01-20 08:56:12 -08:00
Shyju Krishnankutty	5ddb4cd546	Register one orchestration per workflow.	2026-01-15 16:26:20 -08:00
Shyju Krishnankutty	50662c3415	Minor cleanup/reorg	2026-01-15 15:15:08 -08:00
Shyju Krishnankutty	6fbb4dcb87	Minor cleanups	2026-01-15 11:43:28 -08:00
Shyju Krishnankutty	ff230c86ce	cleanup	2026-01-15 11:10:46 -08:00
Shyju Krishnankutty	6e029eb039	WIP	2026-01-15 07:49:07 -08:00
Shyju Krishnankutty	defb533b95	working e2e orchestration completion.	2026-01-14 16:18:21 -08:00
Shyju Krishnankutty	7f22a87a24	WIP. runs all executors/agents in workflow sequantially.	2026-01-14 12:34:10 -08:00
Shyju Krishnankutty	4340f37e97	wip	2026-01-13 19:38:26 -08:00
Shyju Krishnankutty	aea354b09c	WIP	2026-01-12 17:27:31 -08:00
Shyju Krishnankutty	da6b2534c2	WIP	2026-01-12 09:06:27 -08:00