Python: Update package version (#3258)

* package version 260116

* removed name tags

.github/ISSUE_TEMPLATE/config.yml

@@ -0,0 +1,8 @@
+blank_issues_enabled: true
+contact_links:
+  - name: Documentation
+    url: https://aka.ms/agent-framework
+    about: Check out the official documentation for guides and API reference.
+  - name: Discussions
+    url: https://github.com/microsoft/agent-framework/discussions
+    about: Ask questions about Agent Framework.

.github/ISSUE_TEMPLATE/dotnet-issue.yml

@@ -0,0 +1,70 @@
+name: .NET Bug Report
+description: Report a bug in the Agent Framework .NET SDK
+title: ".NET: [Bug]: "
+labels: ["bug", ".NET"]
+type: bug
+body:
+  - type: textarea
+    id: description
+    attributes:
+      label: Description
+      description: Please provide a clear and detailed description of the bug.
+      placeholder: |
+        - What happened?
+        - What did you expect to happen?
+        - Steps to reproduce the issue
+    validations:
+      required: true
+
+  - type: textarea
+    id: code-sample
+    attributes:
+      label: Code Sample
+      description: If applicable, provide a minimal code sample that demonstrates the issue.
+      placeholder: |
+        ```csharp
+        // Your code here
+        ```
+      render: markdown
+    validations:
+      required: false
+
+  - type: textarea
+    id: error-messages
+    attributes:
+      label: Error Messages / Stack Traces
+      description: Include any error messages or stack traces you received.
+      placeholder: |
+        ```
+        Paste error messages or stack traces here
+        ```
+      render: markdown
+    validations:
+      required: false
+
+  - type: input
+    id: dotnet-packages
+    attributes:
+      label: Package Versions
+      description: List the Microsoft.Agents.* packages and versions you are using
+      placeholder: "e.g., Microsoft.Agents.AI.Abstractions: 1.0.0, Microsoft.Agents.AI.OpenAI: 1.0.0"
+    validations:
+      required: true
+
+  - type: input
+    id: dotnet-version
+    attributes:
+      label: .NET Version
+      description: What version of .NET are you using?
+      placeholder: "e.g., .NET 8.0"
+    validations:
+      required: false
+
+  - type: textarea
+    id: additional-context
+    attributes:
+      label: Additional Context
+      description: Add any other context or screenshots that might be helpful.
+      placeholder: "Any additional information..."
+    validations:
+      required: false

.github/ISSUE_TEMPLATE/feature-request.yml

@@ -0,0 +1,51 @@
+name: Feature Request
+description: Request a new feature for Microsoft Agent Framework
+title: "[Feature]: "
+type: feature
+body:
+
+  - type: textarea
+    id: description
+    attributes:
+      label: Description
+      description: Please describe the feature you'd like and why it would be useful.
+      placeholder: |
+        Describe the feature you're requesting:
+        - What problem does it solve?
+        - What would the expected behavior be?
+        - Are there any alternatives you've considered?
+    validations:
+      required: true
+
+  - type: textarea
+    id: code-sample
+    attributes:
+      label: Code Sample
+      description: If applicable, provide a code sample showing how you'd like to use this feature.
+      placeholder: |
+        ```python
+        # Your code here
+        ```
+
+        or
+
+        ```csharp
+        // Your code here
+        ```
+      render: markdown
+    validations:
+      required: false
+
+  - type: dropdown
+    id: language
+    attributes:
+      label: Language/SDK
+      description: Which language/SDK does this feature apply to?
+      options:
+        - Both
+        - .NET
+        - Python
+        - Other / Not Applicable
+      default: 0
+    validations:
+      required: false

.github/ISSUE_TEMPLATE/python-issue.yml

@@ -0,0 +1,70 @@
+name: Python Bug Report
+description: Report a bug in the Agent Framework Python SDK
+title: "Python: [Bug]: "
+labels: ["bug", "Python"]
+type: bug
+body:
+  - type: textarea
+    id: description
+    attributes:
+      label: Description
+      description: Please provide a clear and detailed description of the bug.
+      placeholder: |
+        - What happened?
+        - What did you expect to happen?
+        - Steps to reproduce the issue
+    validations:
+      required: true
+
+  - type: textarea
+    id: code-sample
+    attributes:
+      label: Code Sample
+      description: If applicable, provide a minimal code sample that demonstrates the issue.
+      placeholder: |
+        ```python
+        # Your code here
+        ```
+      render: markdown
+    validations:
+      required: false
+
+  - type: textarea
+    id: error-messages
+    attributes:
+      label: Error Messages / Stack Traces
+      description: Include any error messages or stack traces you received.
+      placeholder: |
+        ```
+        Paste error messages or stack traces here
+        ```
+      render: markdown
+    validations:
+      required: false
+
+  - type: input
+    id: python-packages
+    attributes:
+      label: Package Versions
+      description: List the agent-framework-* packages and versions you are using
+      placeholder: "e.g., agent-framework-core: 1.0.0, agent-framework-azure-ai: 1.0.0"
+    validations:
+      required: true
+
+  - type: input
+    id: python-version
+    attributes:
+      label: Python Version
+      description: What version of Python are you using?
+      placeholder: "e.g., Python 3.11"
+    validations:
+      required: false
+
+  - type: textarea
+    id: additional-context
+    attributes:
+      label: Additional Context
+      description: Add any other context or screenshots that might be helpful.
+      placeholder: "Any additional information..."
+    validations:
+      required: false

.github/actions/azure-functions-integration-setup/action.yml

@@ -28,6 +28,18 @@ runs:
           echo "Waiting for Azurite (Azure Storage emulator) to be ready"
           timeout 30 bash -c 'until curl --silent http://localhost:10000/devstoreaccount1; do sleep 1; done'
           echo "Azurite (Azure Storage emulator) is ready"
+      - name: Start Redis
+        shell: bash
+        run: |
+          if [ "$(docker ps -aq -f name=redis)" ]; then
+            echo "Stopping and removing existing Redis"
+            docker rm -f redis
+          fi
+          echo "Starting Redis"
+          docker run -d --name redis -p 6379:6379 redis:latest
+          echo "Waiting for Redis to be ready"
+          timeout 30 bash -c 'until docker exec redis redis-cli ping | grep -q PONG; do sleep 1; done'
+          echo "Redis is ready"
       - name: Install Azure Functions Core Tools
         shell: bash
         run: |

.github/upgrades/prompts/SemanticKernelToAgentFramework.md

@@ -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 `AgentRunResponse` instead of `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>`
+4. **Return Types**: Confirm handling of `AgentResponse` 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>>` → `AgentRunResponse`
+- Return types: `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` → `AgentResponse`
 - 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>>` → `AgentRunResponse`
-- `IAsyncEnumerable<StreamingChatMessageContent>` → `IAsyncEnumerable<AgentRunResponseUpdate>`
+- `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` → `AgentResponse`
+- `IAsyncEnumerable<StreamingChatMessageContent>` → `IAsyncEnumerable<AgentResponseUpdate>`
 </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 `AgentRunResponse` instead of `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>`
-   - Streaming: Returns `IAsyncEnumerable<AgentRunResponseUpdate>` instead of `IAsyncEnumerable<StreamingChatMessageContent>`
+   - Non-streaming: Returns single `AgentResponse` instead of `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>`
+   - Streaming: Returns `IAsyncEnumerable<AgentResponseUpdate>` 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
-AgentRunResponse result = await agent.RunAsync(userInput, thread, options);
+AgentResponse 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 (AgentRunResponseUpdate update in agent.RunStreamingAsync(userInput, thread, options))
+await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(userInput, thread, options))
 {
     Console.Write(update);
 }
@@ -420,8 +420,8 @@ await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(userInpu
 **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 `AgentRunResponse`
-4. Change streaming type from `StreamingChatMessageContent` to `AgentRunResponseUpdate`
+3. Change return type handling from `IAsyncEnumerable<AgentResponseItem<ChatMessageContent>>` to `AgentResponse`
+4. Change streaming type from `StreamingChatMessageContent` to `AgentResponseUpdate`
 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 });
 
-AgentRunResponse result = await agent.RunAsync(input, thread, options);
+AgentResponse 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
-AgentRunResponse result = await agent.RunAsync(input, thread, options);
+AgentResponse 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 (AgentRunResponseUpdate update in agent.RunStreamingAsync(input, thread, options))
+await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(input, thread, options))
 {
     if (update.Contents.OfType<UsageContent>().FirstOrDefault() is { } usageContent)
     {

.github/workflows/label-issues.yml

@@ -45,19 +45,58 @@ jobs:
               labels.push("triage")
             }
 
-            // Check if the body or the title contains the word 'python' (case-insensitive)
-            if ((body != null && body.match(/python/i)) || (title != null && title.match(/python/i))) {
-              // Add the 'python' label to the array
-              labels.push("python")
+            // Helper function to extract field value from issue form body
+            // Issue forms format fields as: ### Field Name\n\nValue
+            function getFormFieldValue(body, fieldName) {
+              if (!body) return null
+              const regex = new RegExp(`###\\s*${fieldName}\\s*\\n\\n([^\\n#]+)`, 'i')
+              const match = body.match(regex)
+              return match ? match[1].trim() : null
             }
 
-            // Check if the body or the title contains the words 'dotnet', '.net', 'c#' or 'csharp' (case-insensitive)
-            if ((body != null && body.match(/.net/i)) || (title != null && title.match(/.net/i)) ||
-                (body != null && body.match(/dotnet/i)) || (title != null && title.match(/dotnet/i)) ||
-                (body != null && body.match(/C#/i)) || (title != null && title.match(/C#/i)) ||
-                (body != null && body.match(/csharp/i)) || (title != null && title.match(/csharp/i))) {
-              // Add the '.NET' label to the array
-              labels.push(".NET")
+            // Check for language from issue form dropdown first
+            const languageField = getFormFieldValue(body, 'Language')
+            let languageLabelAdded = false
+
+            if (languageField) {
+              if (languageField === 'Python') {
+                labels.push("python")
+                languageLabelAdded = true
+              } else if (languageField === '.NET') {
+                labels.push(".NET")
+                languageLabelAdded = true
+              }
+              // 'None / Not Applicable' - don't add any language label
+            }
+
+            // Fallback: Check if the body or the title contains the word 'python' (case-insensitive)
+            // Only if language wasn't already determined from the form field
+            if (!languageLabelAdded) {
+              if ((body != null && body.match(/python/i)) || (title != null && title.match(/python/i))) {
+                // Add the 'python' label to the array
+                labels.push("python")
+              }
+
+              // Check if the body or the title contains the words 'dotnet', '.net', 'c#' or 'csharp' (case-insensitive)
+              if ((body != null && body.match(/\.net/i)) || (title != null && title.match(/\.net/i)) ||
+                  (body != null && body.match(/dotnet/i)) || (title != null && title.match(/dotnet/i)) ||
+                  (body != null && body.match(/C#/i)) || (title != null && title.match(/C#/i)) ||
+                  (body != null && body.match(/csharp/i)) || (title != null && title.match(/csharp/i))) {
+                // Add the '.NET' label to the array
+                labels.push(".NET")
+              }
+            }
+
+            // Check for issue type from issue form dropdown
+            const issueTypeField = getFormFieldValue(body, 'Type of Issue')
+            if (issueTypeField) {
+              if (issueTypeField === 'Bug') {
+                labels.push("bug")
+              } else if (issueTypeField === 'Feature Request') {
+                labels.push("enhancement")
+              } else if (issueTypeField === 'Question') {
+                labels.push("question")
+              }
             }
 
             // Add the labels to the issue (only if there are labels to add)

.github/workflows/merge-gatekeeper.yml

@@ -29,3 +29,4 @@ jobs:
           token: ${{ secrets.GITHUB_TOKEN }}
           timeout: 3600
           interval: 30
+          ignored: CodeQL

.github/workflows/python-merge-tests.yml

@@ -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 300 --retries 3 --retry-delay 10
+        run: uv run poe all-tests -n logical --dist loadfile --dist worksteal --timeout 600 --retries 3 --retry-delay 10
         working-directory: ./python
       - name: Test core samples
         timeout-minutes: 10
@@ -154,7 +154,7 @@ jobs:
           subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
       - name: Test with pytest
         timeout-minutes: 10
-        run: uv run poe azure-ai-tests -n logical --dist loadfile --dist worksteal --timeout 300 --retries 3 --retry-delay 10
+        run: uv run --directory packages/azure-ai poe integration-tests -n logical --dist loadfile --dist worksteal --timeout 300 --retries 3 --retry-delay 10
         working-directory: ./python
       - name: Test Azure AI samples
         timeout-minutes: 10

.gitignore

@@ -206,6 +206,7 @@ agents.md
 WARP.md
 **/memory-bank/
 **/projectBrief.md
+**/tmpclaude*
 
 # Azurite storage emulator files
 */__azurite_db_blob__.json
@@ -226,3 +227,4 @@ local.settings.json
 
 # Database files
 *.db
+python/dotnet-ref

agent-samples/README.md

@@ -1,3 +1,3 @@
 # Declarative Agents
 
-This folder contains sample agent definitions than be ran using the declarative agent support, for python see the [declarative agent python sample folder](../python/samples/getting_started/declarative/).
+This folder contains sample agent definitions that can be run using the declarative agent support, for python see the [declarative agent python sample folder](../python/samples/getting_started/declarative/).

docs/decisions/0001-agent-run-response.md

@@ -64,7 +64,7 @@ Approaches observed from the compared SDKs:
 | AutoGen | **Approach 1** Separates messages into Agent-Agent (maps to Primary) and Internal (maps to Secondary) and these are returned as separate properties on the agent response object.  See [types of messages](https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/messages.html#types-of-messages) and [Response](https://microsoft.github.io/autogen/stable/reference/python/autogen_agentchat.base.html#autogen_agentchat.base.Response) | **Approach 2** Returns a stream of internal events and the last item is a Response object. See [ChatAgent.on_messages_stream](https://microsoft.github.io/autogen/stable/reference/python/autogen_agentchat.base.html#autogen_agentchat.base.ChatAgent.on_messages_stream) |
 | OpenAI Agent SDK | **Approach 1** Separates new_items (Primary+Secondary) from final output (Primary) as separate properties on the [RunResult](https://github.com/openai/openai-agents-python/blob/main/src/agents/result.py#L39) | **Approach 1** Similar to non-streaming, has a way of streaming updates via a method on the response object which includes all data, and then a separate final output property on the response object which is populated only when the run is complete. See [RunResultStreaming](https://github.com/openai/openai-agents-python/blob/main/src/agents/result.py#L136) |
 | Google ADK | **Approach 2** [Emits events](https://google.github.io/adk-docs/runtime/#step-by-step-breakdown) with [FinalResponse](https://github.com/google/adk-java/blob/main/core/src/main/java/com/google/adk/events/Event.java#L232) true (Primary) / false (Secondary) and callers have to filter out those with false to get just the final response message | **Approach 2** Similar to non-streaming except [events](https://google.github.io/adk-docs/runtime/#streaming-vs-non-streaming-output-partialtrue) are emitted with [Partial](https://github.com/google/adk-java/blob/main/core/src/main/java/com/google/adk/events/Event.java#L133) true to indicate that they are streaming messages. A final non partial event is also emitted. |
-| AWS (Strands) | **Approach 3** Returns an [AgentResult](https://strandsagents.com/latest/api-reference/agent/#strands.agent.agent_result.AgentResult) (Primary) with messages and a reason for the run's completion. | **Approach 2** [Streams events](https://strandsagents.com/latest/api-reference/agent/#strands.agent.agent.Agent.stream_async) (Primary+Secondary) including, response text, current_tool_use, even data from "callbacks" (strands plugins) |
+| AWS (Strands) | **Approach 3** Returns an [AgentResult](https://strandsagents.com/latest/documentation/docs/api-reference/python/agent/agent_result/) (Primary) with messages and a reason for the run's completion. | **Approach 2** [Streams events](https://strandsagents.com/latest/documentation/docs/api-reference/python/agent/agent/#strands.agent.agent.Agent.stream_async) (Primary+Secondary) including, response text, current_tool_use, even data from "callbacks" (strands plugins) |
 | LangGraph | **Approach 2** A mixed list of all [messages](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) | **Approach 2** A mixed list of all [messages](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) |
 | Agno | **Combination of various approaches** Returns a [RunResponse](https://docs.agno.com/reference/agents/run-response) object with text content, messages (essentially chat history including inputs and instructions), reasoning and thinking text properties. Secondary events could potentially be extracted from messages. | **Approach 2** Returns [RunResponseEvent](https://docs.agno.com/reference/agents/run-response#runresponseevent-types-and-attributes) objects including tool call, memory update, etc, information, where the [RunResponseCompletedEvent](https://docs.agno.com/reference/agents/run-response#runresponsecompletedevent) has similar properties to RunResponse|
 | A2A | **Approach 3** Returns a [Task or Message](https://a2aproject.github.io/A2A/latest/specification/#71-messagesend) where the message is the final result (Primary) and task is a reference to a long running process. | **Approach 2** Returns a [stream](https://a2aproject.github.io/A2A/latest/specification/#72-messagestream) that contains task updates (Secondary) and a final message (Primary) |
@@ -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 `AgentRunResponse.Messages` property while Secondary updates are in a new `AgentRunResponse.Updates` property.
-`AgentRunResponse.Text` returns the Primary content text.
+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.
 
 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<AgentRunResponse> RunAsync(
+    public abstract Task<AgentResponse> RunAsync(
         IReadOnlyCollection<ChatMessage> messages,
         AgentThread? thread = null,
         AgentRunOptions? options = null,
         CancellationToken cancellationToken = default);
 
-    public abstract IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
+    public abstract IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
         IReadOnlyCollection<ChatMessage> messages,
         AgentThread? thread = null,
         AgentRunOptions? options = null,
         CancellationToken cancellationToken = default);
 }
 
-class AgentRunResponse : ChatResponse
+class AgentResponse : ChatResponse
 {
 }
 
-public class AgentRunResponseUpdate : ChatResponseUpdate
+public class AgentResponseUpdate : 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<AgentRunResponse> RunAsync(
+    public abstract Task<AgentResponse> RunAsync(
         IReadOnlyCollection<ChatMessage> messages,
         AgentThread? thread = null,
         AgentRunOptions? options = null,
         CancellationToken cancellationToken = default);
 
-    public abstract IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
+    public abstract IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
         IReadOnlyCollection<ChatMessage> messages,
         AgentThread? thread = null,
         AgentRunOptions? options = null,
         CancellationToken cancellationToken = default);
 }
 
-class AgentRunResponse // Compare with ChatResponse
+class AgentResponse // Compare with ChatResponse
 {
     public string Text { get; } // Aggregation of TextContent from messages.
 
@@ -294,12 +294,12 @@ class AgentRunResponse // Compare with ChatResponse
     public AdditionalPropertiesDictionary? AdditionalProperties { get; set; }
 }
 
-// Not Included in AgentRunResponse compared to ChatResponse
+// Not Included in AgentResponse compared to ChatResponse
 public ChatFinishReason? FinishReason { get; set; }
 public string? ConversationId { get; set; }
 public string? ModelId { get; set; }
 
-public class AgentRunResponseUpdate // Compare with ChatResponseUpdate
+public class AgentResponseUpdate // Compare with ChatResponseUpdate
 {
     public string Text { get; } // Aggregation of TextContent from Contents.
 
