Updated package versions (#2104 )

Python: Use the last entry in the task history to avoid empty responses (#2101 )
* Use the last entry in the task history to avoid empty responses * History only contains Messages
2026-06-16 21:04:09 +08:00 · 2025-11-11 23:30:34 +00:00 · 2025-11-11 22:56:53 +00:00 · 2025-11-11 20:00:59 +00:00 · 2025-11-11 19:43:26 +00:00 · 2025-11-11 19:01:37 +00:00
1074 changed files with 117207 additions and 17008 deletions
@@ -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/
@@ -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>
@@ -38,7 +38,7 @@ jobs:

      # Initializes the CodeQL tools for scanning.
      - name: Initialize CodeQL
-        uses: github/codeql-action/init@v3
+        uses: github/codeql-action/init@v4
        with:
          languages: ${{ matrix.language }}
          # If you wish to specify custom queries, you can do so here or in a config file.
@@ -51,7 +51,7 @@ jobs:
      # Autobuild attempts to build any compiled languages  (C/C++, C#, Go, or Java).
      # If this step fails, then you should remove it and run the build manually (see below)
      - name: Autobuild
-        uses: github/codeql-action/autobuild@v3
+        uses: github/codeql-action/autobuild@v4

      # ℹ️ Command-line programs to run using the OS shell.
      # 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun
@@ -64,6 +64,6 @@ jobs:
      #     ./location_of_script_within_repo/buildscript.sh

      - name: Perform CodeQL Analysis
-        uses: github/codeql-action/analyze@v3
+        uses: github/codeql-action/analyze@v4
        with:
          category: "/language:${{matrix.language}}"
@@ -8,11 +8,11 @@ name: dotnet-build-and-test
 on:
  workflow_dispatch:
  pull_request:
-    branches: ["main"]
+    branches: ["main", "feature*"]
  merge_group:
-    branches: ["main"]
+    branches: ["main", "feature*"]
  push:
-    branches: ["main"]
+    branches: ["main", "feature*"]
  schedule:
    - cron: "0 0 * * *" # Run at midnight UTC daily

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

      - name: Setup dotnet
@@ -127,7 +128,15 @@ jobs:
        run: |
          export UT_PROJECTS=$(find ./dotnet -type f -name "*.UnitTests.csproj" | tr '\n' ' ')
          for project in $UT_PROJECTS; do
-            dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx --collect:"XPlat Code Coverage" --results-directory:"TestResults/Coverage/" -- DataCollectionRunSettings.DataCollectors.DataCollector.Configuration.ExcludeByAttribute=GeneratedCodeAttribute,CompilerGeneratedAttribute,ExcludeFromCodeCoverageAttribute
+            # Query the project's target frameworks using MSBuild with the current configuration
+            target_frameworks=$(dotnet msbuild $project -getProperty:TargetFrameworks -p:Configuration=${{ matrix.configuration }} -nologo 2>/dev/null | tr -d '\r')
+            
+            # Check if the project supports the target framework
+            if [[ "$target_frameworks" == *"${{ matrix.targetFramework }}"* ]]; then
+              dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx --collect:"XPlat Code Coverage" --results-directory:"TestResults/Coverage/" -- DataCollectionRunSettings.DataCollectors.DataCollector.Configuration.ExcludeByAttribute=GeneratedCodeAttribute,CompilerGeneratedAttribute,ExcludeFromCodeCoverageAttribute
+            else
+              echo "Skipping $project - does not support target framework ${{ matrix.targetFramework }} (supports: $target_frameworks)"
+            fi
          done
      
      - name: Log event name and matrix integration-tests
@@ -148,7 +157,15 @@ jobs:
        run: |
          export INTEGRATION_TEST_PROJECTS=$(find ./dotnet -type f -name "*IntegrationTests.csproj" | tr '\n' ' ')
          for project in $INTEGRATION_TEST_PROJECTS; do
-            dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx
+            # Query the project's target frameworks using MSBuild with the current configuration
+            target_frameworks=$(dotnet msbuild $project -getProperty:TargetFrameworks -p:Configuration=${{ matrix.configuration }} -nologo 2>/dev/null | tr -d '\r')
+            
+            # Check if the project supports the target framework
+            if [[ "$target_frameworks" == *"${{ matrix.targetFramework }}"* ]]; then
+              dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx
+            else
+              echo "Skipping $project - does not support target framework ${{ matrix.targetFramework }} (supports: $target_frameworks)"
+            fi
          done
        env:
          # OpenAI Models
@@ -166,14 +183,14 @@ jobs:

