Update 3

* Fix the ordering of chained resolvers in JsonSerializerOptions

We want the resolvers from AIJsonUtilities to be used before the ones from the source generator, in case the source generator emits its own copy in that assembly for the M.E.AI types.

* Apply suggestions from code review

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update dotnet/src/Microsoft.Agents.AI/AgentJsonUtilities.cs

* Update dotnet/src/Microsoft.Agents.AI.Mem0/Mem0JsonUtilities.cs

Co-authored-by: westey <164392973+westey-m@users.noreply.github.com>

* Remove unused using directive in Mem0JsonUtilities

Removed unused using directive for Microsoft.Extensions.AI.

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: westey <164392973+westey-m@users.noreply.github.com>

.github/.linkspector.yml

@@ -12,11 +12,14 @@ ignorePatterns:
   - pattern: "https:\/\/platform.openai.com"
   - pattern: "http:\/\/localhost"
   - pattern: "http:\/\/127.0.0.1"
+  - pattern: "https:\/\/localhost"
+  - pattern: "https:\/\/127.0.0.1"
   - pattern: "0001-spec.md"
   - pattern: "0001-madr-architecture-decisions.md"
   - pattern: "https://api.powerplatform.com/.default"
   - pattern: "https://your-resource.openai.azure.com/"
   - pattern: "http://host.docker.internal"
+  - pattern: "https://openai.github.io/openai-agents-js/openai/agents/classes/"
 # excludedDirs:
   # Folders which include links to localhost, since it's not ignored with regular expressions
 baseUrl: https://github.com/microsoft/agent-framework/

.github/upgrades/prompts/SemanticKernelToAgentFramework.md

@@ -1052,7 +1052,7 @@ AgentThread thread = agent.GetNewThread();
 
 **Add Agent Framework Packages:**
 ```xml
-<PackageReference Include="Microsoft.Agents.AI.AzureAI" />
+<PackageReference Include="Microsoft.Agents.AI.AzureAI.Persistent" />
 <PackageReference Include="Azure.Identity" />
 ```
 </configuration_changes>

.github/workflows/dotnet-build-and-test.yml

@@ -74,6 +74,7 @@ jobs:
             .
             .github
             dotnet
+            python
             workflow-samples
 
       - name: Setup dotnet

.github/workflows/dotnet-format.yml

@@ -7,7 +7,7 @@ name: dotnet-format
 on:
   workflow_dispatch:
   pull_request:
-    branches: ["main", "feature*"]
+    branches: ["main"]
     paths:
       - dotnet/**
       - '.github/workflows/dotnet-format.yml'

.github/workflows/python-code-quality.yml

@@ -18,7 +18,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.10"]
+        python-version: ["3.10", "3.14"]
     runs-on: ubuntu-latest
     continue-on-error: true
     defaults:

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

@@ -16,13 +16,39 @@ env:
   UV_CACHE_DIR: /tmp/.uv-cache
 
 jobs:
+  paths-filter:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      pull-requests: read
+    outputs:
+      pythonChanges: ${{ steps.filter.outputs.python}}
+    steps:
+      - uses: actions/checkout@v5
+      - uses: dorny/paths-filter@v3
+        id: filter
+        with:
+          filters: |
+            python:
+              - 'python/**'
+      # run only if 'python' files were changed
+      - name: python tests
+        if: steps.filter.outputs.python == 'true'
+        run: echo "Python file"
+      # run only if not 'python' files were changed
+      - name: not python tests
+        if: steps.filter.outputs.python != 'true'
+        run: echo "NOT python file"
+
   python-lab-tests:
     name: Python Lab Tests
+    needs: paths-filter
+    if: needs.paths-filter.outputs.pythonChanges == 'true'
     runs-on: ${{ matrix.os }}
     strategy:
       fail-fast: true
       matrix:
-        python-version: ["3.10", "3.11", "3.12", "3.13"]
+        python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
         # TODO(ekzhu): re-enable macos-latest when this is fixed: https://github.com/actions/runner-images/issues/11881
         os: [ubuntu-latest, windows-latest]
     env:

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

@@ -60,6 +60,8 @@ jobs:
       OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
       OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
       OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
+      ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
+      ANTHROPIC_CHAT_MODEL_ID: ${{ vars.ANTHROPIC_CHAT_MODEL_ID }}
       AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
       AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
       AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}

.github/workflows/python-tests.yml

@@ -16,7 +16,7 @@ jobs:
     strategy:
       fail-fast: true
       matrix:
-        python-version: ["3.10", "3.11", "3.12", "3.13"]
+        python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
         # todo: add macos-latest when problems are resolved
         os: [ubuntu-latest, windows-latest]
     env:

.gitignore

@@ -203,4 +203,12 @@ agents.md
 
 # AI
 .claude/
-WARP.md
+WARP.md
+
+# Frontend
+**/frontend/node_modules/
+**/frontend/.vite/
+**/frontend/dist/
+
+# Database files
+*.db

COMMUNITY.md

@@ -0,0 +1,22 @@
+# Welcome to the Agent Framework Community
+
+Below are some ways that you can get involved in the Agent Framework Community.
+
+## Engage on GitHub
+
+- [Discussions](https://github.com/microsoft/agent-framework/discussions): Ask questions, provide feedback and ideas to what you'd like to see from the Agent Framework.
+- [Issues](https://github.com/microsoft/agent-framework/issues) - If you find a bug, unexpected behavior or have a feature request, please open an issue.
+- [Pull Requests](https://github.com/microsoft/agent-framework/pulls) - We welcome contributions! Please see our [Contributing Guide](https://github.com/microsoft/agent-framework/blob/main/CONTRIBUTING.md)
+
+We do our best to respond to each submission.
+
+## Public Community Office Hours
+
+We regularly have Community Office Hours that are open to the **public** to join.
+
+Add Agent Framework events to your calendar. We are running two community calls to accommodate different time zones for Q&A Office Hours:
+
+- **Americas & EMEA timezone:** Every Wednesday at 8:00 AM Pacific Time/17:00 CET. Adjusted for daylight savings. Join here: [AF-AG-SK-Americas-Europe-OfficeHours](https://aka.ms/sk-officehours).
+- **Asia Pacific timezone:** The second Wednesday of every month at 4:00 PM Pacific Time Wednesday. In much of Asia this occurs on Thursday local time. Adjusted for daylight savings. Join here: [AF-AG-SK-APAC-OfficeHours](https://aka.ms/sk-apac-officehours).
+
+If you are unable to make it live, all meetings will be recorded and posted online.

docs/FAQS.md

@@ -23,23 +23,23 @@ To download nightly builds follow the following steps:
     <configuration>
       <packageSources>
         <add key="nuget.org" value="https://api.nuget.org/v3/index.json" protocolVersion="3" />
-        <add key="github" value="https://nuget.pkg.github.com/microsoft/index.json" />
+        <add key="GitHubMicrosoft" value="https://nuget.pkg.github.com/microsoft/index.json" />
       </packageSources>
     
       <packageSourceMapping>
         <packageSource key="nuget.org">
           <package pattern="*" />
         </packageSource>
-        <packageSource key="github">
+        <packageSource key="GitHubMicrosoft">
           <package pattern="*nightly"/>
         </packageSource>
       </packageSourceMapping>
     
       <packageSourceCredentials>
-        <github>
-            <add key="Username" value="<Your GitHub Id>" />
-            <add key="ClearTextPassword" value="<Your Personal Access Token>" />
-          </github>
+        <GitHubMicrosoft>
+          <add key="Username" value="<Your GitHub Id>" />
+          <add key="ClearTextPassword" value="<Your Personal Access Token>" />
+        </GitHubMicrosoft>
       </packageSourceCredentials>
     </configuration>
     ```

docs/decisions/0006-userapproval.md

@@ -22,7 +22,6 @@ This document aims to provide options and capture the decision on how to model t
 See various features that would need to be supported via this type of mechanism, plus how various other frameworks support this:
 
 - Also see [dotnet issue 6492](https://github.com/dotnet/extensions/issues/6492), which discusses the need for a similar pattern in the context of MCP approvals.
-- Also see [the openai RunToolApprovalItem](https://openai.github.io/openai-agents-js/openai/agents/classes/runtoolapprovalitem/).
 - Also see [the openai human-in-the-loop guide](https://openai.github.io/openai-agents-js/guides/human-in-the-loop/#approval-requests).
 - Also see [the openai MCP guide](https://openai.github.io/openai-agents-js/guides/mcp/#optional-approval-flow).
 - Also see [MCP Approval Requests from OpenAI](https://platform.openai.com/docs/guides/tools-remote-mcp#approvals).

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

@@ -0,0 +1,95 @@
+---
+status: accepted
+contact: javiercn
+date: 2025-10-29
+deciders: javiercn, DeagleGross, moonbox3, markwallace-microsoft
+consulted: Agent Framework team
+informed: .NET community
+---
+
+# AG-UI Protocol Support for .NET Agent Framework
+
+## Context and Problem Statement
+
+The .NET Agent Framework needed a standardized way to enable communication between AI agents and user-facing applications with support for streaming, real-time updates, and bidirectional communication. Without AG-UI protocol support, .NET agents could not interoperate with the growing ecosystem of AG-UI-compatible frontends and agent frameworks (LangGraph, CrewAI, Pydantic AI, etc.), limiting the framework's adoption and utility.
+
+The AG-UI (Agent-User Interaction) protocol is an open, lightweight, event-based protocol that addresses key challenges in agentic applications including streaming support for long-running agents, event-driven architecture for nondeterministic behavior, and protocol interoperability that complements MCP (tool/context) and A2A (agent-to-agent) protocols.
+
+## Decision Drivers
+
+- Need for streaming communication between agents and client applications
+- Requirement for protocol interoperability with other AI frameworks
+- Support for long-running, multi-turn conversation sessions
+- Real-time UI updates for nondeterministic agent behavior
+- Standardized approach to agent-to-UI communication
+- Framework abstraction to protect consumers from protocol changes
+
+## Considered Options
+
+1. **Implement AG-UI event types as public API surface** - Expose AG-UI event models directly to consumers
+2. **Use custom AIContent types for lifecycle events** - Create new content types (RunStartedContent, RunFinishedContent, RunErrorContent)
+3. **Current approach** - Internal event types with framework-native abstractions
+
+## Decision Outcome
+
+Chosen option: "Current approach with internal event types and framework-native abstractions", because it:
+
+- 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
+- Focuses on core text streaming functionality
+- Leverages existing properties (ConversationId, ResponseId, ErrorContent) instead of custom types
+- Provides bidirectional client and server support
+
+### Implementation Details
+
+**In Scope:**
+1. **Client-side AG-UI consumption** (`Microsoft.Agents.AI.AGUI` package)
+   - `AGUIAgent` class for connecting to remote AG-UI servers
+   - `AGUIAgentThread` for managing conversation threads
+   - HTTP/SSE streaming support
+   - Event-to-framework type conversion
+
+2. **Server-side AG-UI hosting** (`Microsoft.Agents.AI.Hosting.AGUI.AspNetCore` package)
+   - `MapAGUIAgent` extension method for ASP.NET Core
+   - Server-Sent Events (SSE) response formatting
+   - Framework-to-event type conversion
+   - Agent factory pattern for per-request instantiation
+
+3. **Text streaming events**
+   - Lifecycle events: `RunStarted`, `RunFinished`, `RunError`
+   - Text message events: `TextMessageStart`, `TextMessageContent`, `TextMessageEnd`
+   - Thread and run ID management via `ConversationId` and `ResponseId`
+
+### Key Design Decisions
+
+1. **Event Models as Internal Types** - AG-UI event types are internal with conversion via extension methods; public API uses the existing types in Microsoft.Extensions.AI as those are the abstractions people are familiar with
+
+2. **No Custom Content Types** - Run lifecycle communicated through existing `ChatResponseUpdate` properties (`ConversationId`, `ResponseId`) and standard `ErrorContent` type
+
+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`)
+
+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.
+
+6. **Custom JSON Converter** - Uses custom polymorphic deserialization via `BaseEventJsonConverter` instead of built-in System.Text.Json support to handle AG-UI protocol's flexible discriminator positioning
+
+### Consequences
+
+**Positive:**
+- .NET developers can consume AG-UI servers from any framework
+- .NET agents accessible from any AG-UI-compatible client
+- Standardized streaming communication patterns
+- Protected from protocol changes through internal implementation
+- Symmetric conversion logic between client and server
+- Framework-native public API surface
+
+**Negative:**
+- Custom JSON converter required (internal implementation detail)
+- Shared code uses preprocessor directives (`#if ASPNETCORE`)
+- Additional abstraction layer between protocol and public API
+
+**Neutral:**
+- Initial implementation focused on text streaming
+- Applications responsible for thread persistence

dotnet/Directory.Packages.props

@@ -15,9 +15,10 @@
     <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="9.8.0" />
+    <PackageVersion Include="CommunityToolkit.Aspire.OllamaSharp" Version="9.9.0" />
     <!-- Azure.* -->
-    <PackageVersion Include="Azure.AI.Agents.Persistent" Version="1.2.0-beta.6" />
+    <PackageVersion Include="Azure.AI.Agents" Version="2.0.0-alpha.20251104.7" />
+    <PackageVersion Include="Azure.AI.Agents.Persistent" Version="1.2.0-beta.7" />
     <PackageVersion Include="Azure.AI.OpenAI" Version="2.5.0-beta.1" />
     <PackageVersion Include="Azure.Identity" Version="1.17.0" />
     <PackageVersion Include="Azure.Monitor.OpenTelemetry.Exporter" Version="1.4.0" />
@@ -30,6 +31,7 @@
     <PackageVersion Include="System.CommandLine" Version="2.0.0-rc.2.25502.107" />
     <PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="9.0.10" />
     <PackageVersion Include="System.Linq.AsyncEnumerable" Version="10.0.0-rc.2.25502.107" />
+    <PackageVersion Include="System.Net.Http.Json" Version="9.0.10" />
     <PackageVersion Include="System.Net.ServerSentEvents" Version="9.0.10" />
     <PackageVersion Include="System.Text.Json" Version="9.0.10" />
     <PackageVersion Include="System.Threading.Channels" Version="9.0.10" />
@@ -40,18 +42,19 @@
     <PackageVersion Include="OpenTelemetry.Exporter.Console" Version="1.13.1" />
     <PackageVersion Include="OpenTelemetry.Exporter.InMemory" Version="1.13.1" />
     <PackageVersion Include="OpenTelemetry.Exporter.OpenTelemetryProtocol" Version="1.13.1" />
-    <PackageVersion Include="OpenTelemetry.Extensions.Hosting" Version="1.12.0" />
-    <PackageVersion Include="OpenTelemetry.Instrumentation.AspNetCore" Version="1.12.0" />
-    <PackageVersion Include="OpenTelemetry.Instrumentation.Http" Version="1.12.0" />
+    <PackageVersion Include="OpenTelemetry.Extensions.Hosting" Version="1.13.1" />
+    <PackageVersion Include="OpenTelemetry.Instrumentation.AspNetCore" Version="1.13.0" />
+    <PackageVersion Include="OpenTelemetry.Instrumentation.Http" Version="1.13.0" />
     <PackageVersion Include="OpenTelemetry.Instrumentation.Runtime" Version="1.12.0" />
     <!-- Microsoft.AspNetCore.* -->
     <PackageVersion Include="Microsoft.AspNetCore.OpenApi" Version="9.0.10" />
     <PackageVersion Include="Swashbuckle.AspNetCore.SwaggerUI" Version="9.0.4" />
     <!-- Microsoft.Extensions.* -->
-    <PackageVersion Include="Microsoft.Extensions.AI" Version="9.10.1" />
-    <PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="9.10.1" />
+    <PackageVersion Include="Microsoft.Extensions.AI" Version="9.10.2" />
+    <PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="9.10.2" />
     <PackageVersion Include="Microsoft.Extensions.AI.AzureAIInference" Version="9.10.0-preview.1.25513.3" />
-    <PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="9.10.1-preview.1.25521.4" />
+    <PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="9.10.2-preview.1.25552.1" />
+    <PackageVersion Include="Microsoft.Extensions.Caching.Memory" Version="9.0.10" />
     <PackageVersion Include="Microsoft.Extensions.Configuration" Version="9.0.10" />
     <PackageVersion Include="Microsoft.Extensions.Configuration.Binder" Version="9.0.10" />
     <PackageVersion Include="Microsoft.Extensions.Configuration.EnvironmentVariables" Version="9.0.10" />
@@ -65,12 +68,16 @@
     <PackageVersion Include="Microsoft.Extensions.Logging.Abstractions" Version="9.0.10" />
     <PackageVersion Include="Microsoft.Extensions.Logging.Console" Version="9.0.10" />
     <PackageVersion Include="Microsoft.Extensions.ServiceDiscovery" Version="$(AspireAppHostSdkVersion)" />
-    <!-- Vector Stores -->
+    <PackageVersion Include="Microsoft.Extensions.VectorData.Abstractions" Version="9.7.0" />
+    <!-- Semantic Kernel -->
     <PackageVersion Include="Microsoft.SemanticKernel" Version="1.66.0" />
-    <PackageVersion Include="Microsoft.SemanticKernel.Connectors.InMemory" Version="1.66.0-preview" />
     <PackageVersion Include="Microsoft.SemanticKernel.Agents.Core" Version="1.66.0" />
     <PackageVersion Include="Microsoft.SemanticKernel.Agents.OpenAI" Version="1.66.0-preview" />
     <PackageVersion Include="Microsoft.SemanticKernel.Agents.AzureAI" Version="1.66.0-preview" />
+    <PackageVersion Include="Microsoft.SemanticKernel.Plugins.OpenApi" Version="1.66.0" />
+    <!-- Vector Stores -->
+    <PackageVersion Include="Microsoft.SemanticKernel.Connectors.InMemory" Version="1.66.0-preview" />
+    <PackageVersion Include="Microsoft.SemanticKernel.Connectors.Qdrant" Version="1.66.0-preview" />
     <!-- Agent SDKs -->
     <PackageVersion Include="Microsoft.Agents.CopilotStudio.Client" Version="1.2.41" />
     <!-- A2A -->
@@ -80,12 +87,12 @@
     <PackageVersion Include="ModelContextProtocol" Version="0.4.0-preview.3" />
     <!-- Inference SDKs -->
     <PackageVersion Include="Anthropic.SDK" Version="5.8.0" />
-    <PackageVersion Include="AWSSDK.Extensions.Bedrock.MEAI" Version="4.0.4.1" />
+    <PackageVersion Include="AWSSDK.Extensions.Bedrock.MEAI" Version="4.0.4.2" />
     <PackageVersion Include="Microsoft.ML.OnnxRuntimeGenAI" Version="0.10.0" />
     <PackageVersion Include="OllamaSharp" Version="5.4.8" />
-    <PackageVersion Include="OpenAI" Version="2.5.0" />
+    <PackageVersion Include="OpenAI" Version="2.6.0" />
     <!-- Identity -->
-    <PackageVersion Include="Microsoft.Identity.Client.Extensions.Msal" Version="4.77.1" />
+    <PackageVersion Include="Microsoft.Identity.Client.Extensions.Msal" Version="4.78.0" />
     <!-- Workflows -->
     <PackageVersion Include="Microsoft.Bot.ObjectModel" Version="1.2025.1003.2" />
     <PackageVersion Include="Microsoft.Bot.ObjectModel.Json" Version="1.2025.1003.2" />
@@ -95,7 +102,7 @@
     <PackageVersion Include="System.Linq.Async" Version="6.0.3" />
     <!-- Test -->
     <PackageVersion Include="FluentAssertions" Version="8.8.0" />
-    <PackageVersion Include="Microsoft.AspNetCore.Mvc.Testing" Version="9.0.10" />
+    <PackageVersion Include="Microsoft.AspNetCore.TestHost" Version="9.0.10" />
     <PackageVersion Include="Microsoft.NET.Test.Sdk" Version="18.0.0" />
     <PackageVersion Include="Moq" Version="[4.18.4]" />
     <PackageVersion Include="Microsoft.SemanticKernel.Agents.Abstractions" Version="1.66.0" />
@@ -145,4 +152,4 @@
       <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
     </PackageReference>
   </ItemGroup>
-</Project>
+</Project>