@@ -317,7 +317,7 @@ public class AgentRunResponseUpdate // Compare with ChatResponseUpdate
     public AdditionalPropertiesDictionary? AdditionalProperties { get; set; }
 }
 
-// Not Included in AgentRunResponseUpdate compared to ChatResponseUpdate
+// Not Included in AgentResponseUpdate 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 AgentRunResponse
+class AgentResponse
 {
     ...
     public AgentRun RunReference { get; set; } // Reference to long running process
@@ -368,7 +368,7 @@ class AgentRunResponse
 }
 
 
-public class AgentRunResponseUpdate
+public class AgentResponseUpdate
 {
     ...
     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 `AgentRunResponse<T>`, that allows us to get the agent result already deserialized into our preferred type.
+We would add a generic version of `AgentResponse<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; }
 }
 
-AgentRunResponse<Movie[]> response = agent.RunAsync<Movie[]>("What are the top 3 children's movies of the 80s.");
+AgentResponse<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
-AgentRunResponse response = agent.RunAsync("What are the top 3 children's movies of the 80s.");
+AgentResponse 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 `AgentRunResponse`.
+We will however add support for easily extracting a structured output type from the `AgentResponse`.
 
 ## Addendum 1: AIContext Derived Types for different response types / Gap Analysis (Work in progress)
 
@@ -495,8 +495,8 @@ We need to decide what AIContent types, each agent response type will be mapped
 | SDK | Structured Outputs support |
 |-|-|
 | AutoGen | **Approach 1** Supports [configuring an agent](https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/agents.html#structured-output) at agent creation. |
-| Google ADK | **Approach 1** Both [input and output shemas can be specified for LLM Agents](https://google.github.io/adk-docs/agents/llm-agents/#structuring-data-input_schema-output_schema-output_key) at construction time. This option is specific to this agent type and other agent types do not necessarily support |
-| AWS (Strands) | **Approach 2** Supports a special invocation method called [structured_output](https://strandsagents.com/latest/api-reference/agent/#strands.agent.agent.Agent.structured_output) |
+| Google ADK | **Approach 1** Both [input and output schemas can be specified for LLM Agents](https://google.github.io/adk-docs/agents/llm-agents/#structuring-data-input_schema-output_schema-output_key) at construction time. This option is specific to this agent type and other agent types do not necessarily support |
+| AWS (Strands) | **Approach 2** Supports a special invocation method called [structured_output](https://strandsagents.com/latest/documentation/docs/api-reference/python/agent/agent/#strands.agent.agent.Agent.structured_output) |
 | LangGraph | **Approach 1** Supports [configuring an agent](https://langchain-ai.github.io/langgraph/agents/agents/?h=structured#6-configure-structured-output) at agent construction time, and a [structured response](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) can be retrieved as a special property on the agent response |
 | Agno | **Approach 1** Supports [configuring an agent](https://docs.agno.com/examples/getting-started/structured-output) at agent construction time |
 | A2A | **Informal Approach 2** Doesn't formally support schema negotiation, but [hints can be provided via metadata](https://a2a-protocol.org/latest/specification/#97-structured-data-exchange-requesting-and-providing-json) at invocation time |
@@ -508,7 +508,7 @@ We need to decide what AIContent types, each agent response type will be mapped
 |-|-|
 | AutoGen | Supports a [stop reason](https://microsoft.github.io/autogen/stable/reference/python/autogen_agentchat.base.html#autogen_agentchat.base.TaskResult.stop_reason) which is a freeform text string |
 | Google ADK | [No equivalent present](https://github.com/google/adk-python/blob/main/src/google/adk/events/event.py) |
-| AWS (Strands) | Exposes a [stop_reason](https://strandsagents.com/latest/api-reference/types/#strands.types.event_loop.StopReason) property on the [AgentResult](https://strandsagents.com/latest/api-reference/agent/#strands.agent.agent_result.AgentResult) class with options that are tied closely to LLM operations. |
+| AWS (Strands) | Exposes a [stop_reason](https://strandsagents.com/latest/documentation/docs/api-reference/python/types/event_loop/#strands.types.event_loop.StopReason) property on the [AgentResult](https://strandsagents.com/latest/documentation/docs/api-reference/python/agent/agent_result/) class with options that are tied closely to LLM operations. |
 | LangGraph | No equivalent present, output contains only [messages](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) |
 | Agno | [No equivalent present](https://docs.agno.com/reference/agents/run-response) |
 | A2A | No equivalent present, response only contains a [message](https://a2a-protocol.org/latest/specification/#64-message-object) or [task](https://a2a-protocol.org/latest/specification/#61-task-object). |

docs/decisions/0005-python-naming-conventions.md

@@ -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 |
-| AgentRunResponse & AgentRunResponseUpdate | AgentResponse & AgentResponseUpdate | rejected | Rejected, because it is the response to a run invocation and AgentResponse is too generic. | None |
+| AgentResponse & AgentResponseUpdate | 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 |
 

docs/decisions/0006-userapproval.md

@@ -161,11 +161,11 @@ while (response.ApprovalRequests.Count > 0)
     response = await agent.RunAsync(messages, thread);
 }
 
-class AgentRunResponse
+class AgentResponse
 {
     ...
 
-    // A new property on AgentRunResponse to aggregate the ApprovalRequestContent items from
+    // A new property on AgentResponse 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 AgentRunResponse
+class AgentResponse
 {
     ...
 
-    // A new property on AgentRunResponse to aggregate the UserInputRequestContent items from
+    // A new property on AgentResponse 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 AgentRunResponse
+class AgentResponse
 {
     ...
 
-    // A new property on AgentRunResponse to aggregate the UserInputRequestContent items from
+    // A new property on AgentResponse to aggregate the UserInputRequestContent items from
     // the response messages (Similar to the Text property).
     public IEnumerable<UserInputRequestContent> UserInputRequests { get; set; }
 

docs/decisions/0007-agent-filtering-middleware.md

@@ -115,7 +115,7 @@ public class AIAgent
         }
     }
 
-    public async Task<AgentRunResponse> RunAsync(
+    public async Task<AgentResponse> 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<AgentRunResponse> ExecuteCoreLogicAsync(
+    protected abstract Task<AgentResponse> 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<AgentRunResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
+    public override async Task<AgentResponse> 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<AgentRunResponseUpdate> RunStreamingAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default)
+    public override async IAsyncEnumerable<AgentResponseUpdate> 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 AgentRunResponseUpdate(update.Role, this.FilterContent(update.Text));
+                yield return new AgentResponseUpdate(update.Role, this.FilterContent(update.Text));
             }
             else
             {
@@ -252,7 +252,7 @@ internal sealed class RunningCallbackHandlerAgent : DelegatingAIAgent
         this._func = func;
     }
 
-    public override async Task<AgentRunResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
+    public override async Task<AgentResponse> 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<AgentRunResponse> RunAsync(
+    public override async Task<AgentResponse> 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 AgentRunResponse? Response { get; set; }
+    public AgentResponse? Response { get; set; }
     public AgentThread? Thread { get; }
 
     public AgentRunContext(AIAgent agent, IList<ChatMessage> messages, AgentThread? thread, AgentRunOptions? options)

docs/decisions/0009-support-long-running-operations.md

@@ -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 `AgentRunResponse` or `ChatResponse`
+Items of this content type will be returned in a chat message as part of the `AgentResponse` 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<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) { ... }
+    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) { ... }
 
     // New methods for uncommon operations
-    public virtual Task<AgentRunResponse?> CancelRunAsync(string id, AgentCancelRunOptions? options = null, CancellationToken cancellationToken = default)
+    public virtual Task<AgentResponse?> CancelRunAsync(string id, AgentCancelRunOptions? options = null, CancellationToken cancellationToken = default)
     {
-        return Task.FromResult<AgentRunResponse?>(null);
+        return Task.FromResult<AgentResponse?>(null);
     }
 
-    public virtual Task<AgentRunResponse?> DeleteRunAsync(string id, AgentDeleteRunOptions? options = null, CancellationToken cancellationToken = default)
+    public virtual Task<AgentResponse?> DeleteRunAsync(string id, AgentDeleteRunOptions? options = null, CancellationToken cancellationToken = default)
     {
-        return Task.FromResult<AgentRunResponse?>(null);
+        return Task.FromResult<AgentResponse?>(null);
     }
 }
 
 // Agent that supports update and cancellation
 public class CustomAgent : AIAgent
 {
-    public override async Task<AgentRunResponse?> CancelRunAsync(string id, AgentCancelRunOptions? options = null, CancellationToken cancellationToken = default)
+    public override async Task<AgentResponse?> CancelRunAsync(string id, AgentCancelRunOptions? options = null, CancellationToken cancellationToken = default)
     {
         var response = await this._client.CancelRunAsync(id, options?.Thread?.ConversationId);
 
-        return ConvertToAgentRunResponse(response); 
+        return ConvertToAgentResponse(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();
 
-AgentRunResponse response = await agent.RunAsync("What is the capital of France?");
+AgentResponse 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
-AgentRunResponse response = await agent.RunAsync("<prompt>", new AgentRunOptions { AllowLongRunningResponses = true });
+AgentResponse response = await agent.RunAsync("<prompt>", new AgentRunOptions { AllowLongRunningResponses = true });
 
 // Start a quick prompt
-AgentRunResponse response = await agent.RunAsync("<prompt>");
+AgentResponse 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 `AgentRunResponse` and `AgentRunResponseUpdate` responses to indicate that the response is part of a long-running operation. A null value 
+`ContinuationToken` property of the `AgentResponse` and `AgentResponseUpdate` 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 AgentRunResponse
+public class AgentResponse
 {
     public ResponseContinuationToken? ContinuationToken { get; }
 }
  
-public class AgentRunResponseUpdate
+public class AgentResponseUpdate
 {
     public ResponseContinuationToken? ContinuationToken { get; }
 }
 
 // Usage example
-AgentRunResponse response = await agent.RunAsync("What is the capital of France?");
+AgentResponse response = await agent.RunAsync("What is the capital of France?");
 
 AgentRunOptions options = new() { ContinuationToken = response.ContinuationToken };
 

docs/decisions/0010-ag-ui-support.md

@@ -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 (AgentRunResponseUpdate, ChatMessage) for public API
+- Uses existing framework types (AgentResponseUpdate, 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 (`AgentRunResponseUpdate` → AG-UI events) and client (AG-UI events → `AgentRunResponseUpdate`)
+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`)
 
 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.
 

docs/decisions/0011-create-get-agent-api.md

@@ -0,0 +1,368 @@
+---
+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.

docs/decisions/0011-python-typeddict-options.md

@@ -0,0 +1,129 @@
+---
+# 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.

docs/decisions/0012-python-get-response-simplification.md

@@ -0,0 +1,258 @@
+---
+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();
+
+```

docs/specs/001-foundry-sdk-alignment.md

@@ -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 `AgentRunResponse` 
+- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentResponse` 
 - [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 `AgentRunResponse` 
+- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentResponse` 
 - [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 `AgentRunResponse` 
+- [Agent Framework SDK] Invoke the `AIAgent` instance and access response from the `AgentResponse` 
 - [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 `AgentRunResponse` 
+- [Agent Framework SDK] Invoke the `SequentialOrchestration` instance and access response from the `AgentResponse` 
 - [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($"\n# INPUT: {input}\n");
-AgentRunResponse result = await orchestration.RunAsync(input);
+AgentResponse result = await orchestration.RunAsync(input);
 Console.WriteLine($"\n# RESULT: {result}");
 
 // Cleanup

dotnet/Directory.Packages.props

@@ -11,13 +11,13 @@
   </PropertyGroup>
   <ItemGroup>
     <!-- Aspire.* -->
-    <PackageVersion Include="Anthropic" Version="11.0.0" />
+    <PackageVersion Include="Anthropic" Version="12.0.1" />
     <PackageVersion Include="Anthropic.Foundry" Version="0.1.0" />
     <PackageVersion Include="Aspire.Azure.AI.OpenAI" Version="13.0.0-preview.1.25560.3" />
     <PackageVersion Include="Aspire.Hosting.AppHost" Version="$(AspireAppHostSdkVersion)" />
     <PackageVersion Include="Aspire.Hosting.Azure.CognitiveServices" Version="$(AspireAppHostSdkVersion)" />
     <PackageVersion Include="Aspire.Microsoft.Azure.Cosmos" Version="$(AspireAppHostSdkVersion)" />
-    <PackageVersion Include="CommunityToolkit.Aspire.OllamaSharp" Version="13.0.0-beta.440" />
+    <PackageVersion Include="CommunityToolkit.Aspire.OllamaSharp" Version="13.0.0" />
     <!-- Azure.* -->
     <PackageVersion Include="Azure.AI.Projects" Version="1.2.0-beta.5" />
     <PackageVersion Include="Azure.AI.Projects.OpenAI" Version="1.0.0-beta.5" />
@@ -26,7 +26,7 @@
     <PackageVersion Include="Azure.Identity" Version="1.17.1" />
     <PackageVersion Include="Azure.Monitor.OpenTelemetry.Exporter" Version="1.4.0" />
     <!-- Google Gemini  -->
-    <PackageVersion Include="Google.GenAI" Version="0.6.0" />
+    <PackageVersion Include="Google.GenAI" Version="0.11.0" />
     <PackageVersion Include="Mscc.GenerativeAI.Microsoft" Version="2.9.3" />
     <!-- Microsoft.Azure.* -->
     <PackageVersion Include="Microsoft.Azure.Cosmos" Version="3.54.0" />
@@ -100,7 +100,7 @@
     <!-- MCP -->
     <PackageVersion Include="ModelContextProtocol" Version="0.4.0-preview.3" />
     <!-- Inference SDKs -->
-    <PackageVersion Include="AWSSDK.Extensions.Bedrock.MEAI" Version="4.0.4.11" />
+    <PackageVersion Include="AWSSDK.Extensions.Bedrock.MEAI" Version="4.0.5.1" />
     <PackageVersion Include="Microsoft.ML.OnnxRuntimeGenAI" Version="0.10.0" />
     <PackageVersion Include="OllamaSharp" Version="5.4.8" />
     <PackageVersion Include="OpenAI" Version="2.8.0" />
@@ -112,19 +112,21 @@
     <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="1.16.2" />
-    <PackageVersion Include="Microsoft.DurableTask.Client.AzureManaged" Version="1.16.2-preview.1" />
-    <PackageVersion Include="Microsoft.DurableTask.Worker" Version="1.16.2" />
-    <PackageVersion Include="Microsoft.DurableTask.Worker.AzureManaged" Version="1.16.2-preview.1" />
+    <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" />
     <!-- 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="1.9.0" />
-    <PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" Version="1.0.0" />
+    <PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" Version="1.11.0" />
+    <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" />
     <PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Mcp" Version="1.0.0" />
     <PackageVersion Include="Microsoft.Azure.Functions.Worker.Sdk" Version="2.0.7" />
+    <!-- Redis -->
+    <PackageVersion Include="StackExchange.Redis" Version="2.10.1" />
     <!-- Test -->
     <PackageVersion Include="FluentAssertions" Version="8.8.0" />
     <PackageVersion Include="Microsoft.AspNetCore.TestHost" Condition="'$(TargetFramework)' == 'net8.0'" Version="8.0.22" />

dotnet/README.md

@@ -21,7 +21,7 @@ var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT
 
 var agent = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
     .GetOpenAIResponseClient(deploymentName)
-    .CreateAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
+    .AsAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
 
 Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
 ```

dotnet/agent-framework-dotnet.slnx

@@ -33,6 +33,7 @@
     <Project Path="samples/AzureFunctions/05_AgentOrchestration_HITL/05_AgentOrchestration_HITL.csproj" />
     <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" />
   </Folder>
   <Folder Name="/Samples/GettingStarted/">
     <File Path="samples/GettingStarted/README.md" />

dotnet/nuget/nuget-package.props

@@ -2,9 +2,9 @@
   <PropertyGroup>
     <!-- Central version prefix - applies to all nuget packages. -->
     <VersionPrefix>1.0.0</VersionPrefix>
-    <PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).251204.1</PackageVersion>
-    <PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.251204.1</PackageVersion>
-    <GitTag>1.0.0-preview.251204.1</GitTag>
+    <PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).260108.1</PackageVersion>
+    <PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.260108.1</PackageVersion>
+    <GitTag>1.0.0-preview.260108.1</GitTag>
 
     <Configurations>Debug;Release;Publish</Configurations>
     <IsPackable>true</IsPackable>

dotnet/samples/A2AClientServer/A2AClient/HostClientAgent.cs

@@ -29,7 +29,7 @@ internal sealed class HostClientAgent
             // Create the agent that uses the remote agents as tools
             this.Agent = new OpenAIClient(new ApiKeyCredential(apiKey))
              .GetChatClient(modelId)
-             .CreateAIAgent(instructions: "You specialize in handling queries for users and using your tools to provide answers.", name: "HostClient", tools: tools);
+             .AsAIAgent(instructions: "You specialize in handling queries for users and using your tools to provide answers.", name: "HostClient", tools: tools);
         }
         catch (Exception ex)
         {

dotnet/samples/A2AClientServer/A2AClient/Program.cs

@@ -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 = hostAgent.Agent!.GetNewThread();
+        AgentThread thread = await hostAgent.Agent!.GetNewThreadAsync(cancellationToken);
         try
         {
             while (true)

dotnet/samples/A2AClientServer/A2AServer/HostAgentFactory.cs

@@ -35,7 +35,7 @@ internal static class HostAgentFactory
     {
         AIAgent agent = new OpenAIClient(apiKey)
              .GetChatClient(model)
-             .CreateAIAgent(instructions, name, tools: tools);
+             .AsAIAgent(instructions, name, tools: tools);
 
         AgentCard agentCard = agentType.ToUpperInvariant() switch
         {

dotnet/samples/AGUIClientServer/AGUIClient/Program.cs

@@ -83,12 +83,12 @@ public static class Program
             serverUrl,
             jsonSerializerOptions: AGUIClientSerializerContext.Default.Options);
 
-        AIAgent agent = chatClient.CreateAIAgent(
+        AIAgent agent = chatClient.AsAIAgent(
             name: "agui-client",
             description: "AG-UI Client Agent",
             tools: [changeBackground, readClientClimateSensors]);
 
-        AgentThread thread = agent.GetNewThread();
+        AgentThread thread = await agent.GetNewThreadAsync(cancellationToken);
         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 (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread, cancellationToken: cancellationToken))
+                await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread, cancellationToken: cancellationToken))
                 {
                     // Use AsChatResponseUpdate to access ChatResponseUpdate properties
                     ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();

dotnet/samples/AGUIClientServer/AGUIDojoServer/AgenticUI/AgenticUIAgent.cs

@@ -19,12 +19,12 @@ internal sealed class AgenticUIAgent : DelegatingAIAgent
         this._jsonSerializerOptions = jsonSerializerOptions;
     }
 
-    public override Task<AgentRunResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
+    protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
     {
-        return this.RunStreamingAsync(messages, thread, options, cancellationToken).ToAgentRunResponseAsync(cancellationToken);
+        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
     }
 
-    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
+    protected override async IAsyncEnumerable<AgentResponseUpdate> 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 AgentRunResponseUpdate(
+            yield return new AgentResponseUpdate(
                 new ChatResponseUpdate(role: ChatRole.System, stateEventsToEmit)
                 {
                     MessageId = "delta_" + Guid.NewGuid().ToString("N"),

dotnet/samples/AGUIClientServer/AGUIDojoServer/ChatClientAgentFactory.cs

@@ -33,7 +33,7 @@ internal static class ChatClientAgentFactory
     {
         ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
 
-        return chatClient.AsIChatClient().CreateAIAgent(
+        return chatClient.AsIChatClient().AsAIAgent(
             name: "AgenticChat",
             description: "A simple chat agent using Azure OpenAI");
     }
@@ -42,7 +42,7 @@ internal static class ChatClientAgentFactory
     {
         ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
 
-        return chatClient.AsIChatClient().CreateAIAgent(
+        return chatClient.AsIChatClient().AsAIAgent(
             name: "BackendToolRenderer",
             description: "An agent that can render backend tools using Azure OpenAI",
             tools: [AIFunctionFactory.Create(
@@ -56,7 +56,7 @@ internal static class ChatClientAgentFactory
     {
         ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
 
-        return chatClient.AsIChatClient().CreateAIAgent(
+        return chatClient.AsIChatClient().AsAIAgent(
             name: "HumanInTheLoopAgent",
             description: "An agent that involves human feedback in its decision-making process using Azure OpenAI");
     }
@@ -65,7 +65,7 @@ internal static class ChatClientAgentFactory
     {
         ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
 
-        return chatClient.AsIChatClient().CreateAIAgent(
+        return chatClient.AsIChatClient().AsAIAgent(
             name: "ToolBasedGenerativeUIAgent",
             description: "An agent that uses tools to generate user interfaces using Azure OpenAI");
     }
@@ -73,7 +73,7 @@ internal static class ChatClientAgentFactory
     public static AIAgent CreateAgenticUI(JsonSerializerOptions options)
     {
         ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
-        var baseAgent = chatClient.AsIChatClient().CreateAIAgent(new ChatClientAgentOptions
+        var baseAgent = chatClient.AsIChatClient().AsAIAgent(new ChatClientAgentOptions
         {
             Name = "AgenticUIAgent",
             Description = "An agent that generates agentic user interfaces using Azure OpenAI",
@@ -116,7 +116,7 @@ internal static class ChatClientAgentFactory
     {
         ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
 
-        var baseAgent = chatClient.AsIChatClient().CreateAIAgent(
+        var baseAgent = chatClient.AsIChatClient().AsAIAgent(
             name: "SharedStateAgent",
             description: "An agent that demonstrates shared state patterns using Azure OpenAI");
 
@@ -127,7 +127,7 @@ internal static class ChatClientAgentFactory
     {
         ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
 
-        var baseAgent = chatClient.AsIChatClient().CreateAIAgent(new ChatClientAgentOptions
+        var baseAgent = chatClient.AsIChatClient().AsAIAgent(new ChatClientAgentOptions
         {
             Name = "PredictiveStateUpdatesAgent",
             Description = "An agent that demonstrates predictive state updates using Azure OpenAI",

dotnet/samples/AGUIClientServer/AGUIDojoServer/PredictiveStateUpdates/PredictiveStateUpdatesAgent.cs

@@ -20,12 +20,12 @@ internal sealed class PredictiveStateUpdatesAgent : DelegatingAIAgent
         this._jsonSerializerOptions = jsonSerializerOptions;
     }
 
-    public override Task<AgentRunResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
+    protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
     {
-        return this.RunStreamingAsync(messages, thread, options, cancellationToken).ToAgentRunResponseAsync(cancellationToken);
+        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
     }
 
-    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
+    protected override async IAsyncEnumerable<AgentResponseUpdate> 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 AgentRunResponseUpdate(
+                    yield return new AgentResponseUpdate(
                         new ChatResponseUpdate(role: ChatRole.Assistant, [new DataContent(stateBytes, "application/json")])
                         {
                             MessageId = "snapshot" + Guid.NewGuid().ToString("N"),

dotnet/samples/AGUIClientServer/AGUIDojoServer/SharedState/SharedStateAgent.cs

@@ -19,12 +19,12 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
         this._jsonSerializerOptions = jsonSerializerOptions;
     }
 
-    public override Task<AgentRunResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
+    protected override Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
     {
-        return this.RunStreamingAsync(messages, thread, options, cancellationToken).ToAgentRunResponseAsync(cancellationToken);
+        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken).ToAgentResponseAsync(cancellationToken);
     }
 
-    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
+    protected override async IAsyncEnumerable<AgentResponseUpdate> 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<AgentRunResponseUpdate>();
+        var allUpdates = new List<AgentResponseUpdate>();
         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.ToAgentRunResponse();
+        var response = allUpdates.ToAgentResponse();
 
         if (response.TryDeserialize(this._jsonSerializerOptions, out JsonElement stateSnapshot))
         {
             byte[] stateBytes = JsonSerializer.SerializeToUtf8Bytes(
                 stateSnapshot,
                 this._jsonSerializerOptions.GetTypeInfo(typeof(JsonElement)));
-            yield return new AgentRunResponseUpdate
+            yield return new AgentResponseUpdate
             {
                 Contents = [new DataContent(stateBytes, "application/json")]
             };

dotnet/samples/AGUIClientServer/AGUIServer/Program.cs

@@ -23,7 +23,7 @@ var agent = new AzureOpenAIClient(
         new Uri(endpoint),
         new DefaultAzureCredential())
     .GetChatClient(deploymentName)
-    .CreateAIAgent(
+    .AsAIAgent(
         name: "AGUIAssistant",
         tools: [
             AIFunctionFactory.Create(

dotnet/samples/AGUIClientServer/README.md

@@ -119,7 +119,7 @@ The `AGUIServer` uses the `MapAGUI` extension method to expose an agent through
 ```csharp
 AIAgent agent = new OpenAIClient(apiKey)
     .GetChatClient(model)
-    .CreateAIAgent(
+    .AsAIAgent(
         instructions: "You are a helpful assistant.",
         name: "AGUIAssistant");
 
@@ -144,16 +144,16 @@ var chatClient = new AGUIChatClient(
     modelId: "agui-client",
     jsonSerializerOptions: null);
 
-AIAgent agent = chatClient.CreateAIAgent(
+AIAgent agent = chatClient.AsAIAgent(
     instructions: null,
     name: "agui-client",
     description: "AG-UI Client Agent",
     tools: []);
 
 bool isFirstUpdate = true;
-AgentRunResponseUpdate? currentUpdate = null;
+AgentResponseUpdate? currentUpdate = null;
 
-await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread))
+await foreach (AgentResponseUpdate 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 `AgentRunResponseUpdate` objects
+3. Parses events into `AgentResponseUpdate` 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)
-- **AgentRunResponseUpdate**: Contains the response data with:
+- **AgentResponseUpdate**: 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** `AgentRunResponseUpdate` in a run indicates the run has started
+  - The **first** `AgentResponseUpdate` in a run indicates the run has started
   - Subsequent updates contain streaming content as the agent processes
-  - The **last** `AgentRunResponseUpdate` in a run indicates the run has finished
+  - The **last** `AgentResponseUpdate` in a run indicates the run has finished
   - If an error occurs, the update will contain `ErrorContent`

dotnet/samples/AGUIWebChat/README.md

@@ -74,7 +74,7 @@ AzureOpenAIClient azureOpenAIClient = new AzureOpenAIClient(
 ChatClient chatClient = azureOpenAIClient.GetChatClient(deploymentName);
 
 // Create AI agent
-ChatClientAgent agent = chatClient.AsIChatClient().CreateAIAgent(
+ChatClientAgent agent = chatClient.AsIChatClient().AsAIAgent(
     name: "ChatAssistant",
     instructions: "You are a helpful assistant.");
 
@@ -162,7 +162,7 @@ dotnet run
 Edit the instructions in `Server/Program.cs`:
 
 ```csharp
-ChatClientAgent agent = chatClient.AsIChatClient().CreateAIAgent(
+ChatClientAgent agent = chatClient.AsIChatClient().AsAIAgent(
     name: "ChatAssistant",
     instructions: "You are a helpful coding assistant specializing in C# and .NET.");
 ```

dotnet/samples/AGUIWebChat/Server/Program.cs

@@ -25,7 +25,7 @@ AzureOpenAIClient azureOpenAIClient = new(
 
 ChatClient chatClient = azureOpenAIClient.GetChatClient(deploymentName);
 
-ChatClientAgent agent = chatClient.AsIChatClient().CreateAIAgent(
+ChatClientAgent agent = chatClient.AsIChatClient().AsAIAgent(
     name: "ChatAssistant",
     instructions: "You are a helpful assistant.");
 

dotnet/samples/AgentWebChat/AgentWebChat.Web/A2AAgentClient.cs

@@ -25,7 +25,7 @@ internal sealed class A2AAgentClient : AgentClientBase
         this._uri = baseUri;
     }
 
-    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
+    public override async IAsyncEnumerable<AgentResponseUpdate> 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<AgentRunResponseUpdate>();
+        var results = new List<AgentResponseUpdate>();
 
         try
         {
@@ -60,7 +60,7 @@ internal sealed class A2AAgentClient : AgentClientBase
                 var responseMessage = message.ToChatMessage();
                 if (responseMessage is { Contents.Count: > 0 })
                 {
-                    results.Add(new AgentRunResponseUpdate(responseMessage.Role, responseMessage.Contents)
+                    results.Add(new AgentResponseUpdate(responseMessage.Role, responseMessage.Contents)
                     {
                         MessageId = message.MessageId,
                         CreatedAt = DateTimeOffset.UtcNow
@@ -90,7 +90,7 @@ internal sealed class A2AAgentClient : AgentClientBase
                                 RawRepresentation = artifact,
                             };
 
-                            results.Add(new AgentRunResponseUpdate(chatMessage.Role, chatMessage.Contents)
+                            results.Add(new AgentResponseUpdate(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 AgentRunResponseUpdate(ChatRole.Assistant, $"Error: {ex.Message}")
+            results.Add(new AgentResponseUpdate(ChatRole.Assistant, $"Error: {ex.Message}")
             {
                 MessageId = Guid.NewGuid().ToString("N"),
                 CreatedAt = DateTimeOffset.UtcNow

dotnet/samples/AgentWebChat/AgentWebChat.Web/IAgentClient.cs

@@ -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<AgentRunResponseUpdate> RunStreamingAsync(
+    public abstract IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
         string agentName,
         IList<ChatMessage> messages,
         string? threadId = null,

dotnet/samples/AgentWebChat/AgentWebChat.Web/OpenAIChatCompletionsAgentClient.cs

@@ -16,7 +16,7 @@ namespace AgentWebChat.Web;
 /// </summary>
 internal sealed class OpenAIChatCompletionsAgentClient(HttpClient httpClient) : AgentClientBase
 {
-    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
+    public override async IAsyncEnumerable<AgentResponseUpdate> 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 AgentRunResponseUpdate(update);
+            yield return new AgentResponseUpdate(update);
         }
     }
 }

dotnet/samples/AgentWebChat/AgentWebChat.Web/OpenAIResponsesAgentClient.cs

@@ -15,7 +15,7 @@ namespace AgentWebChat.Web;
 /// </summary>
 internal sealed class OpenAIResponsesAgentClient(HttpClient httpClient) : AgentClientBase
 {
-    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
+    public override async IAsyncEnumerable<AgentResponseUpdate> 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 AgentRunResponseUpdate(update);
+            yield return new AgentResponseUpdate(update);
         }
     }
 }

dotnet/samples/AzureFunctions/01_SingleAgent/Program.cs

@@ -25,7 +25,7 @@ AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
 const string JokerName = "Joker";
 const string JokerInstructions = "You are good at telling jokes.";
 
-AIAgent agent = client.GetChatClient(deploymentName).CreateAIAgent(JokerInstructions, JokerName);
+AIAgent agent = client.GetChatClient(deploymentName).AsAIAgent(JokerInstructions, JokerName);
 
 // Configure the function app to host the AI agent.
 // This will automatically generate HTTP API endpoints for the agent.

dotnet/samples/AzureFunctions/02_AgentOrchestration_Chaining/FunctionTriggers.cs

@@ -19,13 +19,13 @@ public static class FunctionTriggers
     public static async Task<string> RunOrchestrationAsync([OrchestrationTrigger] TaskOrchestrationContext context)
     {
         DurableAIAgent writer = context.GetAgent("WriterAgent");
-        AgentThread writerThread = writer.GetNewThread();
+        AgentThread writerThread = await writer.GetNewThreadAsync();
 
-        AgentRunResponse<TextResponse> initial = await writer.RunAsync<TextResponse>(
+        AgentResponse<TextResponse> initial = await writer.RunAsync<TextResponse>(
             message: "Write a concise inspirational sentence about learning.",
             thread: writerThread);
 
-        AgentRunResponse<TextResponse> refined = await writer.RunAsync<TextResponse>(
+        AgentResponse<TextResponse> refined = await writer.RunAsync<TextResponse>(
             message: $"Improve this further while keeping it under 25 words: {initial.Result.Text}",
             thread: writerThread);
 

dotnet/samples/AzureFunctions/02_AgentOrchestration_Chaining/Program.cs

@@ -29,7 +29,7 @@ const string WriterInstructions =
     when given an improved sentence you polish it further.
     """;
 
-AIAgent writerAgent = client.GetChatClient(deploymentName).CreateAIAgent(WriterInstructions, WriterName);
+AIAgent writerAgent = client.GetChatClient(deploymentName).AsAIAgent(WriterInstructions, WriterName);
 
 using IHost app = FunctionsApplication
     .CreateBuilder(args)

dotnet/samples/AzureFunctions/03_AgentOrchestration_Concurrency/FunctionTriggers.cs

@@ -26,9 +26,9 @@ public static class FunctionsTriggers
         DurableAIAgent chemist = context.GetAgent("ChemistAgent");
 
         // Start both agent runs concurrently
-        Task<AgentRunResponse<TextResponse>> physicistTask = physicist.RunAsync<TextResponse>(prompt);
+        Task<AgentResponse<TextResponse>> physicistTask = physicist.RunAsync<TextResponse>(prompt);
 
-        Task<AgentRunResponse<TextResponse>> chemistTask = chemist.RunAsync<TextResponse>(prompt);
+        Task<AgentResponse<TextResponse>> chemistTask = chemist.RunAsync<TextResponse>(prompt);
 
         // Wait for both tasks to complete using Task.WhenAll
         await Task.WhenAll(physicistTask, chemistTask);

dotnet/samples/AzureFunctions/03_AgentOrchestration_Concurrency/Program.cs

@@ -28,8 +28,8 @@ const string PhysicistInstructions = "You are an expert in physics. You answer q
 const string ChemistName = "ChemistAgent";
 const string ChemistInstructions = "You are an expert in chemistry. You answer questions from a chemistry perspective.";
 
-AIAgent physicistAgent = client.GetChatClient(deploymentName).CreateAIAgent(PhysicistInstructions, PhysicistName);
-AIAgent chemistAgent = client.GetChatClient(deploymentName).CreateAIAgent(ChemistInstructions, ChemistName);
+AIAgent physicistAgent = client.GetChatClient(deploymentName).AsAIAgent(PhysicistInstructions, PhysicistName);
+AIAgent chemistAgent = client.GetChatClient(deploymentName).AsAIAgent(ChemistInstructions, ChemistName);
 
 using IHost app = FunctionsApplication
     .CreateBuilder(args)

dotnet/samples/AzureFunctions/04_AgentOrchestration_Conditionals/FunctionTriggers.cs

@@ -21,10 +21,10 @@ public static class FunctionTriggers
 
         // Get the spam detection agent
         DurableAIAgent spamDetectionAgent = context.GetAgent("SpamDetectionAgent");
-        AgentThread spamThread = spamDetectionAgent.GetNewThread();
+        AgentThread spamThread = await spamDetectionAgent.GetNewThreadAsync();
 
         // Step 1: Check if the email is spam
-        AgentRunResponse<DetectionResult> spamDetectionResponse = await spamDetectionAgent.RunAsync<DetectionResult>(
+        AgentResponse<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 = emailAssistantAgent.GetNewThread();
+        AgentThread emailThread = await emailAssistantAgent.GetNewThreadAsync();
 
-        AgentRunResponse<EmailResponse> emailAssistantResponse = await emailAssistantAgent.RunAsync<EmailResponse>(
+        AgentResponse<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:

dotnet/samples/AzureFunctions/04_AgentOrchestration_Conditionals/Program.cs

@@ -29,10 +29,10 @@ const string EmailAssistantName = "EmailAssistantAgent";
 const string EmailAssistantInstructions = "You are an email assistant that helps users draft responses to emails with professionalism.";
 
 AIAgent spamDetectionAgent = client.GetChatClient(deploymentName)
-    .CreateAIAgent(SpamDetectionInstructions, SpamDetectionName);
+    .AsAIAgent(SpamDetectionInstructions, SpamDetectionName);
 
 AIAgent emailAssistantAgent = client.GetChatClient(deploymentName)
-    .CreateAIAgent(EmailAssistantInstructions, EmailAssistantName);
+    .AsAIAgent(EmailAssistantInstructions, EmailAssistantName);
 
 using IHost app = FunctionsApplication
     .CreateBuilder(args)

dotnet/samples/AzureFunctions/05_AgentOrchestration_HITL/FunctionTriggers.cs

@@ -24,13 +24,13 @@ public static class FunctionTriggers
 
         // Get the writer agent
         DurableAIAgent writerAgent = context.GetAgent("WriterAgent");
-        AgentThread writerThread = writerAgent.GetNewThread();
+        AgentThread writerThread = await writerAgent.GetNewThreadAsync();
 
         // Set initial status
         context.SetCustomStatus($"Starting content generation for topic: {input.Topic}");
 
         // Step 1: Generate initial content
-        AgentRunResponse<GeneratedContent> writerResponse = await writerAgent.RunAsync<GeneratedContent>(
+        AgentResponse<GeneratedContent> writerResponse = await writerAgent.RunAsync<GeneratedContent>(
             message: $"Write a short article about '{input.Topic}'.",
             thread: writerThread);
         GeneratedContent content = writerResponse.Result;

dotnet/samples/AzureFunctions/05_AgentOrchestration_HITL/Program.cs

@@ -29,7 +29,7 @@ const string WriterInstructions =
     You write engaging, informative, and well-structured content that follows best practices for readability and accuracy.
     """;
 
-AIAgent writerAgent = client.GetChatClient(deploymentName).CreateAIAgent(WriterInstructions, WriterName);
+AIAgent writerAgent = client.GetChatClient(deploymentName).AsAIAgent(WriterInstructions, WriterName);
 
 using IHost app = FunctionsApplication
     .CreateBuilder(args)

dotnet/samples/AzureFunctions/06_LongRunningTools/FunctionTriggers.cs

@@ -20,13 +20,13 @@ public static class FunctionTriggers
 
         // Get the writer agent
         DurableAIAgent writerAgent = context.GetAgent("Writer");
-        AgentThread writerThread = writerAgent.GetNewThread();
+        AgentThread writerThread = await writerAgent.GetNewThreadAsync();
 
         // Set initial status
         context.SetCustomStatus($"Starting content generation for topic: {input.Topic}");
 
         // Step 1: Generate initial content
-        AgentRunResponse<GeneratedContent> writerResponse = await writerAgent.RunAsync<GeneratedContent>(
+        AgentResponse<GeneratedContent> writerResponse = await writerAgent.RunAsync<GeneratedContent>(
             message: $"Write a short article about '{input.Topic}'.",
             thread: writerThread);
         GeneratedContent content = writerResponse.Result;

dotnet/samples/AzureFunctions/06_LongRunningTools/Program.cs

@@ -33,7 +33,7 @@ const string WriterAgentInstructions =
     You write engaging, informative, and well-structured content that follows best practices for readability and accuracy.
     """;
 
-AIAgent writerAgent = client.GetChatClient(deploymentName).CreateAIAgent(WriterAgentInstructions, WriterAgentName);
+AIAgent writerAgent = client.GetChatClient(deploymentName).AsAIAgent(WriterAgentInstructions, WriterAgentName);
 
 // Agent that can start content generation workflows using tools
 const string PublisherAgentName = "Publisher";
@@ -57,7 +57,7 @@ using IHost app = FunctionsApplication
             // Initialize the tools to be used by the agent.
             Tools publisherTools = new(sp.GetRequiredService<ILogger<Tools>>());
 