      # Generate test reports and check coverage
      - name: Generate test reports
-        uses: danielpalme/ReportGenerator-GitHub-Action@5.4.16
+        uses: danielpalme/ReportGenerator-GitHub-Action@5.4.18
        with:
          reports: "./TestResults/Coverage/**/coverage.cobertura.xml"
          targetdir: "./TestResults/Reports"
          reporttypes: "HtmlInline;JsonSummary"

      - name: Upload coverage report artifact
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v5
        with:
          name: CoverageReport-${{ matrix.os }}-${{ matrix.targetFramework }}-${{ matrix.configuration }} # Artifact name
          path: ./TestResults/Reports # Directory containing files to upload
@@ -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:
@@ -26,7 +26,7 @@ jobs:
    steps:
      - uses: actions/checkout@v5
      - name: Set up uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v7
        with:
          version-file: "python/pyproject.toml"
          enable-cache: true
@@ -1,27 +1,54 @@
 name: Python - Lab Tests

 on:
+  workflow_dispatch:
  pull_request:
-    branches: ["main", "feature*"]
-    paths:
-      - "python/packages/lab/**"
-  push:
    branches: ["main"]
    paths:
      - "python/packages/lab/**"
+  merge_group:
+    branches: ["main"]
+  schedule:
+    - cron: "0 0 * * *" # Run at midnight UTC daily