dotnet/agent-framework-dotnet.slnx

@@ -18,6 +18,10 @@
     <Project Path="samples/AgentWebChat/AgentWebChat.ServiceDefaults/AgentWebChat.ServiceDefaults.csproj" />
     <Project Path="samples/AgentWebChat/AgentWebChat.Web/AgentWebChat.Web.csproj" />
   </Folder>
+  <Folder Name="/Samples/AGUIClientServer/">
+    <Project Path="samples/AGUIClientServer/AGUIClient/AGUIClient.csproj" />
+    <Project Path="samples/AGUIClientServer/AGUIServer/AGUIServer.csproj" />
+  </Folder>
   <Folder Name="/Samples/GettingStarted/">
     <File Path="samples/GettingStarted/README.md" />
   </Folder>
@@ -39,11 +43,29 @@
     <Project Path="samples/GettingStarted/AgentProviders/Agent_With_OpenAIChatCompletion/Agent_With_OpenAIChatCompletion.csproj" />
     <Project Path="samples/GettingStarted/AgentProviders/Agent_With_OpenAIResponses/Agent_With_OpenAIResponses.csproj" />
   </Folder>
+  <Folder Name="/Samples/GettingStarted/AgentProviders/AzureAIAgents/">
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step01.1_Basics/AzureAIAgents_Step01.1_Basics.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step01.2_Running/AzureAIAgents_Step01.2_Running.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step02_MultiturnConversation/AzureAIAgents_Step02_MultiturnConversation.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step03.1_UsingFunctionTools/AzureAIAgents_Step03.1_UsingFunctionTools.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step03.2_UsingFunctionTools_FromOpenAPI/AzureAIAgents_Step03.2_UsingFunctionTools_FromOpenAPI.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step04_UsingFunctionToolsWithApprovals/AzureAIAgents_Step04_UsingFunctionToolsWithApprovals.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step05_StructuredOutput/AzureAIAgents_Step05_StructuredOutput.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step06_PersistedConversations/AzureAIAgents_Step06_PersistedConversations.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step07_Observability/AzureAIAgents_Step07_Observability.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step08_DependencyInjection/AzureAIAgents_Step08_DependencyInjection.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step09_AsMcpTool/AzureAIAgents_Step09_AsMcpTool.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step10_UsingImages/AzureAIAgents_Step10_UsingImages.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step11_AsFunctionTool/AzureAIAgents_Step11_AsFunctionTool.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step12_Middleware/AzureAIAgents_Step12_Middleware.csproj" />
+    <Project Path="samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step13_Plugins/AzureAIAgents_Step13_Plugins.csproj" />
+  </Folder>
   <Folder Name="/Samples/GettingStarted/Agents/">
     <File Path="samples/GettingStarted/Agents/README.md" />
     <Project Path="samples/GettingStarted/Agents/Agent_Step01_Running/Agent_Step01_Running.csproj" />
     <Project Path="samples/GettingStarted/Agents/Agent_Step02_MultiturnConversation/Agent_Step02_MultiturnConversation.csproj" />
-    <Project Path="samples/GettingStarted/Agents/Agent_Step03_UsingFunctionTools/Agent_Step03_UsingFunctionTools.csproj" />
+    <Project Path="samples/GettingStarted/Agents/Agent_Step03.1_UsingFunctionTools/Agent_Step03.1_UsingFunctionTools.csproj" />
+    <Project Path="samples/GettingStarted/Agents/Agent_Step03.2_UsingFunctionTools_FromOpenAPI/Agent_Step03.2_UsingFunctionTools_FromOpenAPI.csproj" />
     <Project Path="samples/GettingStarted/Agents/Agent_Step04_UsingFunctionToolsWithApprovals/Agent_Step04_UsingFunctionToolsWithApprovals.csproj" />
     <Project Path="samples/GettingStarted/Agents/Agent_Step05_StructuredOutput/Agent_Step05_StructuredOutput.csproj" />
     <Project Path="samples/GettingStarted/Agents/Agent_Step06_PersistedConversations/Agent_Step06_PersistedConversations.csproj" />
@@ -56,18 +78,31 @@
     <Project Path="samples/GettingStarted/Agents/Agent_Step13_Memory/Agent_Step13_Memory.csproj" />
     <Project Path="samples/GettingStarted/Agents/Agent_Step14_Middleware/Agent_Step14_Middleware.csproj" />
     <Project Path="samples/GettingStarted/Agents/Agent_Step15_Plugins/Agent_Step15_Plugins.csproj" />
-    <Project Path="samples/GettingStarted/Agents/Agent_Step16_ChatReduction/Agent_Step16_ChatReduction.csproj" />
     <Project Path="samples/GettingStarted/Agents/Agent_Step17_BackgroundResponses/Agent_Step17_BackgroundResponses.csproj" />
+    <Project Path="samples/GettingStarted/Agents/Agent_Step18_TextSearchRag/Agent_Step18_TextSearchRag.csproj" />
+    <Project Path="samples/GettingStarted/Agents/Agent_Step19_Mem0Provider/Agent_Step19_Mem0Provider.csproj" />
+    <Project Path="samples/GettingStarted/Agents/Agent_Step20_BackgroundResponsesWithToolsAndPersistence/Agent_Step20_BackgroundResponsesWithToolsAndPersistence.csproj" />
+  </Folder>
+  <Folder Name="/Samples/GettingStarted/DevUI/">
+    <File Path="samples/GettingStarted/DevUI/README.md" />
+    <Project Path="samples/GettingStarted/DevUI/DevUI_Step01_BasicUsage/DevUI_Step01_BasicUsage.csproj" />
   </Folder>
   <Folder Name="/Samples/GettingStarted/AgentWithOpenAI/">
     <File Path="samples/GettingStarted/AgentWithOpenAI/README.md" />
     <Project Path="samples/GettingStarted/AgentWithOpenAI/Agent_OpenAI_Step01_Running/Agent_OpenAI_Step01_Running.csproj" />
     <Project Path="samples/GettingStarted/AgentWithOpenAI/Agent_OpenAI_Step02_Reasoning/Agent_OpenAI_Step02_Reasoning.csproj" />
   </Folder>
+  <Folder Name="/Samples/GettingStarted/AgentWithRAG/">
+    <File Path="samples/GettingStarted/AgentWithRAG/README.md" />
+    <Project Path="samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step01_BasicTextRAG/AgentWithRAG_Step01_BasicTextRAG.csproj" />
+    <Project Path="samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step02_ExternalDataSourceRAG/AgentWithRAG_Step02_ExternalDataSourceRAG.csproj" />
+  </Folder>
   <Folder Name="/Samples/GettingStarted/ModelContextProtocol/">
+    <File Path="samples/GettingStarted/ModelContextProtocol/README.md" />
     <Project Path="samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server/Agent_MCP_Server.csproj" />
     <Project Path="samples/GettingStarted/ModelContextProtocol/Agent_MCP_Server_Auth/Agent_MCP_Server_Auth.csproj" />
     <Project Path="samples/GettingStarted/ModelContextProtocol/FoundryAgent_Hosted_MCP/FoundryAgent_Hosted_MCP.csproj" />
+    <Project Path="samples/GettingStarted/ModelContextProtocol/ResponseAgent_Hosted_MCP/ResponseAgent_Hosted_MCP.csproj" />
   </Folder>
   <Folder Name="/Samples/GettingStarted/Observability/">
     <Project Path="samples/GettingStarted/AgentOpenTelemetry/AgentOpenTelemetry.csproj" />
@@ -120,6 +155,7 @@
   <Folder Name="/Samples/GettingStarted/Workflows/Observability/">
     <Project Path="samples/GettingStarted/Workflows/Observability/ApplicationInsights/ApplicationInsights.csproj" />
     <Project Path="samples/GettingStarted/Workflows/Observability/AspireDashboard/AspireDashboard.csproj" />
+    <Project Path="samples/GettingStarted/Workflows/Observability/WorkflowAsAnAgent/WorkflowAsAnAgentObservability.csproj" />
   </Folder>
   <Folder Name="/Samples/GettingStarted/Workflows/Visualization/">
     <Project Path="samples/GettingStarted/Workflows/Visualization/Visualization.csproj" Id="99bf0bc6-2440-428e-b3e7-d880e4b7a5fd" />
@@ -132,9 +168,12 @@
     <Project Path="samples/GettingStarted/Workflows/_Foundational/05_MultiModelService/05_MultiModelService.csproj" />
     <Project Path="samples/GettingStarted/Workflows/_Foundational/06_SubWorkflows/06_SubWorkflows.csproj" />
     <Project Path="samples/GettingStarted/Workflows/_Foundational/07_MixedWorkflowAgentsAndExecutors/07_MixedWorkflowAgentsAndExecutors.csproj" />
+    <Project Path="samples/GettingStarted/Workflows/_Foundational/08_WriterCriticWorkflow/08_WriterCriticWorkflow.csproj" />
   </Folder>
-  <Folder Name="/Samples/SemanticKernelMigration/">
-    <File Path="samples/SemanticKernelMigration/README.md" />
+  <Folder Name="/Samples/Catalog/">
+    <Project Path="samples/Catalog/AgentsInWorkflows/AgentsInWorkflows.csproj" />
+    <Project Path="samples/Catalog/AgentWithTextSearchRag/AgentWithTextSearchRag.csproj" />
+    <Project Path="samples/Catalog/DeepResearchAgent/DeepResearchAgent.csproj" />
   </Folder>
   <Folder Name="/Solution Items/">
     <File Path=".editorconfig" />
@@ -258,10 +297,14 @@
   <Folder Name="/src/">
     <Project Path="src/Microsoft.Agents.AI.A2A/Microsoft.Agents.AI.A2A.csproj" />
     <Project Path="src/Microsoft.Agents.AI.Abstractions/Microsoft.Agents.AI.Abstractions.csproj" />
+    <Project Path="src/Microsoft.Agents.AI.AGUI/Microsoft.Agents.AI.AGUI.csproj" />
+    <Project Path="src/Microsoft.Agents.AI.AzureAI.Persistent/Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
     <Project Path="src/Microsoft.Agents.AI.AzureAI/Microsoft.Agents.AI.AzureAI.csproj" />
     <Project Path="src/Microsoft.Agents.AI.CopilotStudio/Microsoft.Agents.AI.CopilotStudio.csproj" />
+    <Project Path="src/Microsoft.Agents.AI.DevUI/Microsoft.Agents.AI.DevUI.csproj" />
     <Project Path="src/Microsoft.Agents.AI.Hosting.A2A.AspNetCore/Microsoft.Agents.AI.Hosting.A2A.AspNetCore.csproj" />
     <Project Path="src/Microsoft.Agents.AI.Hosting.A2A/Microsoft.Agents.AI.Hosting.A2A.csproj" />
+    <Project Path="src/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj" />
     <Project Path="src/Microsoft.Agents.AI.Hosting.OpenAI/Microsoft.Agents.AI.Hosting.OpenAI.csproj" />
     <Project Path="src/Microsoft.Agents.AI.Hosting/Microsoft.Agents.AI.Hosting.csproj" />
     <Project Path="src/Microsoft.Agents.AI.Mem0/Microsoft.Agents.AI.Mem0.csproj" />
@@ -275,6 +318,7 @@
     <Project Path="tests/AgentConformance.IntegrationTests/AgentConformance.IntegrationTests.csproj" />
     <Project Path="tests/AzureAIAgentsPersistent.IntegrationTests/AzureAIAgentsPersistent.IntegrationTests.csproj" />
     <Project Path="tests/CopilotStudio.IntegrationTests/CopilotStudio.IntegrationTests.csproj" />
+    <Project Path="tests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.IntegrationTests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.IntegrationTests.csproj" />
     <Project Path="tests/Microsoft.Agents.AI.Mem0.IntegrationTests/Microsoft.Agents.AI.Mem0.IntegrationTests.csproj" />
     <Project Path="tests/Microsoft.Agents.AI.Workflows.Declarative.IntegrationTests/Microsoft.Agents.AI.Workflows.Declarative.IntegrationTests.csproj" />
     <Project Path="tests/OpenAIAssistant.IntegrationTests/OpenAIAssistant.IntegrationTests.csproj" />
@@ -284,8 +328,11 @@
   <Folder Name="/Tests/UnitTests/">
     <Project Path="tests/Microsoft.Agents.AI.A2A.UnitTests/Microsoft.Agents.AI.A2A.UnitTests.csproj" />
     <Project Path="tests/Microsoft.Agents.AI.Abstractions.UnitTests/Microsoft.Agents.AI.Abstractions.UnitTests.csproj" />
+    <Project Path="tests/Microsoft.Agents.AI.AGUI.UnitTests/Microsoft.Agents.AI.AGUI.UnitTests.csproj" />
+    <Project Path="tests/Microsoft.Agents.AI.AzureAI.Persistent.UnitTests/Microsoft.Agents.AI.AzureAI.Persistent.UnitTests.csproj" />
     <Project Path="tests/Microsoft.Agents.AI.AzureAI.UnitTests/Microsoft.Agents.AI.AzureAI.UnitTests.csproj" />
     <Project Path="tests/Microsoft.Agents.AI.Hosting.A2A.Tests/Microsoft.Agents.AI.Hosting.A2A.Tests.csproj" Id="2a1c544d-237d-4436-8732-ba0c447ac06b" />
+    <Project Path="tests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.UnitTests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.UnitTests.csproj" />
     <Project Path="tests/Microsoft.Agents.AI.Hosting.OpenAI.UnitTests/Microsoft.Agents.AI.Hosting.OpenAI.UnitTests.csproj" />
     <Project Path="tests/Microsoft.Agents.AI.Hosting.UnitTests/Microsoft.Agents.AI.Hosting.UnitTests.csproj" />
     <Project Path="tests/Microsoft.Agents.AI.Mem0.UnitTests/Microsoft.Agents.AI.Mem0.UnitTests.csproj" />
@@ -294,4 +341,4 @@
     <Project Path="tests/Microsoft.Agents.AI.Workflows.Declarative.UnitTests/Microsoft.Agents.AI.Workflows.Declarative.UnitTests.csproj" />
     <Project Path="tests/Microsoft.Agents.AI.Workflows.UnitTests/Microsoft.Agents.AI.Workflows.UnitTests.csproj" />
   </Folder>
-</Solution>
+</Solution>

dotnet/nuget.config

@@ -3,10 +3,14 @@
   <packageSources>
     <clear />
     <add key="nuget.org" value="https://api.nuget.org/v3/index.json" />
+    <add key="azure-sdk-for-net" value="https://pkgs.dev.azure.com/azure-sdk/public/_packaging/azure-sdk-for-net/nuget/v3/index.json" />
   </packageSources>
   <packageSourceMapping>
     <packageSource key="nuget.org">
       <package pattern="*" />
     </packageSource>
+    <packageSource key="azure-sdk-for-net">
+      <package pattern="Azure.AI.Agents" />
+    </packageSource>
   </packageSourceMapping>
 </configuration>

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)-$(VersionSuffix).251028.1</PackageVersion>
-    <PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.251028.1</PackageVersion>
-    <GitTag>1.0.0-preview.251028.1</GitTag>
+    <PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).251105.1</PackageVersion>
+    <PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.251105.1</PackageVersion>
+    <GitTag>1.0.0-preview.251105.1</GitTag>
 
     <Configurations>Debug;Release;Publish</Configurations>
     <IsPackable>true</IsPackable>

dotnet/samples/A2AClientServer/A2AServer/A2AServer.csproj

@@ -20,7 +20,7 @@
     <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.A2A\Microsoft.Agents.AI.Hosting.A2A.csproj" />
 
     <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.A2A\Microsoft.Agents.AI.A2A.csproj" />
-    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.AzureAI.Persistent\Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
     <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
   </ItemGroup>
 

dotnet/samples/AGUIClientServer/AGUIClient/AGUIClient.csproj

@@ -0,0 +1,22 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+    <UserSecretsId>a8b2e9f0-1ea3-4f18-9d41-42d1a6f8fe10</UserSecretsId>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="System.CommandLine" />
+    <PackageReference Include="Microsoft.Extensions.Hosting" />
+    <PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
+    <PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.AGUI\Microsoft.Agents.AI.AGUI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/AGUIClientServer/AGUIClient/Program.cs

@@ -0,0 +1,137 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to use the AG-UI client to connect to a remote AG-UI server
+// and display streaming updates including conversation/response metadata, text content, and errors.
+
+using System.CommandLine;
+using System.Reflection;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.AGUI;
+using Microsoft.Extensions.AI;
+using Microsoft.Extensions.Configuration;
+using Microsoft.Extensions.Logging;
+
+namespace AGUIClient;
+
+public static class Program
+{
+    public static async Task<int> Main(string[] args)
+    {
+        // Create root command with options
+        RootCommand rootCommand = new("AGUIClient");
+        rootCommand.SetAction((_, ct) => HandleCommandsAsync(ct));
+
+        // Run the command
+        return await rootCommand.Parse(args).InvokeAsync();
+    }
+
+    private static async Task HandleCommandsAsync(CancellationToken cancellationToken)
+    {
+        // Set up the logging
+        using ILoggerFactory loggerFactory = LoggerFactory.Create(builder =>
+        {
+            builder.AddConsole();
+            builder.SetMinimumLevel(LogLevel.Information);
+        });
+        ILogger logger = loggerFactory.CreateLogger("AGUIClient");
+
+        // Retrieve configuration settings
+        IConfigurationRoot configRoot = new ConfigurationBuilder()
+            .AddEnvironmentVariables()
+            .AddUserSecrets(Assembly.GetExecutingAssembly())
+            .Build();
+
+        string serverUrl = configRoot["AGUI_SERVER_URL"] ?? "http://localhost:5100";
+
+        logger.LogInformation("Connecting to AG-UI server at: {ServerUrl}", serverUrl);
+
+        // Create the AG-UI client agent
+        using HttpClient httpClient = new()
+        {
+            Timeout = TimeSpan.FromSeconds(60)
+        };
+
+        AGUIAgent agent = new(
+            id: "agui-client",
+            description: "AG-UI Client Agent",
+            httpClient: httpClient,
+            endpoint: serverUrl);
+
+        AgentThread thread = agent.GetNewThread();
+        List<ChatMessage> messages = [new(ChatRole.System, "You are a helpful assistant.")];
+        try
+        {
+            while (true)
+            {
+                // Get user message
+                Console.Write("\nUser (:q or quit to exit): ");
+                string? message = Console.ReadLine();
+                if (string.IsNullOrWhiteSpace(message))
+                {
+                    Console.WriteLine("Request cannot be empty.");
+                    continue;
+                }
+
+                if (message is ":q" or "quit")
+                {
+                    break;
+                }
+
+                messages.Add(new(ChatRole.User, message));
+
+                // Call RunStreamingAsync to get streaming updates
+                bool isFirstUpdate = true;
+                string? threadId = null;
+                await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread, cancellationToken: cancellationToken))
+                {
+                    // Use AsChatResponseUpdate to access ChatResponseUpdate properties
+                    ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();
+                    if (chatUpdate.ConversationId != null)
+                    {
+                        threadId = chatUpdate.ConversationId;
+                    }
+
+                    // Display run started information from the first update
+                    if (isFirstUpdate && threadId != null && update.ResponseId != null)
+                    {
+                        Console.ForegroundColor = ConsoleColor.Yellow;
+                        Console.WriteLine($"\n[Run Started - Thread: {threadId}, Run: {update.ResponseId}]");
+                        Console.ResetColor();
+                        isFirstUpdate = false;
+                    }
+
+                    // Display different content types with appropriate formatting
+                    foreach (AIContent content in update.Contents)
+                    {
+                        switch (content)
+                        {
+                            case TextContent textContent:
+                                Console.ForegroundColor = ConsoleColor.Cyan;
+                                Console.Write(textContent.Text);
+                                Console.ResetColor();
+                                break;
+
+                            case ErrorContent errorContent:
+                                Console.ForegroundColor = ConsoleColor.Red;
+                                string code = errorContent.AdditionalProperties?["Code"] as string ?? "Unknown";
+                                Console.WriteLine($"\n[Error - Code: {code}, Message: {errorContent.Message}]");
+                                Console.ResetColor();
+                                break;
+                        }
+                    }
+                }
+                messages.Clear();
+                Console.WriteLine();
+            }
+        }
+        catch (OperationCanceledException)
+        {
+            logger.LogInformation("AGUIClient operation was canceled.");
+        }
+        catch (Exception ex) when (ex is not OutOfMemoryException and not StackOverflowException and not ThreadAbortException and not AccessViolationException)
+        {
+            logger.LogError(ex, "An error occurred while running the AGUIClient");
+            return;
+        }
+    }
+}

dotnet/samples/AGUIClientServer/AGUIClient/README.md

@@ -0,0 +1,34 @@
+# AG-UI Client
+
+This is a console application that demonstrates how to connect to an AG-UI server and interact with remote agents using the AG-UI protocol.
+
+## Features
+
+- Connects to an AG-UI server endpoint
+- Displays streaming updates with color-coded output:
+  - **Yellow**: Run started notifications
+  - **Cyan**: Agent text responses (streamed)
+  - **Green**: Run finished notifications
+  - **Red**: Error messages (if any)
+- Interactive prompt loop for sending messages
+
+## Configuration
+
+Set the following environment variable to specify the AG-UI server URL:
+
+```powershell
+$env:AGUI_SERVER_URL="http://localhost:5100"
+```
+
+If not set, the default is `http://localhost:5100`.
+
+## Running the Client
+
+1. Make sure the AG-UI server is running
+2. Run the client:
+   ```bash
+   cd AGUIClient
+   dotnet run
+   ```
+3. Enter your messages and observe the streaming updates
+4. Type `:q` or `quit` to exit

dotnet/samples/AGUIClientServer/AGUIServer/AGUIServer.csproj

@@ -0,0 +1,24 @@
+<Project Sdk="Microsoft.NET.Sdk.Web">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+    <UserSecretsId>a8b2e9f0-1ea3-4f18-9d41-42d1a6f8fe10</UserSecretsId>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
+    <PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.AGUI\Microsoft.Agents.AI.AGUI.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/AGUIClientServer/AGUIServer/AGUIServer.http

@@ -0,0 +1,17 @@
+@host = http://localhost:5100
+
+### Send a message to the AG-UI agent
+POST {{host}}/
+Content-Type: application/json
+
+{
+  "threadId": "thread_123",
+  "runId": "run_456",
+  "messages": [
+    {
+      "role": "user",
+      "content": "What is the capital of France?"
+    }
+  ],
+  "context": {}
+}

dotnet/samples/AGUIClientServer/AGUIServer/Program.cs

@@ -0,0 +1,26 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI.Hosting.AGUI.AspNetCore;
+using Microsoft.Extensions.AI;
+using OpenAI;
+
+WebApplicationBuilder builder = WebApplication.CreateBuilder(args);
+builder.Services.AddHttpClient().AddLogging();
+WebApplication app = builder.Build();
+
+string endpoint = builder.Configuration["AZURE_OPENAI_ENDPOINT"] ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+string deploymentName = builder.Configuration["AZURE_OPENAI_DEPLOYMENT_NAME"] ?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT_NAME is not set.");
+
+// Create the AI agent
+var agent = new AzureOpenAIClient(
+        new Uri(endpoint),
+        new DefaultAzureCredential())
+    .GetChatClient(deploymentName)
+    .CreateAIAgent(name: "AGUIAssistant");
+
+// Map the AG-UI agent endpoint
+app.MapAGUI("/", agent);
+
+await app.RunAsync();

dotnet/samples/AGUIClientServer/README.md

@@ -0,0 +1,202 @@
+# AG-UI Client and Server Sample
+
+This sample demonstrates how to use the AG-UI (Agent UI) protocol to enable communication between a client application and a remote agent server. The AG-UI protocol provides a standardized way for clients to interact with AI agents.
+
+## Overview
+
+The demonstration has two components:
+
+1. **AGUIServer** - An ASP.NET Core web server that hosts an AI agent and exposes it via the AG-UI protocol
+2. **AGUIClient** - A console application that connects to the AG-UI server and displays streaming updates
+
+> **Warning**
+> The AG-UI protocol is still under development and changing.
+> We will try to keep these samples updated as the protocol evolves.
+
+## Configuring Environment Variables
+
+Configure the required Azure OpenAI environment variables:
+
+```powershell
+$env:AZURE_OPENAI_ENDPOINT="<<your-model-endpoint>>"
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4.1-mini"
+```
+
+> **Note:** This sample uses `DefaultAzureCredential` for authentication. Make sure you're authenticated with Azure (e.g., via `az login`, Visual Studio, or environment variables).
+
+## Running the Sample
+
+### Step 1: Start the AG-UI Server
+
+```bash
+cd AGUIServer
+dotnet build
+dotnet run --urls "http://localhost:5100"
+```
+
+The server will start and listen on `http://localhost:5100`.
+
+### Step 2: Testing with the REST Client (Optional)
+
+Before running the client, you can test the server using the included `.http` file:
+
+1. Open [./AGUIServer/AGUIServer.http](./AGUIServer/AGUIServer.http) in Visual Studio or VS Code with the REST Client extension
+2. Send a test request to verify the server is working
+3. Observe the server-sent events stream in the response
+
+Sample request:
+```http
+POST http://localhost:5100/
+Content-Type: application/json
+
+{
+  "threadId": "thread_123",
+  "runId": "run_456",
+  "messages": [
+    {
+      "role": "user",
+      "content": "What is the capital of France?"
+    }
+  ],
+  "context": {}
+}
+```
+
+### Step 3: Run the AG-UI Client
+
+In a new terminal window:
+
+```bash
+cd AGUIClient
+dotnet run
+```
+
+Optionally, configure a different server URL:
+
+```powershell
+$env:AGUI_SERVER_URL="http://localhost:5100"
+```
+
+### Step 4: Interact with the Agent
+
+1. The client will connect to the AG-UI server
+2. Enter your message at the prompt
+3. Observe the streaming updates with color-coded output:
+   - **Yellow**: Run started notification showing thread and run IDs
+   - **Cyan**: Agent's text response (streamed character by character)
+   - **Green**: Run finished notification
+   - **Red**: Error messages (if any occur)
+4. Type `:q` or `quit` to exit
+
+## Sample Output
+
+```
+AGUIClient> dotnet run
+info: AGUIClient[0]
+      Connecting to AG-UI server at: http://localhost:5100
+
+User (:q or quit to exit): What is the capital of France?
+
+[Run Started - Thread: thread_abc123, Run: run_xyz789]
+The capital of France is Paris. It is known for its rich history, culture, and iconic landmarks such as the Eiffel Tower and the Louvre Museum.
+[Run Finished - Thread: thread_abc123, Run: run_xyz789]
+
+User (:q or quit to exit): Tell me a fun fact about space
+
+[Run Started - Thread: thread_abc123, Run: run_def456]
+Here's a fun fact: A day on Venus is longer than its year! Venus takes about 243 Earth days to rotate once on its axis, but only about 225 Earth days to orbit the Sun.
+[Run Finished - Thread: thread_abc123, Run: run_def456]
+
+User (:q or quit to exit): :q
+```
+
+## How It Works
+
+### Server Side
+
+The `AGUIServer` uses the `MapAGUI` extension method to expose an agent through the AG-UI protocol:
+
+```csharp
+AIAgent agent = new OpenAIClient(apiKey)
+    .GetChatClient(model)
+    .CreateAIAgent(
+        instructions: "You are a helpful assistant.",
+        name: "AGUIAssistant");
+
+app.MapAGUI("/", agent);
+```
+
+This automatically handles:
+- HTTP POST requests with message payloads
+- Converting agent responses to AG-UI event streams
+- Server-sent events (SSE) formatting
+- Thread and run management
+
+### Client Side
+
+The `AGUIClient` uses the `AGUIAgent` class to connect to the remote server:
+
+```csharp
+AGUIAgent agent = new(
+    id: "agui-client",
+    description: "AG-UI Client Agent",
+    messages: [],
+    httpClient: httpClient,
+    endpoint: serverUrl);
+
+bool isFirstUpdate = true;
+AgentRunResponseUpdate? currentUpdate = null;
+
+await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread))
+{
+    // First update indicates run started
+    if (isFirstUpdate)
+    {
+        Console.WriteLine($"[Run Started - Thread: {update.ConversationId}, Run: {update.ResponseId}]");
+        isFirstUpdate = false;
+    }
+    
+    currentUpdate = update;
+    
+    foreach (AIContent content in update.Contents)
+    {
+        switch (content)
+        {
+            case TextContent textContent:
+                // Display streaming text
+                Console.Write(textContent.Text);
+                break;
+            case ErrorContent errorContent:
+                // Display error notification
+                Console.WriteLine($"[Error: {errorContent.Message}]");
+                break;
+        }
+    }
+}
+
+// Last update indicates run finished
+if (currentUpdate != null)
+{
+    Console.WriteLine($"\n[Run Finished - Thread: {currentUpdate.ConversationId}, Run: {currentUpdate.ResponseId}]");
+}
+```
+
+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
+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:
+  - `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
+  - Subsequent updates contain streaming content as the agent processes
+  - The **last** `AgentRunResponseUpdate` in a run indicates the run has finished
+  - If an error occurs, the update will contain `ErrorContent`

dotnet/samples/AgentWebChat/AgentWebChat.AgentHost/Program.cs

@@ -20,14 +20,14 @@ builder.Services.AddProblemDetails();
 // Configure the chat model and our agent.
 builder.AddKeyedChatClient("chat-model");
 