-            return client.GetChatClient(deploymentName).CreateAIAgent(
+            return client.GetChatClient(deploymentName).AsAIAgent(
                 instructions: PublisherAgentInstructions,
                 name: PublisherAgentName,
                 services: sp,

dotnet/samples/AzureFunctions/07_AgentAsMcpTool/Program.cs

@@ -28,13 +28,13 @@ AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
     : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
 
 // Define three AI agents we are going to use in this application.
-AIAgent agent1 = client.GetChatClient(deploymentName).CreateAIAgent("You are good at telling jokes.", "Joker");
+AIAgent agent1 = client.GetChatClient(deploymentName).AsAIAgent("You are good at telling jokes.", "Joker");
 
 AIAgent agent2 = client.GetChatClient(deploymentName)
-    .CreateAIAgent("Check stock prices.", "StockAdvisor");
+    .AsAIAgent("Check stock prices.", "StockAdvisor");
 
 AIAgent agent3 = client.GetChatClient(deploymentName)
-    .CreateAIAgent("Recommend plants.", "PlantAdvisor", description: "Get plant recommendations.");
+    .AsAIAgent("Recommend plants.", "PlantAdvisor", description: "Get plant recommendations.");
 
 using IHost app = FunctionsApplication
     .CreateBuilder(args)

dotnet/samples/AzureFunctions/08_ReliableStreaming/08_ReliableStreaming.csproj

@@ -0,0 +1,47 @@
+<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>ReliableStreaming</AssemblyName>
+    <RootNamespace>ReliableStreaming</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.AspNetCore" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <!-- Redis for reliable streaming -->
+  <ItemGroup>
+    <PackageReference Include="StackExchange.Redis" />
+  </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" />
+  </ItemGroup>
+</Project>

dotnet/samples/AzureFunctions/08_ReliableStreaming/FunctionTriggers.cs

@@ -0,0 +1,319 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Text;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.DurableTask;
+using Microsoft.Agents.AI.Hosting.AzureFunctions;
+using Microsoft.AspNetCore.Http;
+using Microsoft.AspNetCore.Http.Features;
+using Microsoft.AspNetCore.Mvc;
+using Microsoft.Azure.Functions.Worker;
+using Microsoft.DurableTask.Client;
+using Microsoft.Extensions.Logging;
+
+namespace ReliableStreaming;
+
+/// <summary>
+/// HTTP trigger functions for reliable streaming of durable agent responses.
+/// </summary>
+/// <remarks>
+/// This class exposes two endpoints:
+/// <list type="bullet">
+/// <item>
+/// <term>Create</term>
+/// <description>Starts an agent run and streams responses. The response format depends on the
+/// <c>Accept</c> header: <c>text/plain</c> returns raw text (ideal for terminals), while
+/// <c>text/event-stream</c> or any other value returns Server-Sent Events (SSE).</description>
+/// </item>
+/// <item>
+/// <term>Stream</term>
+/// <description>Resumes a stream from a cursor position, enabling reliable message delivery</description>
+/// </item>
+/// </list>
+/// </remarks>
+public sealed class FunctionTriggers
+{
+    private readonly RedisStreamResponseHandler _streamHandler;
+    private readonly ILogger<FunctionTriggers> _logger;
+
+    /// <summary>
+    /// Initializes a new instance of the <see cref="FunctionTriggers"/> class.
+    /// </summary>
+    /// <param name="streamHandler">The Redis stream handler for reading/writing agent responses.</param>
+    /// <param name="logger">The logger instance.</param>
+    public FunctionTriggers(RedisStreamResponseHandler streamHandler, ILogger<FunctionTriggers> logger)
+    {
+        this._streamHandler = streamHandler;
+        this._logger = logger;
+    }
+
+    /// <summary>
+    /// Creates a new agent session, starts an agent run with the provided prompt,
+    /// and streams the response back to the client.
+    /// </summary>
+    /// <remarks>
+    /// <para>
+    /// The response format depends on the <c>Accept</c> header:
+    /// <list type="bullet">
+    /// <item><c>text/plain</c>: Returns raw text output, ideal for terminal display with curl</item>
+    /// <item><c>text/event-stream</c> or other: Returns Server-Sent Events (SSE) with cursor support</item>
+    /// </list>
+    /// </para>
+    /// <para>
+    /// The response includes an <c>x-conversation-id</c> header containing the conversation ID.
+    /// For SSE responses, clients can use this conversation ID to resume the stream if disconnected
+    /// by calling the <see cref="StreamAsync"/> endpoint with the conversation ID and the last received cursor.
+    /// </para>
+    /// <para>
+    /// Each SSE event contains the following fields:
+    /// <list type="bullet">
+    /// <item><c>id</c>: The Redis stream entry ID (use as cursor for resumption)</item>
+    /// <item><c>event</c>: Either "message" for content or "done" for stream completion</item>
+    /// <item><c>data</c>: The text content of the response chunk</item>
+    /// </list>
+    /// </para>
+    /// </remarks>
+    /// <param name="request">The HTTP request containing the prompt in the body.</param>
+    /// <param name="durableClient">The Durable Task client for signaling agents.</param>
+    /// <param name="context">The function invocation context.</param>
+    /// <param name="cancellationToken">Cancellation token.</param>
+    /// <returns>A streaming response in the format specified by the Accept header.</returns>
+    [Function(nameof(CreateAsync))]
+    public async Task<IActionResult> CreateAsync(
+        [HttpTrigger(AuthorizationLevel.Anonymous, "post", Route = "agent/create")] HttpRequest request,
+        [DurableClient] DurableTaskClient durableClient,
+        FunctionContext context,
+        CancellationToken cancellationToken)
+    {
+        // Read the prompt from the request body
+        string prompt = await new StreamReader(request.Body).ReadToEndAsync(cancellationToken);
+        if (string.IsNullOrWhiteSpace(prompt))
+        {
+            return new BadRequestObjectResult("Request body must contain a prompt.");
+        }
+
+        AIAgent agentProxy = durableClient.AsDurableAgentProxy(context, "TravelPlanner");
+
+        // Create a new agent thread
+        AgentThread thread = await agentProxy.GetNewThreadAsync(cancellationToken);
+        string agentSessionId = thread.GetService<AgentSessionId>().ToString();
+
+        this._logger.LogInformation("Creating new agent session: {AgentSessionId}", agentSessionId);
+
+        // Run the agent in the background (fire-and-forget)
+        DurableAgentRunOptions options = new() { IsFireAndForget = true };
+        await agentProxy.RunAsync(prompt, thread, options, cancellationToken);
+
+        this._logger.LogInformation("Agent run started for session: {AgentSessionId}", agentSessionId);
+
+        // Check Accept header to determine response format
+        // text/plain = raw text output (ideal for terminals)
+        // text/event-stream or other = SSE format (supports resumption)
+        string? acceptHeader = request.Headers.Accept.FirstOrDefault();
+        bool useSseFormat = acceptHeader?.Contains("text/plain", StringComparison.OrdinalIgnoreCase) != true;
+
+        return await this.StreamToClientAsync(
+            conversationId: agentSessionId, cursor: null, useSseFormat, request.HttpContext, cancellationToken);
+    }
+
+    /// <summary>
+    /// Resumes streaming from a specific cursor position for an existing session.
+    /// </summary>
+    /// <remarks>
+    /// <para>
+    /// Use this endpoint to resume a stream after disconnection. Pass the conversation ID
+    /// (from the <c>x-conversation-id</c> response header) and the last received cursor
+    /// (Redis stream entry ID) to continue from where you left off.
+    /// </para>
+    /// <para>
+    /// If no cursor is provided, streaming starts from the beginning of the stream.
+    /// This allows clients to replay the entire response if needed.
+    /// </para>
+    /// <para>
+    /// The response format depends on the <c>Accept</c> header:
+    /// <list type="bullet">
+    /// <item><c>text/plain</c>: Returns raw text output, ideal for terminal display with curl</item>
+    /// <item><c>text/event-stream</c> or other: Returns Server-Sent Events (SSE) with cursor support</item>
+    /// </list>
+    /// </para>
+    /// </remarks>
+    /// <param name="request">The HTTP request. Use the <c>cursor</c> query parameter to specify the cursor position.</param>
+    /// <param name="conversationId">The conversation ID to stream from.</param>
+    /// <param name="cancellationToken">Cancellation token.</param>
+    /// <returns>A streaming response in the format specified by the Accept header.</returns>
+    [Function(nameof(StreamAsync))]
+    public async Task<IActionResult> StreamAsync(
+        [HttpTrigger(AuthorizationLevel.Anonymous, "get", Route = "agent/stream/{conversationId}")] HttpRequest request,
+        string conversationId,
+        CancellationToken cancellationToken)
+    {
+        if (string.IsNullOrWhiteSpace(conversationId))
+        {
+            return new BadRequestObjectResult("Conversation ID is required.");
+        }
+
+        // Get the cursor from query string (optional)
+        string? cursor = request.Query["cursor"].FirstOrDefault();
+
+        this._logger.LogInformation(
+            "Resuming stream for conversation {ConversationId} from cursor: {Cursor}",
+            conversationId,
+            cursor ?? "(beginning)");
+
+        // Check Accept header to determine response format
+        // text/plain = raw text output (ideal for terminals)
+        // text/event-stream or other = SSE format (supports cursor-based resumption)
+        string? acceptHeader = request.Headers.Accept.FirstOrDefault();
+        bool useSseFormat = acceptHeader?.Contains("text/plain", StringComparison.OrdinalIgnoreCase) != true;
+
+        return await this.StreamToClientAsync(conversationId, cursor, useSseFormat, request.HttpContext, cancellationToken);
+    }
+
+    /// <summary>
+    /// Streams chunks from the Redis stream to the HTTP response.
+    /// </summary>
+    /// <param name="conversationId">The conversation ID to stream from.</param>
+    /// <param name="cursor">Optional cursor to resume from. If null, streams from the beginning.</param>
+    /// <param name="useSseFormat">True to use SSE format, false for plain text.</param>
+    /// <param name="httpContext">The HTTP context for writing the response.</param>
+    /// <param name="cancellationToken">Cancellation token.</param>
+    /// <returns>An empty result after streaming completes.</returns>
+    private async Task<IActionResult> StreamToClientAsync(
+        string conversationId,
+        string? cursor,
+        bool useSseFormat,
+        HttpContext httpContext,
+        CancellationToken cancellationToken)
+    {
+        // Set response headers based on format
+        httpContext.Response.Headers.ContentType = useSseFormat
+            ? "text/event-stream"
+            : "text/plain; charset=utf-8";
+        httpContext.Response.Headers.CacheControl = "no-cache";
+        httpContext.Response.Headers.Connection = "keep-alive";
+        httpContext.Response.Headers["x-conversation-id"] = conversationId;
+
+        // Disable response buffering if supported
+        httpContext.Features.Get<IHttpResponseBodyFeature>()?.DisableBuffering();
+
+        try
+        {
+            await foreach (StreamChunk chunk in this._streamHandler.ReadStreamAsync(
+                conversationId,
+                cursor,
+                cancellationToken))
+            {
+                if (chunk.Error != null)
+                {
+                    this._logger.LogWarning("Stream error for conversation {ConversationId}: {Error}", conversationId, chunk.Error);
+                    await WriteErrorAsync(httpContext.Response, chunk.Error, useSseFormat, cancellationToken);
+                    break;
+                }
+
+                if (chunk.IsDone)
+                {
+                    await WriteEndOfStreamAsync(httpContext.Response, chunk.EntryId, useSseFormat, cancellationToken);
+                    break;
+                }
+
+                if (chunk.Text != null)
+                {
+                    await WriteChunkAsync(httpContext.Response, chunk, useSseFormat, cancellationToken);
+                }
+            }
+        }
+        catch (OperationCanceledException)
+        {
+            this._logger.LogInformation("Client disconnected from stream {ConversationId}", conversationId);
+        }
+
+        return new EmptyResult();
+    }
+
+    /// <summary>
+    /// Writes a text chunk to the response.
+    /// </summary>
+    private static async Task WriteChunkAsync(
+        HttpResponse response,
+        StreamChunk chunk,
+        bool useSseFormat,
+        CancellationToken cancellationToken)
+    {
+        if (useSseFormat)
+        {
+            await WriteSSEEventAsync(response, "message", chunk.Text!, chunk.EntryId);
+        }
+        else
+        {
+            await response.WriteAsync(chunk.Text!, cancellationToken);
+        }
+
+        await response.Body.FlushAsync(cancellationToken);
+    }
+
+    /// <summary>
+    /// Writes an end-of-stream marker to the response.
+    /// </summary>
+    private static async Task WriteEndOfStreamAsync(
+        HttpResponse response,
+        string entryId,
+        bool useSseFormat,
+        CancellationToken cancellationToken)
+    {
+        if (useSseFormat)
+        {
+            await WriteSSEEventAsync(response, "done", "[DONE]", entryId);
+        }
+        else
+        {
+            await response.WriteAsync("\n", cancellationToken);
+        }
+
+        await response.Body.FlushAsync(cancellationToken);
+    }
+
+    /// <summary>
+    /// Writes an error message to the response.
+    /// </summary>
+    private static async Task WriteErrorAsync(
+        HttpResponse response,
+        string error,
+        bool useSseFormat,
+        CancellationToken cancellationToken)
+    {
+        if (useSseFormat)
+        {
+            await WriteSSEEventAsync(response, "error", error, null);
+        }
+        else
+        {
+            await response.WriteAsync($"\n[Error: {error}]\n", cancellationToken);
+        }
+
+        await response.Body.FlushAsync(cancellationToken);
+    }
+
+    /// <summary>
+    /// Writes a Server-Sent Event to the response stream.
+    /// </summary>
+    private static async Task WriteSSEEventAsync(
+        HttpResponse response,
+        string eventType,
+        string data,
+        string? id)
+    {
+        StringBuilder sb = new();
+
+        // Include the ID if provided (used as cursor for resumption)
+        if (!string.IsNullOrEmpty(id))
+        {
+            sb.AppendLine($"id: {id}");
+        }
+
+        sb.AppendLine($"event: {eventType}");
+        sb.AppendLine($"data: {data}");
+        sb.AppendLine(); // Empty line marks end of event
+
+        await response.WriteAsync(sb.ToString());
+    }
+}

dotnet/samples/AzureFunctions/08_ReliableStreaming/Program.cs

@@ -0,0 +1,100 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to implement reliable streaming for durable agents using Redis Streams.
+// It exposes two HTTP endpoints:
+// 1. Create - Starts an agent run and streams responses back via Server-Sent Events (SSE)
+// 2. Stream - Resumes a stream from a specific cursor position, enabling reliable message delivery
+//
+// This pattern is inspired by OpenAI's background mode for the Responses API, which allows clients
+// to disconnect and reconnect to ongoing agent responses without losing messages.
+
+using Azure;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI.DurableTask;
+using Microsoft.Agents.AI.Hosting.AzureFunctions;
+using Microsoft.Azure.Functions.Worker.Builder;
+using Microsoft.Extensions.AI;
+using Microsoft.Extensions.DependencyInjection;
+using Microsoft.Extensions.Hosting;
+using OpenAI.Chat;
+using ReliableStreaming;
+using StackExchange.Redis;
+
+// 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.");
+
+// Get Redis connection string from environment variable.
+string redisConnectionString = Environment.GetEnvironmentVariable("REDIS_CONNECTION_STRING")
+    ?? "localhost:6379";
+
+// Get the Redis stream TTL from environment variable (default: 10 minutes).
+int redisStreamTtlMinutes = int.TryParse(
+    Environment.GetEnvironmentVariable("REDIS_STREAM_TTL_MINUTES"),
+    out int ttlMinutes) ? ttlMinutes : 10;
+
+// 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());
+
+// Travel Planner agent instructions - designed to produce longer responses for demonstrating streaming.
+const string TravelPlannerName = "TravelPlanner";
+const string TravelPlannerInstructions =
+    """
+    You are an expert travel planner who creates detailed, personalized travel itineraries.
+    When asked to plan a trip, you should:
+    1. Create a comprehensive day-by-day itinerary
+    2. Include specific recommendations for activities, restaurants, and attractions
+    3. Provide practical tips for each destination
+    4. Consider weather and local events when making recommendations
+    5. Include estimated times and logistics between activities
+    
+    Always use the available tools to get current weather forecasts and local events
+    for the destination to make your recommendations more relevant and timely.
+    
+    Format your response with clear headings for each day and include emoji icons
+    to make the itinerary easy to scan and visually appealing.
+    """;
+
+// Configure the function app to host the AI agent.
+FunctionsApplicationBuilder builder = FunctionsApplication
+    .CreateBuilder(args)
+    .ConfigureFunctionsWebApplication()
+    .ConfigureDurableAgents(options =>
+    {
+        // Define the Travel Planner agent with tools for weather and events
+        options.AddAIAgentFactory(TravelPlannerName, sp =>
+        {
+            return client.GetChatClient(deploymentName).AsAIAgent(
+                instructions: TravelPlannerInstructions,
+                name: TravelPlannerName,
+                services: sp,
+                tools: [
+                    AIFunctionFactory.Create(TravelTools.GetWeatherForecast),
+                    AIFunctionFactory.Create(TravelTools.GetLocalEvents),
+                ]);
+        });
+    });
+
+// Register Redis connection as a singleton
+builder.Services.AddSingleton<IConnectionMultiplexer>(_ =>
+    ConnectionMultiplexer.Connect(redisConnectionString));
+
+// Register the Redis stream response handler - this captures agent responses
+// and publishes them to Redis Streams for reliable delivery.
+// Registered as both the concrete type (for FunctionTriggers) and the interface (for the agent framework).
+builder.Services.AddSingleton(sp =>
+    new RedisStreamResponseHandler(
+        sp.GetRequiredService<IConnectionMultiplexer>(),
+        TimeSpan.FromMinutes(redisStreamTtlMinutes)));
+builder.Services.AddSingleton<IAgentResponseHandler>(sp =>
+    sp.GetRequiredService<RedisStreamResponseHandler>());
+
+using IHost app = builder.Build();
+
+app.Run();