 env:
  # Configure a constant location for the uv cache
  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:
@@ -43,8 +43,8 @@ jobs:
      - name: not python tests
        if: steps.filter.outputs.python != 'true'
        run: echo "NOT python file"
-  python-tests-main:
-    name: Python Tests - Main
+  python-tests-core:
+    name: Python Tests - Core
    needs: paths-filter
    if: github.event_name != 'pull_request' && needs.paths-filter.outputs.pythonChanges == 'true'
    runs-on: ${{ matrix.os }}
@@ -60,56 +60,8 @@ jobs:
      OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
      OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
      OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
-      LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
-    defaults:
-      run:
-        working-directory: python
-    steps:
-      - uses: actions/checkout@v5
-      - name: Set up python and install the project
-        id: python-setup
-        uses: ./.github/actions/python-setup
-        with:
-          python-version: ${{ matrix.python-version }}
-          os: ${{ runner.os }}
-        env:
-          # Configure a constant location for the uv cache
-          UV_CACHE_DIR: /tmp/.uv-cache
-      - name: Test with pytest
-        timeout-minutes: 10
-        run: uv run poe all-tests -n logical --dist loadfile --dist worksteal --timeout 300 --retries 3 --retry-delay 10
-        working-directory: ./python
-      - name: Test main samples
-        timeout-minutes: 10
-        if: env.RUN_SAMPLES_TESTS == 'true'
-        run: uv run pytest tests/samples/ -m "openai"
-        working-directory: ./python
-      - name: Surface failing tests
-        if: always()
-        uses: pmeier/pytest-results-action@v0.7.2
-        with:
-          path: ./python/**.xml
-          summary: true
-          display-options: fEX
-          fail-on-empty: false
-          title: Test results
-
-  python-tests-azure-ai:
-    name: Python Tests - Azure
-    needs: paths-filter
-    if: github.event_name != 'pull_request' && needs.paths-filter.outputs.pythonChanges == 'true'
-    runs-on: ${{ matrix.os }}
-    environment: ${{ matrix.environment }}
-    strategy:
-      fail-fast: true
-      matrix:
-        python-version: ["3.10"]
-        os: [ubuntu-latest]
-        environment: ["integration"]
-    env:
-      UV_PYTHON: ${{ matrix.python-version }}
-      AZURE_AI_PROJECT_ENDPOINT: ${{ secrets.AZUREAI__ENDPOINT }}
-      AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.AZUREAI__DEPLOYMENTNAME }}
+      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 }}
@@ -139,10 +91,67 @@ jobs:
        timeout-minutes: 10
        run: uv run poe all-tests -n logical --dist loadfile --dist worksteal --timeout 300 --retries 3 --retry-delay 10
        working-directory: ./python
-      - name: Test azure samples
+      - name: Test core samples
        timeout-minutes: 10
        if: env.RUN_SAMPLES_TESTS == 'true'
-        run: uv run pytest tests/samples/ -m "azure-ai" -m "azure"
+        run: uv run pytest tests/samples/ -m "openai" -m "azure"
+        working-directory: ./python
+      - name: Surface failing tests
+        if: always()
+        uses: pmeier/pytest-results-action@v0.7.2
+        with:
+          path: ./python/**.xml
+          summary: true
+          display-options: fEX
+          fail-on-empty: false
+          title: Test results
+
+  python-tests-azure-ai:
+    name: Python Tests - Azure AI
+    needs: paths-filter
+    if: github.event_name != 'pull_request' && needs.paths-filter.outputs.pythonChanges == 'true'
+    runs-on: ${{ matrix.os }}
+    environment: ${{ matrix.environment }}
+    strategy:
+      fail-fast: true
+      matrix:
+        python-version: ["3.10"]
+        os: [ubuntu-latest]
+        environment: ["integration"]
+    env:
+      UV_PYTHON: ${{ matrix.python-version }}
+      AZURE_AI_PROJECT_ENDPOINT: ${{ secrets.AZUREAI__ENDPOINT }}
+      AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.AZUREAI__DEPLOYMENTNAME }}
+      LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
+    defaults:
+      run:
+        working-directory: python
+    steps:
+      - uses: actions/checkout@v5
+      - name: Set up python and install the project
+        id: python-setup
+        uses: ./.github/actions/python-setup
+        with:
+          python-version: ${{ matrix.python-version }}
+          os: ${{ runner.os }}
+        env:
+          # Configure a constant location for the uv cache
+          UV_CACHE_DIR: /tmp/.uv-cache
+      - name: Azure CLI Login
+        if: github.event_name != 'pull_request'
+        uses: azure/login@v2
+        with:
+          client-id: ${{ secrets.AZURE_CLIENT_ID }}
+          tenant-id: ${{ secrets.AZURE_TENANT_ID }}
+          subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
+      - name: Test with pytest
+        timeout-minutes: 10
+        run: uv run poe azure-ai-tests -n logical --dist loadfile --dist worksteal --timeout 300 --retries 3 --retry-delay 10
+        working-directory: ./python
+      - name: Test Azure AI samples
+        timeout-minutes: 10
+        if: env.RUN_SAMPLES_TESTS == 'true'
+        run: uv run pytest tests/samples/ -m "azure-ai"
        working-directory: ./python
      - name: Surface failing tests
        if: always()
@@ -161,7 +170,7 @@ jobs:
    runs-on: ubuntu-latest
    needs:
      [
-        python-tests-main,
+        python-tests-core,
        python-tests-azure-ai
      ]
    steps:
@@ -21,7 +21,7 @@ jobs:
    steps:
      - uses: actions/checkout@v5
      - name: Download coverage report
-        uses: actions/download-artifact@v5
+        uses: actions/download-artifact@v6
        with:
          github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
          run-id: ${{ github.event.workflow_run.id }}
@@ -39,7 +39,7 @@ jobs:
          echo "PR_NUMBER=$PR_NUMBER" >> $GITHUB_ENV
      - name: Pytest coverage comment
        id: coverageComment
-        uses: MishaKav/pytest-coverage-comment@v1.1.57
+        uses: MishaKav/pytest-coverage-comment@v1.1.59
        with:
          github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
          issue-number: ${{ env.PR_NUMBER }}
@@ -38,7 +38,7 @@ jobs:
      - name: Run all tests with coverage report
        run: uv run poe all-tests-cov --cov-report=xml:python-coverage.xml -q --junitxml=pytest.xml
      - name: Upload coverage report
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v5
        with:
          path: |
            python/python-coverage.xml
@@ -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:
@@ -203,4 +203,12 @@ agents.md

 # AI
 .claude/
-WARP.md
+WARP.md
+
+# Frontend
+**/frontend/node_modules/
+**/frontend/.vite/
+**/frontend/dist/
+
+# Database files
+*.db
@@ -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.
@@ -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>
    ```
@@ -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).
@@ -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
@@ -175,7 +175,7 @@ Sub-packages are comprised of two parts, the code itself and the dependencies, t
 - Subpackage naming should also follow this, so in principle a package name is `<vendor/folder>-<feature/brand>`, so `google-gemini`, `azure-purview`, `microsoft-copilotstudio`, etc. For smaller vendors, where it's less likely to have a multitude of connectors, we can skip the feature/brand part, so `mem0`, `redis`, etc.
 - For Microsoft services we will have two vendor folders, `azure` and `microsoft`, where `azure` contains all Azure services, while `microsoft` contains other Microsoft services, such as Copilot Studio Agents.