-builder.AddAIAgent(
+var pirateAgentBuilder = builder.AddAIAgent(
     "pirate",
     instructions: "You are a pirate. Speak like a pirate",
     description: "An agent that speaks like a pirate.",
     chatClientServiceKey: "chat-model")
     .WithInMemoryThreadStore();
 
-builder.AddAIAgent("knights-and-knaves", (sp, key) =>
+var knightsKnavesAgentBuilder = builder.AddAIAgent("knights-and-knaves", (sp, key) =>
 {
     var chatClient = sp.GetRequiredKeyedService<IChatClient>("chat-model");
 
@@ -80,6 +80,8 @@ var literatureAgent = builder.AddAIAgent("literator",
 
 builder.AddSequentialWorkflow("science-sequential-workflow", [chemistryAgent, mathsAgent, literatureAgent]).AddAsAIAgent();
 builder.AddConcurrentWorkflow("science-concurrent-workflow", [chemistryAgent, mathsAgent, literatureAgent]).AddAsAIAgent();
+
+builder.AddOpenAIChatCompletions();
 builder.AddOpenAIResponses();
 
 var app = builder.Build();
@@ -104,8 +106,8 @@ app.MapA2A(agentName: "knights-and-knaves", path: "/a2a/knights-and-knaves", age
 
 app.MapOpenAIResponses();
 
-app.MapOpenAIChatCompletions("pirate");
-app.MapOpenAIChatCompletions("knights-and-knaves");
+app.MapOpenAIChatCompletions(pirateAgentBuilder);
+app.MapOpenAIChatCompletions(knightsKnavesAgentBuilder);
 
 // Map the agents HTTP endpoints
 app.MapAgentDiscovery("/agents");

dotnet/samples/Catalog/AgentWithTextSearchRag/AgentWithTextSearchRag.csproj

@@ -0,0 +1,21 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/Catalog/AgentWithTextSearchRag/Program.cs

@@ -0,0 +1,82 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to use TextSearchProvider to add retrieval augmented generation (RAG)
+// capabilities to an AI agent. The provider runs a search against an external knowledge base
+// before each model invocation and injects the results into the model context.
+
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.Data;
+using Microsoft.Extensions.AI;
+using OpenAI;
+
+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";
+
+TextSearchProviderOptions textSearchOptions = new()
+{
+    // Run the search prior to every model invocation and keep a short rolling window of conversation context.
+    SearchTime = TextSearchProviderOptions.TextSearchBehavior.BeforeAIInvoke,
+    RecentMessageMemoryLimit = 6,
+};
+
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+    .GetChatClient(deploymentName)
+    .CreateAIAgent(new ChatClientAgentOptions
+    {
+        Instructions = "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available.",
+        AIContextProviderFactory = ctx => new TextSearchProvider(MockSearchAsync, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions)
+    });
+
+AgentThread thread = agent.GetNewThread();
+
+Console.WriteLine(">> Asking about returns\n");
+Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", thread));
+
+Console.WriteLine("\n>> Asking about shipping\n");
+Console.WriteLine(await agent.RunAsync("How long does standard shipping usually take?", thread));
+
+Console.WriteLine("\n>> Asking about product care\n");
+Console.WriteLine(await agent.RunAsync("What is the best way to maintain the TrailRunner tent fabric?", thread));
+
+static Task<IEnumerable<TextSearchProvider.TextSearchResult>> MockSearchAsync(string query, CancellationToken cancellationToken)
+{
+    // The mock search inspects the user's question and returns pre-defined snippets
+    // that resemble documents stored in an external knowledge source.
+    List<TextSearchProvider.TextSearchResult> results = new();
+
+    if (query.Contains("return", StringComparison.OrdinalIgnoreCase) || query.Contains("refund", StringComparison.OrdinalIgnoreCase))
+    {
+        results.Add(new()
+        {
+            SourceName = "Contoso Outdoors Return Policy",
+            SourceLink = "https://contoso.com/policies/returns",
+            Text = "Customers may return any item within 30 days of delivery. Items should be unused and include original packaging. Refunds are issued to the original payment method within 5 business days of inspection."
+        });
+    }
+
+    if (query.Contains("shipping", StringComparison.OrdinalIgnoreCase))
+    {
+        results.Add(new()
+        {
+            SourceName = "Contoso Outdoors Shipping Guide",
+            SourceLink = "https://contoso.com/help/shipping",
+            Text = "Standard shipping is free on orders over $50 and typically arrives in 3-5 business days within the continental United States. Expedited options are available at checkout."
+        });
+    }
+
+    if (query.Contains("tent", StringComparison.OrdinalIgnoreCase) || query.Contains("fabric", StringComparison.OrdinalIgnoreCase))
+    {
+        results.Add(new()
+        {
+            SourceName = "TrailRunner Tent Care Instructions",
+            SourceLink = "https://contoso.com/manuals/trailrunner-tent",
+            Text = "Clean the tent fabric with lukewarm water and a non-detergent soap. Allow it to air dry completely before storage and avoid prolonged UV exposure to extend the lifespan of the waterproof coating."
+        });
+    }
+
+    return Task.FromResult<IEnumerable<TextSearchProvider.TextSearchResult>>(results);
+}

dotnet/samples/Catalog/AgentWithTextSearchRag/README.md

@@ -0,0 +1,41 @@
+# What this sample demonstrates
+
+This sample demonstrates how to use TextSearchProvider to add retrieval augmented generation (RAG) capabilities to an AI agent. The provider runs a search against an external knowledge base before each model invocation and injects the results into the model context.
+
+Key features:
+- Configuring TextSearchProvider with custom search behavior
+- Running searches before AI invocations to provide relevant context
+- Managing conversation memory with a rolling window approach
+- Citing source documents in AI responses
+
+## Prerequisites
+
+Before running this sample, ensure you have:
+
+1. An Azure OpenAI endpoint configured
+2. A deployment of a chat model (e.g., gpt-4o-mini)
+3. Azure CLI installed and authenticated
+
+## Environment Variables
+
+Set the following environment variables:
+
+```powershell
+# Replace with your Azure OpenAI endpoint
+$env:AZURE_OPENAI_ENDPOINT="https://your-openai-resource.openai.azure.com/"
+
+# Optional, defaults to gpt-4o-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
+```
+
+## How It Works
+
+The sample uses a mock search function that demonstrates the RAG pattern:
+
+1. When the user asks a question, the TextSearchProvider intercepts it
+2. The search function looks for relevant documents based on the query
+3. Retrieved documents are injected into the model's context
+4. The AI responds using both its training and the provided context
+5. The agent can cite specific source documents in its answers
+
+The mock search function returns pre-defined snippets for demonstration purposes. In a production scenario, you would replace this with actual searches against your knowledge base (e.g., Azure AI Search, vector database, etc.).

dotnet/samples/Catalog/AgentsInWorkflows/AgentsInWorkflows.csproj

@@ -0,0 +1,23 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Workflows\Microsoft.Agents.AI.Workflows.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.AzureAI.Persistent\Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/Catalog/AgentsInWorkflows/Program.cs

@@ -0,0 +1,48 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to integrate AI agents into a workflow pipeline.
+// Three translation agents are connected sequentially to create a translation chain:
+// English → French → Spanish → English, showing how agents can be composed as workflow executors.
+
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.Workflows;
+using Microsoft.Extensions.AI;
+
+// Set up the Azure OpenAI client
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+IChatClient chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
+    .GetChatClient(deploymentName)
+    .AsIChatClient();
+
+// Create agents
+AIAgent frenchAgent = GetTranslationAgent("French", chatClient);
+AIAgent spanishAgent = GetTranslationAgent("Spanish", chatClient);
+AIAgent englishAgent = GetTranslationAgent("English", chatClient);
+
+// Build the workflow by adding executors and connecting them
+Workflow workflow = new WorkflowBuilder(frenchAgent)
+    .AddEdge(frenchAgent, spanishAgent)
+    .AddEdge(spanishAgent, englishAgent)
+.Build();
+
+// Execute the workflow
+await using StreamingRun run = await InProcessExecution.StreamAsync(workflow, new ChatMessage(ChatRole.User, "Hello World!"));
+
+// Must send the turn token to trigger the agents.
+// The agents are wrapped as executors. When they receive messages,
+// they will cache the messages and only start processing when they receive a TurnToken.
+await run.TrySendMessageAsync(new TurnToken(emitEvents: true));
+await foreach (WorkflowEvent evt in run.WatchStreamAsync())
+{
+    if (evt is AgentRunUpdateEvent executorComplete)
+    {
+        Console.WriteLine($"{executorComplete.ExecutorId}: {executorComplete.Data}");
+    }
+}
+
+static ChatClientAgent GetTranslationAgent(string targetLanguage, IChatClient chatClient) =>
+    new(chatClient, $"You are a translation assistant that translates the provided text to {targetLanguage}.");

dotnet/samples/Catalog/AgentsInWorkflows/README.md

@@ -0,0 +1,26 @@
+# What this sample demonstrates
+
+This sample demonstrates the use of AI agents as executors within a workflow.
+
+This workflow uses three translation agents:
+1. French Agent - translates input text to French
+2. Spanish Agent - translates French text to Spanish
+3. English Agent - translates Spanish text back to English
+
+The agents are connected sequentially, creating a translation chain that demonstrates how AI-powered components can be seamlessly integrated into workflow pipelines.
+
+## Prerequisites
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 8.0 SDK or later
+- Azure OpenAI service endpoint and deployment configured
+- Azure CLI installed and authenticated (for Azure credential authentication)
+
+**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+
+Set the following environment variables:
+
+```powershell
+$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini

dotnet/samples/Catalog/DeepResearchAgent/DeepResearchAgent.csproj

@@ -0,0 +1,20 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents.Persistent" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.AzureAI.Persistent\Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/Catalog/DeepResearchAgent/Program.cs

@@ -0,0 +1,52 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create an Azure AI Foundry Agent with the Deep Research Tool.
+
+using Azure.AI.Agents.Persistent;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deepResearchDeploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEEP_RESEARCH_DEPLOYMENT_NAME") ?? "o3-deep-research";
+var modelDeploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o";
+var bingConnectionId = Environment.GetEnvironmentVariable("BING_CONNECTION_ID") ?? throw new InvalidOperationException("BING_CONNECTION_ID is not set.");
+
+// Configure extended network timeout for long-running Deep Research tasks.
+PersistentAgentsAdministrationClientOptions persistentAgentsClientOptions = new();
+persistentAgentsClientOptions.Retry.NetworkTimeout = TimeSpan.FromMinutes(20);
+
+// Get a client to create/retrieve server side agents with.
+PersistentAgentsClient persistentAgentsClient = new(endpoint, new AzureCliCredential(), persistentAgentsClientOptions);
+
+// Define and configure the Deep Research tool.
+DeepResearchToolDefinition deepResearchTool = new(new DeepResearchDetails(
+    bingGroundingConnections: [new(bingConnectionId)],
+    model: deepResearchDeploymentName)
+ );
+
+// Create an agent with the Deep Research tool on the Azure AI agent service.
+AIAgent agent = await persistentAgentsClient.CreateAIAgentAsync(
+    model: modelDeploymentName,
+    name: "DeepResearchAgent",
+    instructions: "You are a helpful Agent that assists in researching scientific topics.",
+    tools: [deepResearchTool]);
+
+const string Task = "Research the current state of studies on orca intelligence and orca language, " +
+    "including what is currently known about orcas' cognitive capabilities and communication systems.";
+
+Console.WriteLine($"# User: '{Task}'");
+Console.WriteLine();
+
+try
+{
+    AgentThread thread = agent.GetNewThread();
+
+    await foreach (var response in agent.RunStreamingAsync(Task, thread))
+    {
+        Console.Write(response.Text);
+    }
+}
+finally
+{
+    await persistentAgentsClient.Administration.DeleteAgentAsync(agent.Id);
+}

dotnet/samples/Catalog/DeepResearchAgent/README.md

@@ -0,0 +1,47 @@
+# What this sample demonstrates
+
+This sample demonstrates how to create an Azure AI Agent with the Deep Research Tool, which leverages the o3-deep-research reasoning model to perform comprehensive research on complex topics.
+
+Key features:
+- Configuring and using the Deep Research Tool with Bing grounding
+- Creating a persistent AI agent with deep research capabilities
+- Executing deep research queries and retrieving results
+
+## Prerequisites
+
+Before running this sample, ensure you have:
+
+1. An Azure AI Foundry project set up
+2. A deep research model deployment (e.g., o3-deep-research)
+3. A model deployment (e.g., gpt-4o)
+4. A Bing Connection configured in your Azure AI Foundry project
+5. Azure CLI installed and authenticated
+
+**Important**: Please visit the following documentation for detailed setup instructions:
+- [Deep Research Tool Documentation](https://aka.ms/agents-deep-research)
+- [Research Tool Setup](https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/tools/deep-research#research-tool-setup)
+
+Pay special attention to the purple `Note` boxes in the Azure documentation.
+
+**Note**: The Bing Connection ID must be from the **project**, not the resource. It has the following format:
+
+```
+/subscriptions/<sub_id>/resourceGroups/<rg_name>/providers/<provider_name>/accounts/<account_name>/projects/<project_name>/connections/<connection_name>
+```
+
+## Environment Variables
+
+Set the following environment variables:
+
+```powershell
+# Replace with your Azure AI Foundry project endpoint
+$env:AZURE_FOUNDRY_PROJECT_ENDPOINT="https://your-project.services.ai.azure.com/"
+
+# Replace with your Bing connection ID from the project
+$env:BING_CONNECTION_ID="/subscriptions/.../connections/your-bing-connection"
+
+# Optional, defaults to o3-deep-research
+$env:AZURE_FOUNDRY_PROJECT_DEEP_RESEARCH_DEPLOYMENT_NAME="o3-deep-research"
+
+# Optional, defaults to gpt-4o
+$env:AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME="gpt-4o"

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

@@ -23,7 +23,7 @@ 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 = await agentCard.GetAIAgentAsync();
+AIAgent a2aAgent = agentCard.GetAIAgent();
 
 // Create the main agent, and provide the a2a agent skills as a function tools.
 AIAgent agent = new AzureOpenAIClient(

dotnet/samples/GettingStarted/AgentOpenTelemetry/Program.cs

@@ -125,7 +125,7 @@ var agent = new ChatClientAgent(instrumentedChatClient,
     instructions: "You are a helpful assistant that provides concise and informative responses.",
     tools: [AIFunctionFactory.Create(GetWeatherAsync)])
     .AsBuilder()
-    .UseOpenTelemetry(SourceName) // enable telemetry at the agent level
+    .UseOpenTelemetry(SourceName, configure: (cfg) => cfg.EnableSensitiveData = true) // enable telemetry at the agent level
     .Build();
 
 var thread = agent.GetNewThread();
@@ -134,6 +134,8 @@ appLogger.LogInformation("Agent created successfully with ID: {AgentId}", agent.
 
 // Create a parent span for the entire agent session
 using var sessionActivity = activitySource.StartActivity("Agent Session");
+Console.WriteLine($"Trace ID: {sessionActivity?.TraceId} ");
+
 var sessionId = Guid.NewGuid().ToString("N");
 sessionActivity?
     .SetTag("agent.name", "OpenTelemetryDemoAgent")
@@ -147,7 +149,7 @@ using (appLogger.BeginScope(new Dictionary<string, object> { ["SessionId"] = ses
 
     while (true)
     {
-        Console.Write("You: ");
+        Console.Write("You (or 'exit' to quit): ");
         var userInput = Console.ReadLine();
 
         if (string.IsNullOrWhiteSpace(userInput) || userInput.Equals("exit", StringComparison.OrdinalIgnoreCase))

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step01.1_Basics/AzureAIAgents_Step01.1_Basics.csproj

@@ -0,0 +1,21 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <NoWarn>$(NoWarn);IDE0059</NoWarn>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step01.1_Basics/Program.cs

@@ -0,0 +1,54 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a AI agents with Azure Foundry Agents as the backend.
+
+using Azure.AI.Agents;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string JokerInstructions = "You are good at telling jokes.";
+const string JokerName = "JokerAgent";
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
+
+// Define the agent you want to create. (Prompt Agent in this case)
+var agentDefinition = new PromptAgentDefinition(model: deploymentName) { Instructions = JokerInstructions };
+
+// Azure.AI.Agents SDK creates and manages agent by name and versions.
+// You can create a server side agent version with the Azure.AI.Agents SDK client below.
+var agentVersion = agentsClient.CreateAgentVersion(agentName: JokerName, definition: agentDefinition);
+
+// Note:
+//      agentVersion.Id = "<agentName>:<versionNumber>",
+//      agentVersion.Version = <versionNumber>,
+//      agentVersion.Name = <agentName>
+
+// You can retrieve an AIAgent for a already created server side agent version.
+AIAgent jokerAgentV1 = agentsClient.GetAIAgent(agentVersion);
+
+// You can also create another AIAgent version (V2) by providing the same name with a different definition.
+AIAgent jokerAgentV2 = agentsClient.CreateAIAgent(name: JokerName, model: deploymentName, instructions: JokerInstructions + "V2");
+
+// You can also get the AIAgent latest version just providing its name.
+AIAgent jokerAgentLatest = agentsClient.GetAIAgent(name: JokerName);
+var latestVersion = jokerAgentLatest.GetService<AgentVersion>()!;
+
+// The AIAgent version can be accessed via the GetService method.
+Console.WriteLine($"Latest agent version id: {latestVersion.Id}");
+
+// Once you have the AIAgent, you can invoke it like any other AIAgent.
+AgentThread thread = jokerAgentLatest.GetNewThread();
+Console.WriteLine(await jokerAgentLatest.RunAsync("Tell me a joke about a pirate.", thread));
+
+// This will use the same thread to continue the conversation.
+Console.WriteLine(await jokerAgentLatest.RunAsync("Now tell me a joke about a cat and a dog using last joke as the anchor.", thread));
+
+// Cleanup by agent name removes both agent versions created (jokerAgentV1 + jokerAgentV2).
+agentsClient.DeleteAgent(jokerAgentV1.Name);
+
+// It is also possible delete just a specific agent version by the composition (name + version number).
+// agentsClient.DeleteAgentVersion(latestVersion.Name, latestVersion.Version);

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step01.1_Basics/README.md

@@ -0,0 +1,16 @@
+# Prerequisites
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 8.0 SDK or later
+- Azure Foundry service endpoint and deployment configured
+- Azure CLI installed and authenticated (for Azure credential authentication)
+
+**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+
+Set the following environment variables:
+
+```powershell
+$env:AZURE_FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
+$env:AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+```

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step01.2_Running/AzureAIAgents_Step01.2_Running.csproj

@@ -0,0 +1,20 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step01.2_Running/Program.cs

@@ -0,0 +1,40 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with Azure Foundry Agents as the backend.
+
+using Azure.AI.Agents;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string JokerInstructions = "You are good at telling jokes.";
+const string JokerName = "JokerAgent";
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
+
+// Define the agent you want to create. (Prompt Agent in this case)
+var agentDefinition = new PromptAgentDefinition(model: deploymentName) { Instructions = JokerInstructions };
+
+// Azure.AI.Agents SDK creates and manages agent by name and versions.
+// You can create a server side agent version with the Azure.AI.Agents SDK client below.
+var agentVersion = agentsClient.CreateAgentVersion(agentName: JokerName, definition: agentDefinition);
+
+// You can retrieve an AIAgent for a already created server side agent version.
+AIAgent jokerAgent = agentsClient.GetAIAgent(agentVersion);
+
+// Invoke the agent and output the text result.
+AgentThread thread = jokerAgent.GetNewThread();
+Console.WriteLine(await jokerAgent.RunAsync("Tell me a joke about a pirate.", thread));
+
+// Invoke the agent with streaming support.
+thread = jokerAgent.GetNewThread();
+await foreach (var update in jokerAgent.RunStreamingAsync("Tell me a joke about a pirate.", thread))
+{
+    Console.WriteLine(update);
+}
+
+// Cleanup by agent name removes the agent version created.
+agentsClient.DeleteAgent(jokerAgent.Name);

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step02_MultiturnConversation/AzureAIAgents_Step02_MultiturnConversation.csproj

@@ -0,0 +1,20 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step02_MultiturnConversation/Program.cs

@@ -0,0 +1,44 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with a multi-turn conversation.
+
+using Azure.AI.Agents;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string JokerInstructions = "You are good at telling jokes.";
+const string JokerName = "JokerAgent";
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
+
+// Define the agent you want to create. (Prompt Agent in this case)
+var agentDefinition = new PromptAgentDefinition(model: deploymentName) { Instructions = JokerInstructions };
+
+// Create a server side agent version with the Azure.AI.Agents SDK client.
+var agentVersion = agentsClient.CreateAgentVersion(agentName: JokerName, definition: agentDefinition);
+
+// Retrieve an AIAgent for the created server side agent version.
+AIAgent jokerAgent = agentsClient.GetAIAgent(agentVersion);
+
+// Invoke the agent with a multi-turn conversation, where the context is preserved in the thread object.
+AgentThread thread = jokerAgent.GetNewThread();
+Console.WriteLine(await jokerAgent.RunAsync("Tell me a joke about a pirate.", thread));
+Console.WriteLine(await jokerAgent.RunAsync("Now add some emojis to the joke and tell it in the voice of a pirate's parrot.", thread));
+
+// Invoke the agent with a multi-turn conversation and streaming, where the context is preserved in the thread object.
+thread = jokerAgent.GetNewThread();
+await foreach (var update in jokerAgent.RunStreamingAsync("Tell me a joke about a pirate.", thread))
+{
+    Console.WriteLine(update);
+}
+await foreach (var update in jokerAgent.RunStreamingAsync("Now add some emojis to the joke and tell it in the voice of a pirate's parrot.", thread))
+{
+    Console.WriteLine(update);
+}
+
+// Cleanup by agent name removes the agent version created.
+agentsClient.DeleteAgent(jokerAgent.Name);