dotnet/samples/AzureFunctions/08_ReliableStreaming/README.md

@@ -0,0 +1,264 @@
+# Reliable Streaming with Redis
+
+This sample demonstrates how to implement reliable streaming for durable agents using Redis Streams as a message broker. It enables clients to disconnect and reconnect to ongoing agent responses without losing messages, inspired by [OpenAI's background mode](https://platform.openai.com/docs/guides/background) for the Responses API.
+
+## Key Concepts Demonstrated
+
+- **Reliable message delivery**: Agent responses are persisted to Redis Streams, allowing clients to resume from any point
+- **Content negotiation**: Use `Accept: text/plain` for raw terminal output, or `Accept: text/event-stream` for SSE format
+- **Server-Sent Events (SSE)**: Standard streaming format that works with `curl`, browsers, and most HTTP clients
+- **Cursor-based resumption**: Each SSE event includes an `id` field that can be used to resume the stream
+- **Fire-and-forget agent invocation**: The agent runs in the background while the client streams from Redis via an HTTP trigger function
+
+## 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.
+
+### Additional Requirements: Redis
+
+This sample requires a Redis instance. Start a local Redis instance using Docker:
+
+```bash
+docker run -d --name redis -p 6379:6379 redis:latest
+```
+
+To verify Redis is running:
+
+```bash
+docker ps | grep redis
+```
+
+## Running the Sample
+
+Start the Azure Functions host:
+
+```bash
+func start
+```
+
+### 1. Test Streaming with curl
+
+Open a new terminal and start a travel planning request. Use the `-i` flag to see response headers (including the conversation ID) and `Accept: text/plain` for raw text output:
+
+**Bash (Linux/macOS/WSL):**
+
+```bash
+curl -i -N -X POST http://localhost:7071/api/agent/create \
+  -H "Content-Type: text/plain" \
+  -H "Accept: text/plain" \
+  -d "Plan a 7-day trip to Tokyo, Japan for next month. Include daily activities, restaurant recommendations, and tips for getting around."
+```
+
+**PowerShell:**
+
+```powershell
+curl -i -N -X POST http://localhost:7071/api/agent/create `
+  -H "Content-Type: text/plain" `
+  -H "Accept: text/plain" `
+  -d "Plan a 7-day trip to Tokyo, Japan for next month. Include daily activities, restaurant recommendations, and tips for getting around."
+```
+
+You'll first see the response headers, including:
+
+```text
+HTTP/1.1 200 OK
+Content-Type: text/plain; charset=utf-8
+x-conversation-id: @dafx-travelplanner@a1b2c3d4e5f67890abcdef1234567890
+...
+```
+
+Then the agent's response will stream to your terminal in chunks, similar to a ChatGPT-style experience (though not character-by-character).
+
+> **Note:** The `-N` flag in curl disables output buffering, which is essential for seeing the stream in real-time. The `-i` flag includes the HTTP headers in the output.
+
+### 2. Demonstrate Stream Interruption and Resumption
+
+This is the key feature of reliable streaming! Follow these steps to see it in action:
+
+#### Step 1: Start a stream and note the conversation ID
+
+Run the curl command from step 1. Watch for the `x-conversation-id` header in the response - **copy this value**, you'll need it to resume.
+
+```text
+x-conversation-id: @dafx-travelplanner@a1b2c3d4e5f67890abcdef1234567890
+```
+
+#### Step 2: Interrupt the stream
+
+While the agent is still generating text, press **`Ctrl+C`** to interrupt the stream. The agent continues running in the background - your messages are being saved to Redis!
+
+#### Step 3: Resume the stream
+
+Use the conversation ID you copied to resume streaming from where you left off. Include the `Accept: text/plain` header to get raw text output:
+
+**Bash (Linux/macOS/WSL):**
+
+```bash
+# Replace with your actual conversation ID from the x-conversation-id header
+CONVERSATION_ID="@dafx-travelplanner@a1b2c3d4e5f67890abcdef1234567890"
+
+curl -N -H "Accept: text/plain" "http://localhost:7071/api/agent/stream/${CONVERSATION_ID}"
+```
+
+**PowerShell:**
+
+```powershell
+# Replace with your actual conversation ID from the x-conversation-id header
+$conversationId = "@dafx-travelplanner@a1b2c3d4e5f67890abcdef1234567890"
+
+curl -N -H "Accept: text/plain" "http://localhost:7071/api/agent/stream/$conversationId"
+```
+
+You'll see the **entire response replayed from the beginning**, including the parts you already received before interrupting.
+
+#### Step 4 (Advanced): Resume from a specific cursor
+
+If you're using SSE format, each event includes an `id` field that you can use as a cursor to resume from a specific point:
+
+```bash
+# Resume from a specific cursor position
+curl -N "http://localhost:7071/api/agent/stream/${CONVERSATION_ID}?cursor=1734567890123-0"
+```
+
+### 3. Alternative: SSE Format for Programmatic Clients
+
+If you need the full Server-Sent Events format with cursors for resumable streaming, use `Accept: text/event-stream` (or omit the Accept header):
+
+```bash
+curl -i -N -X POST http://localhost:7071/api/agent/create \
+  -H "Content-Type: text/plain" \
+  -H "Accept: text/event-stream" \
+  -d "Plan a 7-day trip to Tokyo, Japan."
+```
+
+This returns SSE-formatted events with `id`, `event`, and `data` fields:
+
+```text
+id: 1734567890123-0
+event: message
+data: # 7-Day Tokyo Adventure
+
+id: 1734567890124-0
+event: message
+data: ## Day 1: Arrival and Exploration
+
+id: 1734567890999-0
+event: done
+data: [DONE]
+```
+
+The `id` field is the Redis stream entry ID - use it as the `cursor` parameter to resume from that exact point.
+
+### Understanding the Response Headers
+
+| Header | Description |
+|--------|-------------|
+| `x-conversation-id` | The conversation ID (session key). Use this to resume the stream. |
+| `Content-Type` | Either `text/plain` or `text/event-stream` depending on your `Accept` header. |
+| `Cache-Control` | Set to `no-cache` to prevent caching of the stream. |
+
+## Architecture Overview
+
+```text
+┌─────────────┐      POST /agent/create     ┌─────────────────────┐
+│   Client    │  (Accept: text/plain or SSE)│  Azure Functions    │
+│   (curl)    │ ──────────────────────────► │  (FunctionTriggers) │
+└─────────────┘                             └──────────┬──────────┘
+       ▲                                               │
+       │ Text or SSE stream                  Signal Entity
+       │                                               │
+       │                                               ▼
+       │                                    ┌─────────────────────┐
+       │                                    │   AgentEntity       │
+       │                                    │   (Durable Entity)  │
+       │                                    └──────────┬──────────┘
+       │                                               │
+       │                                    IAgentResponseHandler
+       │                                               │
+       │                                               ▼
+       │                                    ┌─────────────────────┐
+       │                                    │ RedisStreamResponse │
+       │                                    │      Handler        │
+       │                                    └──────────┬──────────┘
+       │                                               │
+       │                                     XADD (write)
+       │                                               │
+       │                                               ▼
+       │                                    ┌─────────────────────┐
+       └─────────── XREAD (poll) ────────── │   Redis Streams     │
+                                            │  (Durable Log)      │
+                                            └─────────────────────┘
+```
+
+### Data Flow
+
+1. **Client sends prompt**: The `Create` endpoint receives the prompt and generates a new agent thread.
+
+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.
+
+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.
+
+5. **Resumption**: If the client disconnects, it can call the `Stream` endpoint with the conversation ID (from the `x-conversation-id` header) and optionally the last received cursor to resume from that point.
+
+## Message Delivery Guarantees
+
+This sample provides **at-least-once delivery** with the following characteristics:
+
+- **Durability**: Messages are persisted to Redis Streams with configurable TTL (default: 10 minutes).
+- **Ordering**: Messages are delivered in order within a session.
+- **Resumption**: Clients can resume from any point using cursor-based pagination.
+- **Replay**: Clients can replay the entire stream by omitting the cursor.
+
+### Important Considerations
+
+- **No exactly-once delivery**: If a client disconnects exactly when receiving a message, it may receive that message again upon resumption. Clients should handle duplicate messages idempotently.
+- **TTL expiration**: Streams expire after the configured TTL. Clients cannot resume streams that have expired.
+- **Redis guarantees**: Redis streams are backed by Redis persistence mechanisms (RDB/AOF). Ensure your Redis instance is configured for durability as needed.
+
+## When to Use These Patterns
+
+The patterns demonstrated in this sample are ideal for:
+
+- **Long-running agent tasks**: When agent responses take minutes to complete (e.g., deep research, complex planning)
+- **Unreliable network connections**: Mobile apps, unstable WiFi, or connections that may drop
+- **Resumable experiences**: Users should be able to close and reopen an app without losing context
+- **Background processing**: When you want to fire off a task and check on it later
+
+These patterns may be overkill for:
+
+- **Simple, fast responses**: If responses complete in a few seconds, standard streaming is simpler
+- **Stateless interactions**: If there's no need to resume or replay conversations
+- **Very high throughput**: Redis adds latency; for maximum throughput, direct streaming may be better
+
+## Configuration
+
+| Environment Variable | Description | Default |
+|---------------------|-------------|---------|
+| `REDIS_CONNECTION_STRING` | Redis connection string | `localhost:6379` |
+| `REDIS_STREAM_TTL_MINUTES` | How long streams are retained after last write | `10` |
+| `AZURE_OPENAI_ENDPOINT` | Azure OpenAI endpoint URL | (required) |
+| `AZURE_OPENAI_DEPLOYMENT` | Azure OpenAI deployment name | (required) |
+| `AZURE_OPENAI_KEY` | API key (optional, uses Azure CLI auth if not set) | (optional) |
+
+## Cleanup
+
+To stop and remove the Redis Docker containers:
+
+```bash
+docker stop redis
+docker rm redis
+```
+
+## Disclaimer
+
+> ⚠️ **This sample is for illustration purposes only and is not intended to be production-ready.**
+>
+> A production implementation should consider:
+>
+> - Redis cluster configuration for high availability
+> - Authentication and authorization for the streaming endpoints
+> - Rate limiting and abuse prevention
+> - Monitoring and alerting for stream health
+> - Graceful handling of Redis failures

dotnet/samples/AzureFunctions/08_ReliableStreaming/RedisStreamResponseHandler.cs

@@ -0,0 +1,212 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Runtime.CompilerServices;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.DurableTask;
+using StackExchange.Redis;
+
+namespace ReliableStreaming;
+
+/// <summary>
+/// Represents a chunk of data read from a Redis stream.
+/// </summary>
+/// <param name="EntryId">The Redis stream entry ID (can be used as a cursor for resumption).</param>
+/// <param name="Text">The text content of the chunk, or null if this is a completion/error marker.</param>
+/// <param name="IsDone">True if this chunk marks the end of the stream.</param>
+/// <param name="Error">An error message if something went wrong, or null otherwise.</param>
+public readonly record struct StreamChunk(string EntryId, string? Text, bool IsDone, string? Error);
+
+/// <summary>
+/// An implementation of <see cref="IAgentResponseHandler"/> that publishes agent response updates
+/// to Redis Streams for reliable delivery. This enables clients to disconnect and reconnect
+/// to ongoing agent responses without losing messages.
+/// </summary>
+/// <remarks>
+/// <para>
+/// Redis Streams provide a durable, append-only log that supports consumer groups and message
+/// acknowledgment. This implementation uses auto-generated IDs (which are timestamp-based)
+/// as sequence numbers, allowing clients to resume from any point in the stream.
+/// </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.
+/// </para>
+/// </remarks>
+public sealed class RedisStreamResponseHandler : IAgentResponseHandler
+{
+    private const int MaxEmptyReads = 300; // 5 minutes at 1 second intervals
+    private const int PollIntervalMs = 1000;
+
+    private readonly IConnectionMultiplexer _redis;
+    private readonly TimeSpan _streamTtl;
+
+    /// <summary>
+    /// Initializes a new instance of the <see cref="RedisStreamResponseHandler" /> class.
+    /// </summary>
+    /// <param name="redis">The Redis connection multiplexer.</param>
+    /// <param name="streamTtl">The time-to-live for stream entries. Streams will expire after this duration of inactivity.</param>
+    public RedisStreamResponseHandler(IConnectionMultiplexer redis, TimeSpan streamTtl)
+    {
+        this._redis = redis;
+        this._streamTtl = streamTtl;
+    }
+
+    /// <inheritdoc/>
+    public async ValueTask OnStreamingResponseUpdateAsync(
+        IAsyncEnumerable<AgentResponseUpdate> messageStream,
+        CancellationToken cancellationToken)
+    {
+        // Get the current session ID from the DurableAgentContext
+        // This is set by the AgentEntity before invoking the response handler
+        DurableAgentContext? context = DurableAgentContext.Current;
+        if (context is null)
+        {
+            throw new InvalidOperationException(
+                "DurableAgentContext.Current is not set. This handler must be used within a durable agent context.");
+        }
+
+        // Get session ID from the current thread context, which is only available in the context of
+        // a durable agent execution.
+        string agentSessionId = context.CurrentThread.GetService<AgentSessionId>().ToString();
+        string streamKey = GetStreamKey(agentSessionId);
+
+        IDatabase db = this._redis.GetDatabase();
+        int sequenceNumber = 0;
+
+        await foreach (AgentResponseUpdate update in messageStream.WithCancellation(cancellationToken))
+        {
+            // Extract just the text content - this avoids serialization round-trip issues
+            string text = update.Text;
+
+            // Only publish non-empty text chunks
+            if (!string.IsNullOrEmpty(text))
+            {
+                // Create the stream entry with the text and metadata
+                NameValueEntry[] entries =
+                [
+                    new NameValueEntry("text", text),
+                    new NameValueEntry("sequence", sequenceNumber++),
+                    new NameValueEntry("timestamp", DateTimeOffset.UtcNow.ToUnixTimeMilliseconds()),
+                ];
+
+                // Add to the Redis Stream with auto-generated ID (timestamp-based)
+                await db.StreamAddAsync(streamKey, entries);
+
+                // Refresh the TTL on each write to keep the stream alive during active streaming
+                await db.KeyExpireAsync(streamKey, this._streamTtl);
+            }
+        }
+
+        // Add a sentinel entry to mark the end of the stream
+        NameValueEntry[] endEntries =
+        [
+            new NameValueEntry("text", ""),
+            new NameValueEntry("sequence", sequenceNumber),
+            new NameValueEntry("timestamp", DateTimeOffset.UtcNow.ToUnixTimeMilliseconds()),
+            new NameValueEntry("done", "true"),
+        ];
+        await db.StreamAddAsync(streamKey, endEntries);
+
+        // Set final TTL - the stream will be cleaned up after this duration
+        await db.KeyExpireAsync(streamKey, this._streamTtl);
+    }
+
+    /// <inheritdoc/>
+    public ValueTask OnAgentResponseAsync(AgentResponse message, CancellationToken cancellationToken)
+    {
+        // This handler is optimized for streaming responses.
+        // For non-streaming responses, we don't need to store in Redis since
+        // the response is returned directly to the caller.
+        return ValueTask.CompletedTask;
+    }
+
+    /// <summary>
+    /// Reads chunks from a Redis stream for the given session, yielding them as they become available.
+    /// </summary>
+    /// <param name="conversationId">The conversation ID to read from.</param>
+    /// <param name="cursor">Optional cursor to resume from. If null, reads from the beginning.</param>
+    /// <param name="cancellationToken">Cancellation token.</param>
+    /// <returns>An async enumerable of stream chunks.</returns>
+    public async IAsyncEnumerable<StreamChunk> ReadStreamAsync(
+        string conversationId,
+        string? cursor,
+        [EnumeratorCancellation] CancellationToken cancellationToken)
+    {
+        string streamKey = GetStreamKey(conversationId);
+
+        IDatabase db = this._redis.GetDatabase();
+        string startId = string.IsNullOrEmpty(cursor) ? "0-0" : cursor;
+
+        int emptyReadCount = 0;
+        bool hasSeenData = false;
+
+        while (!cancellationToken.IsCancellationRequested)
+        {
+            StreamEntry[]? entries = null;
+            string? errorMessage = null;
+
+            try
+            {
+                entries = await db.StreamReadAsync(streamKey, startId, count: 100);
+            }
+            catch (Exception ex)
+            {
+                errorMessage = ex.Message;
+            }
+
+            if (errorMessage != null)
+            {
+                yield return new StreamChunk(startId, null, false, errorMessage);
+                yield break;
+            }
+
+            // entries is guaranteed to be non-null if errorMessage is null
+            if (entries!.Length == 0)
+            {
+                if (!hasSeenData)
+                {
+                    emptyReadCount++;
+                    if (emptyReadCount >= MaxEmptyReads)
+                    {
+                        yield return new StreamChunk(
+                            startId,
+                            null,
+                            false,
+                            $"Stream not found or timed out after {MaxEmptyReads * PollIntervalMs / 1000} seconds");
+                        yield break;
+                    }
+                }
+
+                await Task.Delay(PollIntervalMs, cancellationToken);
+                continue;
+            }
+
+            hasSeenData = true;
+
+            foreach (StreamEntry entry in entries)
+            {
+                startId = entry.Id.ToString();
+                string? text = entry["text"];
+                string? done = entry["done"];
+
+                if (done == "true")
+                {
+                    yield return new StreamChunk(startId, null, true, null);
+                    yield break;
+                }
+
+                if (!string.IsNullOrEmpty(text))
+                {
+                    yield return new StreamChunk(startId, text, false, null);
+                }
+            }
+        }
+    }
+
+    /// <summary>
+    /// Gets the Redis Stream key for a given conversation ID.
+    /// </summary>
+    /// <param name="conversationId">The conversation ID.</param>
+    /// <returns>The Redis Stream key.</returns>
+    internal static string GetStreamKey(string conversationId) => $"agent-stream:{conversationId}";
+}