-This setup was discussed at length and the decision is captured in [ADR-0007](../decisions/0007-python-subpackages.md).
+This setup was discussed at length and the decision is captured in [ADR-0008](../decisions/0008-python-subpackages.md).

 #### Evolving the package structure
 For each of the advanced components, we have two reason why we may split them into a folder, with an `__init__.py` and optionally a `_files.py`:
@@ -7,7 +7,7 @@
  </PropertyGroup>
  <PropertyGroup>
    <!-- Aspire -->
-    <AspireAppHostSdkVersion>9.5.1</AspireAppHostSdkVersion>
+    <AspireAppHostSdkVersion>9.5.2</AspireAppHostSdkVersion>
  </PropertyGroup>
  <ItemGroup>
    <!-- Aspire.* -->
@@ -15,41 +15,45 @@
    <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.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" />
    <!-- System.* -->
+    <PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="9.0.10" />
+    <PackageVersion Include="Microsoft.Bcl.HashCode" Version="6.0.0" />
+    <PackageVersion Include="System.ClientModel" Version="1.7.0" />
    <PackageVersion Include="System.CodeDom" Version="9.0.10" />
    <PackageVersion Include="System.Collections.Immutable" Version="9.0.10" />
    <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" />
    <PackageVersion Include="System.Threading.Tasks.Extensions" Version="4.6.3" />
-    <PackageVersion Include="Microsoft.Bcl.HashCode" Version="6.0.0" />
-    <PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="9.0.10" />
    <!-- OpenTelemetry -->
-    <PackageVersion Include="OpenTelemetry" Version="1.12.0" />
-    <PackageVersion Include="OpenTelemetry.Api" Version="1.12.0" />
-    <PackageVersion Include="OpenTelemetry.Exporter.Console" Version="1.12.0" />
-    <PackageVersion Include="OpenTelemetry.Exporter.InMemory" Version="1.12.0" />
-    <PackageVersion Include="OpenTelemetry.Exporter.OpenTelemetryProtocol" Version="1.12.0" />
-    <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.Instrumentation.Runtime" Version="1.12.0" />
+    <PackageVersion Include="OpenTelemetry" Version="1.13.1" />
+    <PackageVersion Include="OpenTelemetry.Api" Version="1.13.1" />
+    <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="1.13.1" />
+    <PackageVersion Include="OpenTelemetry.Instrumentation.AspNetCore" Version="1.13.0" />
+    <PackageVersion Include="OpenTelemetry.Instrumentation.Http" Version="1.13.0" />
+    <PackageVersion Include="OpenTelemetry.Instrumentation.Runtime" Version="1.13.0" />
    <!-- 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="9.10.0" />
-    <PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="9.10.0" />
+    <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="9.10.0-preview.1.25513.3" />
+    <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" />
@@ -63,27 +67,31 @@
    <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)" />
+    <PackageVersion Include="Microsoft.Extensions.VectorData.Abstractions" Version="9.7.0" />
    <!-- Vector Stores -->
-    <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.Connectors.InMemory" Version="1.67.0-preview" />
+    <PackageVersion Include="Microsoft.SemanticKernel.Connectors.Qdrant" Version="1.67.0-preview" />
+    <!-- Semantic Kernel -->
+    <PackageVersion Include="Microsoft.SemanticKernel" Version="1.67.0" />
+    <PackageVersion Include="Microsoft.SemanticKernel.Agents.Core" Version="1.67.0" />
+    <PackageVersion Include="Microsoft.SemanticKernel.Agents.OpenAI" Version="1.67.0-preview" />
+    <PackageVersion Include="Microsoft.SemanticKernel.Agents.AzureAI" Version="1.67.0-preview" />
+    <PackageVersion Include="Microsoft.SemanticKernel.Plugins.OpenApi" Version="1.67.0" />
    <!-- Agent SDKs -->
    <PackageVersion Include="Microsoft.Agents.CopilotStudio.Client" Version="1.2.41" />
    <!-- A2A -->
-    <PackageVersion Include="A2A" Version="0.3.1-preview" />
-    <PackageVersion Include="A2A.AspNetCore" Version="0.3.1-preview" />
+    <PackageVersion Include="A2A" Version="0.3.3-preview" />