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step03.1_UsingFunctionTools/AzureAIAgents_Step03.1_UsingFunctionTools.csproj

@@ -0,0 +1,21 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step03.1_UsingFunctionTools/Program.cs

@@ -0,0 +1,43 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to use an agent with function tools.
+// It shows both non-streaming and streaming agent interactions using weather-related tools.
+
+using System.ComponentModel;
+using Azure.AI.Agents;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+[Description("Get the weather for a given location.")]
+static string GetWeather([Description("The location to get the weather for.")] string location)
+    => $"The weather in {location} is cloudy with a high of 15°C.";
+
+const string AssistantInstructions = "You are a helpful assistant that can get weather information.";
+const string AssistantName = "WeatherAssistant";
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
+
+// Define the agent with function tools.
+var tool = AIFunctionFactory.Create(GetWeather);
+
+// Create AIAgent directly
+AIAgent agent = await agentsClient.CreateAIAgentAsync(name: AssistantName, model: deploymentName, instructions: AssistantInstructions, tools: [tool]);
+
+// Non-streaming agent interaction with function tools.
+AgentThread thread = agent.GetNewThread();
+Console.WriteLine(await agent.RunAsync("What is the weather like in Amsterdam?", thread));
+
+// Streaming agent interaction with function tools.
+thread = agent.GetNewThread();
+await foreach (var update in agent.RunStreamingAsync("What is the weather like in Amsterdam?", thread))
+{
+    Console.WriteLine(update);
+}
+
+// Cleanup by agent name removes the agent version created.
+agentsClient.DeleteAgent(agent.Name);

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step03.2_UsingFunctionTools_FromOpenAPI/AzureAIAgents_Step03.2_UsingFunctionTools_FromOpenAPI.csproj

@@ -0,0 +1,28 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.SemanticKernel.Plugins.OpenApi" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <None Update="OpenAPISpec.json">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step03.2_UsingFunctionTools_FromOpenAPI/OpenAPISpec.json

@@ -0,0 +1,354 @@
+{
+    "openapi": "3.0.1",
+    "info": {
+        "title": "Github Versions API",
+        "version": "1.0.0"
+    },
+    "servers": [
+        {
+            "url": "https://api.github.com"
+        }
+    ],
+    "components": {
+        "schemas": {
+            "basic-error": {
+                "title": "Basic Error",
+                "description": "Basic Error",
+                "type": "object",
+                "properties": {
+                    "message": {
+                        "type": "string"
+                    },
+                    "documentation_url": {
+                        "type": "string"
+                    },
+                    "url": {
+                        "type": "string"
+                    },
+                    "status": {
+                        "type": "string"
+                    }
+                }
+            },
+            "label": {
+                "title": "Label",
+                "description": "Color-coded labels help you categorize and filter your issues (just like labels in Gmail).",
+                "type": "object",
+                "properties": {
+                    "id": {
+                        "description": "Unique identifier for the label.",
+                        "type": "integer",
+                        "format": "int64",
+                        "example": 208045946
+                    },
+                    "node_id": {
+                        "type": "string",
+                        "example": "MDU6TGFiZWwyMDgwNDU5NDY="
+                    },
+                    "url": {
+                        "description": "URL for the label",
+                        "example": "https://api.github.com/repositories/42/labels/bug",
+                        "type": "string",
+                        "format": "uri"
+                    },
+                    "name": {
+                        "description": "The name of the label.",
+                        "example": "bug",
+                        "type": "string"
+                    },
+                    "description": {
+                        "description": "Optional description of the label, such as its purpose.",
+                        "type": "string",
+                        "example": "Something isn't working",
+                        "nullable": true
+                    },
+                    "color": {
+                        "description": "6-character hex code, without the leading #, identifying the color",
+                        "example": "FFFFFF",
+                        "type": "string"
+                    },
+                    "default": {
+                        "description": "Whether this label comes by default in a new repository.",
+                        "type": "boolean",
+                        "example": true
+                    }
+                },
+                "required": [
+                    "id",
+                    "node_id",
+                    "url",
+                    "name",
+                    "description",
+                    "color",
+                    "default"
+                ]
+            },
+            "tag": {
+                "title": "Tag",
+                "description": "Tag",
+                "type": "object",
+                "properties": {
+                    "name": {
+                        "type": "string",
+                        "example": "v0.1"
+                    },
+                    "commit": {
+                        "type": "object",
+                        "properties": {
+                            "sha": {
+                                "type": "string"
+                            },
+                            "url": {
+                                "type": "string",
+                                "format": "uri"
+                            }
+                        },
+                        "required": [
+                            "sha",
+                            "url"
+                        ]
+                    },
+                    "zipball_url": {
+                        "type": "string",
+                        "format": "uri",
+                        "example": "https://github.com/octocat/Hello-World/zipball/v0.1"
+                    },
+                    "tarball_url": {
+                        "type": "string",
+                        "format": "uri",
+                        "example": "https://github.com/octocat/Hello-World/tarball/v0.1"
+                    },
+                    "node_id": {
+                        "type": "string"
+                    }
+                },
+                "required": [
+                    "name",
+                    "node_id",
+                    "commit",
+                    "zipball_url",
+                    "tarball_url"
+                ]
+            }
+        },
+        "examples": {
+            "label-items": {
+                "value": [
+                    {
+                        "id": 208045946,
+                        "node_id": "MDU6TGFiZWwyMDgwNDU5NDY=",
+                        "url": "https://api.github.com/repos/octocat/Hello-World/labels/bug",
+                        "name": "bug",
+                        "description": "Something isn't working",
+                        "color": "f29513",
+                        "default": true
+                    },
+                    {
+                        "id": 208045947,
+                        "node_id": "MDU6TGFiZWwyMDgwNDU5NDc=",
+                        "url": "https://api.github.com/repos/octocat/Hello-World/labels/enhancement",
+                        "name": "enhancement",
+                        "description": "New feature or request",
+                        "color": "a2eeef",
+                        "default": false
+                    }
+                ]
+            },
+            "tag-items": {
+                "value": [
+                    {
+                        "name": "v0.1",
+                        "commit": {
+                            "sha": "c5b97d5ae6c19d5c5df71a34c7fbeeda2479ccbc",
+                            "url": "https://api.github.com/repos/octocat/Hello-World/commits/c5b97d5ae6c19d5c5df71a34c7fbeeda2479ccbc"
+                        },
+                        "zipball_url": "https://github.com/octocat/Hello-World/zipball/v0.1",
+                        "tarball_url": "https://github.com/octocat/Hello-World/tarball/v0.1",
+                        "node_id": "MDQ6VXNlcjE="
+                    }
+                ]
+            }
+        },
+        "parameters": {
+            "owner": {
+                "name": "owner",
+                "description": "The account owner of the repository. The name is not case sensitive.",
+                "in": "path",
+                "required": true,
+                "schema": {
+                    "type": "string"
+                }
+            },
+            "repo": {
+                "name": "repo",
+                "description": "The name of the repository without the `.git` extension. The name is not case sensitive.",
+                "in": "path",
+                "required": true,
+                "schema": {
+                    "type": "string"
+                }
+            },
+            "per-page": {
+                "name": "per_page",
+                "description": "The number of results per page (max 100). For more information, see \"[Using pagination in the REST API](https://docs.github.com/rest/using-the-rest-api/using-pagination-in-the-rest-api).\"",
+                "in": "query",
+                "schema": {
+                    "type": "integer",
+                    "default": 30
+                }
+            },
+            "page": {
+                "name": "page",
+                "description": "The page number of the results to fetch. For more information, see \"[Using pagination in the REST API](https://docs.github.com/rest/using-the-rest-api/using-pagination-in-the-rest-api).\"",
+                "in": "query",
+                "schema": {
+                    "type": "integer",
+                    "default": 1
+                }
+            }
+        },
+        "responses": {
+            "not_found": {
+                "description": "Resource not found",
+                "content": {
+                    "application/json": {
+                        "schema": {
+                            "$ref": "#/components/schemas/basic-error"
+                        }
+                    }
+                }
+            }
+        },
+        "headers": {
+            "link": {
+                "example": "<https://api.github.com/resource?page=2>; rel=\"next\", <https://api.github.com/resource?page=5>; rel=\"last\"",
+                "schema": {
+                    "type": "string"
+                }
+            }
+        }
+    },
+    "paths": {
+        "/repos/{owner}/{repo}/tags": {
+            "get": {
+                "summary": "List repository tags",
+                "description": "",
+                "tags": [
+                    "repos"
+                ],
+                "operationId": "repos/list-tags",
+                "externalDocs": {
+                    "description": "API method documentation",
+                    "url": "https://docs.github.com/rest/repos/repos#list-repository-tags"
+                },
+                "parameters": [
+                    {
+                        "$ref": "#/components/parameters/owner"
+                    },
+                    {
+                        "$ref": "#/components/parameters/repo"
+                    },
+                    {
+                        "$ref": "#/components/parameters/per-page"
+                    },
+                    {
+                        "$ref": "#/components/parameters/page"
+                    }
+                ],
+                "responses": {
+                    "200": {
+                        "description": "Response",
+                        "content": {
+                            "application/json": {
+                                "schema": {
+                                    "type": "array",
+                                    "items": {
+                                        "$ref": "#/components/schemas/tag"
+                                    }
+                                },
+                                "examples": {
+                                    "default": {
+                                        "$ref": "#/components/examples/tag-items"
+                                    }
+                                }
+                            }
+                        },
+                        "headers": {
+                            "Link": {
+                                "$ref": "#/components/headers/link"
+                            }
+                        }
+                    }
+                },
+                "x-github": {
+                    "githubCloudOnly": false,
+                    "enabledForGitHubApps": true,
+                    "category": "repos",
+                    "subcategory": "repos"
+                }
+            }
+        },
+        "/repos/{owner}/{repo}/labels": {
+            "get": {
+                "summary": "List labels for a repository",
+                "description": "Lists all labels for a repository.",
+                "tags": [
+                    "issues"
+                ],
+                "operationId": "issues/list-labels-for-repo",
+                "externalDocs": {
+                    "description": "API method documentation",
+                    "url": "https://docs.github.com/rest/issues/labels#list-labels-for-a-repository"
+                },
+                "parameters": [
+                    {
+                        "$ref": "#/components/parameters/owner"
+                    },
+                    {
+                        "$ref": "#/components/parameters/repo"
+                    },
+                    {
+                        "$ref": "#/components/parameters/per-page"
+                    },
+                    {
+                        "$ref": "#/components/parameters/page"
+                    }
+                ],
+                "responses": {
+                    "200": {
+                        "description": "Response",
+                        "content": {
+                            "application/json": {
+                                "schema": {
+                                    "type": "array",
+                                    "items": {
+                                        "$ref": "#/components/schemas/label"
+                                    }
+                                },
+                                "examples": {
+                                    "default": {
+                                        "$ref": "#/components/examples/label-items"
+                                    }
+                                }
+                            }
+                        },
+                        "headers": {
+                            "Link": {
+                                "$ref": "#/components/headers/link"
+                            }
+                        }
+                    },
+                    "404": {
+                        "$ref": "#/components/responses/not_found"
+                    }
+                },
+                "x-github": {
+                    "githubCloudOnly": false,
+                    "enabledForGitHubApps": true,
+                    "category": "issues",
+                    "subcategory": "labels"
+                }
+            }
+        }
+    }
+}

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step03.2_UsingFunctionTools_FromOpenAPI/Program.cs

@@ -0,0 +1,38 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to use an agent with function tools provided via an OpenAPI spec.
+// It uses functionality from Semantic Kernel to parse the OpenAPI spec and create function tools to use with the Agent Framework Agent.
+
+using Azure.AI.Agents;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+using Microsoft.SemanticKernel;
+using Microsoft.SemanticKernel.Plugins.OpenApi;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+// Load the OpenAPI Spec from a file.
+KernelPlugin plugin = await OpenApiKernelPluginFactory.CreateFromOpenApiAsync("github", "OpenAPISpec.json");
+
+// Convert the Semantic Kernel plugin to Agent Framework function tools.
+// This requires a dummy Kernel instance, since KernelFunctions cannot execute without one.
+Kernel kernel = new();
+List<AITool> tools = plugin.Select(x => x.WithKernel(kernel)).Cast<AITool>().ToList();
+
+const string AssistantInstructions = "You are a helpful assistant that can query GitHub repositories.";
+const string AssistantName = "GitHubAssistant";
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
+
+// Create AIAgent directly
+AIAgent agent = await agentsClient.CreateAIAgentAsync(name: AssistantName, model: deploymentName, instructions: AssistantInstructions, tools: tools);
+
+// Run the agent with the OpenAPI function tools.
+AgentThread thread = agent.GetNewThread();
+Console.WriteLine(await agent.RunAsync("Please list the names, colors and descriptions of all the labels available in the microsoft/agent-framework repository on github.", thread));
+
+// Cleanup by agent name removes the agent version created.
+agentsClient.DeleteAgent(agent.Name);

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step04_UsingFunctionToolsWithApprovals/AzureAIAgents_Step04_UsingFunctionToolsWithApprovals.csproj

@@ -0,0 +1,21 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step04_UsingFunctionToolsWithApprovals/Program.cs

@@ -0,0 +1,64 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to use an agent with function tools that require a human in the loop for approvals.
+// It shows both non-streaming and streaming agent interactions using weather-related tools.
+// If the agent is hosted in a service, with a remote user, combine this sample with the Persisted Conversations sample to persist the chat history
+// while the agent is waiting for user input.
+
+using System.ComponentModel;
+using Azure.AI.Agents;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+// Create a sample function tool that the agent can use.
+[Description("Get the weather for a given location.")]
+static string GetWeather([Description("The location to get the weather for.")] string location)
+    => $"The weather in {location} is cloudy with a high of 15°C.";
+
+const string AssistantInstructions = "You are a helpful assistant that can get weather information.";
+const string AssistantName = "WeatherAssistant";
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
+
+var approvalTool = new ApprovalRequiredAIFunction(AIFunctionFactory.Create(GetWeather));
+
+// Create AIAgent directly
+AIAgent agent = await agentsClient.CreateAIAgentAsync(name: AssistantName, model: deploymentName, instructions: AssistantInstructions, tools: [approvalTool]);
+
+// Call the agent with approval-required function tools.
+// The agent will request approval before invoking the function.
+AgentThread thread = agent.GetNewThread();
+var response = await agent.RunAsync("What is the weather like in Amsterdam?", thread);
+
+// Check if there are any user input requests (approvals needed).
+var userInputRequests = response.UserInputRequests.ToList();
+
+while (userInputRequests.Count > 0)
+{
+    // Ask the user to approve each function call request.
+    // For simplicity, we are assuming here that only function approval requests are being made.
+    var userInputMessages = userInputRequests
+        .OfType<FunctionApprovalRequestContent>()
+        .Select(functionApprovalRequest =>
+        {
+            Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {functionApprovalRequest.FunctionCall.Name}");
+            var approved = Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false;
+            return new ChatMessage(ChatRole.User, [functionApprovalRequest.CreateResponse(approved)]);
+        })
+        .ToList();
+
+    // Pass the user input responses back to the agent for further processing.
+    response = await agent.RunAsync(userInputMessages, thread);
+
+    userInputRequests = response.UserInputRequests.ToList();
+}
+
+Console.WriteLine($"\nAgent: {response}");
+
+// Cleanup by agent name removes the agent version created.
+agentsClient.DeleteAgent(agent.Name);

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step05_StructuredOutput/AzureAIAgents_Step05_StructuredOutput.csproj

@@ -0,0 +1,21 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step05_StructuredOutput/Program.cs

@@ -0,0 +1,79 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to configure an agent to produce structured output.
+
+using System.ComponentModel;
+using System.Text.Json;
+using System.Text.Json.Serialization;
+using Azure.AI.Agents;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using SampleApp;
+
+#pragma warning disable CA5399
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = "gpt-5"; // Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string AssistantInstructions = "You are a helpful assistant that extracts structured information about people.";
+const string AssistantName = "StructuredOutputAssistant";
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
+
+// Create ChatClientAgent directly
+ChatClientAgent agent = await agentsClient.CreateAIAgentAsync(
+    model: deploymentName,
+    new ChatClientAgentOptions(name: AssistantName, instructions: AssistantInstructions));
+
+// Set PersonInfo as the type parameter of RunAsync method to specify the expected structured output from the agent and invoke the agent with some unstructured input.
+AgentRunResponse<PersonInfo> response = await agent.RunAsync<PersonInfo>("Please provide information about John Smith, who is a 35-year-old software engineer.");
+
+// Access the structured output via the Result property of the agent response.
+Console.WriteLine("Assistant Output:");
+Console.WriteLine($"Name: {response.Result.Name}");
+Console.WriteLine($"Age: {response.Result.Age}");
+Console.WriteLine($"Occupation: {response.Result.Occupation}");
+
+// Create the ChatClientAgent with the specified name, instructions, and expected structured output the agent should produce.
+ChatClientAgent agentWithPersonInfo = agentsClient.CreateAIAgent(model: deploymentName, new ChatClientAgentOptions(name: AssistantName, instructions: AssistantInstructions)
+{
+    ChatOptions = new()
+    {
+        ResponseFormat = Microsoft.Extensions.AI.ChatResponseFormat.ForJsonSchema<PersonInfo>()
+    }
+});
+
+// Invoke the agent with some unstructured input while streaming, to extract the structured information from.
+var updates = agentWithPersonInfo.RunStreamingAsync("Please provide information about John Smith, who is a 35-year-old software engineer.");
+
+// Assemble all the parts of the streamed output, since we can only deserialize once we have the full json,
+// then deserialize the response into the PersonInfo class.
+PersonInfo personInfo = (await updates.ToAgentRunResponseAsync()).Deserialize<PersonInfo>(JsonSerializerOptions.Web);
+
+Console.WriteLine("Assistant Output:");
+Console.WriteLine($"Name: {personInfo.Name}");
+Console.WriteLine($"Age: {personInfo.Age}");
+Console.WriteLine($"Occupation: {personInfo.Occupation}");
+
+// Cleanup by agent name removes the agent version created.
+agentsClient.DeleteAgent(agent.Name);
+
+namespace SampleApp
+{
+    /// <summary>
+    /// Represents information about a person, including their name, age, and occupation, matched to the JSON schema used in the agent.
+    /// </summary>
+    [Description("Information about a person including their name, age, and occupation")]
+    public class PersonInfo
+    {
+        [JsonPropertyName("name")]
+        public string? Name { get; set; }
+
+        [JsonPropertyName("age")]
+        public int? Age { get; set; }
+
+        [JsonPropertyName("occupation")]
+        public string? Occupation { get; set; }
+    }
+}

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step06_PersistedConversations/AzureAIAgents_Step06_PersistedConversations.csproj

@@ -0,0 +1,20 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step06_PersistedConversations/Program.cs

@@ -0,0 +1,44 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with a conversation that can be persisted to disk.
+
+using System.Text.Json;
+using Azure.AI.Agents;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string JokerInstructions = "You are good at telling jokes.";
+const string JokerName = "JokerAgent";
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
+
+AIAgent agent = await agentsClient.CreateAIAgentAsync(name: JokerName, model: deploymentName, instructions: JokerInstructions);
+
+// Start a new thread for the agent conversation.
+AgentThread thread = agent.GetNewThread();
+
+// Run the agent with a new thread.
+Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", thread));
+
+// Serialize the thread state to a JsonElement, so it can be stored for later use.
+JsonElement serializedThread = thread.Serialize();
+
+// Save the serialized thread to a temporary file (for demonstration purposes).
+string tempFilePath = Path.GetTempFileName();
+await File.WriteAllTextAsync(tempFilePath, JsonSerializer.Serialize(serializedThread));
+
+// Load the serialized thread from the temporary file (for demonstration purposes).
+JsonElement reloadedSerializedThread = JsonSerializer.Deserialize<JsonElement>(await File.ReadAllTextAsync(tempFilePath));
+
+// Deserialize the thread state after loading from storage.
+AgentThread resumedThread = agent.DeserializeThread(reloadedSerializedThread);
+
+// Run the agent again with the resumed thread.
+Console.WriteLine(await agent.RunAsync("Now tell the same joke in the voice of a pirate, and add some emojis to the joke.", resumedThread));
+
+// Cleanup by agent name removes the agent version created.
+agentsClient.DeleteAgent(agent.Name);

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step07_Observability/AzureAIAgents_Step07_Observability.csproj

@@ -0,0 +1,23 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Azure.Monitor.OpenTelemetry.Exporter" />
+    <PackageReference Include="OpenTelemetry" />
+    <PackageReference Include="OpenTelemetry.Exporter.Console" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step07_Observability/Program.cs

@@ -0,0 +1,52 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with Azure Foundry Agents as the backend that logs telemetry using OpenTelemetry.
+
+using Azure.AI.Agents;
+using Azure.Identity;
+using Azure.Monitor.OpenTelemetry.Exporter;
+using Microsoft.Agents.AI;
+using OpenTelemetry;
+using OpenTelemetry.Trace;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var applicationInsightsConnectionString = Environment.GetEnvironmentVariable("APPLICATIONINSIGHTS_CONNECTION_STRING");
+
+const string JokerInstructions = "You are good at telling jokes.";
+const string JokerName = "JokerAgent";
+
+// Create TracerProvider with console exporter
+// This will output the telemetry data to the console.
+string sourceName = Guid.NewGuid().ToString("N");
+var tracerProviderBuilder = Sdk.CreateTracerProviderBuilder()
+    .AddSource(sourceName)
+    .AddConsoleExporter();
+if (!string.IsNullOrWhiteSpace(applicationInsightsConnectionString))
+{
+    tracerProviderBuilder.AddAzureMonitorTraceExporter(options => options.ConnectionString = applicationInsightsConnectionString);
+}
+using var tracerProvider = tracerProviderBuilder.Build();
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
+
+// Define the agent you want to create. (Prompt Agent in this case)
+AIAgent agent = agentsClient.CreateAIAgent(name: JokerName, model: deploymentName, instructions: JokerInstructions)
+    .AsBuilder()
+    .UseOpenTelemetry(sourceName: sourceName)
+    .Build();
+
+// Invoke the agent and output the text result.
+AgentThread thread = agent.GetNewThread();
+Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", thread));
+
+// Invoke the agent with streaming support.
+thread = agent.GetNewThread();
+await foreach (var update in agent.RunStreamingAsync("Tell me a joke about a pirate.", thread))
+{
+    Console.WriteLine(update);
+}
+
+// Cleanup by agent name removes the agent version created.
+agentsClient.DeleteAgent(agent.Name);

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step08_DependencyInjection/AzureAIAgents_Step08_DependencyInjection.csproj

@@ -0,0 +1,21 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.Hosting" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step08_DependencyInjection/Program.cs