dotnet/samples/AzureFunctions/08_ReliableStreaming/Tools.cs

@@ -0,0 +1,161 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.ComponentModel;
+
+namespace ReliableStreaming;
+
+/// <summary>
+/// Mock travel tools that return hardcoded data for demonstration purposes.
+/// In a real application, these would call actual weather and events APIs.
+/// </summary>
+internal static class TravelTools
+{
+    /// <summary>
+    /// Gets a weather forecast for a destination on a specific date.
+    /// Returns mock weather data for demonstration purposes.
+    /// </summary>
+    /// <param name="destination">The destination city or location.</param>
+    /// <param name="date">The date for the forecast (e.g., "2025-01-15" or "next Monday").</param>
+    /// <returns>A weather forecast summary.</returns>
+    [Description("Gets the weather forecast for a destination on a specific date. Use this to provide weather-aware recommendations in the itinerary.")]
+    public static string GetWeatherForecast(string destination, string date)
+    {
+        // Mock weather data based on destination for realistic responses
+        Dictionary<string, (string condition, int highF, int lowF)> weatherByRegion = new(StringComparer.OrdinalIgnoreCase)
+        {
+            ["Tokyo"] = ("Partly cloudy with a chance of light rain", 58, 45),
+            ["Paris"] = ("Overcast with occasional drizzle", 52, 41),
+            ["New York"] = ("Clear and cold", 42, 28),
+            ["London"] = ("Foggy morning, clearing in afternoon", 48, 38),
+            ["Sydney"] = ("Sunny and warm", 82, 68),
+            ["Rome"] = ("Sunny with light breeze", 62, 48),
+            ["Barcelona"] = ("Partly sunny", 59, 47),
+            ["Amsterdam"] = ("Cloudy with light rain", 46, 38),
+            ["Dubai"] = ("Sunny and hot", 85, 72),
+            ["Singapore"] = ("Tropical thunderstorms in afternoon", 88, 77),
+            ["Bangkok"] = ("Hot and humid, afternoon showers", 91, 78),
+            ["Los Angeles"] = ("Sunny and pleasant", 72, 55),
+            ["San Francisco"] = ("Morning fog, afternoon sun", 62, 52),
+            ["Seattle"] = ("Rainy with breaks", 48, 40),
+            ["Miami"] = ("Warm and sunny", 78, 65),
+            ["Honolulu"] = ("Tropical paradise weather", 82, 72),
+        };
+
+        // Find a matching destination or use a default
+        (string condition, int highF, int lowF) forecast = ("Partly cloudy", 65, 50);
+        foreach (KeyValuePair<string, (string, int, int)> entry in weatherByRegion)
+        {
+            if (destination.Contains(entry.Key, StringComparison.OrdinalIgnoreCase))
+            {
+                forecast = entry.Value;
+                break;
+            }
+        }
+
+        return $"""
+            Weather forecast for {destination} on {date}:
+            Conditions: {forecast.condition}
+            High: {forecast.highF}°F ({(forecast.highF - 32) * 5 / 9}°C)
+            Low: {forecast.lowF}°F ({(forecast.lowF - 32) * 5 / 9}°C)
+            
+            Recommendation: {GetWeatherRecommendation(forecast.condition)}
+            """;
+    }
+
+    /// <summary>
+    /// Gets local events happening at a destination around a specific date.
+    /// Returns mock event data for demonstration purposes.
+    /// </summary>
+    /// <param name="destination">The destination city or location.</param>
+    /// <param name="date">The date to search for events (e.g., "2025-01-15" or "next week").</param>
+    /// <returns>A list of local events and activities.</returns>
+    [Description("Gets local events and activities happening at a destination around a specific date. Use this to suggest timely activities and experiences.")]
+    public static string GetLocalEvents(string destination, string date)
+    {
+        // Mock events data based on destination
+        Dictionary<string, string[]> eventsByCity = new(StringComparer.OrdinalIgnoreCase)
+        {
+            ["Tokyo"] = [
+                "🎭 Kabuki Theater Performance at Kabukiza Theatre - Traditional Japanese drama",
+                "🌸 Winter Illuminations at Yoyogi Park - Spectacular light displays",
+                "🍜 Ramen Festival at Tokyo Station - Sample ramen from across Japan",
+                "🎮 Gaming Expo at Tokyo Big Sight - Latest video games and technology",
+            ],
+            ["Paris"] = [
+                "🎨 Impressionist Exhibition at Musée d'Orsay - Extended evening hours",
+                "🍷 Wine Tasting Tour in Le Marais - Local sommelier guided",
+                "🎵 Jazz Night at Le Caveau de la Huchette - Historic jazz club",
+                "🥐 French Pastry Workshop - Learn from master pâtissiers",
+            ],
+            ["New York"] = [
+                "🎭 Broadway Show: Hamilton - Limited engagement performances",
+                "🏀 Knicks vs Lakers at Madison Square Garden",
+                "🎨 Modern Art Exhibit at MoMA - New installations",
+                "🍕 Pizza Walking Tour of Brooklyn - Artisan pizzerias",
+            ],
+            ["London"] = [
+                "👑 Royal Collection Exhibition at Buckingham Palace",
+                "🎭 West End Musical: The Phantom of the Opera",
+                "🍺 Craft Beer Festival at Brick Lane",
+                "🎪 Winter Wonderland at Hyde Park - Rides and markets",
+            ],
+            ["Sydney"] = [
+                "🏄 Pro Surfing Competition at Bondi Beach",
+                "🎵 Opera at Sydney Opera House - La Bohème",
+                "🦘 Wildlife Night Safari at Taronga Zoo",
+                "🍽️ Harbor Dinner Cruise with fireworks",
+            ],
+            ["Rome"] = [
+                "🏛️ After-Hours Vatican Tour - Skip the crowds",
+                "🍝 Pasta Making Class in Trastevere",
+                "🎵 Classical Concert at Borghese Gallery",
+                "🍷 Wine Tasting in Roman Cellars",
+            ],
+        };
+
+        // Find events for the destination or use generic events
+        string[] events = [
+            "🎭 Local theater performance",
+            "🍽️ Food and wine festival",
+            "🎨 Art gallery opening",
+            "🎵 Live music at local venues",
+        ];
+
+        foreach (KeyValuePair<string, string[]> entry in eventsByCity)
+        {
+            if (destination.Contains(entry.Key, StringComparison.OrdinalIgnoreCase))
+            {
+                events = entry.Value;
+                break;
+            }
+        }
+
+        string eventList = string.Join("\n• ", events);
+        return $"""
+            Local events in {destination} around {date}:
+            
+            • {eventList}
+            
+            💡 Tip: Book popular events in advance as they may sell out quickly!
+            """;
+    }
+
+    private static string GetWeatherRecommendation(string condition)
+    {
+        // Use case-insensitive comparison instead of ToLowerInvariant() to satisfy CA1308
+        return condition switch
+        {
+            string c when c.Contains("rain", StringComparison.OrdinalIgnoreCase) || c.Contains("drizzle", StringComparison.OrdinalIgnoreCase) =>
+                "Bring an umbrella and waterproof jacket. Consider indoor activities for backup.",
+            string c when c.Contains("fog", StringComparison.OrdinalIgnoreCase) =>
+                "Morning visibility may be limited. Plan outdoor sightseeing for afternoon.",
+            string c when c.Contains("cold", StringComparison.OrdinalIgnoreCase) =>
+                "Layer up with warm clothing. Hot drinks and cozy cafés recommended.",
+            string c when c.Contains("hot", StringComparison.OrdinalIgnoreCase) || c.Contains("warm", StringComparison.OrdinalIgnoreCase) =>
+                "Stay hydrated and use sunscreen. Plan strenuous activities for cooler morning hours.",
+            string c when c.Contains("thunder", StringComparison.OrdinalIgnoreCase) || c.Contains("storm", StringComparison.OrdinalIgnoreCase) =>
+                "Keep an eye on weather updates. Have indoor alternatives ready.",
+            _ => "Pleasant conditions expected. Great day for outdoor exploration!"
+        };
+    }
+}

dotnet/samples/AzureFunctions/08_ReliableStreaming/host.json

@@ -0,0 +1,21 @@
+{
+  "version": "2.0",
+  "logging": {
+    "logLevel": {
+      "Microsoft.Agents.AI.DurableTask": "Information",
+      "Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
+      "DurableTask": "Information",
+      "Microsoft.DurableTask": "Information",
+      "ReliableStreaming": "Information"
+    }
+  },
+  "extensions": {
+    "durableTask": {
+      "hubName": "default",
+      "storageProvider": {
+        "type": "AzureManaged",
+        "connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
+      }
+    }
+  }
+}

dotnet/samples/AzureFunctions/08_ReliableStreaming/local.settings.json

@@ -0,0 +1,12 @@
+{
+  "IsEncrypted": false,
+  "Values": {
+    "FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated",
+    "AzureWebJobsStorage": "UseDevelopmentStorage=true",
+    "DURABLE_TASK_SCHEDULER_CONNECTION_STRING": "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None",
+    "AZURE_OPENAI_ENDPOINT": "<AZURE_OPENAI_ENDPOINT>",
+    "AZURE_OPENAI_DEPLOYMENT": "<AZURE_OPENAI_DEPLOYMENT>",
+    "REDIS_CONNECTION_STRING": "localhost:6379",
+    "REDIS_STREAM_TTL_MINUTES": "10"
+  }
+}

dotnet/samples/AzureFunctions/README.md

@@ -9,6 +9,7 @@ This directory contains samples for Azure Functions.
 - **[05_AgentOrchestration_HITL](05_AgentOrchestration_HITL)**: A sample that demonstrates how to implement a human-in-the-loop workflow using durable orchestration, including external event handling for human approval.
 - **[06_LongRunningTools](06_LongRunningTools)**: A sample that demonstrates how agents can start and interact with durable orchestrations from tool calls to enable long-running tool scenarios.
 - **[07_AgentAsMcpTool](07_AgentAsMcpTool)**: A sample that demonstrates how to configure durable AI agents to be accessible as Model Context Protocol (MCP) tools.
+- **[08_ReliableStreaming](08_ReliableStreaming)**: A sample that demonstrates how to implement reliable streaming for durable agents using Redis Streams, enabling clients to disconnect and reconnect without losing messages.
 
 ## Running the Samples
 

dotnet/samples/GettingStarted/A2A/A2AAgent_AsFunctionTools/Program.cs

@@ -23,14 +23,14 @@ A2ACardResolver agentCardResolver = new(new Uri(a2aAgentHost));
 AgentCard agentCard = await agentCardResolver.GetAgentCardAsync();
 
 // Create an instance of the AIAgent for an existing A2A agent specified by the agent card.
-AIAgent a2aAgent = agentCard.GetAIAgent();
+AIAgent a2aAgent = agentCard.AsAIAgent();
 
 // Create the main agent, and provide the a2a agent skills as a function tools.
 AIAgent agent = new AzureOpenAIClient(
     new Uri(endpoint),
     new AzureCliCredential())
     .GetChatClient(deploymentName)
-    .CreateAIAgent(
+    .AsAIAgent(
         instructions: "You are a helpful assistant that helps people with travel planning.",
         tools: [.. CreateFunctionTools(a2aAgent, agentCard)]
     );

dotnet/samples/GettingStarted/A2A/A2AAgent_PollingForTaskCompletion/Program.cs

@@ -14,12 +14,12 @@ A2ACardResolver agentCardResolver = new(new Uri(a2aAgentHost));
 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();
+AIAgent agent = agentCard.AsAIAgent();
 
-AgentThread thread = agent.GetNewThread();
+AgentThread thread = await agent.GetNewThreadAsync();
 
 // Start the initial run with a long-running task.
-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);
+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);
 
 // Poll until the response is complete.
 while (response.ContinuationToken is { } token)

dotnet/samples/GettingStarted/AGUI/README.md

@@ -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 `AgentRunResponseUpdate` objects
+3. Client parses events into `AgentResponseUpdate` objects
 4. Updates are displayed based on content type
 5. `ConversationId` maintains conversation context
 

dotnet/samples/GettingStarted/AGUI/Step01_GettingStarted/Client/Program.cs

@@ -16,11 +16,11 @@ using HttpClient httpClient = new()
 
 AGUIChatClient chatClient = new(httpClient, serverUrl);
 
-AIAgent agent = chatClient.CreateAIAgent(
+AIAgent agent = chatClient.AsAIAgent(
     name: "agui-client",
     description: "AG-UI Client Agent");
 
-AgentThread thread = agent.GetNewThread();
+AgentThread thread = await agent.GetNewThreadAsync();
 List<ChatMessage> messages =
 [
     new(ChatRole.System, "You are a helpful assistant.")
@@ -51,7 +51,7 @@ try
         bool isFirstUpdate = true;
         string? threadId = null;
 
-        await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread))
+        await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread))
         {
             ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();
 

dotnet/samples/GettingStarted/AGUI/Step01_GettingStarted/Server/Program.cs

@@ -24,7 +24,7 @@ ChatClient chatClient = new AzureOpenAIClient(
         new DefaultAzureCredential())
     .GetChatClient(deploymentName);
 
-AIAgent agent = chatClient.AsIChatClient().CreateAIAgent(
+AIAgent agent = chatClient.AsIChatClient().AsAIAgent(
     name: "AGUIAssistant",
     instructions: "You are a helpful assistant.");
 

dotnet/samples/GettingStarted/AGUI/Step02_BackendTools/Client/Program.cs

@@ -16,11 +16,11 @@ using HttpClient httpClient = new()
 
 AGUIChatClient chatClient = new(httpClient, serverUrl);
 
-AIAgent agent = chatClient.CreateAIAgent(
+AIAgent agent = chatClient.AsAIAgent(
     name: "agui-client",
     description: "AG-UI Client Agent");
 
-AgentThread thread = agent.GetNewThread();
+AgentThread thread = await agent.GetNewThreadAsync();
 List<ChatMessage> messages =
 [
     new(ChatRole.System, "You are a helpful assistant.")
@@ -51,7 +51,7 @@ try
         bool isFirstUpdate = true;
         string? threadId = null;
 
-        await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread))
+        await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread))
         {
             ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();
 

dotnet/samples/GettingStarted/AGUI/Step02_BackendTools/Server/Program.cs

@@ -79,7 +79,7 @@ ChatClient chatClient = new AzureOpenAIClient(
         new DefaultAzureCredential())
     .GetChatClient(deploymentName);
 
-ChatClientAgent agent = chatClient.AsIChatClient().CreateAIAgent(
+ChatClientAgent agent = chatClient.AsIChatClient().AsAIAgent(
     name: "AGUIAssistant",
     instructions: "You are a helpful assistant with access to restaurant information.",
     tools: tools);

dotnet/samples/GettingStarted/AGUI/Step03_FrontendTools/Client/Program.cs

@@ -28,12 +28,12 @@ using HttpClient httpClient = new()
 
 AGUIChatClient chatClient = new(httpClient, serverUrl);
 
-AIAgent agent = chatClient.CreateAIAgent(
+AIAgent agent = chatClient.AsAIAgent(
     name: "agui-client",
     description: "AG-UI Client Agent",
     tools: frontendTools);
 
-AgentThread thread = agent.GetNewThread();
+AgentThread thread = await agent.GetNewThreadAsync();
 List<ChatMessage> messages =
 [
     new(ChatRole.System, "You are a helpful assistant.")
@@ -64,7 +64,7 @@ try
         bool isFirstUpdate = true;
         string? threadId = null;
 
-        await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread))
+        await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread))
         {
             ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();
 

dotnet/samples/GettingStarted/AGUI/Step03_FrontendTools/Server/Program.cs

@@ -24,7 +24,7 @@ ChatClient chatClient = new AzureOpenAIClient(
         new DefaultAzureCredential())
     .GetChatClient(deploymentName);
 
-AIAgent agent = chatClient.AsIChatClient().CreateAIAgent(
+AIAgent agent = chatClient.AsIChatClient().AsAIAgent(
     name: "AGUIAssistant",
     instructions: "You are a helpful assistant.");
 

dotnet/samples/GettingStarted/AGUI/Step04_HumanInLoop/Client/Program.cs

@@ -16,7 +16,7 @@ using HttpClient httpClient = new()
 AGUIChatClient chatClient = new(httpClient, serverUrl);
 
 // Create agent
-ChatClientAgent baseAgent = chatClient.CreateAIAgent(
+ChatClientAgent baseAgent = chatClient.AsAIAgent(
     name: "AGUIAssistant",
     instructions: "You are a helpful assistant.");
 
@@ -51,8 +51,8 @@ while ((input = Console.ReadLine()) != null && !input.Equals("exit", StringCompa
     {
         approvalResponses.Clear();
 
-        List<AgentRunResponseUpdate> chatResponseUpdates = [];
-        await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread, cancellationToken: default))
+        List<AgentResponseUpdate> chatResponseUpdates = [];
+        await foreach (AgentResponseUpdate 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
             }
         }
 
-        AgentRunResponse response = chatResponseUpdates.ToAgentRunResponse();
+        AgentResponse response = chatResponseUpdates.ToAgentResponse();
         messages.AddRange(response.Messages);
         foreach (AIContent approvalResponse in approvalResponses)
         {

dotnet/samples/GettingStarted/AGUI/Step04_HumanInLoop/Client/ServerFunctionApprovalClientAgent.cs

@@ -22,17 +22,17 @@ internal sealed class ServerFunctionApprovalClientAgent : DelegatingAIAgent
         this._jsonSerializerOptions = jsonSerializerOptions;
     }
 
-    public override Task<AgentRunResponse> RunAsync(
+    protected override Task<AgentResponse> RunCoreAsync(
         IEnumerable<ChatMessage> messages,
         AgentThread? thread = null,
         AgentRunOptions? options = null,
         CancellationToken cancellationToken = default)
     {
-        return this.RunStreamingAsync(messages, thread, options, cancellationToken)
-            .ToAgentRunResponseAsync(cancellationToken);
+        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken)
+            .ToAgentResponseAsync(cancellationToken);
     }
 
-    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
+    protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
         IEnumerable<ChatMessage> messages,
         AgentThread? thread = null,
         AgentRunOptions? options = null,
@@ -166,8 +166,8 @@ internal sealed class ServerFunctionApprovalClientAgent : DelegatingAIAgent
         return result ?? messages;
     }
 
-    private static AgentRunResponseUpdate ProcessIncomingServerApprovalRequests(
-        AgentRunResponseUpdate update,
+    private static AgentResponseUpdate ProcessIncomingServerApprovalRequests(
+        AgentResponseUpdate 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 AgentRunResponseUpdate(new ChatResponseUpdate()
+            return new AgentResponseUpdate(new ChatResponseUpdate()
             {
                 Role = chatUpdate.Role,
                 Contents = updatedContents,

dotnet/samples/GettingStarted/AGUI/Step04_HumanInLoop/Server/Program.cs

@@ -57,7 +57,7 @@ ChatClient openAIChatClient = new AzureOpenAIClient(
         new DefaultAzureCredential())
     .GetChatClient(deploymentName);
 
-ChatClientAgent baseAgent = openAIChatClient.AsIChatClient().CreateAIAgent(
+ChatClientAgent baseAgent = openAIChatClient.AsIChatClient().AsAIAgent(
     name: "AGUIAssistant",
     instructions: "You are a helpful assistant in charge of approving expenses",
     tools: tools);

dotnet/samples/GettingStarted/AGUI/Step04_HumanInLoop/Server/ServerFunctionApprovalServerAgent.cs

@@ -22,17 +22,17 @@ internal sealed class ServerFunctionApprovalAgent : DelegatingAIAgent
         this._jsonSerializerOptions = jsonSerializerOptions;
     }
 
-    public override Task<AgentRunResponse> RunAsync(
+    protected override Task<AgentResponse> RunCoreAsync(
         IEnumerable<ChatMessage> messages,
         AgentThread? thread = null,
         AgentRunOptions? options = null,
         CancellationToken cancellationToken = default)
     {
-        return this.RunStreamingAsync(messages, thread, options, cancellationToken)
-            .ToAgentRunResponseAsync(cancellationToken);
+        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken)
+            .ToAgentResponseAsync(cancellationToken);
     }
 
-    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
+    protected override async IAsyncEnumerable<AgentResponseUpdate> RunCoreStreamingAsync(
         IEnumerable<ChatMessage> messages,
         AgentThread? thread = null,
         AgentRunOptions? options = null,
@@ -172,8 +172,8 @@ internal sealed class ServerFunctionApprovalAgent : DelegatingAIAgent
         return result ?? messages;
     }
 
-    private static AgentRunResponseUpdate ProcessOutgoingApprovalRequests(
-        AgentRunResponseUpdate update,
+    private static AgentResponseUpdate ProcessOutgoingApprovalRequests(
+        AgentResponseUpdate 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 AgentRunResponseUpdate(new ChatResponseUpdate()
+            return new AgentResponseUpdate(new ChatResponseUpdate()
             {
                 Role = chatUpdate.Role,
                 Contents = updatedContents,

dotnet/samples/GettingStarted/AGUI/Step05_StateManagement/Client/Program.cs

@@ -19,7 +19,7 @@ using HttpClient httpClient = new()
 
 AGUIChatClient chatClient = new(httpClient, serverUrl);
 
-AIAgent baseAgent = chatClient.CreateAIAgent(
+AIAgent baseAgent = chatClient.AsAIAgent(
     name: "recipe-client",
     description: "AG-UI Recipe Client Agent");
 
@@ -30,7 +30,7 @@ JsonSerializerOptions jsonOptions = new(JsonSerializerDefaults.Web)
 };
 StatefulAgent<AgentState> agent = new(baseAgent, jsonOptions, new AgentState());
 
-AgentThread thread = agent.GetNewThread();
+AgentThread thread = await agent.GetNewThreadAsync();
 List<ChatMessage> messages =
 [
     new(ChatRole.System, "You are a helpful recipe assistant.")
@@ -70,7 +70,7 @@ try
 
         Console.WriteLine();
 
-        await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread))
+        await foreach (AgentResponseUpdate update in agent.RunStreamingAsync(messages, thread))
         {
             ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();
 

dotnet/samples/GettingStarted/AGUI/Step05_StateManagement/Client/StatefulAgent.cs

@@ -35,18 +35,18 @@ internal sealed class StatefulAgent<TState> : DelegatingAIAgent
     }
 
     /// <inheritdoc />
-    public override Task<AgentRunResponse> RunAsync(
+    protected override Task<AgentResponse> RunCoreAsync(
         IEnumerable<ChatMessage> messages,
         AgentThread? thread = null,
         AgentRunOptions? options = null,
         CancellationToken cancellationToken = default)
     {
-        return this.RunStreamingAsync(messages, thread, options, cancellationToken)
-            .ToAgentRunResponseAsync(cancellationToken);
+        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken)
+            .ToAgentResponseAsync(cancellationToken);
     }
 
     /// <inheritdoc />
-    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
+    protected override async IAsyncEnumerable<AgentResponseUpdate> 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 (AgentRunResponseUpdate update in this.InnerAgent.RunStreamingAsync(messagesWithState, thread, options, cancellationToken))
+        await foreach (AgentResponseUpdate update in this.InnerAgent.RunStreamingAsync(messagesWithState, thread, options, cancellationToken))
         {
             // Check if this update contains a state snapshot
             foreach (AIContent content in update.Contents)

dotnet/samples/GettingStarted/AGUI/Step05_StateManagement/Server/Program.cs

@@ -34,7 +34,7 @@ ChatClient chatClient = new AzureOpenAIClient(
         new DefaultAzureCredential())
     .GetChatClient(deploymentName);
 