+    <PackageVersion Include="A2A.AspNetCore" Version="0.3.3-preview" />
    <!-- MCP -->
-    <PackageVersion Include="ModelContextProtocol" Version="0.4.0-preview.2" />
+    <PackageVersion Include="ModelContextProtocol" Version="0.4.0-preview.3" />
    <!-- Inference SDKs -->
-    <PackageVersion Include="Anthropic.SDK" Version="5.6.0" />
-    <PackageVersion Include="AWSSDK.Extensions.Bedrock.MEAI" Version="4.0.4" />
-    <PackageVersion Include="Microsoft.ML.OnnxRuntimeGenAI" Version="0.9.2" />
-    <PackageVersion Include="OllamaSharp" Version="5.4.7" />
-    <PackageVersion Include="OpenAI" Version="2.5.0" />
+    <PackageVersion Include="Anthropic.SDK" Version="5.8.0" />
+    <PackageVersion Include="AWSSDK.Extensions.Bedrock.MEAI" Version="4.0.4.6" />
+    <PackageVersion Include="Microsoft.ML.OnnxRuntimeGenAI" Version="0.10.0" />
+    <PackageVersion Include="OllamaSharp" Version="5.4.8" />
+    <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" />
@@ -92,11 +100,12 @@
    <!-- Community -->
    <PackageVersion Include="System.Linq.Async" Version="6.0.3" />
    <!-- Test -->
-    <PackageVersion Include="FluentAssertions" Version="8.7.1" />
+    <PackageVersion Include="FluentAssertions" Version="8.8.0" />
+    <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" />
-    <PackageVersion Include="Microsoft.SemanticKernel.Agents.Yaml" Version="1.66.0-beta" />
+    <PackageVersion Include="Microsoft.SemanticKernel.Agents.Abstractions" Version="1.67.0" />
+    <PackageVersion Include="Microsoft.SemanticKernel.Agents.Yaml" Version="1.67.0-beta" />
    <PackageVersion Include="xunit" Version="2.9.3" />
    <PackageVersion Include="xunit.abstractions" Version="2.0.3" />
    <PackageVersion Include="xunit.runner.visualstudio" Version="3.1.3" />
@@ -126,7 +135,7 @@
      <PrivateAssets>all</PrivateAssets>
      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
    </PackageReference>
-    <PackageVersion Include="Roslynator.Analyzers" Version="[4.14.0]" />
+    <PackageVersion Include="Roslynator.Analyzers" Version="[4.14.1]" />
    <PackageReference Include="Roslynator.Analyzers">
      <PrivateAssets>all</PrivateAssets>
      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
@@ -18,6 +18,11 @@
    <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/AGUIDojoServer/AGUIDojoServer.csproj" />
+    <Project Path="samples/AGUIClientServer/AGUIServer/AGUIServer.csproj" />
+  </Folder>
  <Folder Name="/Samples/GettingStarted/">
    <File Path="samples/GettingStarted/README.md" />
  </Folder>
@@ -53,20 +58,39 @@
    <Project Path="samples/GettingStarted/Agents/Agent_Step10_AsMcpTool/Agent_Step10_AsMcpTool.csproj" />
    <Project Path="samples/GettingStarted/Agents/Agent_Step11_UsingImages/Agent_Step11_UsingImages.csproj" />
    <Project Path="samples/GettingStarted/Agents/Agent_Step12_AsFunctionTool/Agent_Step12_AsFunctionTool.csproj" />
-    <Project Path="samples/GettingStarted/Agents/Agent_Step13_Memory/Agent_Step13_Memory.csproj" />
+    <Project Path="samples/GettingStarted/Agents/Agent_Step13_BackgroundResponsesWithToolsAndPersistence/Agent_Step13_BackgroundResponsesWithToolsAndPersistence.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" />
+  </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/AgentWithMemory/">
+    <File Path="samples/GettingStarted/AgentWithMemory/README.md" />
+    <Project Path="samples/GettingStarted/AgentWithMemory/AgentWithMemory_Step01_ChatHistoryMemory/AgentWithMemory_Step01_ChatHistoryMemory.csproj" />
+    <Project Path="samples/GettingStarted/AgentWithMemory/AgentWithMemory_Step02_MemoryUsingMem0/AgentWithMemory_Step02_MemoryUsingMem0.csproj" />
+    <Project Path="samples/GettingStarted/AgentWithMemory/AgentWithMemory_Step03_CustomMemory/AgentWithMemory_Step03_CustomMemory.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_CustomVectorStoreRAG/AgentWithRAG_Step02_CustomVectorStoreRAG.csproj" />
+    <Project Path="samples/GettingStarted/AgentWithRAG/AgentWithRAG_Step03_CustomRAGDataSource/AgentWithRAG_Step03_CustomRAGDataSource.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" />