@@ -0,0 +1,80 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+#pragma warning disable CA1812
+
+// This sample shows how to use dependency injection to register an AIAgent and use it from a hosted service with a user input chat loop.
+
+using Azure.AI.Agents;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.DependencyInjection;
+using Microsoft.Extensions.Hosting;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string JokerInstructions = "You are good at telling jokes.";
+const string JokerName = "JokerAgent";
+
+// Create a host builder that we will register services with and then run.
+HostApplicationBuilder builder = Host.CreateApplicationBuilder(args);
+
+// Add the agents client to the service collection.
+builder.Services.AddSingleton((sp) => new AgentsClient(new Uri(endpoint), new AzureCliCredential()));
+
+// Add the AI agent to the service collection.
+builder.Services.AddSingleton<AIAgent>((sp)
+    => sp.GetRequiredService<AgentsClient>()
+        .CreateAIAgent(name: JokerName, model: deploymentName, instructions: JokerInstructions));
+
+// Add a sample service that will use the agent to respond to user input.
+builder.Services.AddHostedService<SampleService>();
+
+// Build and run the host.
+using IHost host = builder.Build();
+await host.RunAsync().ConfigureAwait(false);
+
+/// <summary>
+/// A sample service that uses an AI agent to respond to user input.
+/// </summary>
+internal sealed class SampleService(AIAgent agent, IHostApplicationLifetime appLifetime) : IHostedService
+{
+    private AgentThread? _thread;
+
+    public async Task StartAsync(CancellationToken cancellationToken)
+    {
+        // Create a thread that will be used for the entirety of the service lifetime so that the user can ask follow up questions.
+        this._thread = agent.GetNewThread();
+        _ = this.RunAsync(appLifetime.ApplicationStopping);
+    }
+
+    public async Task RunAsync(CancellationToken cancellationToken)
+    {
+        // Delay a little to allow the service to finish starting.
+        await Task.Delay(100, cancellationToken);
+
+        while (!cancellationToken.IsCancellationRequested)
+        {
+            Console.WriteLine("\nAgent: Ask me to tell you a joke about a specific topic. To exit just press Ctrl+C or enter without any input.\n");
+            Console.Write("> ");
+            var input = Console.ReadLine();
+
+            // If the user enters no input, signal the application to shut down.
+            if (string.IsNullOrWhiteSpace(input))
+            {
+                appLifetime.StopApplication();
+                break;
+            }
+
+            // Stream the output to the console as it is generated.
+            await foreach (var update in agent.RunStreamingAsync(input, this._thread, cancellationToken: cancellationToken))
+            {
+                Console.Write(update);
+            }
+
+            Console.WriteLine();
+        }
+    }
+
+    public Task StopAsync(CancellationToken cancellationToken) => Task.CompletedTask;
+}

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step09_AsMcpTool/AzureAIAgents_Step09_AsMcpTool.csproj

@@ -0,0 +1,25 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <UserSecretsId>3afc9b74-af74-4d8e-ae96-fa1c511d11ac</UserSecretsId>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents.Persistent" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.Hosting" />
+    <PackageReference Include="ModelContextProtocol" />
+    <PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
+  </ItemGroup>
+  
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step09_AsMcpTool/Program.cs

@@ -0,0 +1,42 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to expose an AI agent as an MCP tool.
+
+using Azure.AI.Agents;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.DependencyInjection;
+using Microsoft.Extensions.Hosting;
+using ModelContextProtocol.Server;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string JokerInstructions = "You are good at telling jokes, and you always start each joke with 'Aye aye, captain!'.";
+const string JokerName = "JokerAgent";
+const string JokerDescription = "An agent that tells jokes.";
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
+
+// Define the agent you want to create. (Prompt Agent in this case)
+AIAgent agent = agentsClient.CreateAIAgent(
+    name: JokerName,
+    model: deploymentName,
+    instructions: JokerInstructions,
+    creationOptions: new() { Description = JokerDescription });
+
+// Convert the agent to an AIFunction and then to an MCP tool.
+// The agent name and description will be used as the mcp tool name and description.
+McpServerTool tool = McpServerTool.Create(agent.AsAIFunction());
+
+// Register the MCP server with StdIO transport and expose the tool via the server.
+HostApplicationBuilder builder = Host.CreateEmptyApplicationBuilder(settings: null);
+builder.Services
+    .AddMcpServer()
+    .WithStdioServerTransport()
+    .WithTools([tool]);
+
+Console.WriteLine("Starting MCP Tool server. Press Ctrl+C to exit.");
+
+await builder.Build().RunAsync();

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step09_AsMcpTool/README.md

@@ -0,0 +1,29 @@
+This sample demonstrates how to expose an existing AI agent as an MCP tool.
+
+## Run the sample
+
+To run the sample, please use one of the following MCP clients: https://modelcontextprotocol.io/clients
+
+Alternatively, use the QuickstartClient sample from this repository: https://github.com/modelcontextprotocol/csharp-sdk/tree/main/samples/QuickstartClient
+
+## Run the sample using MCP Inspector
+
+To use the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector), follow these steps:
+
+1. Open a terminal in the Agent_Step10_AsMcpTool project directory.
+1. Run the `npx @modelcontextprotocol/inspector dotnet run` command to start the MCP Inspector. Make sure you have [node.js](https://nodejs.org/en/download/) and npm installed.
+   ```bash
+   npx @modelcontextprotocol/inspector dotnet run
+   ```
+1. When the inspector is running, it will display a URL in the terminal, like this:
+   ```
+   MCP Inspector is up and running at http://127.0.0.1:6274
+   ```
+1. Open a web browser and navigate to the URL displayed in the terminal. If not opened automatically, this will open the MCP Inspector interface.
+1. In the MCP Inspector interface, add the following environment variables to allow your MCP server to access Azure AI Foundry Project to create and run the agent:
+    - AZURE_FOUNDRY_PROJECT_ENDPOINT = https://your-resource.openai.azure.com/ # Replace with your Azure AI Foundry Project endpoint
+    - AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME = gpt-4o-mini # Replace with your model deployment name
+1. Find and click the `Connect` button in the MCP Inspector interface to connect to the MCP server.
+1. As soon as the connection is established, open the `Tools` tab in the MCP Inspector interface and select the `Joker` tool from the list.
+1. Specify your prompt as a value for the `query` argument, for example: `Tell me a joke about a pirate` and click the `Run Tool` button to run the tool.
+1. The agent will process the request and return a response in accordance with the provided instructions that instruct it to always start each joke with 'Aye aye, captain!'.

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step10_UsingImages/AzureAIAgents_Step10_UsingImages.csproj

@@ -0,0 +1,20 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+  </ItemGroup>
+  
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step10_UsingImages/Program.cs

@@ -0,0 +1,35 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to use Image Multi-Modality with an AI agent.
+
+using Azure.AI.Agents;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = System.Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o";
+
+const string VisionInstructions = "You are a helpful agent that can analyze images";
+const string VisionName = "VisionAgent";
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
+
+// Define the agent you want to create. (Prompt Agent in this case)
+AIAgent agent = agentsClient.CreateAIAgent(name: VisionName, model: deploymentName, instructions: VisionInstructions);
+
+ChatMessage message = new(ChatRole.User, [
+    new TextContent("What do you see in this image?"),
+    new UriContent("https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg", "image/jpeg")
+]);
+
+var thread = agent.GetNewThread();
+
+await foreach (var update in agent.RunStreamingAsync(message, thread))
+{
+    Console.WriteLine(update);
+}
+
+// Cleanup by agent name removes the agent version created.
+agentsClient.DeleteAgent(agent.Name);

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step10_UsingImages/README.md

@@ -0,0 +1,52 @@
+# Using Images with AI Agents
+
+This sample demonstrates how to use image multi-modality with an AI agent. It shows how to create a vision-enabled agent that can analyze and describe images using Azure OpenAI.
+
+## What this sample demonstrates
+
+- Creating a persistent AI agent with vision capabilities
+- Sending both text and image content to an agent in a single message
+- Using `UriContent` to Uri referenced images
+- Processing multimodal input (text + image) with an AI agent
+
+## Key features
+
+- **Vision Agent**: Creates an agent specifically instructed to analyze images
+- **Multimodal Input**: Combines text questions with image uri in a single message
+- **Azure OpenAI Integration**: Uses AzureOpenAI LLM agents
+
+## Prerequisites
+
+Before running this sample, ensure you have:
+
+1. An Azure OpenAI project set up
+2. A compatible model deployment (e.g., gpt-4o)
+3. Azure CLI installed and authenticated
+
+## Environment Variables
+
+Set the following environment variables:
+
+```powershell
+$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI endpoint
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o" # Replace with your model deployment name (optional, defaults to gpt-4o)
+```
+
+## Run the sample
+
+Navigate to the sample directory and run:
+
+```powershell
+cd Agent_Step11_UsingImages
+dotnet run
+```
+
+## Expected behavior
+
+The sample will:
+
+1. Create a vision-enabled agent named "VisionAgent"
+2. Send a message containing both text ("What do you see in this image?") and a Uri image of a green walk
+3. The agent will analyze the image and provide a description
+4. Clean up resources by deleting the thread and agent
+

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step11_AsFunctionTool/AzureAIAgents_Step11_AsFunctionTool.csproj

@@ -0,0 +1,22 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <UserSecretsId>3afc9b74-af74-4d8e-ae96-fa1c511d11ac</UserSecretsId>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
+  </ItemGroup>
+  
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step11_AsFunctionTool/Program.cs

@@ -0,0 +1,47 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use an Azure Foundry Agents AI agent as a function tool.
+
+using System.ComponentModel;
+using Azure.AI.Agents;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string WeatherInstructions = "You answer questions about the weather.";
+const string WeatherName = "WeatherAgent";
+const string MainInstructions = "You are a helpful assistant who responds in French.";
+const string MainName = "MainAgent";
+
+[Description("Get the weather for a given location.")]
+static string GetWeather([Description("The location to get the weather for.")] string location)
+    => $"The weather in {location} is cloudy with a high of 15°C.";
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
+
+// Create the weather agent with function tools.
+var weatherTool = AIFunctionFactory.Create(GetWeather);
+AIAgent weatherAgent = agentsClient.CreateAIAgent(
+    name: WeatherName,
+    model: deploymentName,
+    instructions: WeatherInstructions,
+    tools: [weatherTool]);
+
+// Create the main agent, and provide the weather agent as a function tool.
+AIAgent agent = agentsClient.CreateAIAgent(
+    name: MainName,
+    model: deploymentName,
+    instructions: MainInstructions,
+    tools: [weatherAgent.AsAIFunction()]);
+
+// Invoke the agent and output the text result.
+AgentThread thread = agent.GetNewThread();
+Console.WriteLine(await agent.RunAsync("What is the weather like in Amsterdam?", thread));
+
+// Cleanup by agent name removes the agent versions created.
+agentsClient.DeleteAgent(agent.Name);
+agentsClient.DeleteAgent(weatherAgent.Name);

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step12_Middleware/AzureAIAgents_Step12_Middleware.csproj

@@ -0,0 +1,22 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Extensions.Logging.Console" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Azure.AI.Agents" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step12_Middleware/Program.cs

@@ -0,0 +1,222 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows multiple middleware layers working together with Azure Foundry Agents:
+// agent run (PII filtering and guardrails),
+// function invocation (logging and result overrides), and human-in-the-loop
+// approval workflows for sensitive function calls.
+
+using System.ComponentModel;
+using System.Text.RegularExpressions;
+using Azure.AI.Agents;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+
+// Get Azure AI Foundry configuration from environment variables
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = System.Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o";
+
+const string AssistantInstructions = "You are an AI assistant that helps people find information.";
+const string AssistantName = "InformationAssistant";
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
+
+[Description("Get the weather for a given location.")]
+static string GetWeather([Description("The location to get the weather for.")] string location)
+    => $"The weather in {location} is cloudy with a high of 15°C.";
+
+[Description("The current datetime offset.")]
+static string GetDateTime()
+    => DateTimeOffset.Now.ToString();
+
+var dateTimeTool = AIFunctionFactory.Create(GetDateTime, name: nameof(GetDateTime));
+var getWeatherTool = AIFunctionFactory.Create(GetWeather, name: nameof(GetWeather));
+
+// Define the agent you want to create. (Prompt Agent in this case)
+AIAgent originalAgent = agentsClient.CreateAIAgent(
+    name: AssistantName,
+    model: deploymentName,
+    instructions: AssistantInstructions,
+    tools: [getWeatherTool, dateTimeTool]);
+
+// Adding middleware to the agent level
+var middlewareEnabledAgent = originalAgent
+    .AsBuilder()
+    .Use(FunctionCallMiddleware)
+    .Use(FunctionCallOverrideWeather)
+    .Use(PIIMiddleware, null)
+    .Use(GuardrailMiddleware, null)
+    .Build();
+
+var thread = middlewareEnabledAgent.GetNewThread();
+
+Console.WriteLine("\n\n=== Example 1: Wording Guardrail ===");
+var guardRailedResponse = await middlewareEnabledAgent.RunAsync("Tell me something harmful.");
+Console.WriteLine($"Guard railed response: {guardRailedResponse}");
+
+Console.WriteLine("\n\n=== Example 2: PII detection ===");
+var piiResponse = await middlewareEnabledAgent.RunAsync("My name is John Doe, call me at 123-456-7890 or email me at john@something.com");
+Console.WriteLine($"Pii filtered response: {piiResponse}");
+
+Console.WriteLine("\n\n=== Example 3: Agent function middleware ===");
+
+// Agent function middleware support is limited to agents that wraps a upstream ChatClientAgent or derived from it.
+
+var functionCallResponse = await middlewareEnabledAgent.RunAsync("What's the current time and the weather in Seattle?", thread);
+Console.WriteLine($"Function calling response: {functionCallResponse}");
+
+// Special per-request middleware agent.
+Console.WriteLine("\n\n=== Example 4: Middleware with human in the loop function approval ===");
+
+AIAgent humamInTheLoopAgent = agentsClient.CreateAIAgent(
+    name: "HumanInTheLoopAgent",
+    model: deploymentName,
+    instructions: "You are an Human in the loop testing AI assistant that helps people find information.",
+
+    // Adding a function with approval required
+    tools: [new ApprovalRequiredAIFunction(AIFunctionFactory.Create(GetWeather, name: nameof(GetWeather)))]);
+
+// Using the ConsolePromptingApprovalMiddleware for a specific request to handle user approval during function calls.
+var response = await humamInTheLoopAgent
+    .AsBuilder()
+    .Use(ConsolePromptingApprovalMiddleware, null)
+    .Build()
+    .RunAsync("What's the current time and the weather in Seattle?");
+
+Console.WriteLine($"HumamInTheLoopAgent agent middleware response: {response}");
+
+// Function invocation middleware that logs before and after function calls.
+async ValueTask<object?> FunctionCallMiddleware(AIAgent agent, FunctionInvocationContext context, Func<FunctionInvocationContext, CancellationToken, ValueTask<object?>> next, CancellationToken cancellationToken)
+{
+    Console.WriteLine($"Function Name: {context!.Function.Name} - Middleware 1 Pre-Invoke");
+    var result = await next(context, cancellationToken);
+    Console.WriteLine($"Function Name: {context!.Function.Name} - Middleware 1 Post-Invoke");
+
+    return result;
+}
+
+// Function invocation middleware that overrides the result of the GetWeather function.
+async ValueTask<object?> FunctionCallOverrideWeather(AIAgent agent, FunctionInvocationContext context, Func<FunctionInvocationContext, CancellationToken, ValueTask<object?>> next, CancellationToken cancellationToken)
+{
+    Console.WriteLine($"Function Name: {context!.Function.Name} - Middleware 2 Pre-Invoke");
+
+    var result = await next(context, cancellationToken);
+
+    if (context.Function.Name == nameof(GetWeather))
+    {
+        // Override the result of the GetWeather function
+        result = "The weather is sunny with a high of 25°C.";
+    }
+    Console.WriteLine($"Function Name: {context!.Function.Name} - Middleware 2 Post-Invoke");
+    return result;
+}
+
+// This middleware redacts PII information from input and output messages.
+async Task<AgentRunResponse> PIIMiddleware(IEnumerable<ChatMessage> messages, AgentThread? thread, AgentRunOptions? options, AIAgent innerAgent, CancellationToken cancellationToken)
+{
+    // Redact PII information from input messages
+    var filteredMessages = FilterMessages(messages);
+    Console.WriteLine("Pii Middleware - Filtered Messages Pre-Run");
+
+    var response = await innerAgent.RunAsync(filteredMessages, thread, options, cancellationToken).ConfigureAwait(false);
+
+    // Redact PII information from output messages
+    response.Messages = FilterMessages(response.Messages);
+
+    Console.WriteLine("Pii Middleware - Filtered Messages Post-Run");
+
+    return response;
+
+    static IList<ChatMessage> FilterMessages(IEnumerable<ChatMessage> messages)
+    {
+        return messages.Select(m => new ChatMessage(m.Role, FilterPii(m.Text))).ToList();
+    }
+
+    static string FilterPii(string content)
+    {
+        // Regex patterns for PII detection (simplified for demonstration)
+        Regex[] piiPatterns = [
+            new(@"\b\d{3}-\d{3}-\d{4}\b", RegexOptions.Compiled), // Phone number (e.g., 123-456-7890)
+                    new(@"\b[\w\.-]+@[\w\.-]+\.\w+\b", RegexOptions.Compiled), // Email address
+                    new(@"\b[A-Z][a-z]+\s[A-Z][a-z]+\b", RegexOptions.Compiled) // Full name (e.g., John Doe)
+        ];
+
+        foreach (var pattern in piiPatterns)
+        {
+            content = pattern.Replace(content, "[REDACTED: PII]");
+        }
+
+        return content;
+    }
+}
+
+// This middleware enforces guardrails by redacting certain keywords from input and output messages.
+async Task<AgentRunResponse> GuardrailMiddleware(IEnumerable<ChatMessage> messages, AgentThread? thread, AgentRunOptions? options, AIAgent innerAgent, CancellationToken cancellationToken)
+{
+    // Redact keywords from input messages
+    var filteredMessages = FilterMessages(messages);
+
+    Console.WriteLine("Guardrail Middleware - Filtered messages Pre-Run");
+
+    // Proceed with the agent run
+    var response = await innerAgent.RunAsync(filteredMessages, thread, options, cancellationToken);
+
+    // Redact keywords from output messages
+    response.Messages = FilterMessages(response.Messages);
+
+    Console.WriteLine("Guardrail Middleware - Filtered messages Post-Run");
+
+    return response;
+
+    List<ChatMessage> FilterMessages(IEnumerable<ChatMessage> messages)
+    {
+        return messages.Select(m => new ChatMessage(m.Role, FilterContent(m.Text))).ToList();
+    }
+
+    static string FilterContent(string content)
+    {
+        foreach (var keyword in new[] { "harmful", "illegal", "violence" })
+        {
+            if (content.Contains(keyword, StringComparison.OrdinalIgnoreCase))
+            {
+                return "[REDACTED: Forbidden content]";
+            }
+        }
+
+        return content;
+    }
+}
+
+// This middleware handles Human in the loop console interaction for any user approval required during function calling.
+async Task<AgentRunResponse> ConsolePromptingApprovalMiddleware(IEnumerable<ChatMessage> messages, AgentThread? thread, AgentRunOptions? options, AIAgent innerAgent, CancellationToken cancellationToken)
+{
+    var response = await innerAgent.RunAsync(messages, thread, options, cancellationToken);
+
+    var userInputRequests = response.UserInputRequests.ToList();
+
+    while (userInputRequests.Count > 0)
+    {
+        // Ask the user to approve each function call request.
+        // For simplicity, we are assuming here that only function approval requests are being made.
+
+        // Pass the user input responses back to the agent for further processing.
+        response.Messages = userInputRequests
+            .OfType<FunctionApprovalRequestContent>()
+            .Select(functionApprovalRequest =>
+            {
+                Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {functionApprovalRequest.FunctionCall.Name}");
+                return new ChatMessage(ChatRole.User, [functionApprovalRequest.CreateResponse(Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false)]);
+            })
+            .ToList();
+
+        response = await innerAgent.RunAsync(response.Messages, thread, options, cancellationToken);
+
+        userInputRequests = response.UserInputRequests.ToList();
+    }
+
+    return response;
+}
+
+// Cleanup by agent name removes the agent version created.
+agentsClient.DeleteAgent(middlewareEnabledAgent.Name);

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step12_Middleware/README.md

@@ -0,0 +1,41 @@
+# Agent Middleware 
+
+This sample demonstrates how to add middleware to intercept:
+- Chat client calls (global and per‑request)
+- Agent runs (guardrails and PII filtering)
+- Function calling (logging/override)
+
+## What This Sample Shows
+
+1. Azure OpenAI integration via `AzureOpenAIClient` and `AzureCliCredential`
+2. Chat client middleware using `ChatClientBuilder.Use(...)`
+3. Agent run middleware (PII redaction and wording guardrails)
+4. Function invocation middleware (logging and overriding a tool result)
+5. Per‑request chat client middleware
+6. Per‑request function pipeline with approval
+7. Combining agent‑level and per‑request middleware
+
+## Function Invocation Middleware
+
+Not all agents support function invocation middleware.
+
+Attempting to use function middleware on agents that do not wrap a ChatClientAgent or derives from it will throw an InvalidOperationException.
+
+## Prerequisites
+
+1. Environment variables:
+   - `AZURE_OPENAI_ENDPOINT`: Your Azure OpenAI endpoint
+   - `AZURE_OPENAI_DEPLOYMENT_NAME`: Chat deployment name (optional; defaults to `gpt-4o`)
+2. Sign in with Azure CLI (PowerShell):
+   ```powershell
+   az login
+   ```
+
+## Running the Sample
+
+Use PowerShell:
+```powershell
+cd dotnet/samples/GettingStarted/Agents/Agent_Step14_Middleware
+dotnet run
+```
+

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step13_Plugins/AzureAIAgents_Step13_Plugins.csproj

@@ -0,0 +1,24 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <NoWarn>$(NoWarn);CA1812</NoWarn>
+    <RootNamespace>Agent_Step15_Plugins</RootNamespace>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Extensions.Logging.Console" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Azure.AI.Agents" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
+  </ItemGroup>
+  
+</Project>

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureAIAgent/AzureAIAgents_Step13_Plugins/Program.cs

@@ -0,0 +1,139 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to use plugins with an AI agent. Plugin classes can
+// depend on other services that need to be injected. In this sample, the
+// AgentPlugin class uses the WeatherProvider and CurrentTimeProvider classes
+// to get weather and current time information. Both services are registered
+// in the service collection and injected into the plugin.
+// Plugin classes may have many methods, but only some are intended to be used
+// as AI functions. The AsAITools method of the plugin class shows how to specify
+// which methods should be exposed to the AI agent.
+
+using Azure.AI.Agents;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+using Microsoft.Extensions.DependencyInjection;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string AssistantInstructions = "You are a helpful assistant that helps people find information.";
+const string AssistantName = "PluginAssistant";
+
+// Create a service collection to hold the agent plugin and its dependencies.
+ServiceCollection services = new();
+services.AddSingleton<WeatherProvider>();
+services.AddSingleton<CurrentTimeProvider>();
+services.AddSingleton<AgentPlugin>(); // The plugin depends on WeatherProvider and CurrentTimeProvider registered above.
+
+IServiceProvider serviceProvider = services.BuildServiceProvider();
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+var agentsClient = new AgentsClient(new Uri(endpoint), new AzureCliCredential());
+
+// Define the agent with plugin tools
+// Define the agent you want to create. (Prompt Agent in this case)
+AIAgent agent = agentsClient.CreateAIAgent(
+    name: AssistantName,
+    model: deploymentName,
+    instructions: AssistantInstructions,
+    tools: serviceProvider.GetRequiredService<AgentPlugin>().AsAITools().ToList(),
+    services: serviceProvider);
+
+// Invoke the agent and output the text result.
+AgentThread thread = agent.GetNewThread();
+Console.WriteLine(await agent.RunAsync("Tell me current time and weather in Seattle.", thread));
+
+// Cleanup by agent name removes the agent version created.
+agentsClient.DeleteAgent(agent.Name);
+
+/// <summary>
+/// The agent plugin that provides weather and current time information.
+/// </summary>
+/// <param name="weatherProvider">The weather provider to get weather information.</param>
+internal sealed class AgentPlugin(WeatherProvider weatherProvider)
+{
+    /// <summary>
+    /// Gets the weather information for the specified location.
+    /// </summary>
+    /// <remarks>
+    /// This method demonstrates how to use the dependency that was injected into the plugin class.
+    /// </remarks>
+    /// <param name="location">The location to get the weather for.</param>
+    /// <returns>The weather information for the specified location.</returns>
+    public string GetWeather(string location)
+    {
+        return weatherProvider.GetWeather(location);
+    }
+
+    /// <summary>
+    /// Gets the current date and time for the specified location.
+    /// </summary>
+    /// <remarks>
+    /// This method demonstrates how to resolve a dependency using the service provider passed to the method.
+    /// </remarks>
+    /// <param name="sp">The service provider to resolve the <see cref="CurrentTimeProvider"/>.</param>
+    /// <param name="location">The location to get the current time for.</param>
+    /// <returns>The current date and time as a <see cref="DateTimeOffset"/>.</returns>
+    public DateTimeOffset GetCurrentTime(IServiceProvider sp, string location)
+    {
+        // Resolve the CurrentTimeProvider from the service provider
+        var currentTimeProvider = sp.GetRequiredService<CurrentTimeProvider>();
+
+        return currentTimeProvider.GetCurrentTime(location);
+    }
+
+    /// <summary>
+    /// Returns the functions provided by this plugin.
+    /// </summary>
+    /// <remarks>
+    /// In real world scenarios, a class may have many methods and only a subset of them may be intended to be exposed as AI functions.
+    /// This method demonstrates how to explicitly specify which methods should be exposed to the AI agent.
+    /// </remarks>
+    /// <returns>The functions provided by this plugin.</returns>
+    public IEnumerable<AITool> AsAITools()
+    {
+        yield return AIFunctionFactory.Create(this.GetWeather);
+        yield return AIFunctionFactory.Create(this.GetCurrentTime);
+    }
+}
+
+/// <summary>
+/// The weather provider that returns weather information.
+/// </summary>
+internal sealed class WeatherProvider
+{
+    /// <summary>
+    /// Gets the weather information for the specified location.
+    /// </summary>
+    /// <remarks>
+    /// The weather information is hardcoded for demonstration purposes.
+    /// In a real application, this could call a weather API to get actual weather data.
+    /// </remarks>
+    /// <param name="location">The location to get the weather for.</param>
+    /// <returns>The weather information for the specified location.</returns>
+    public string GetWeather(string location)
+    {
+        return $"The weather in {location} is cloudy with a high of 15°C.";
+    }
+}
+
+/// <summary>
+/// Provides the current date and time.
+/// </summary>
+/// <remarks>
+/// This class returns the current date and time using the system's clock.
+/// </remarks>
+internal sealed class CurrentTimeProvider
+{
+    /// <summary>
+    /// Gets the current date and time.
+    /// </summary>
+    /// <param name="location">The location to get the current time for (not used in this implementation).</param>
+    /// <returns>The current date and time as a <see cref="DateTimeOffset"/>.</returns>
+    public DateTimeOffset GetCurrentTime(string location)
+    {
+        return DateTimeOffset.Now;
+    }
+}

dotnet/samples/GettingStarted/AgentProviders/Agent_With_AzureFoundryAgent/Agent_With_AzureFoundryAgent.csproj