-AIAgent baseAgent = chatClient.AsIChatClient().CreateAIAgent(
+AIAgent baseAgent = chatClient.AsIChatClient().AsAIAgent(
     name: "RecipeAgent",
     instructions: """
         You are a helpful recipe assistant. When users ask you to create or suggest a recipe,

dotnet/samples/GettingStarted/AGUI/Step05_StateManagement/Server/SharedStateAgent.cs

@@ -17,17 +17,17 @@ internal sealed class SharedStateAgent : DelegatingAIAgent
         this._jsonSerializerOptions = jsonSerializerOptions;
     }
 
-    public override Task<AgentRunResponse> RunAsync(
+    protected override Task<AgentResponse> RunCoreAsync(
         IEnumerable<ChatMessage> messages,
         AgentThread? thread = null,
         AgentRunOptions? options = null,
         CancellationToken cancellationToken = default)
     {
-        return this.RunStreamingAsync(messages, thread, options, cancellationToken)
-            .ToAgentRunResponseAsync(cancellationToken);
+        return this.RunCoreStreamingAsync(messages, thread, options, cancellationToken)
+            .ToAgentResponseAsync(cancellationToken);
     }
 
-    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
+    protected override async IAsyncEnumerable<AgentResponseUpdate> 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<AgentRunResponseUpdate>();
+        var allUpdates = new List<AgentResponseUpdate>();
         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.ToAgentRunResponse();
+        var response = allUpdates.ToAgentResponse();
 
         // 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 AgentRunResponseUpdate
+            yield return new AgentResponseUpdate
             {
                 Contents = [new DataContent(stateBytes, "application/json")]
             };

dotnet/samples/GettingStarted/AgentOpenTelemetry/Program.cs

@@ -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 = agent.GetNewThread();
+var thread = await agent.GetNewThreadAsync();
 
 appLogger.LogInformation("Agent created successfully with ID: {AgentId}", agent.Id);
 

dotnet/samples/GettingStarted/AgentProviders/Agent_With_A2A/Program.cs

@@ -14,5 +14,5 @@ A2ACardResolver agentCardResolver = new(new Uri(a2aAgentHost));
 AIAgent agent = await agentCardResolver.GetAIAgentAsync();
 
 // Invoke the agent and output the text result.
-AgentRunResponse response = await agent.RunAsync("Tell me a joke about a pirate.");
+AgentResponse response = await agent.RunAsync("Tell me a joke about a pirate.");
 Console.WriteLine(response);

dotnet/samples/GettingStarted/AgentProviders/Agent_With_A2A/README.md

@@ -26,9 +26,9 @@ using Microsoft.Agents.AI.A2A;
 A2AClient a2aClient = new(new Uri("https://your-a2a-agent-host/echo"));
 
 // Create an AIAgent from the A2AClient
-AIAgent agent = a2aClient.GetAIAgent();
+AIAgent agent = a2aClient.AsAIAgent();
 