@@ -119,6 +143,7 @@
  <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" />
@@ -130,9 +155,13 @@
    <Project Path="samples/GettingStarted/Workflows/_Foundational/04_AgentWorkflowPatterns/04_AgentWorkflowPatterns.csproj" />
    <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/HostedAgents/">
+    <Project Path="samples/HostedAgents/AgentsInWorkflows/AgentsInWorkflows.csproj" />
+    <Project Path="samples/HostedAgents/AgentWithTextSearchRag/AgentWithTextSearchRag.csproj" />
+    <Project Path="samples/HostedAgents/DeepResearchAgent/DeepResearchAgent.csproj" />
  </Folder>
  <Folder Name="/Solution Items/">
    <File Path=".editorconfig" />
@@ -160,8 +189,14 @@
  <Folder Name="/Solution Items/docs/" />
  <Folder Name="/Solution Items/docs/decisions/">
    <File Path="../docs/decisions/0001-agent-run-response.md" />
-    <File Path="../docs/decisions/0001-agent-tools.md" />
-    <File Path="../docs/decisions/0002-agent-opentelemetry-instrumentation.md" />
+    <File Path="../docs/decisions/0002-agent-tools.md" />
+    <File Path="../docs/decisions/0003-agent-opentelemetry-instrumentation.md" />
+    <File Path="../docs/decisions/0004-foundry-sdk-extensions.md" />
+    <File Path="../docs/decisions/0005-python-naming-conventions.md" />
+    <File Path="../docs/decisions/0006-userapproval.md" />
+    <File Path="../docs/decisions/0007-agent-filtering-middleware.md" />
+    <File Path="../docs/decisions/0008-python-subpackages.md" />
+    <File Path="../docs/decisions/0009-support-long-running-operations.md" />
    <File Path="../docs/decisions/adr-short-template.md" />
    <File Path="../docs/decisions/adr-template.md" />
    <File Path="../docs/decisions/README.md" />
@@ -228,6 +263,7 @@
  </Folder>
  <Folder Name="/Solution Items/src/Shared/IntegrationTests/">
    <File Path="src/Shared/IntegrationTests/AzureAIConfiguration.cs" />
+    <File Path="src/Shared/IntegrationTests/Mem0Configuration.cs" />
    <File Path="src/Shared/IntegrationTests/OpenAIConfiguration.cs" />
    <File Path="src/Shared/IntegrationTests/README.md" />
  </Folder>
@@ -249,12 +285,16 @@
  <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.AzureAI/Microsoft.Agents.AI.AzureAI.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.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" />
    <Project Path="src/Microsoft.Agents.AI.OpenAI/Microsoft.Agents.AI.OpenAI.csproj" />
    <Project Path="src/Microsoft.Agents.AI.Workflows.Declarative/Microsoft.Agents.AI.Workflows.Declarative.csproj" />
    <Project Path="src/Microsoft.Agents.AI.Workflows/Microsoft.Agents.AI.Workflows.csproj" />
@@ -265,6 +305,8 @@
    <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" />
    <Project Path="tests/OpenAIChatCompletion.IntegrationTests/OpenAIChatCompletion.IntegrationTests.csproj" />
@@ -273,12 +315,16 @@
  <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.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.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.Hosting.A2A.UnitTests/Microsoft.Agents.AI.Hosting.A2A.UnitTests.csproj" />
+    <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" />
    <Project Path="tests/Microsoft.Agents.AI.OpenAI.UnitTests/Microsoft.Agents.AI.OpenAI.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.UnitTests/Microsoft.Agents.AI.UnitTests.csproj" />
    <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>
@@ -2,9 +2,9 @@
  <PropertyGroup>
    <!-- Central version prefix - applies to all nuget packages. -->
    <VersionPrefix>1.0.0</VersionPrefix>
-    <PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).251016.1</PackageVersion>
-    <PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.251016.1</PackageVersion>
-    <GitTag>1.0.0-preview.251016.1</GitTag>
+    <PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).251110.2</PackageVersion>
+    <PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.251110.2</PackageVersion>
+    <GitTag>1.0.0-preview.251110.2</GitTag>