@@ -14,7 +14,7 @@
   </ItemGroup>
 
   <ItemGroup>
-    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI.Persistent\Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
   </ItemGroup>
 
 </Project>

dotnet/samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step01_BasicTextRAG/AgentWithRAG_Step01_BasicTextRAG.csproj

@@ -0,0 +1,22 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+    <PackageReference Include="Microsoft.SemanticKernel.Connectors.InMemory" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step01_BasicTextRAG/Program.cs

@@ -0,0 +1,105 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to use TextSearchProvider to add retrieval augmented generation (RAG) capabilities to an AI agent.
+// The sample uses an In-Memory vector store, which can easily be replaced with any other vector store that implements the Microsoft.Extensions.VectorData abstractions.
+// The TextSearchProvider runs a search against the vector store via the TextSearchStore before each model invocation and injects the results into the model context.
+// The TextSearchStore is a sample store implementation that hardcodes a storage schema and uses the vector store to store and retrieve documents.
+
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.Data;
+using Microsoft.Agents.AI.Samples;
+using Microsoft.Extensions.AI;
+using Microsoft.Extensions.VectorData;
+using Microsoft.SemanticKernel.Connectors.InMemory;
+using OpenAI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var embeddingDeploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-3-large";
+
+AzureOpenAIClient azureOpenAIClient = new(
+    new Uri(endpoint),
+    new AzureCliCredential());
+
+// Create an In-Memory vector store that uses the Azure OpenAI embedding model to generate embeddings.
+VectorStore vectorStore = new InMemoryVectorStore(new()
+{
+    EmbeddingGenerator = azureOpenAIClient.GetEmbeddingClient(embeddingDeploymentName).AsIEmbeddingGenerator()
+});
+
+// Create a store that defines a storage schema, and uses the vector store to store and retrieve documents.
+TextSearchStore textSearchStore = new(vectorStore, "product-and-policy-info", 3072);
+
+// Upload sample documents into the store.
+await textSearchStore.UpsertDocumentsAsync(GetSampleDocuments());
+
+// Create an adapter function that the TextSearchProvider can use to run searches against the TextSearchStore.
+Func<string, CancellationToken, Task<IEnumerable<TextSearchProvider.TextSearchResult>>> SearchAdapter = async (text, ct) =>
+{
+    // Here we are limiting the search results to the single top result to demonstrate that we are accurately matching
+    // specific search results for each question, but in a real world case, more results should be used.
+    var searchResults = await textSearchStore.SearchAsync(text, 1, ct);
+    return searchResults.Select(r => new TextSearchProvider.TextSearchResult
+    {
+        SourceName = r.SourceName,
+        SourceLink = r.SourceLink,
+        Text = r.Text ?? string.Empty,
+        RawRepresentation = r
+    });
+};
+
+// Configure the options for the TextSearchProvider.
+TextSearchProviderOptions textSearchOptions = new()
+{
+    // Run the search prior to every model invocation.
+    SearchTime = TextSearchProviderOptions.TextSearchBehavior.BeforeAIInvoke,
+};
+
+// Create the AI agent with the TextSearchProvider as the AI context provider.
+AIAgent agent = azureOpenAIClient
+    .GetChatClient(deploymentName)
+    .CreateAIAgent(new ChatClientAgentOptions
+    {
+        Instructions = "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available.",
+        AIContextProviderFactory = ctx => new TextSearchProvider(SearchAdapter, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions)
+    });
+
+AgentThread thread = agent.GetNewThread();
+
+Console.WriteLine(">> Asking about returns\n");
+Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", thread));
+
+Console.WriteLine("\n>> Asking about shipping\n");
+Console.WriteLine(await agent.RunAsync("How long does standard shipping usually take?", thread));
+
+Console.WriteLine("\n>> Asking about product care\n");
+Console.WriteLine(await agent.RunAsync("What is the best way to maintain the TrailRunner tent fabric?", thread));
+
+// Produces some sample search documents.
+// Each one contains a source name and link, which the agent can use to cite sources in its responses.
+static IEnumerable<TextSearchDocument> GetSampleDocuments()
+{
+    yield return new TextSearchDocument
+    {
+        SourceId = "return-policy-001",
+        SourceName = "Contoso Outdoors Return Policy",
+        SourceLink = "https://contoso.com/policies/returns",
+        Text = "Customers may return any item within 30 days of delivery. Items should be unused and include original packaging. Refunds are issued to the original payment method within 5 business days of inspection."
+    };
+    yield return new TextSearchDocument
+    {
+        SourceId = "shipping-guide-001",
+        SourceName = "Contoso Outdoors Shipping Guide",
+        SourceLink = "https://contoso.com/help/shipping",
+        Text = "Standard shipping is free on orders over $50 and typically arrives in 3-5 business days within the continental United States. Expedited options are available at checkout."
+    };
+    yield return new TextSearchDocument
+    {
+        SourceId = "tent-care-001",
+        SourceName = "TrailRunner Tent Care Instructions",
+        SourceLink = "https://contoso.com/manuals/trailrunner-tent",
+        Text = "Clean the tent fabric with lukewarm water and a non-detergent soap. Allow it to air dry completely before storage and avoid prolonged UV exposure to extend the lifespan of the waterproof coating."
+    };
+}

dotnet/samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step01_BasicTextRAG/TextSearchStore/TextSearchDocument.cs

@@ -0,0 +1,51 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+namespace Microsoft.Agents.AI.Samples;
+
+/// <summary>
+/// Represents a document that can be used for Retrieval Augmented Generation (RAG) that stores textual data.
+/// </summary>
+public sealed class TextSearchDocument
+{
+    /// <summary>
+    /// Gets or sets an optional list of namespaces that the document should belong to.
+    /// </summary>
+    /// <remarks>
+    /// A namespace is a logical grouping of documents, e.g. may include a group id to scope the document to a specific group of users.
+    /// </remarks>
+    public IList<string> Namespaces { get; set; } = [];
+
+    /// <summary>
+    /// Gets or sets the content as text.
+    /// </summary>
+    public string? Text { get; set; }
+
+    /// <summary>
+    /// Gets or sets an optional source ID for the document.
+    /// </summary>
+    /// <remarks>
+    /// This ID should be unique within the collection that the document is stored in, and can
+    /// be used to map back to the source artifact for this document.
+    /// If updates need to be made later or the source document was deleted and this document
+    /// also needs to be deleted, this id can be used to find the document again.
+    /// </remarks>
+    public string? SourceId { get; set; }
+
+    /// <summary>
+    /// Gets or sets an optional name for the source document.
+    /// </summary>
+    /// <remarks>
+    /// This can be used to provide display names for citation links when the document is referenced as
+    /// part of a response to a query.
+    /// </remarks>
+    public string? SourceName { get; set; }
+
+    /// <summary>
+    /// Gets or sets an optional link back to the source of the document.
+    /// </summary>
+    /// <remarks>
+    /// This can be used to provide citation links when the document is referenced as
+    /// part of a response to a query.
+    /// </remarks>
+    public string? SourceLink { get; set; }
+}

dotnet/samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step01_BasicTextRAG/TextSearchStore/TextSearchStore.cs

@@ -0,0 +1,392 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Linq.Expressions;
+using System.Text.RegularExpressions;
+using Microsoft.Extensions.VectorData;
+
+namespace Microsoft.Agents.AI.Samples;
+
+/// <summary>
+/// A class that allows for easy storage and retrieval of documents in a Vector Store for Retrieval Augmented Generation (RAG).
+/// </summary>
+/// <remarks>
+/// <para>
+/// This class provides an opinionated schema for storing documents in a vector store. It is valuable for simple scenarios
+/// where you want to store text + embedding, or a reference to an external document + embedding without needing to customize the schema.
+/// If you want to control the schema yourself, use an implementation of <see cref="VectorStoreCollection{TKey, TRecord}"/> directly instead.
+/// </para>
+/// <para>
+/// This class and its related types are currently provided as a sample implementation, but may be promoted to a first-class supported API in future releases.
+/// </para>
+/// </remarks>
+public sealed partial class TextSearchStore : IDisposable
+{
+#if NET
+    [GeneratedRegex(@"\p{L}+", RegexOptions.IgnoreCase, "en-US")]
+    private static partial Regex AnyLanguageWordRegex();
+
+    private static readonly Func<string, ICollection<string>> s_defaultWordSegmenter = text => AnyLanguageWordRegex().Matches(text).Select(x => x.Value).ToList();
+#else
+    private static readonly Regex s_anyLanguageWordRegex = new(@"\p{L}+", RegexOptions.Compiled);
+    private static Regex AnyLanguageWordRegex() => s_anyLanguageWordRegex;
+
+    private static readonly Func<string, ICollection<string>> s_defaultWordSegmenter = text =>
+    {
+        List<string> words = new();
+        foreach (Match word in AnyLanguageWordRegex().Matches(text))
+        {
+            words.Add(word.Value);
+        }
+        return words;
+    };
+#endif
+
+    private readonly VectorStore _vectorStore;
+    private readonly TextSearchStoreOptions _options;
+    private readonly Func<string, ICollection<string>> _wordSegmenter;
+
+    private readonly VectorStoreCollection<object, Dictionary<string, object?>> _vectorStoreRecordCollection;
+    private readonly SemaphoreSlim _collectionInitializationLock = new(1, 1);
+    private bool _collectionInitialized;
+    private bool _disposedValue;
+
+    /// <summary>
+    /// Initializes a new instance of the <see cref="TextSearchStore"/> class.
+    /// </summary>
+    /// <param name="vectorStore">The vector store to store and read the memories from.</param>
+    /// <param name="collectionName">The name of the collection in the vector store to store and read the memories from.</param>
+    /// <param name="vectorDimensions">The number of dimensions to use for the memory embeddings.</param>
+    /// <param name="options">Options to configure the behavior of this class.</param>
+    /// <exception cref="NotSupportedException">Thrown if the key type provided is not supported.</exception>
+    public TextSearchStore(
+        VectorStore vectorStore,
+        string collectionName,
+        int vectorDimensions,
+        TextSearchStoreOptions? options = default)
+    {
+        // Verify
+        if (vectorStore is null)
+        {
+            throw new ArgumentNullException(nameof(vectorStore));
+        }
+
+        if (string.IsNullOrWhiteSpace(collectionName))
+        {
+            throw new ArgumentException("Collection name cannot be null or whitespace.", nameof(collectionName));
+        }
+
+        if (vectorDimensions < 1)
+        {
+            throw new ArgumentOutOfRangeException(nameof(vectorDimensions), "Vector dimensions must be greater than zero.");
+        }
+
+        if (options?.KeyType is not null && options.KeyType != typeof(string) && options.KeyType != typeof(Guid))
+        {
+            throw new NotSupportedException($"Unsupported key of type '{options.KeyType.Name}'");
+        }
+
+        if (options?.KeyType is not null && options.KeyType != typeof(string) && options?.UseSourceIdAsPrimaryKey is true)
+        {
+            throw new NotSupportedException($"The {nameof(TextSearchStoreOptions.UseSourceIdAsPrimaryKey)} option can only be used when the key type is 'string'.");
+        }
+
+        // Assign
+        this._vectorStore = vectorStore;
+        this._options = options ?? new TextSearchStoreOptions();
+        this._wordSegmenter = this._options.WordSegmenter ?? s_defaultWordSegmenter;
+
+        // Create a definition so that we can use the dimensions provided at runtime.
+        VectorStoreCollectionDefinition ragDocumentDefinition = new()
+        {
+            Properties = new List<VectorStoreProperty>()
+            {
+                new VectorStoreKeyProperty("Key", this._options.KeyType ?? typeof(string)),
+                new VectorStoreDataProperty("Namespaces", typeof(List<string>)) { IsIndexed = true },
+                new VectorStoreDataProperty("SourceId", typeof(string)) { IsIndexed = true },
+                new VectorStoreDataProperty("Text", typeof(string)) { IsFullTextIndexed = true },
+                new VectorStoreDataProperty("SourceName", typeof(string)),
+                new VectorStoreDataProperty("SourceLink", typeof(string)),
+                new VectorStoreVectorProperty("TextEmbedding", typeof(string), vectorDimensions),
+            }
+        };
+
+        this._vectorStoreRecordCollection = this._vectorStore.GetDynamicCollection(collectionName, ragDocumentDefinition);
+    }
+
+    /// <summary>
+    /// Upserts a batch of text chunks into the vector store.
+    /// </summary>
+    /// <param name="textChunks">The text chunks to upload.</param>
+    /// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
+    /// <returns>A task that completes when the documents have been upserted.</returns>
+    public async Task UpsertTextAsync(IEnumerable<string> textChunks, CancellationToken cancellationToken = default)
+    {
+        if (textChunks == null)
+        {
+            throw new ArgumentNullException(nameof(textChunks));
+        }
+
+        var vectorStoreRecordCollection = await this.EnsureCollectionExistsAsync(cancellationToken).ConfigureAwait(false);
+
+        var storageDocuments = textChunks.Select(textChunk =>
+        {
+            // Without text we cannot generate a vector.
+            if (string.IsNullOrWhiteSpace(textChunk))
+            {
+                throw new ArgumentException("One of the provided text chunks is null.", nameof(textChunks));
+            }
+
+            return new Dictionary<string, object?>
+            {
+                { "Key", this.GenerateUniqueKey(null) },
+                { "Namespaces", new List<string>() },
+                { "Text", textChunk },
+                { "TextEmbedding", textChunk },
+            };
+        });
+
+        await vectorStoreRecordCollection.UpsertAsync(storageDocuments, cancellationToken).ConfigureAwait(false);
+    }
+
+    /// <summary>
+    /// Upserts a batch of documents into the vector store.
+    /// </summary>
+    /// <param name="documents">The documents to upload.</param>
+    /// <param name="options">Optional options to control the upsert behavior.</param>
+    /// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
+    /// <returns>A task that completes when the documents have been upserted.</returns>
+    public async Task UpsertDocumentsAsync(IEnumerable<TextSearchDocument> documents, TextSearchStoreUpsertOptions? options = null, CancellationToken cancellationToken = default)
+    {
+        if (documents is null)
+        {
+            throw new ArgumentNullException(nameof(documents));
+        }
+
+        var vectorStoreRecordCollection = await this.EnsureCollectionExistsAsync(cancellationToken).ConfigureAwait(false);
+
+        var storageDocuments = documents.Select(document =>
+        {
+            if (document is null)
+            {
+                throw new ArgumentNullException(nameof(documents), "One of the provided documents is null.");
+            }
+
+            // Without text we cannot generate a vector.
+            if (string.IsNullOrWhiteSpace(document.Text))
+            {
+                throw new ArgumentException($"The {nameof(TextSearchDocument.Text)} property must be set.", nameof(document));
+            }
+
+            // If we aren't persisting the text, we need a source id or link to refer back to the original document.
+            if (options?.DoNotPersistSourceText is true && string.IsNullOrWhiteSpace(document.SourceId) && string.IsNullOrWhiteSpace(document.SourceLink))
+            {
+                throw new ArgumentException($"Either the {nameof(TextSearchDocument.SourceId)} or {nameof(TextSearchDocument.SourceLink)} properties must be set when the {nameof(TextSearchStoreUpsertOptions.DoNotPersistSourceText)} setting is true.", nameof(document));
+            }
+
+            var key = this.GenerateUniqueKey(this._options.UseSourceIdAsPrimaryKey ?? false ? document.SourceId : null);
+
+            return new Dictionary<string, object?>()
+            {
+                { "Key", key },
+                { "Namespaces", document.Namespaces.ToList() },
+                { "SourceId", document.SourceId },
+                { "Text", options?.DoNotPersistSourceText is true ? null : document.Text },
+                { "SourceName", document.SourceName },
+                { "SourceLink", document.SourceLink },
+                { "TextEmbedding", document.Text },
+            };
+        });
+
+        await vectorStoreRecordCollection.UpsertAsync(storageDocuments, cancellationToken).ConfigureAwait(false);
+    }
+
+    /// <summary>
+    /// Search the database for documents similar to the provided query.
+    /// </summary>
+    /// <param name="query">The text query to find similar documents to.</param>
+    /// <param name="top">The maximum number of results to return.</param>
+    /// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
+    /// <returns>The search results.</returns>
+    public async Task<IEnumerable<TextSearchDocument>> SearchAsync(string query, int top, CancellationToken cancellationToken = default)
+    {
+        var searchResult = await this.SearchCoreAsync(query, top, cancellationToken).ConfigureAwait(false);
+
+        return searchResult.Select(x => new TextSearchDocument()
+        {
+            Namespaces = (List<string>)x["Namespaces"]!,
+            Text = (string?)x["Text"],
+            SourceId = (string?)x["SourceId"],
+            SourceName = (string?)x["SourceName"],
+            SourceLink = (string?)x["SourceLink"],
+        });
+    }
+
+    /// <summary>
+    /// Internal search implementation with hydration of id / link only storage.
+    /// </summary>
+    /// <param name="query">The text query to find similar documents to.</param>
+    /// <param name="top">The maximum number of results to return.</param>
+    /// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
+    /// <returns>The search results.</returns>
+    private async Task<IEnumerable<Dictionary<string, object?>>> SearchCoreAsync(string query, int top, CancellationToken cancellationToken = default)
+    {
+        // Short circuit if the query is empty.
+        if (string.IsNullOrWhiteSpace(query))
+        {
+            return [];
+        }
+
+        var vectorStoreRecordCollection = await this.EnsureCollectionExistsAsync(cancellationToken).ConfigureAwait(false);
+
+        // If the user has not opted out of hybrid search, check if the vector store supports it.
+        var hybridSearchCollection = this._options.UseHybridSearch ?? true ?
+            vectorStoreRecordCollection.GetService(typeof(IKeywordHybridSearchable<Dictionary<string, object?>>)) as IKeywordHybridSearchable<Dictionary<string, object?>> :
+            null;
+
+        // Optional filter to limit the search to a specific namespace.
+        Expression<Func<Dictionary<string, object?>, bool>>? filter = string.IsNullOrWhiteSpace(this._options.SearchNamespace) ? null : x => ((List<string>)x["Namespaces"]!).Contains(this._options.SearchNamespace);
+
+        // Execute a hybrid search if possible, otherwise perform a regular vector search.
+        var searchResult = hybridSearchCollection is null
+            ? vectorStoreRecordCollection.SearchAsync(
+                query,
+                top,
+                options: new()
+                {
+                    Filter = filter,
+                },
+                cancellationToken: cancellationToken)
+            : hybridSearchCollection.HybridSearchAsync(
+                query,
+                this._wordSegmenter(query),
+                top,
+                options: new()
+                {
+                    Filter = filter,
+                },
+                cancellationToken: cancellationToken);
+
+        // Retrieve the documents from the search results.
+        List<Dictionary<string, object?>> searchResponseDocs = new();
+        await foreach (var searchResponseDoc in searchResult.WithCancellation(cancellationToken).ConfigureAwait(false))
+        {
+            searchResponseDocs.Add(searchResponseDoc.Record);
+        }
+
+        // Find any source ids and links for which the text needs to be retrieved.
+        var sourceIdsToRetrieve = searchResponseDocs
+            .Where(x => string.IsNullOrWhiteSpace((string?)x["Text"]))
+            .Select(x => new TextSearchStoreOptions.SourceRetrievalRequest((string?)x["SourceId"], (string?)x["SourceLink"]))
+            .ToList();
+
+        // If we have none, we can return early.
+        if (sourceIdsToRetrieve.Count == 0)
+        {
+            return searchResponseDocs;
+        }
+
+        if (this._options.SourceRetrievalCallback is null)
+        {
+            throw new InvalidOperationException($"The {nameof(TextSearchStoreOptions.SourceRetrievalCallback)} option must be set if retrieving documents without stored text.");
+        }
+
+        // Retrieve the source text for the documents that need it.
+        var retrievalResponses = await this._options.SourceRetrievalCallback(sourceIdsToRetrieve).ConfigureAwait(false);
+
+        if (retrievalResponses is null)
+        {
+            throw new InvalidOperationException($"The {nameof(TextSearchStoreOptions.SourceRetrievalCallback)} must return a non-null value.");
+        }
+
+        // Update the retrieved documents with the retrieved text.
+        return searchResponseDocs.GroupJoin(
+            retrievalResponses,
+            searchResponseDoc => (searchResponseDoc["SourceId"], searchResponseDoc["SourceLink"]),
+            retrievalResponse => (retrievalResponse.SourceId, retrievalResponse.SourceLink),
+            (searchResponseDoc, textRetrievalResponse) => (searchResponseDoc, textRetrievalResponse))
+            .SelectMany(
+                joinedSet => joinedSet.textRetrievalResponse.DefaultIfEmpty(),
+                (combined, textRetrievalResponse) =>
+                {
+                    combined.searchResponseDoc["Text"] = textRetrievalResponse?.Text ?? combined.searchResponseDoc["Text"];
+                    return combined.searchResponseDoc;
+                });
+    }
+
+    /// <summary>
+    /// Thread safe method to get the collection and ensure that it is created at least once.
+    /// </summary>
+    /// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
+    /// <returns>The created collection.</returns>
+    private async Task<VectorStoreCollection<object, Dictionary<string, object?>>> EnsureCollectionExistsAsync(CancellationToken cancellationToken)
+    {
+        // Return immediately if the collection is already created, no need to do any locking in this case.
+        if (this._collectionInitialized)
+        {
+            return this._vectorStoreRecordCollection;
+        }
+
+        // Wait on a lock to ensure that only one thread can create the collection.
+        await this._collectionInitializationLock.WaitAsync(cancellationToken).ConfigureAwait(false);
+
+        // If multiple threads waited on the lock, and the first already created the collection,
+        // we can return immediately without doing any work in subsequent threads.
+        if (this._collectionInitialized)
+        {
+            this._collectionInitializationLock.Release();
+            return this._vectorStoreRecordCollection;
+        }
+
+        // Only the winning thread should reach this point and create the collection.
+        try
+        {
+            await this._vectorStoreRecordCollection.EnsureCollectionExistsAsync(cancellationToken).ConfigureAwait(false);
+            this._collectionInitialized = true;
+        }
+        finally
+        {
+            this._collectionInitializationLock.Release();
+        }
+
+        return this._vectorStoreRecordCollection;
+    }
+
+    /// <summary>
+    /// Generates a unique key for the RAG document.
+    /// </summary>
+    /// <param name="sourceId">Source id of the source document for this RAG document.</param>
+    /// <returns>A new unique key.</returns>
+    /// <exception cref="NotSupportedException">Thrown if the requested key type is not supported.</exception>
+    private object GenerateUniqueKey(string? sourceId)
+        => this._options.KeyType switch
+        {
+            _ when (this._options.KeyType == null || this._options.KeyType == typeof(string)) && !string.IsNullOrWhiteSpace(sourceId) => sourceId!,
+            _ when this._options.KeyType == null || this._options.KeyType == typeof(string) => Guid.NewGuid().ToString(),
+            _ when this._options.KeyType == typeof(Guid) => Guid.NewGuid(),
+
+            _ => throw new NotSupportedException($"Unsupported key of type '{this._options.KeyType.Name}'")
+        };
+
+    /// <inheritdoc/>
+    private void Dispose(bool disposing)
+    {
+        if (!this._disposedValue)
+        {
+            if (disposing)
+            {
+                this._vectorStoreRecordCollection.Dispose();
+                this._collectionInitializationLock.Dispose();
+            }
+
+            this._disposedValue = true;
+        }
+    }
+
+    /// <inheritdoc/>
+    public void Dispose()
+    {
+        // Do not change this code. Put cleanup code in 'Dispose(bool disposing)' method
+        this.Dispose(disposing: true);
+        GC.SuppressFinalize(this);
+    }
+}

dotnet/samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step01_BasicTextRAG/TextSearchStore/TextSearchStoreOptions.cs