 // Run the agent
-AgentRunResponse response = await agent.RunAsync("Tell me a joke about a pirate.");
+AgentResponse response = await agent.RunAsync("Tell me a joke about a pirate.");
 Console.WriteLine(response);
 ```

dotnet/samples/GettingStarted/AgentProviders/Agent_With_Anthropic/Program.cs

@@ -26,7 +26,7 @@ AnthropicClient? client = (resource is null)
         ? new AnthropicFoundryClient(new AnthropicFoundryApiKeyCredentials(apiKey, resource)) // If an apiKey is provided, use Foundry with ApiKey authentication
         : new AnthropicFoundryClient(new AnthropicAzureTokenCredential(new AzureCliCredential(), resource)); // Otherwise, use Foundry with Azure Client authentication
 
-AIAgent agent = client.CreateAIAgent(model: deploymentName, instructions: JokerInstructions, name: JokerName);
+AIAgent agent = client.AsAIAgent(model: deploymentName, instructions: JokerInstructions, name: JokerName);
 
 // Invoke the agent and output the text result.
 Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgentsPersistent/Program.cs

@@ -31,7 +31,7 @@ AIAgent agent2 = await persistentAgentsClient.CreateAIAgentAsync(
     instructions: JokerInstructions);
 
 // You can then invoke the agent like any other AIAgent.
-AgentThread thread = agent1.GetNewThread();
+AgentThread thread = await agent1.GetNewThreadAsync();
 Console.WriteLine(await agent1.RunAsync("Tell me a joke about a pirate.", thread));
 
 // Cleanup for sample purposes.

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIProject/Program.cs

@@ -27,7 +27,7 @@ var createdAgentVersion = aiProjectClient.Agents.CreateAgentVersion(agentName: J
 //      agentVersion.Name = <agentName>
 
 // You can retrieve an AIAgent for an already created server side agent version.
-AIAgent existingJokerAgent = aiProjectClient.GetAIAgent(createdAgentVersion);
+AIAgent existingJokerAgent = aiProjectClient.AsAIAgent(createdAgentVersion);
 
 // You can also create another AIAgent version by providing the same name with a different definition.
 AIAgent newJokerAgent = aiProjectClient.CreateAIAgent(name: JokerName, model: deploymentName, instructions: "You are extremely hilarious at telling jokes.");
@@ -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 = jokerAgentLatest.GetNewThread();
+AgentThread thread = await jokerAgentLatest.GetNewThreadAsync();
 Console.WriteLine(await jokerAgentLatest.RunAsync("Tell me a joke about a pirate.", thread));
 
 // This will use the same thread to continue the conversation.

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureFoundryModel/Program.cs

@@ -25,7 +25,7 @@ OpenAIClient client = string.IsNullOrWhiteSpace(apiKey)
 
 AIAgent agent = client
     .GetChatClient(model)
-    .CreateAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
+    .AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
 
 // Invoke the agent and output the text result.
 Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureOpenAIChatCompletion/Program.cs

@@ -14,7 +14,7 @@ AIAgent agent = new AzureOpenAIClient(
     new Uri(endpoint),
     new AzureCliCredential())
      .GetChatClient(deploymentName)
-     .CreateAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
+     .AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
 
 // Invoke the agent and output the text result.
 Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureOpenAIResponses/Program.cs

@@ -14,7 +14,7 @@ AIAgent agent = new AzureOpenAIClient(
     new Uri(endpoint),
     new AzureCliCredential())
      .GetResponsesClient(deploymentName)
-     .CreateAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
+     .AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
 
 // Invoke the agent and output the text result.
 Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));

dotnet/samples/GettingStarted/AgentProviders/Agent_With_CustomImplementation/Program.cs

@@ -28,29 +28,37 @@ namespace SampleApp
     {
         public override string? Name => "UpperCaseParrotAgent";
 
-        public override AgentThread GetNewThread()
-            => new CustomAgentThread();
+        public override ValueTask<AgentThread> GetNewThreadAsync(CancellationToken cancellationToken = default)
+            => new(new CustomAgentThread());
 
-        public override AgentThread DeserializeThread(JsonElement serializedThread, JsonSerializerOptions? jsonSerializerOptions = null)
-            => new CustomAgentThread(serializedThread, jsonSerializerOptions);
+        public override ValueTask<AgentThread> DeserializeThreadAsync(JsonElement serializedThread, JsonSerializerOptions? jsonSerializerOptions = null, CancellationToken cancellationToken = default)
+            => new(new CustomAgentThread(serializedThread, jsonSerializerOptions));
 
-        public override async Task<AgentRunResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
+        protected override async Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
         {
             // Create a thread if the user didn't supply one.
-            thread ??= this.GetNewThread();
+            thread ??= await this.GetNewThreadAsync(cancellationToken);
 
             if (thread is not CustomAgentThread typedThread)
             {
                 throw new ArgumentException($"The provided thread is not of type {nameof(CustomAgentThread)}.", nameof(thread));
             }
 
+            // Get existing messages from the store
+            var invokingContext = new ChatMessageStore.InvokingContext(messages);
+            var storeMessages = await typedThread.MessageStore.InvokingAsync(invokingContext, cancellationToken);
+
             // Clone the input messages and turn them into response messages with upper case text.
-            List<ChatMessage> responseMessages = CloneAndToUpperCase(messages, this.DisplayName).ToList();
+            List<ChatMessage> responseMessages = CloneAndToUpperCase(messages, this.Name).ToList();
 
             // Notify the thread of the input and output messages.
-            await typedThread.MessageStore.AddMessagesAsync(messages.Concat(responseMessages), cancellationToken);
+            var invokedContext = new ChatMessageStore.InvokedContext(messages, storeMessages)
+            {
+                ResponseMessages = responseMessages
+            };
+            await typedThread.MessageStore.InvokedAsync(invokedContext, cancellationToken);
 
-            return new AgentRunResponse
+            return new AgentResponse
             {
                 AgentId = this.Id,
                 ResponseId = Guid.NewGuid().ToString("N"),
@@ -58,28 +66,36 @@ namespace SampleApp
             };
         }
 
-        public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default)
+        protected override async IAsyncEnumerable<AgentResponseUpdate> 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 ??= this.GetNewThread();
+            thread ??= await this.GetNewThreadAsync(cancellationToken);
 
             if (thread is not CustomAgentThread typedThread)
             {
                 throw new ArgumentException($"The provided thread is not of type {nameof(CustomAgentThread)}.", nameof(thread));
             }
 
+            // Get existing messages from the store
+            var invokingContext = new ChatMessageStore.InvokingContext(messages);
+            var storeMessages = await typedThread.MessageStore.InvokingAsync(invokingContext, cancellationToken);
+
             // Clone the input messages and turn them into response messages with upper case text.
-            List<ChatMessage> responseMessages = CloneAndToUpperCase(messages, this.DisplayName).ToList();
+            List<ChatMessage> responseMessages = CloneAndToUpperCase(messages, this.Name).ToList();
 
             // Notify the thread of the input and output messages.
-            await typedThread.MessageStore.AddMessagesAsync(messages.Concat(responseMessages), cancellationToken);
+            var invokedContext = new ChatMessageStore.InvokedContext(messages, storeMessages)
+            {
+                ResponseMessages = responseMessages
+            };
+            await typedThread.MessageStore.InvokedAsync(invokedContext, cancellationToken);
 
             foreach (var message in responseMessages)
             {
-                yield return new AgentRunResponseUpdate
+                yield return new AgentResponseUpdate
                 {
                     AgentId = this.Id,
-                    AuthorName = this.DisplayName,
+                    AuthorName = message.AuthorName,
                     Role = ChatRole.Assistant,
                     Contents = message.Contents,
                     ResponseId = Guid.NewGuid().ToString("N"),
@@ -88,7 +104,7 @@ namespace SampleApp
             }
         }
 
-        private static IEnumerable<ChatMessage> CloneAndToUpperCase(IEnumerable<ChatMessage> messages, string agentName) => messages.Select(x =>
+        private static IEnumerable<ChatMessage> CloneAndToUpperCase(IEnumerable<ChatMessage> messages, string? agentName) => messages.Select(x =>
             {
                 // Clone the message and update its author to be the agent.
                 var messageClone = x.Clone();

dotnet/samples/GettingStarted/AgentProviders/Agent_With_GoogleGemini/GeminiChatClient.cs

@@ -1,558 +0,0 @@
-// Copyright (c) Microsoft. All rights reserved.
-
-using System.Runtime.CompilerServices;
-using Google.Apis.Util;
-using Google.GenAI;
-using Google.GenAI.Types;
-
-namespace Microsoft.Extensions.AI;
-
-/// <summary>Provides an <see cref="IChatClient"/> implementation based on <see cref="Client"/>.</summary>
-internal sealed class GoogleGenAIChatClient : IChatClient
-{
-    /// <summary>The wrapped <see cref="Client"/> instance (optional).</summary>
-    private readonly Client? _client;
-
-    /// <summary>The wrapped <see cref="Models"/> instance.</summary>
-    private readonly Models _models;
-
-    /// <summary>The default model that should be used when no override is specified.</summary>
-    private readonly string? _defaultModelId;
-
-    /// <summary>Lazily-initialized metadata describing the implementation.</summary>
-    private ChatClientMetadata? _metadata;
-
-    /// <summary>Initializes a new <see cref="GoogleGenAIChatClient"/> instance.</summary>
-    public GoogleGenAIChatClient(Client client, string? defaultModelId)
-    {
-        this._client = client;
-        this._models = client.Models;
-        this._defaultModelId = defaultModelId;
-    }
-
-    /// <summary>Initializes a new <see cref="GoogleGenAIChatClient"/> instance.</summary>
-    public GoogleGenAIChatClient(Models client, string? defaultModelId)
-    {
-        this._models = client;
-        this._defaultModelId = defaultModelId;
-    }
-
-    /// <inheritdoc />
-    public async Task<ChatResponse> GetResponseAsync(IEnumerable<ChatMessage> messages, ChatOptions? options = null, CancellationToken cancellationToken = default)
-    {
-        Utilities.ThrowIfNull(messages, nameof(messages));
-
-        // Create the request.
-        (string? modelId, List<Content> contents, GenerateContentConfig config) = this.CreateRequest(messages, options);
-
-        // Send it.
-        GenerateContentResponse generateResult = await this._models.GenerateContentAsync(modelId!, contents, config).ConfigureAwait(false);
-
-        // Create the response.
-        ChatResponse chatResponse = new(new ChatMessage(ChatRole.Assistant, []))
-        {
-            CreatedAt = generateResult.CreateTime is { } dt ? new DateTimeOffset(dt) : null,
-            ModelId = !string.IsNullOrWhiteSpace(generateResult.ModelVersion) ? generateResult.ModelVersion : modelId,
-            RawRepresentation = generateResult,
-            ResponseId = generateResult.ResponseId,
-        };
-
-        // Populate the response messages.
-        chatResponse.FinishReason = PopulateResponseContents(generateResult, chatResponse.Messages[0].Contents);
-
-        // Populate usage information if there is any.
-        if (generateResult.UsageMetadata is { } usageMetadata)
-        {
-            chatResponse.Usage = ExtractUsageDetails(usageMetadata);
-        }
-
-        // Return the response.
-        return chatResponse;
-    }
-
-    /// <inheritdoc />
-    public async IAsyncEnumerable<ChatResponseUpdate> GetStreamingResponseAsync(IEnumerable<ChatMessage> messages, ChatOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default)
-    {
-        Utilities.ThrowIfNull(messages, nameof(messages));
-
-        // Create the request.
-        (string? modelId, List<Content> contents, GenerateContentConfig config) = this.CreateRequest(messages, options);
-
-        // Send it, and process the results.
-        await foreach (GenerateContentResponse generateResult in this._models.GenerateContentStreamAsync(modelId!, contents, config).WithCancellation(cancellationToken).ConfigureAwait(false))
-        {
-            // Create a response update for each result in the stream.
-            ChatResponseUpdate responseUpdate = new(ChatRole.Assistant, [])
-            {
-                CreatedAt = generateResult.CreateTime is { } dt ? new DateTimeOffset(dt) : null,
-                ModelId = !string.IsNullOrWhiteSpace(generateResult.ModelVersion) ? generateResult.ModelVersion : modelId,
-                RawRepresentation = generateResult,
-                ResponseId = generateResult.ResponseId,
-            };
-
-            // Populate the response update contents.
-            responseUpdate.FinishReason = PopulateResponseContents(generateResult, responseUpdate.Contents);
-
-            // Populate usage information if there is any.
-            if (generateResult.UsageMetadata is { } usageMetadata)
-            {
-                responseUpdate.Contents.Add(new UsageContent(ExtractUsageDetails(usageMetadata)));
-            }
-
-            // Yield the update.
-            yield return responseUpdate;
-        }
-    }
-
-    /// <inheritdoc />
-    public object? GetService(System.Type serviceType, object? serviceKey = null)
-    {
-        Utilities.ThrowIfNull(serviceType, nameof(serviceType));
-
-        if (serviceKey is null)
-        {
-            // If there's a request for metadata, lazily-initialize it and return it. We don't need to worry about race conditions,
-            // as there's no requirement that the same instance be returned each time, and creation is idempotent.
-            if (serviceType == typeof(ChatClientMetadata))
-            {
-                return this._metadata ??= new("gcp.gen_ai", new("https://generativelanguage.googleapis.com/"), defaultModelId: this._defaultModelId);
-            }
-
-            // Allow a consumer to "break glass" and access the underlying client if they need it.
-            if (serviceType.IsInstanceOfType(this._models))
-            {
-                return this._models;
-            }
-
-            if (this._client is not null && serviceType.IsInstanceOfType(this._client))
-            {
-                return this._client;
-            }
-
-            if (serviceType.IsInstanceOfType(this))
-            {
-                return this;
-            }
-        }
-
-        return null;
-    }
-
-    /// <inheritdoc />
-    void IDisposable.Dispose() { /* nop */ }
-
-    /// <summary>Creates the message parameters for <see cref="Models.GenerateContentAsync(string, List{Content}, GenerateContentConfig?)"/> from <paramref name="messages"/> and <paramref name="options"/>.</summary>
-    private (string? ModelId, List<Content> Contents, GenerateContentConfig Config) CreateRequest(IEnumerable<ChatMessage> messages, ChatOptions? options)
-    {
-        // Create the GenerateContentConfig object. If the options contains a RawRepresentationFactory, try to use it to
-        // create the request instance, allowing the caller to populate it with GenAI-specific options. Otherwise, create
-        // a new instance directly.
-        string? model = this._defaultModelId;
-        List<Content> contents = [];
-        GenerateContentConfig config = options?.RawRepresentationFactory?.Invoke(this) as GenerateContentConfig ?? new();
-
-        if (options is not null)
-        {
-            if (options.FrequencyPenalty is { } frequencyPenalty)
-            {
-                config.FrequencyPenalty ??= frequencyPenalty;
-            }
-
-            if (options.Instructions is { } instructions)
-            {
-                ((config.SystemInstruction ??= new()).Parts ??= []).Add(new() { Text = instructions });
-            }
-
-            if (options.MaxOutputTokens is { } maxOutputTokens)
-            {
-                config.MaxOutputTokens ??= maxOutputTokens;
-            }
-
-            if (!string.IsNullOrWhiteSpace(options.ModelId))
-            {
-                model = options.ModelId;
-            }
-
-            if (options.PresencePenalty is { } presencePenalty)
-            {
-                config.PresencePenalty ??= presencePenalty;
-            }
-
-            if (options.Seed is { } seed)
-            {
-                config.Seed ??= (int)seed;
-            }
-
-            if (options.StopSequences is { } stopSequences)
-            {
-                (config.StopSequences ??= []).AddRange(stopSequences);
-            }
-
-            if (options.Temperature is { } temperature)
-            {
-                config.Temperature ??= temperature;
-            }
-
-            if (options.TopP is { } topP)
-            {
-                config.TopP ??= topP;
-            }
-
-            if (options.TopK is { } topK)
-            {
-                config.TopK ??= topK;
-            }
-
-            // Populate tools. Each kind of tool is added on its own, except for function declarations,
-            // which are grouped into a single FunctionDeclaration.
-            List<FunctionDeclaration>? functionDeclarations = null;
-            if (options.Tools is { } tools)
-            {
-                foreach (var tool in tools)
-                {
-                    switch (tool)
-                    {
-                        case AIFunctionDeclaration af:
-                            functionDeclarations ??= [];
-                            functionDeclarations.Add(new()
-                            {
-                                Name = af.Name,
-                                Description = af.Description ?? "",
-                                ParametersJsonSchema = af.JsonSchema,
-                            });
-                            break;
-
-                        case HostedCodeInterpreterTool:
-                            (config.Tools ??= []).Add(new() { CodeExecution = new() });
-                            break;
-
-                        case HostedFileSearchTool:
-                            (config.Tools ??= []).Add(new() { Retrieval = new() });
-                            break;
-
-                        case HostedWebSearchTool:
-                            (config.Tools ??= []).Add(new() { GoogleSearch = new() });
-                            break;
-                    }
-                }
-            }
-
-            if (functionDeclarations is { Count: > 0 })
-            {
-                Tool functionTools = new();
-                (functionTools.FunctionDeclarations ??= []).AddRange(functionDeclarations);
-                (config.Tools ??= []).Add(functionTools);
-            }
-
-            // Transfer over the tool mode if there are any tools.
-            if (options.ToolMode is { } toolMode && config.Tools?.Count > 0)
-            {
-                switch (toolMode)
-                {
-                    case NoneChatToolMode:
-                        config.ToolConfig = new() { FunctionCallingConfig = new() { Mode = FunctionCallingConfigMode.NONE } };
-                        break;
-
-                    case AutoChatToolMode:
-                        config.ToolConfig = new() { FunctionCallingConfig = new() { Mode = FunctionCallingConfigMode.AUTO } };
-                        break;
-
-                    case RequiredChatToolMode required:
-                        config.ToolConfig = new() { FunctionCallingConfig = new() { Mode = FunctionCallingConfigMode.ANY } };
-                        if (required.RequiredFunctionName is not null)
-                        {
-                            ((config.ToolConfig.FunctionCallingConfig ??= new()).AllowedFunctionNames ??= []).Add(required.RequiredFunctionName);
-                        }
-                        break;
-                }
-            }
-
-            // Set the response format if specified.
-            if (options.ResponseFormat is ChatResponseFormatJson responseFormat)
-            {
-                config.ResponseMimeType = "application/json";
-                if (responseFormat.Schema is { } schema)
-                {
-                    config.ResponseJsonSchema = schema;
-                }
-            }
-        }
-
-        // Transfer messages to request, handling system messages specially
-        Dictionary<string, string>? callIdToFunctionNames = null;
-        foreach (var message in messages)
-        {
-            if (message.Role == ChatRole.System)
-            {
-                string instruction = message.Text;
-                if (!string.IsNullOrWhiteSpace(instruction))
-                {
-                    ((config.SystemInstruction ??= new()).Parts ??= []).Add(new() { Text = instruction });
-                }
-
-                continue;
-            }
-
-            Content content = new() { Role = message.Role == ChatRole.Assistant ? "model" : "user" };
-            content.Parts ??= [];
-            AddPartsForAIContents(ref callIdToFunctionNames, message.Contents, content.Parts);
-
-            contents.Add(content);
-        }
-
-        // Make sure the request contains at least one content part (the request would always fail if empty).
-        if (!contents.SelectMany(c => c.Parts ?? Enumerable.Empty<Part>()).Any())
-        {
-            contents.Add(new() { Role = "user", Parts = new() { { new() { Text = "" } } } });
-        }
-
-        return (model, contents, config);
-    }
-
-    /// <summary>Creates <see cref="Part"/>s for <paramref name="contents"/> and adds them to <paramref name="parts"/>.</summary>
-    private static void AddPartsForAIContents(ref Dictionary<string, string>? callIdToFunctionNames, IList<AIContent> contents, List<Part> parts)
-    {
-        for (int i = 0; i < contents.Count; i++)
-        {
-            var content = contents[i];
-
-            byte[]? thoughtSignature = null;
-            if (content is not TextReasoningContent { ProtectedData: not null } &&
-                i + 1 < contents.Count &&
-                contents[i + 1] is TextReasoningContent nextReasoning &&
-                string.IsNullOrWhiteSpace(nextReasoning.Text) &&
-                nextReasoning.ProtectedData is { } protectedData)
-            {
-                i++;
-                thoughtSignature = Convert.FromBase64String(protectedData);
-            }
-
-            Part? part = null;
-            switch (content)
-            {
-                case TextContent textContent:
-                    part = new() { Text = textContent.Text };
-                    break;
-
-                case TextReasoningContent reasoningContent:
-                    part = new()
-                    {
-                        Thought = true,
-                        Text = !string.IsNullOrWhiteSpace(reasoningContent.Text) ? reasoningContent.Text : null,
-                        ThoughtSignature = reasoningContent.ProtectedData is not null ? Convert.FromBase64String(reasoningContent.ProtectedData) : null,
-                    };
-                    break;
-
-                case DataContent dataContent:
-                    part = new()
-                    {
-                        InlineData = new()
-                        {
-                            MimeType = dataContent.MediaType,
-                            Data = dataContent.Data.ToArray(),
-                            DisplayName = dataContent.Name,
-                        }
-                    };
-                    break;
-
-                case UriContent uriContent:
-                    part = new()
-                    {
-                        FileData = new()
-                        {
-                            FileUri = uriContent.Uri.AbsoluteUri,
-                            MimeType = uriContent.MediaType,
-                        }
-                    };
-                    break;
-
-                case FunctionCallContent functionCallContent:
-                    (callIdToFunctionNames ??= [])[functionCallContent.CallId] = functionCallContent.Name;
-                    callIdToFunctionNames[""] = functionCallContent.Name; // track last function name in case calls don't have IDs
-
-                    part = new()
-                    {
-                        FunctionCall = new()
-                        {
-                            Id = functionCallContent.CallId,
-                            Name = functionCallContent.Name,
-                            Args = functionCallContent.Arguments is null ? null : functionCallContent.Arguments as Dictionary<string, object> ?? new(functionCallContent.Arguments!),
-                        }
-                    };
-                    break;
-
-                case FunctionResultContent functionResultContent:
-                    part = new()
-                    {
-                        FunctionResponse = new()
-                        {
-                            Id = functionResultContent.CallId,
-                            Name = callIdToFunctionNames?.TryGetValue(functionResultContent.CallId, out string? functionName) is true || callIdToFunctionNames?.TryGetValue("", out functionName) is true ?
-                            functionName :
-                            null,
-                            Response = functionResultContent.Result is null ? null : new() { ["result"] = functionResultContent.Result },
-                        }
-                    };
-                    break;
-            }
-
-            if (part is not null)
-            {
-                part.ThoughtSignature ??= thoughtSignature;
-                parts.Add(part);
-            }
-        }
-    }
-
-    /// <summary>Creates <see cref="AIContent"/>s for <paramref name="parts"/> and adds them to <paramref name="contents"/>.</summary>
-    private static void AddAIContentsForParts(List<Part> parts, IList<AIContent> contents)
-    {
-        foreach (var part in parts)
-        {
-            AIContent? content = null;
-
-            if (!string.IsNullOrEmpty(part.Text))
-            {
-                content = part.Thought is true ?
-                  new TextReasoningContent(part.Text) :
-                  new TextContent(part.Text);
-            }
-            else if (part.InlineData is { } inlineData)
-            {
-                content = new DataContent(inlineData.Data, inlineData.MimeType ?? "application/octet-stream")
-                {
-                    Name = inlineData.DisplayName,
-                };
-            }
-            else if (part.FileData is { FileUri: not null } fileData)
-            {
-                content = new UriContent(new Uri(fileData.FileUri), fileData.MimeType ?? "application/octet-stream");
-            }
-            else if (part.FunctionCall is { Name: not null } functionCall)
-            {
-                content = new FunctionCallContent(functionCall.Id ?? "", functionCall.Name, functionCall.Args!);
-            }
-            else if (part.FunctionResponse is { } functionResponse)
-            {
-                content = new FunctionResultContent(
-                  functionResponse.Id ?? "",
-                  functionResponse.Response?.TryGetValue("output", out var output) is true ? output :
-                  functionResponse.Response?.TryGetValue("error", out var error) is true ? error :
-                  null);
-            }
-
-            if (content is not null)
-            {
-                content.RawRepresentation = part;
-                contents.Add(content);
-
-                if (part.ThoughtSignature is { } thoughtSignature)
-                {
-                    contents.Add(new TextReasoningContent(null)
-                    {
-                        ProtectedData = Convert.ToBase64String(thoughtSignature),
-                    });
-                }
-            }
-        }
-    }
-
-    private static ChatFinishReason? PopulateResponseContents(GenerateContentResponse generateResult, IList<AIContent> responseContents)
-    {
-        ChatFinishReason? finishReason = null;
-
-        // Populate the response messages. There should only be at most one candidate, but if there are more, ignore all but the first.
-        if (generateResult.Candidates is { Count: > 0 } &&
-            generateResult.Candidates[0] is { Content: { } candidateContent } candidate)
-        {
-            // Grab the finish reason if one exists.
-            finishReason = ConvertFinishReason(candidate.FinishReason);
-
-            // Add all of the response content parts as AIContents.
-            if (candidateContent.Parts is { } parts)
-            {
-                AddAIContentsForParts(parts, responseContents);
-            }
-
-            // Add any citation metadata.
-            if (candidate.CitationMetadata is { Citations: { Count: > 0 } citations } &&
-                responseContents.OfType<TextContent>().FirstOrDefault() is TextContent textContent)
-            {
-                foreach (var citation in citations)
-                {
-                    textContent.Annotations =
-                    [
-                        new CitationAnnotation()
-                        {
-                            Title = citation.Title,
-                            Url = Uri.TryCreate(citation.Uri, UriKind.Absolute, out Uri? uri) ? uri : null,
-                            AnnotatedRegions =
-                            [
-                                new TextSpanAnnotatedRegion()
-                                {
-                                    StartIndex = citation.StartIndex,
-                                    EndIndex = citation.EndIndex,
-                                }
-                            ],
-                        }
-                    ];
-                }
-            }
-        }
-
-        // Populate error information if there is any.
-        if (generateResult.PromptFeedback is { } promptFeedback)
-        {
-            responseContents.Add(new ErrorContent(promptFeedback.BlockReasonMessage));
-        }
-
-        return finishReason;
-    }
-
-    /// <summary>Creates an M.E.AI <see cref="ChatFinishReason"/> from a Google <see cref="FinishReason"/>.</summary>
-    private static ChatFinishReason? ConvertFinishReason(FinishReason? finishReason)
-    {
-        return finishReason switch
-        {
-            null => null,
-
-            FinishReason.MAX_TOKENS =>
-              ChatFinishReason.Length,
-
-            FinishReason.MALFORMED_FUNCTION_CALL or
-            FinishReason.UNEXPECTED_TOOL_CALL =>
-              ChatFinishReason.ToolCalls,
-
-            FinishReason.FINISH_REASON_UNSPECIFIED or
-            FinishReason.STOP =>
-              ChatFinishReason.Stop,
-
-            _ => ChatFinishReason.ContentFilter,
-        };
-    }
-
-    /// <summary>Creates a <see cref="UsageDetails"/> populated from the supplied <paramref name="usageMetadata"/>.</summary>
-    private static UsageDetails ExtractUsageDetails(GenerateContentResponseUsageMetadata usageMetadata)
-    {
-        UsageDetails details = new()
-        {
-            InputTokenCount = usageMetadata.PromptTokenCount,
-            OutputTokenCount = usageMetadata.CandidatesTokenCount,
-            TotalTokenCount = usageMetadata.TotalTokenCount,
-        };
-
-        AddIfPresent(nameof(usageMetadata.CachedContentTokenCount), usageMetadata.CachedContentTokenCount);
-        AddIfPresent(nameof(usageMetadata.ThoughtsTokenCount), usageMetadata.ThoughtsTokenCount);
-        AddIfPresent(nameof(usageMetadata.ToolUsePromptTokenCount), usageMetadata.ToolUsePromptTokenCount);
-
-        return details;
-
-        void AddIfPresent(string key, int? value)
-        {
-            if (value is int i)
-            {
-                (details.AdditionalCounts ??= [])[key] = i;
-            }
-        }
-    }
-}

dotnet/samples/GettingStarted/AgentProviders/Agent_With_GoogleGemini/GoogleGenAIExtensions.cs

@@ -1,36 +0,0 @@
-// Copyright (c) Microsoft. All rights reserved.
-
-using Google.Apis.Util;
-using Google.GenAI;
-
-namespace Microsoft.Extensions.AI;
-
-/// <summary>Provides implementations of Microsoft.Extensions.AI abstractions based on <see cref="Client"/>.</summary>
-public static class GoogleGenAIExtensions
-{
-    /// <summary>
-    /// Creates an <see cref="IChatClient"/> wrapper around the specified <see cref="Client"/>.
-    /// </summary>
-    /// <param name="client">The <see cref="Client"/> to wrap.</param>
-    /// <param name="defaultModelId">The default model ID to use for chat requests if not specified in <see cref="ChatOptions.ModelId"/>.</param>
-    /// <returns>An <see cref="IChatClient"/> that wraps the specified client.</returns>
-    /// <exception cref="ArgumentNullException"><paramref name="client"/> is <see langword="null"/>.</exception>
-    public static IChatClient AsIChatClient(this Client client, string? defaultModelId = null)
-    {
-        Utilities.ThrowIfNull(client, nameof(client));
-        return new GoogleGenAIChatClient(client, defaultModelId);
-    }
-
-    /// <summary>
-    /// Creates an <see cref="IChatClient"/> wrapper around the specified <see cref="Models"/>.
-    /// </summary>
-    /// <param name="models">The <see cref="Models"/> client to wrap.</param>
-    /// <param name="defaultModelId">The default model ID to use for chat requests if not specified in <see cref="ChatOptions.ModelId"/>.</param>
-    /// <returns>An <see cref="IChatClient"/> that wraps the specified <see cref="Models"/> client.</returns>
-    /// <exception cref="ArgumentNullException"><paramref name="models"/> is <see langword="null"/>.</exception>
-    public static IChatClient AsIChatClient(this Models models, string? defaultModelId = null)
-    {
-        Utilities.ThrowIfNull(models, nameof(models));
-        return new GoogleGenAIChatClient(models, defaultModelId);
-    }
-}

dotnet/samples/GettingStarted/AgentProviders/Agent_With_GoogleGemini/Program.cs

@@ -14,15 +14,13 @@ string apiKey = Environment.GetEnvironmentVariable("GOOGLE_GENAI_API_KEY") ?? th
 string model = Environment.GetEnvironmentVariable("GOOGLE_GENAI_MODEL") ?? "gemini-2.5-flash";
 
 // Using a Google GenAI IChatClient implementation
-// Until the PR https://github.com/googleapis/dotnet-genai/pull/81 is not merged this option
-// requires usage of also both GeminiChatClient.cs and GoogleGenAIExtensions.cs polyfills to work.
 
 ChatClientAgent agentGenAI = new(
     new Client(vertexAI: false, apiKey: apiKey).AsIChatClient(model),
     name: JokerName,
     instructions: JokerInstructions);
 
-AgentRunResponse response = await agentGenAI.RunAsync("Tell me a joke about a pirate.");
+AgentResponse 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

dotnet/samples/GettingStarted/AgentProviders/Agent_With_GoogleGemini/README.md

@@ -25,12 +25,7 @@ $env:GOOGLE_GENAI_MODEL="gemini-2.5-fast"  # Optional, defaults to gemini-2.5-fa
 
 ### Google GenAI (Official)
 
-The official Google GenAI package provides direct access to Google's Generative AI models. This sample uses an extension method to convert the Google client to an `IChatClient`.
-
-> [!NOTE]
-> Until PR [googleapis/dotnet-genai#81](https://github.com/googleapis/dotnet-genai/pull/81) is merged, this option requires the additional `GeminiChatClient.cs` and `GoogleGenAIExtensions.cs` files included in this sample.
->
-> We appreciate any community push by liking and commenting in the above PR to get it merged and release as part of official Google GenAI package.
+The official Google GenAI package provides direct access to Google's Generative AI models. This sample uses the `AsIChatClient()` extension method to convert the Google client to an `IChatClient`.
 
 ### Mscc.GenerativeAI.Microsoft (Community)
 

dotnet/samples/GettingStarted/AgentProviders/Agent_With_ONNX/Program.cs

@@ -12,7 +12,7 @@ var modelPath = Environment.GetEnvironmentVariable("ONNX_MODEL_PATH") ?? throw n
 
 // Get a chat client for ONNX and use it to construct an AIAgent.
 using OnnxRuntimeGenAIChatClient chatClient = new(modelPath);
-AIAgent agent = chatClient.CreateAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
+AIAgent agent = chatClient.AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
 
 // Invoke the agent and output the text result.
 Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));

dotnet/samples/GettingStarted/AgentProviders/Agent_With_Ollama/Program.cs

@@ -11,7 +11,7 @@ var modelName = Environment.GetEnvironmentVariable("OLLAMA_MODEL_NAME") ?? throw
 
 // Get a chat client for Ollama and use it to construct an AIAgent.
 AIAgent agent = new OllamaApiClient(new Uri(endpoint), modelName)
-    .CreateAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
+    .AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
 
 // Invoke the agent and output the text result.
 Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));

dotnet/samples/GettingStarted/AgentProviders/Agent_With_OpenAIAssistants/Program.cs

@@ -33,7 +33,7 @@ AIAgent agent2 = await assistantClient.CreateAIAgentAsync(
     instructions: JokerInstructions);
 
 // You can invoke the agent like any other AIAgent.
-AgentThread thread = agent1.GetNewThread();
+AgentThread thread = await agent1.GetNewThreadAsync();
 Console.WriteLine(await agent1.RunAsync("Tell me a joke about a pirate.", thread));
 
 // Cleanup for sample purposes.

dotnet/samples/GettingStarted/AgentProviders/Agent_With_OpenAIChatCompletion/Program.cs

@@ -13,7 +13,7 @@ var model = Environment.GetEnvironmentVariable("OPENAI_MODEL") ?? "gpt-4o-mini";
 AIAgent agent = new OpenAIClient(
     apiKey)
      .GetChatClient(model)
-     .CreateAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
+     .AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
 
 // Invoke the agent and output the text result.
 Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));

dotnet/samples/GettingStarted/AgentProviders/Agent_With_OpenAIResponses/Program.cs

@@ -12,7 +12,7 @@ var model = Environment.GetEnvironmentVariable("OPENAI_MODEL") ?? "gpt-4o-mini";
 AIAgent agent = new OpenAIClient(
     apiKey)
      .GetResponsesClient(model)
-     .CreateAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
+     .AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");
 
 // Invoke the agent and output the text result.
 Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));

dotnet/samples/GettingStarted/AgentWithAnthropic/Agent_Anthropic_Step01_Running/Program.cs

@@ -11,7 +11,7 @@ var apiKey = Environment.GetEnvironmentVariable("ANTHROPIC_API_KEY") ?? throw ne
 var model = Environment.GetEnvironmentVariable("ANTHROPIC_MODEL") ?? "claude-haiku-4-5";
 
 AIAgent agent = new AnthropicClient(new ClientOptions { APIKey = apiKey })
-    .CreateAIAgent(model: model, instructions: "You are good at telling jokes.", name: "Joker");
+    .AsAIAgent(model: model, instructions: "You are good at telling jokes.", name: "Joker");
 
 // Invoke the agent and output the text result.
 var response = await agent.RunAsync("Tell me a joke about a pirate.");

dotnet/samples/GettingStarted/AgentWithAnthropic/Agent_Anthropic_Step02_Reasoning/Program.cs

@@ -14,7 +14,7 @@ var maxTokens = 4096;
 var thinkingTokens = 2048;
 
 var agent = new AnthropicClient(new ClientOptions { APIKey = apiKey })
-    .CreateAIAgent(
+    .AsAIAgent(
         model: model,
         clientFactory: (chatClient) => chatClient
             .AsBuilder()