@@ -0,0 +1,140 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+namespace Microsoft.Agents.AI.Samples;
+
+/// <summary>
+/// Contains options for the <see cref="TextSearchStore"/>.
+/// </summary>
+public sealed class TextSearchStoreOptions
+{
+    /// <summary>
+    /// Gets or sets an optional namespace to pre-filter the possible
+    /// records with when doing a vector search.
+    /// </summary>
+    public string? SearchNamespace { get; init; }
+
+    /// <summary>
+    /// Gets or sets a value indicating whether to use the source ID as the primary key for records.
+    /// </summary>
+    /// <remarks>
+    /// <para>
+    /// Using the source ID as the primary key allows for easy updates from the source for any changed
+    /// records, since those records can just be upserted again, and will overwrite the previous version
+    /// of the same record.
+    /// </para>
+    /// <para>
+    /// This setting can only be used when the chosen key type is a string.
+    /// </para>
+    /// </remarks>
+    /// <value>
+    /// Defaults to <c>false</c> if not set.
+    /// </value>
+    public bool? UseSourceIdAsPrimaryKey { get; init; }
+
+    /// <summary>
+    /// Gets or sets a value indicating whether to use hybrid search if it is available for the provided vector store.
+    /// </summary>
+    /// <value>
+    /// Defaults to <c>true</c> if not set.
+    /// </value>
+    public bool? UseHybridSearch { get; init; }
+
+    /// <summary>
+    /// Gets or sets a word segmenter function to split search text into separate words for the purposes of hybrid search.
+    /// This will not be used if <see cref="UseHybridSearch"/> is set to <c>false</c>.
+    /// </summary>
+    /// <remarks>
+    /// Defaults to a simple text-character-based segmenter that splits the text by any character that is not a text character.
+    /// </remarks>
+    public Func<string, ICollection<string>>? WordSegmenter { get; init; }
+
+    /// <summary>
+    /// Gets or sets the type of key to use for records in the text search store.
+    /// </summary>
+    /// <remarks>
+    /// Make sure to pick a key type that is supported by the underlying vector store.
+    /// Note that you have to choose <see cref="string"/> when using <see cref="UseSourceIdAsPrimaryKey"/>.
+    /// </remarks>
+    /// <value>Defaults to <see cref="string"/> if not set. Only <see cref="string"/> and <see cref="Guid"/> is currently supported.</value>
+    public Type? KeyType { get; init; }
+
+    /// <summary>
+    /// Gets or sets an optional callback to load the source text using the source id or source link
+    /// if the source text is not persisted in the database.
+    /// </summary>
+    /// <remarks>
+    /// The response should include the source id or source link, as provided in the request,
+    /// plus the source text loaded from the source.
+    /// </remarks>
+    public Func<List<SourceRetrievalRequest>, Task<IEnumerable<SourceRetrievalResponse>>>? SourceRetrievalCallback { get; init; }
+
+    /// <summary>
+    /// Represents a request to the <see cref="SourceRetrievalCallback"/>.
+    /// </summary>
+    public sealed class SourceRetrievalRequest
+    {
+        /// <summary>
+        /// Initializes a new instance of the <see cref="SourceRetrievalRequest"/> class.
+        /// </summary>
+        /// <param name="sourceId">The source ID of the document to retrieve.</param>
+        /// <param name="sourceLink">The source link of the document to retrieve.</param>
+        public SourceRetrievalRequest(string? sourceId, string? sourceLink)
+        {
+            this.SourceId = sourceId;
+            this.SourceLink = sourceLink;
+        }
+
+        /// <summary>
+        /// Gets or sets the source ID of the document to retrieve.
+        /// </summary>
+        public string? SourceId { get; set; }
+
+        /// <summary>
+        /// Gets or sets the source link of the document to retrieve.
+        /// </summary>
+        public string? SourceLink { get; set; }
+    }
+
+    /// <summary>
+    /// Represents a response from the <see cref="SourceRetrievalCallback"/>.
+    /// </summary>
+    public sealed class SourceRetrievalResponse
+    {
+        /// <summary>
+        /// Initializes a new instance of the <see cref="SourceRetrievalResponse"/> class.
+        /// </summary>
+        /// <param name="request">The request matching this response.</param>
+        /// <param name="text">The source text that was retrieved.</param>
+        public SourceRetrievalResponse(SourceRetrievalRequest request, string text)
+        {
+            if (request == null)
+            {
+                throw new ArgumentNullException(nameof(request));
+            }
+
+            if (text == null)
+            {
+                throw new ArgumentNullException(nameof(text));
+            }
+
+            this.SourceId = request.SourceId;
+            this.SourceLink = request.SourceLink;
+            this.Text = text;
+        }
+
+        /// <summary>
+        /// Gets or sets the source ID of the document that was retrieved.
+        /// </summary>
+        public string? SourceId { get; set; }
+
+        /// <summary>
+        /// Gets or sets the source link of the document that was retrieved.
+        /// </summary>
+        public string? SourceLink { get; set; }
+
+        /// <summary>
+        /// Gets or sets the source text of the document that was retrieved.
+        /// </summary>
+        public string Text { get; set; }
+    }
+}

dotnet/samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step01_BasicTextRAG/TextSearchStore/TextSearchStoreUpsertOptions.cs

@@ -0,0 +1,17 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+namespace Microsoft.Agents.AI.Samples;
+
+/// <summary>
+/// Contains options for <see cref="TextSearchStore.UpsertDocumentsAsync(IEnumerable{TextSearchDocument}, TextSearchStoreUpsertOptions?, CancellationToken)"/>.
+/// </summary>
+public sealed class TextSearchStoreUpsertOptions
+{
+    /// <summary>
+    /// Gets or sets a value indicating whether the source text should be persisted in the database.
+    /// </summary>
+    /// <value>
+    /// Defaults to <see langword="false"/> if not set.
+    /// </value>
+    public bool DoNotPersistSourceText { get; init; }
+}

dotnet/samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step02_ExternalDataSourceRAG/AgentWithRAG_Step02_ExternalDataSourceRAG.csproj

@@ -0,0 +1,22 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+    <PackageReference Include="Microsoft.SemanticKernel.Connectors.Qdrant" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step02_ExternalDataSourceRAG/Program.cs

@@ -0,0 +1,132 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to use Qdrant to add retrieval augmented generation (RAG) capabilities to an AI agent.
+// While the sample is using Qdrant, it can easily be replaced with any other vector store that implements the Microsoft.Extensions.VectorData abstractions.
+// The TextSearchProvider runs a search against the vector store before each model invocation and injects the results into the model context.
+
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.Data;
+using Microsoft.Extensions.AI;
+using Microsoft.Extensions.VectorData;
+using Microsoft.SemanticKernel.Connectors.Qdrant;
+using OpenAI;
+using Qdrant.Client;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var embeddingDeploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-3-large";
+var afOverviewUrl = "https://github.com/MicrosoftDocs/semantic-kernel-docs/blob/main/agent-framework/overview/agent-framework-overview.md";
+var afMigrationUrl = "https://raw.githubusercontent.com/MicrosoftDocs/semantic-kernel-docs/refs/heads/main/agent-framework/migration-guide/from-semantic-kernel/index.md";
+
+AzureOpenAIClient azureOpenAIClient = new(
+    new Uri(endpoint),
+    new AzureCliCredential());
+
+// Create a Qdrant vector store that uses the Azure OpenAI embedding model to generate embeddings.
+QdrantClient client = new("localhost");
+VectorStore vectorStore = new QdrantVectorStore(client, ownsClient: true, new()
+{
+    EmbeddingGenerator = azureOpenAIClient.GetEmbeddingClient(embeddingDeploymentName).AsIEmbeddingGenerator()
+});
+
+// Create a collection and upsert some text into it.
+var documentationCollection = vectorStore.GetCollection<Guid, DocumentationChunk>("documentation");
+await documentationCollection.EnsureCollectionDeletedAsync(); // Clear out any data from previous runs.
+await documentationCollection.EnsureCollectionExistsAsync();
+await UploadDataFromMarkdown(afOverviewUrl, "Microsoft Agent Framework Overview", documentationCollection, 2000, 200);
+await UploadDataFromMarkdown(afMigrationUrl, "Semantic Kernel to Microsoft Agent Framework Migration Guide", documentationCollection, 2000, 200);
+
+// Create an adapter function that the TextSearchProvider can use to run searches against the collection.
+Func<string, CancellationToken, Task<IEnumerable<TextSearchProvider.TextSearchResult>>> SearchAdapter = async (text, ct) =>
+{
+    List<TextSearchProvider.TextSearchResult> results = [];
+    await foreach (var result in documentationCollection.SearchAsync(text, 5, cancellationToken: ct))
+    {
+        results.Add(new TextSearchProvider.TextSearchResult
+        {
+            SourceName = result.Record.SourceName,
+            SourceLink = result.Record.SourceLink,
+            Text = result.Record.Text ?? string.Empty,
+            RawRepresentation = result
+        });
+    }
+    return results;
+};
+
+// Configure the options for the TextSearchProvider.
+TextSearchProviderOptions textSearchOptions = new()
+{
+    // Run the search prior to every model invocation.
+    SearchTime = TextSearchProviderOptions.TextSearchBehavior.BeforeAIInvoke,
+    // Use up to 4 recent messages when searching so that searches
+    // still produce valuable results even when the user is referring
+    // back to previous messages in their request.
+    RecentMessageMemoryLimit = 5
+};
+
+// Create the AI agent with the TextSearchProvider as the AI context provider.
+AIAgent agent = azureOpenAIClient
+    .GetChatClient(deploymentName)
+    .CreateAIAgent(new ChatClientAgentOptions
+    {
+        Instructions = "You are a helpful support specialist for the Microsoft Agent Framework. Answer questions using the provided context and cite the source document when available. Keep responses brief.",
+        AIContextProviderFactory = ctx => new TextSearchProvider(SearchAdapter, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions)
+    });
+
+AgentThread thread = agent.GetNewThread();
+
+Console.WriteLine(">> Asking about SK threads\n");
+Console.WriteLine(await agent.RunAsync("Hi! How do I create a thread in Semantic Kernel?", thread));
+
+// Here we are asking a very vague question when taken out of context,
+// but since we are including previous messages in our search using RecentMessageMemoryLimit
+// the RAG search should still produce useful results.
+Console.WriteLine("\n>> Asking about AF threads\n");
+Console.WriteLine(await agent.RunAsync("and in Agent Framework?", thread));
+
+Console.WriteLine("\n>> Contrasting Approaches\n");
+Console.WriteLine(await agent.RunAsync("Please contrast the two approaches", thread));
+
+Console.WriteLine("\n>> Asking about ancestry\n");
+Console.WriteLine(await agent.RunAsync("What are the predecessors to the Agent Framework?", thread));
+
+static async Task UploadDataFromMarkdown(string markdownUrl, string sourceName, VectorStoreCollection<Guid, DocumentationChunk> vectorStoreCollection, int chunkSize, int overlap)
+{
+    // Download the markdown from the given url.
+    using HttpClient client = new();
+    var markdown = await client.GetStringAsync(new Uri(markdownUrl));
+
+    // Chunk it into separate parts with some overlap between chunks
+    var chunks = new List<DocumentationChunk>();
+    for (int i = 0; i < markdown.Length; i += chunkSize)
+    {
+        var chunk = new DocumentationChunk
+        {
+            Key = Guid.NewGuid(),
+            SourceLink = markdownUrl,
+            SourceName = sourceName,
+            Text = markdown.Substring(i, Math.Min(chunkSize + overlap, markdown.Length - i))
+        };
+        chunks.Add(chunk);
+    }
+
+    // Upsert each chunk into the provided vector store.
+    await vectorStoreCollection.UpsertAsync(chunks);
+}
+
+// Data model that defines the database schema we want to use.
+internal sealed class DocumentationChunk
+{
+    [VectorStoreKey]
+    public Guid Key { get; set; }
+    [VectorStoreData]
+    public string SourceLink { get; set; } = string.Empty;
+    [VectorStoreData]
+    public string SourceName { get; set; } = string.Empty;
+    [VectorStoreData]
+    public string Text { get; set; } = string.Empty;
+    [VectorStoreVector(Dimensions: 3072)]
+    public string Embedding => this.Text;
+}

dotnet/samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step02_ExternalDataSourceRAG/README.md

@@ -0,0 +1,60 @@
+# Agent Framework Retrieval Augmented Generation (RAG) with an external Vector Store with a custom schema
+
+This sample demonstrates how to create and run an agent that uses Retrieval Augmented Generation (RAG) with an external vector store.
+It also uses a custom schema for the documents stored in the vector store.
+This sample uses Qdrant for the vector store, but this can easily be swapped out for any vector store that has a Microsoft.Extensions.VectorStore implementation.
+
+## Prerequisites
+
+- .NET 8.0 SDK or later
+- Azure OpenAI service endpoint
+- Both a chat completion and embedding deployment configured in the Azure OpenAI resource
+- Azure CLI installed and authenticated (for Azure credential authentication)
+- User has the `Cognitive Services OpenAI Contributor` role for the Azure OpenAI resource.
+- An existing Qdrant instance. You can use a managed service or run a local instance using Docker, but the sample assumes the instance is running locally.
+
+**Note**: These samples use Azure OpenAI models. For more information, see [how to deploy Azure OpenAI models with Azure AI Foundry](https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/deploy-models-openai).
+
+**Note**: These samples use Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource and have the `Cognitive Services OpenAI Contributor` role. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+
+## Running the sample from the console
+
+Set the following environment variables:
+
+```powershell
+$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME="text-embedding-3-large"  # Optional, defaults to text-embedding-3-large
+```
+
+If the variables are not set, you will be prompted for the values when running the samples.
+
+To use Qdrant in docker locally, start your Qdrant instance using the default port mappings.
+
+```powershell
+docker run -d --name qdrant -p 6333:6333 -p 6334:6334 qdrant/qdrant:latest
+```
+
+Execute the following command to build the sample:
+
+```powershell
+dotnet build
+```
+
+Execute the following command to run the sample:
+
+```powershell
+dotnet run --no-build
+```
+
+Or just build and run in one step:
+
+```powershell
+dotnet run
+```
+
+## Running the sample from Visual Studio
+
+Open the solution in Visual Studio and set the sample project as the startup project. Then, run the project using the built-in debugger or by pressing `F5`.
+
+You will be prompted for any required environment variables if they are not already set.

dotnet/samples/GettingStarted/AgentWithRAG/README.md

@@ -0,0 +1,8 @@
+# Agent Framework Retrieval Augmented Generation (RAG)
+
+These samples show how to create an agent with the Agent Framework that uses Retrieval Augmented Generation (RAG) to enhance its responses with information from a knowledge base.
+
+|Sample|Description|
+|---|---|
+|[Basic Text RAG](./AgentWithRAG_Step01_BasicTextRAG/)|This sample demonstrates how to create and run a basic agent with simple text Retrieval Augmented Generation (RAG).|
+|[RAG with external Vector Store and custom schema](./AgentWithRAG_Step02_ExternalDataSourceRAG/)|This sample demonstrates how to create and run an agent that uses Retrieval Augmented Generation (RAG) with an external vector store. It also uses a custom schema for the documents stored in the vector store.|

dotnet/samples/GettingStarted/Agents/Agent_Step03.2_UsingFunctionTools_FromOpenAPI/Agent_Step03.2_UsingFunctionTools_FromOpenAPI.csproj

@@ -0,0 +1,28 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+    <PackageReference Include="Microsoft.SemanticKernel.Plugins.OpenApi" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <None Update="OpenAPISpec.json">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/Agents/Agent_Step03.2_UsingFunctionTools_FromOpenAPI/OpenAPISpec.json

@@ -0,0 +1,354 @@
+{
+    "openapi": "3.0.1",
+    "info": {
+        "title": "Github Versions API",
+        "version": "1.0.0"
+    },
+    "servers": [
+        {
+            "url": "https://api.github.com"
+        }
+    ],
+    "components": {
+        "schemas": {
+            "basic-error": {
+                "title": "Basic Error",
+                "description": "Basic Error",
+                "type": "object",
+                "properties": {
+                    "message": {
+                        "type": "string"
+                    },
+                    "documentation_url": {
+                        "type": "string"
+                    },
+                    "url": {
+                        "type": "string"
+                    },
+                    "status": {
+                        "type": "string"
+                    }
+                }
+            },
+            "label": {
+                "title": "Label",
+                "description": "Color-coded labels help you categorize and filter your issues (just like labels in Gmail).",
+                "type": "object",
+                "properties": {
+                    "id": {
+                        "description": "Unique identifier for the label.",
+                        "type": "integer",
+                        "format": "int64",
+                        "example": 208045946
+                    },
+                    "node_id": {
+                        "type": "string",
+                        "example": "MDU6TGFiZWwyMDgwNDU5NDY="
+                    },
+                    "url": {
+                        "description": "URL for the label",
+                        "example": "https://api.github.com/repositories/42/labels/bug",
+                        "type": "string",
+                        "format": "uri"
+                    },
+                    "name": {
+                        "description": "The name of the label.",
+                        "example": "bug",
+                        "type": "string"
+                    },
+                    "description": {
+                        "description": "Optional description of the label, such as its purpose.",
+                        "type": "string",
+                        "example": "Something isn't working",
+                        "nullable": true
+                    },
+                    "color": {
+                        "description": "6-character hex code, without the leading #, identifying the color",
+                        "example": "FFFFFF",
+                        "type": "string"
+                    },
+                    "default": {
+                        "description": "Whether this label comes by default in a new repository.",
+                        "type": "boolean",
+                        "example": true
+                    }
+                },
+                "required": [
+                    "id",
+                    "node_id",
+                    "url",
+                    "name",
+                    "description",
+                    "color",
+                    "default"
+                ]
+            },
+            "tag": {
+                "title": "Tag",
+                "description": "Tag",
+                "type": "object",
+                "properties": {
+                    "name": {
+                        "type": "string",
+                        "example": "v0.1"
+                    },
+                    "commit": {
+                        "type": "object",
+                        "properties": {
+                            "sha": {
+                                "type": "string"
+                            },
+                            "url": {
+                                "type": "string",
+                                "format": "uri"
+                            }
+                        },
+                        "required": [
+                            "sha",
+                            "url"
+                        ]
+                    },
+                    "zipball_url": {
+                        "type": "string",
+                        "format": "uri",
+                        "example": "https://github.com/octocat/Hello-World/zipball/v0.1"
+                    },
+                    "tarball_url": {
+                        "type": "string",
+                        "format": "uri",
+                        "example": "https://github.com/octocat/Hello-World/tarball/v0.1"
+                    },
+                    "node_id": {
+                        "type": "string"
+                    }
+                },
+                "required": [
+                    "name",
+                    "node_id",
+                    "commit",
+                    "zipball_url",
+                    "tarball_url"
+                ]
+            }
+        },
+        "examples": {
+            "label-items": {
+                "value": [
+                    {
+                        "id": 208045946,
+                        "node_id": "MDU6TGFiZWwyMDgwNDU5NDY=",
+                        "url": "https://api.github.com/repos/octocat/Hello-World/labels/bug",
+                        "name": "bug",
+                        "description": "Something isn't working",
+                        "color": "f29513",
+                        "default": true
+                    },
+                    {
+                        "id": 208045947,
+                        "node_id": "MDU6TGFiZWwyMDgwNDU5NDc=",
+                        "url": "https://api.github.com/repos/octocat/Hello-World/labels/enhancement",
+                        "name": "enhancement",
+                        "description": "New feature or request",
+                        "color": "a2eeef",
+                        "default": false
+                    }
+                ]
+            },
+            "tag-items": {
+                "value": [
+                    {
+                        "name": "v0.1",
+                        "commit": {
+                            "sha": "c5b97d5ae6c19d5c5df71a34c7fbeeda2479ccbc",
+                            "url": "https://api.github.com/repos/octocat/Hello-World/commits/c5b97d5ae6c19d5c5df71a34c7fbeeda2479ccbc"
+                        },
+                        "zipball_url": "https://github.com/octocat/Hello-World/zipball/v0.1",
+                        "tarball_url": "https://github.com/octocat/Hello-World/tarball/v0.1",
+                        "node_id": "MDQ6VXNlcjE="
+                    }
+                ]
+            }
+        },
+        "parameters": {
+            "owner": {
+                "name": "owner",
+                "description": "The account owner of the repository. The name is not case sensitive.",
+                "in": "path",
+                "required": true,
+                "schema": {
+                    "type": "string"
+                }
+            },
+            "repo": {
+                "name": "repo",
+                "description": "The name of the repository without the `.git` extension. The name is not case sensitive.",
+                "in": "path",
+                "required": true,
+                "schema": {
+                    "type": "string"
+                }
+            },
+            "per-page": {
+                "name": "per_page",
+                "description": "The number of results per page (max 100). For more information, see \"[Using pagination in the REST API](https://docs.github.com/rest/using-the-rest-api/using-pagination-in-the-rest-api).\"",
+                "in": "query",
+                "schema": {
+                    "type": "integer",
+                    "default": 30
+                }
+            },
+            "page": {
+                "name": "page",
+                "description": "The page number of the results to fetch. For more information, see \"[Using pagination in the REST API](https://docs.github.com/rest/using-the-rest-api/using-pagination-in-the-rest-api).\"",
+                "in": "query",
+                "schema": {
+                    "type": "integer",
+                    "default": 1
+                }
+            }
+        },
+        "responses": {
+            "not_found": {
+                "description": "Resource not found",
+                "content": {
+                    "application/json": {
+                        "schema": {
+                            "$ref": "#/components/schemas/basic-error"
+                        }
+                    }
+                }
+            }
+        },
+        "headers": {
+            "link": {
+                "example": "<https://api.github.com/resource?page=2>; rel=\"next\", <https://api.github.com/resource?page=5>; rel=\"last\"",
+                "schema": {
+                    "type": "string"
+                }
+            }
+        }
+    },
+    "paths": {
+        "/repos/{owner}/{repo}/tags": {
+            "get": {
+                "summary": "List repository tags",
+                "description": "",
+                "tags": [
+                    "repos"
+                ],
+                "operationId": "repos/list-tags",
+                "externalDocs": {
+                    "description": "API method documentation",
+                    "url": "https://docs.github.com/rest/repos/repos#list-repository-tags"
+                },
+                "parameters": [
+                    {
+                        "$ref": "#/components/parameters/owner"
+                    },
+                    {
+                        "$ref": "#/components/parameters/repo"
+                    },
+                    {
+                        "$ref": "#/components/parameters/per-page"
+                    },
+                    {
+                        "$ref": "#/components/parameters/page"
+                    }
+                ],
+                "responses": {
+                    "200": {
+                        "description": "Response",
+                        "content": {
+                            "application/json": {
+                                "schema": {
+                                    "type": "array",
+                                    "items": {
+                                        "$ref": "#/components/schemas/tag"
+                                    }
+                                },
+                                "examples": {
+                                    "default": {
+                                        "$ref": "#/components/examples/tag-items"
+                                    }
+                                }
+                            }
+                        },
+                        "headers": {
+                            "Link": {
+                                "$ref": "#/components/headers/link"
+                            }
+                        }
+                    }
+                },
+                "x-github": {
+                    "githubCloudOnly": false,
+                    "enabledForGitHubApps": true,
+                    "category": "repos",
+                    "subcategory": "repos"
+                }
+            }
+        },
+        "/repos/{owner}/{repo}/labels": {
+            "get": {
+                "summary": "List labels for a repository",
+                "description": "Lists all labels for a repository.",
+                "tags": [
+                    "issues"
+                ],
+                "operationId": "issues/list-labels-for-repo",
+                "externalDocs": {
+                    "description": "API method documentation",
+                    "url": "https://docs.github.com/rest/issues/labels#list-labels-for-a-repository"
+                },
+                "parameters": [
+                    {
+                        "$ref": "#/components/parameters/owner"
+                    },
+                    {
+                        "$ref": "#/components/parameters/repo"
+                    },
+                    {
+                        "$ref": "#/components/parameters/per-page"
+                    },
+                    {
+                        "$ref": "#/components/parameters/page"
+                    }
+                ],
+                "responses": {
+                    "200": {
+                        "description": "Response",
+                        "content": {
+                            "application/json": {
+                                "schema": {
+                                    "type": "array",
+                                    "items": {
+                                        "$ref": "#/components/schemas/label"
+                                    }
+                                },
+                                "examples": {
+                                    "default": {
+                                        "$ref": "#/components/examples/label-items"
+                                    }
+                                }
+                            }
+                        },
+                        "headers": {
+                            "Link": {
+                                "$ref": "#/components/headers/link"
+                            }
+                        }
+                    },
+                    "404": {
+                        "$ref": "#/components/responses/not_found"
+                    }
+                },
+                "x-github": {
+                    "githubCloudOnly": false,
+                    "enabledForGitHubApps": true,
+                    "category": "issues",
+                    "subcategory": "labels"
+                }
+            }
+        }
+    }
+}

dotnet/samples/GettingStarted/Agents/Agent_Step03.2_UsingFunctionTools_FromOpenAPI/Program.cs

@@ -0,0 +1,33 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to use a ChatClientAgent with function tools provided via an OpenAPI spec.
+// It uses functionality from Semantic Kernel to parse the OpenAPI spec and create function tools to use with the Agent Framework Agent.
+
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+using Microsoft.SemanticKernel;
+using Microsoft.SemanticKernel.Plugins.OpenApi;
+using OpenAI;
+
+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";
+
+// Load the OpenAPI Spec from a file.
+KernelPlugin plugin = await OpenApiKernelPluginFactory.CreateFromOpenApiAsync("github", "OpenAPISpec.json");
+
+// Convert the Semantic Kernel plugin to Agent Framework function tools.
+// This requires a dummy Kernel instance, since KernelFunctions cannot execute without one.
+Kernel kernel = new();
+List<AITool> tools = plugin.Select(x => x.WithKernel(kernel)).Cast<AITool>().ToList();
+
+// Create the chat client and agent, and provide the OpenAPI function tools to the agent.
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+    .GetChatClient(deploymentName)
+    .CreateAIAgent(instructions: "You are a helpful assistant", tools: tools);
+
+// Run the agent with the OpenAPI function tools.
+Console.WriteLine(await agent.RunAsync("Please list the names, colors and descriptions of all the labels available in the microsoft/agent-framework repository on github."));

dotnet/samples/GettingStarted/Agents/Agent_Step10_AsMcpTool/Agent_Step10_AsMcpTool.csproj

@@ -18,7 +18,7 @@
   </ItemGroup>
 
   <ItemGroup>
-    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI.Persistent\Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
   </ItemGroup>
   
 </Project>

dotnet/samples/GettingStarted/Agents/Agent_Step17_BackgroundResponses/Program.cs

@@ -1,6 +1,6 @@
 // Copyright (c) Microsoft. All rights reserved.
 
-// This sample shows how to use background responses with ChatClientAgent and OpenAI Responses.
+// This sample shows how to use background responses with ChatClientAgent and Azure OpenAI Responses.
 
 using Azure.AI.OpenAI;
 using Azure.Identity;

dotnet/samples/GettingStarted/Agents/Agent_Step17_BackgroundResponses/README.md

@@ -1,6 +1,6 @@
 # What This Sample Shows
 
-This sample demonstrates how to use background responses with ChatCompletionAgent and OpenAI Responses for long-running operations. Background responses support:
+This sample demonstrates how to use background responses with ChatCompletionAgent and Azure OpenAI Responses for long-running operations. Background responses support:
 
 - **Polling for completion** - Non-streaming APIs can start a background operation and return a continuation token. Poll with the token until the response completes.
 - **Resuming after interruption** - Streaming APIs can be interrupted and resumed from the last update using the continuation token.
@@ -14,7 +14,10 @@ For more information, see the [official documentation](https://learn.microsoft.c
 Before you begin, ensure you have the following prerequisites:
 
 - .NET 8.0 SDK or later
-- OpenAI api key
+- Azure OpenAI service endpoint and deployment configured
+- Azure CLI installed and authenticated (for Azure credential authentication)
+
+**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
 
 Set the following environment variables:
 

dotnet/samples/GettingStarted/Agents/Agent_Step18_TextSearchRag/Agent_Step18_TextSearchRag.csproj

@@ -0,0 +1,21 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/Agents/Agent_Step18_TextSearchRag/Program.cs

@@ -0,0 +1,82 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to use TextSearchProvider to add retrieval augmented generation (RAG)
+// capabilities to an AI agent. The provider runs a search against an external knowledge base
+// before each model invocation and injects the results into the model context.
+
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.Data;
+using Microsoft.Extensions.AI;
+using OpenAI;
+
+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";
+
+TextSearchProviderOptions textSearchOptions = new()
+{
+    // Run the search prior to every model invocation and keep a short rolling window of conversation context.
+    SearchTime = TextSearchProviderOptions.TextSearchBehavior.BeforeAIInvoke,
+    RecentMessageMemoryLimit = 6,
+};
+
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+    .GetChatClient(deploymentName)
+    .CreateAIAgent(new ChatClientAgentOptions
+    {
+        Instructions = "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available.",
+        AIContextProviderFactory = ctx => new TextSearchProvider(MockSearchAsync, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions)
+    });
+
+AgentThread thread = agent.GetNewThread();
+
+Console.WriteLine(">> Asking about returns\n");
+Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", thread));
+
+Console.WriteLine("\n>> Asking about shipping\n");
+Console.WriteLine(await agent.RunAsync("How long does standard shipping usually take?", thread));
+
+Console.WriteLine("\n>> Asking about product care\n");
+Console.WriteLine(await agent.RunAsync("What is the best way to maintain the TrailRunner tent fabric?", thread));
+
+static Task<IEnumerable<TextSearchProvider.TextSearchResult>> MockSearchAsync(string query, CancellationToken cancellationToken)
+{
+    // The mock search inspects the user's question and returns pre-defined snippets
+    // that resemble documents stored in an external knowledge source.
+    List<TextSearchProvider.TextSearchResult> results = new();
+
+    if (query.Contains("return", StringComparison.OrdinalIgnoreCase) || query.Contains("refund", StringComparison.OrdinalIgnoreCase))
+    {
+        results.Add(new()
+        {
+            SourceName = "Contoso Outdoors Return Policy",
+            SourceLink = "https://contoso.com/policies/returns",
+            Text = "Customers may return any item within 30 days of delivery. Items should be unused and include original packaging. Refunds are issued to the original payment method within 5 business days of inspection."
+        });
+    }
+
+    if (query.Contains("shipping", StringComparison.OrdinalIgnoreCase))
+    {
+        results.Add(new()
+        {
+            SourceName = "Contoso Outdoors Shipping Guide",
+            SourceLink = "https://contoso.com/help/shipping",
+            Text = "Standard shipping is free on orders over $50 and typically arrives in 3-5 business days within the continental United States. Expedited options are available at checkout."
+        });
+    }
+
+    if (query.Contains("tent", StringComparison.OrdinalIgnoreCase) || query.Contains("fabric", StringComparison.OrdinalIgnoreCase))
+    {
+        results.Add(new()
+        {
+            SourceName = "TrailRunner Tent Care Instructions",
+            SourceLink = "https://contoso.com/manuals/trailrunner-tent",
+            Text = "Clean the tent fabric with lukewarm water and a non-detergent soap. Allow it to air dry completely before storage and avoid prolonged UV exposure to extend the lifespan of the waterproof coating."
+        });
+    }
+
+    return Task.FromResult<IEnumerable<TextSearchProvider.TextSearchResult>>(results);
+}

dotnet/samples/GettingStarted/Agents/Agent_Step19_Mem0Provider/Agent_Step19_Mem0Provider.csproj

@@ -0,0 +1,22 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Mem0\Microsoft.Agents.AI.Mem0.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/Agents/Agent_Step19_Mem0Provider/Program.cs

@@ -0,0 +1,64 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to use the Mem0Provider to persist and recall memories for an agent.
+// The sample stores conversation messages in a Mem0 service and retrieves relevant memories
+// for subsequent invocations, even across new threads.
+
+using System.Net.Http.Headers;
+using System.Text.Json;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.Mem0;
+using Microsoft.Extensions.AI;
+using OpenAI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+var mem0ServiceUri = Environment.GetEnvironmentVariable("MEM0_ENDPOINT") ?? throw new InvalidOperationException("MEM0_ENDPOINT is not set.");
+var mem0ApiKey = Environment.GetEnvironmentVariable("MEM0_APIKEY") ?? throw new InvalidOperationException("MEM0_APIKEY is not set.");
+
+// Create an HttpClient for Mem0 with the required base address and authentication.
+using HttpClient mem0HttpClient = new();
+mem0HttpClient.BaseAddress = new Uri(mem0ServiceUri);
+mem0HttpClient.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Token", mem0ApiKey);
+
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+    .GetChatClient(deploymentName)
+    .CreateAIAgent(new ChatClientAgentOptions()
+    {
+        Instructions = "You are a friendly travel assistant. Use known memories about the user when responding, and do not invent details.",
+        AIContextProviderFactory = ctx => ctx.SerializedState.ValueKind is not JsonValueKind.Null or JsonValueKind.Undefined
+            // If each thread should have its own Mem0 scope, you can create a new id per thread here:
+            // ? new Mem0Provider(mem0HttpClient, new Mem0ProviderScope() { ThreadId = Guid.NewGuid().ToString() })
+            // In this case we are storing memories scoped by application and user instead so that memories are retained across threads.
+            ? new Mem0Provider(mem0HttpClient, new Mem0ProviderScope() { ApplicationId = "getting-started-agents", UserId = "sample-user" })
+            // For cases where we are restoring from serialized state:
+            : new Mem0Provider(mem0HttpClient, ctx.SerializedState, ctx.JsonSerializerOptions)
+    });
+
+AgentThread thread = agent.GetNewThread();
+
+// Clear any existing memories for this scope to demonstrate fresh behavior.
+Mem0Provider mem0Provider = thread.GetService<Mem0Provider>()!;
+await mem0Provider.ClearStoredMemoriesAsync();
+
+Console.WriteLine(await agent.RunAsync("Hi there! My name is Taylor and I'm planning a hiking trip to Patagonia in November.", thread));
+Console.WriteLine(await agent.RunAsync("I'm travelling with my sister and we love finding scenic viewpoints.", thread));
+
+Console.WriteLine("\nWaiting briefly for Mem0 to index the new memories...\n");
+await Task.Delay(TimeSpan.FromSeconds(2));
+
+Console.WriteLine(await agent.RunAsync("What do you already know about my upcoming trip?", thread));
+
+Console.WriteLine("\n>> Serialize and deserialize the thread to demonstrate persisted state\n");
+JsonElement serializedThread = thread.Serialize();
+AgentThread restoredThread = agent.DeserializeThread(serializedThread);
+Console.WriteLine(await agent.RunAsync("Can you recap the personal details you remember?", restoredThread));
+
+Console.WriteLine("\n>> Start a new thread that shares the same Mem0 scope\n");
+AgentThread newThread = agent.GetNewThread();
+Console.WriteLine(await agent.RunAsync("Summarize what you already know about me.", newThread));

dotnet/samples/GettingStarted/Agents/Agent_Step20_BackgroundResponsesWithToolsAndPersistence/Agent_Step20_BackgroundResponsesWithToolsAndPersistence.csproj

@@ -0,0 +1,20 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+ <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+  
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+  
+</Project>

dotnet/samples/GettingStarted/Agents/Agent_Step20_BackgroundResponsesWithToolsAndPersistence/Program.cs

@@ -0,0 +1,108 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to use background responses with ChatClientAgent and Azure OpenAI Responses for long-running operations.
+// It shows polling for completion using continuation tokens, function calling during background operations,
+// and persisting/restoring agent state between polling cycles.
+
+#pragma warning disable CA1050 // Declare types in namespaces
+
+using System.ComponentModel;
+using System.Text.Json;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+using OpenAI;
+
+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-5";
+
+var stateStore = new Dictionary<string, JsonElement?>();
+
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+     .GetOpenAIResponseClient(deploymentName)
+     .CreateAIAgent(
+        name: "SpaceNovelWriter",
+        instructions: "You are a space novel writer. Always research relevant facts and generate character profiles for the main characters before writing novels." +
+                      "Write complete chapters without asking for approval or feedback. Do not ask the user about tone, style, pace, or format preferences - just write the novel based on the request.",
+        tools: [AIFunctionFactory.Create(ResearchSpaceFactsAsync), AIFunctionFactory.Create(GenerateCharacterProfilesAsync)]);
+
+// Enable background responses (only supported by {Azure}OpenAI Responses at this time).
+AgentRunOptions options = new() { AllowBackgroundResponses = true };
+
+AgentThread thread = agent.GetNewThread();
+
+// Start the initial run.
+AgentRunResponse response = await agent.RunAsync("Write a very long novel about a team of astronauts exploring an uncharted galaxy.", thread, options);
+
+// Poll for background responses until complete.
+while (response.ContinuationToken is not null)
+{
+    PersistAgentState(thread, response.ContinuationToken);
+
+    await Task.Delay(TimeSpan.FromSeconds(10));
+
+    RestoreAgentState(agent, out thread, out object? continuationToken);
+
+    options.ContinuationToken = continuationToken;
+    response = await agent.RunAsync(thread, options);
+}
+
+Console.WriteLine(response.Text);
+
+void PersistAgentState(AgentThread thread, object? continuationToken)
+{
+    stateStore["thread"] = thread.Serialize();
+    stateStore["continuationToken"] = JsonSerializer.SerializeToElement(continuationToken, AgentAbstractionsJsonUtilities.DefaultOptions.GetTypeInfo(typeof(ResponseContinuationToken)));
+}
+
+void RestoreAgentState(AIAgent agent, out AgentThread thread, out object? continuationToken)
+{
+    JsonElement serializedThread = stateStore["thread"] ?? throw new InvalidOperationException("No serialized thread found in state store.");
+    JsonElement? serializedToken = stateStore["continuationToken"];
+
+    thread = agent.DeserializeThread(serializedThread);
+    continuationToken = serializedToken?.Deserialize(AgentAbstractionsJsonUtilities.DefaultOptions.GetTypeInfo(typeof(ResponseContinuationToken)));
+}
+
+[Description("Researches relevant space facts and scientific information for writing a science fiction novel")]
+async Task<string> ResearchSpaceFactsAsync(string topic)
+{
+    Console.WriteLine($"[ResearchSpaceFacts] Researching topic: {topic}");
+
+    // Simulate a research operation
+    await Task.Delay(TimeSpan.FromSeconds(10));
+
+    string result = topic.ToUpperInvariant() switch
+    {
+        var t when t.Contains("GALAXY") => "Research findings: Galaxies contain billions of stars. Uncharted galaxies may have unique stellar formations, exotic matter, and unexplored phenomena like dark energy concentrations.",
+        var t when t.Contains("SPACE") || t.Contains("TRAVEL") => "Research findings: Interstellar travel requires advanced propulsion systems. Challenges include radiation exposure, life support, and navigation through unknown space.",
+        var t when t.Contains("ASTRONAUT") => "Research findings: Astronauts undergo rigorous training in zero-gravity environments, emergency protocols, spacecraft systems, and team dynamics for long-duration missions.",
+        _ => $"Research findings: General space exploration facts related to {topic}. Deep space missions require advanced technology, crew resilience, and contingency planning for unknown scenarios."
+    };
+
+    Console.WriteLine("[ResearchSpaceFacts] Research complete");
+    return result;
+}
+
+[Description("Generates character profiles for the main astronaut characters in the novel")]
+async Task<IEnumerable<string>> GenerateCharacterProfilesAsync()
+{
+    Console.WriteLine("[GenerateCharacterProfiles] Generating character profiles...");
+
+    // Simulate a character generation operation
+    await Task.Delay(TimeSpan.FromSeconds(10));
+
+    string[] profiles = [
+        "Captain Elena Voss: A seasoned mission commander with 15 years of experience. Strong-willed and decisive, she struggles with the weight of responsibility for her crew. Former military pilot turned astronaut.",
+            "Dr. James Chen: Chief science officer and astrophysicist. Brilliant but socially awkward, he finds solace in data and discovery. His curiosity often pushes the mission into uncharted territory.",
+            "Lieutenant Maya Torres: Navigation specialist and youngest crew member. Optimistic and tech-savvy, she brings fresh perspective and innovative problem-solving to challenges.",
+            "Commander Marcus Rivera: Chief engineer with expertise in spacecraft systems. Pragmatic and resourceful, he can fix almost anything with limited resources. Values crew safety above all.",
+            "Dr. Amara Okafor: Medical officer and psychologist. Empathetic and observant, she helps maintain crew morale and mental health during the long journey. Expert in space medicine."
+    ];
+
+    Console.WriteLine($"[GenerateCharacterProfiles] Generated {profiles.Length} character profiles");
+    return profiles;
+}

dotnet/samples/GettingStarted/Agents/Agent_Step20_BackgroundResponsesWithToolsAndPersistence/README.md

@@ -0,0 +1,28 @@
+# What This Sample Shows
+
+This sample demonstrates how to use background responses with ChatCompletionAgent and Azure OpenAI Responses for long-running operations. Background responses support:
+
+- **Polling for completion** - Non-streaming APIs can start a background operation and return a continuation token. Poll with the token until the response completes.
+- **Function calling** - Functions can be called during background operations.
+- **State persistence** - Thread and continuation token can be persisted and restored between polling cycles.
+
+> **Note:** Background responses are currently only supported by OpenAI Responses.
+
+For more information, see the [official documentation](https://learn.microsoft.com/en-us/agent-framework/user-guide/agents/agent-background-responses?pivots=programming-language-csharp).
+
+# Prerequisites
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 8.0 SDK or later
+- Azure OpenAI service endpoint and deployment configured
+- Azure CLI installed and authenticated (for Azure credential authentication)
+
+**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+
+Set the following environment variables:
+
+```powershell
+$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5"  # Optional, defaults to gpt-5
+```

dotnet/samples/GettingStarted/Agents/README.md

@@ -28,7 +28,8 @@ Before you begin, ensure you have the following prerequisites:
 |---|---|
 |[Running a simple agent](./Agent_Step01_Running/)|This sample demonstrates how to create and run a basic agent with instructions|
 |[Multi-turn conversation with a simple agent](./Agent_Step02_MultiturnConversation/)|This sample demonstrates how to implement a multi-turn conversation with a simple agent|
-|[Using function tools with a simple agent](./Agent_Step03_UsingFunctionTools/)|This sample demonstrates how to use function tools with a simple agent|
+|[Using function tools with a simple agent](./Agent_Step03.1_UsingFunctionTools/)|This sample demonstrates how to use function tools with a simple agent|
+|[Using OpenAPI function tools with a simple agent](./Agent_Step03.2_UsingFunctionTools_FromOpenAPI/)|This sample demonstrates how to create function tools from an OpenAPI spec and use them with a simple agent|
 |[Using function tools with approvals](./Agent_Step04_UsingFunctionToolsWithApprovals/)|This sample demonstrates how to use function tools where approvals require human in the loop approvals before execution|
 |[Structured output with a simple agent](./Agent_Step05_StructuredOutput/)|This sample demonstrates how to use structured output with a simple agent|
 |[Persisted conversations with a simple agent](./Agent_Step06_PersistedConversations/)|This sample demonstrates how to persist conversations and reload them later. This is useful for cases where an agent is hosted in a stateless service|
@@ -43,6 +44,9 @@ Before you begin, ensure you have the following prerequisites:
 |[Using plugins with an agent](./Agent_Step15_Plugins/)|This sample demonstrates how to use plugins with an agent|
 |[Reducing chat history size](./Agent_Step16_ChatReduction/)|This sample demonstrates how to reduce the chat history to constrain its size, where chat history is maintained locally|
 |[Background responses](./Agent_Step17_BackgroundResponses/)|This sample demonstrates how to use background responses for long-running operations with polling and resumption support|
+|[Adding RAG with text search](./Agent_Step18_TextSearchRag/)|This sample demonstrates how to enrich agent responses with retrieval augmented generation using the text search provider|
+|[Using Mem0-backed memory](./Agent_Step19_Mem0Provider/)|This sample demonstrates how to use the Mem0Provider to persist and recall memories across conversations|
+|[Background responses with tools and persistence](./Agent_Step20_BackgroundResponsesWithToolsAndPersistence/)|This sample demonstrates advanced background response scenarios including function calling during background operations and state persistence|
 
 ## Running the samples from the console
 

dotnet/samples/GettingStarted/DevUI/DevUI_Step01_BasicUsage/DevUI_Step01_BasicUsage.csproj

@@ -0,0 +1,25 @@
+<Project Sdk="Microsoft.NET.Sdk.Web">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+    <RootNamespace>DevUI_Step01_BasicUsage</RootNamespace>
+    <AutoGenerateBindingRedirects>true</AutoGenerateBindingRedirects>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.DevUI\Microsoft.Agents.AI.DevUI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Hosting\Microsoft.Agents.AI.Hosting.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Hosting.OpenAI\Microsoft.Agents.AI.Hosting.OpenAI.csproj" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+    <PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-rc.2.25502.107" />
+  </ItemGroup>
+
+</Project>