    <Configurations>Debug;Release;Publish</Configurations>
    <IsPackable>true</IsPackable>
@@ -1 +0,0 @@
-launchSettings.json
@@ -1,4 +1,4 @@
-<Project Sdk="Microsoft.NET.Sdk">
+<Project Sdk="Microsoft.NET.Sdk">

  <PropertyGroup>
    <OutputType>Exe</OutputType>
@@ -9,7 +9,6 @@
  </PropertyGroup>

  <ItemGroup>
-    <PackageReference Include="A2A.AspNetCore" />
    <PackageReference Include="Azure.AI.Agents.Persistent" />
    <PackageReference Include="Azure.Identity" />
    <PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-rc.2.25502.107" />
@@ -17,8 +16,11 @@
  </ItemGroup>

  <ItemGroup>
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.A2A.AspNetCore\Microsoft.Agents.AI.Hosting.A2A.AspNetCore.csproj" />
+    <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>

@@ -4,7 +4,6 @@ using A2A;
 using Azure.AI.Agents.Persistent;
 using Azure.Identity;
 using Microsoft.Agents.AI;
-using Microsoft.Agents.AI.A2A;
 using Microsoft.Extensions.AI;
 using OpenAI;

@@ -12,7 +11,7 @@ namespace A2AServer;

 internal static class HostAgentFactory
 {
-    internal static async Task<A2AHostAgent> CreateFoundryHostAgentAsync(string agentType, string model, string endpoint, string assistantId, IList<AITool>? tools = null)
+    internal static async Task<(AIAgent, AgentCard)> CreateFoundryHostAgentAsync(string agentType, string model, string endpoint, string assistantId, IList<AITool>? tools = null)
    {
        var persistentAgentsClient = new PersistentAgentsClient(endpoint, new AzureCliCredential());
        PersistentAgent persistentAgent = await persistentAgentsClient.Administration.GetAgentAsync(assistantId);
@@ -28,10 +27,10 @@ internal static class HostAgentFactory
            _ => throw new ArgumentException($"Unsupported agent type: {agentType}"),
        };

-        return new A2AHostAgent(agent, agentCard);
+        return new(agent, agentCard);
    }

-    internal static async Task<A2AHostAgent> CreateChatCompletionHostAgentAsync(string agentType, string model, string apiKey, string name, string instructions, IList<AITool>? tools = null)
+    internal static async Task<(AIAgent, AgentCard)> CreateChatCompletionHostAgentAsync(string agentType, string model, string apiKey, string name, string instructions, IList<AITool>? tools = null)
    {
        AIAgent agent = new OpenAIClient(apiKey)
             .GetChatClient(model)
@@ -45,7 +44,7 @@ internal static class HostAgentFactory
            _ => throw new ArgumentException($"Unsupported agent type: {agentType}"),
        };

-        return new A2AHostAgent(agent, agentCard);
+        return new(agent, agentCard);
    }

    #region private
@@ -2,7 +2,7 @@
 using A2A;
 using A2A.AspNetCore;
 using A2AServer;
-using Microsoft.Agents.AI.A2A;
+using Microsoft.Agents.AI;
 using Microsoft.AspNetCore.Builder;
 using Microsoft.Extensions.AI;
 using Microsoft.Extensions.Configuration;
@@ -47,10 +47,12 @@ IList<AITool> tools =
    AIFunctionFactory.Create(invoiceQueryPlugin.QueryByInvoiceId)
    ];

-A2AHostAgent? hostAgent = null;
+AIAgent hostA2AAgent;
+AgentCard hostA2AAgentCard;
+
 if (!string.IsNullOrEmpty(endpoint) && !string.IsNullOrEmpty(agentId))
 {
-    hostAgent = agentType.ToUpperInvariant() switch
+    (hostA2AAgent, hostA2AAgentCard) = agentType.ToUpperInvariant() switch
    {
        "INVOICE" => await HostAgentFactory.CreateFoundryHostAgentAsync(agentType, model, endpoint, agentId, tools),
        "POLICY" => await HostAgentFactory.CreateFoundryHostAgentAsync(agentType, model, endpoint, agentId),
@@ -60,7 +62,7 @@ if (!string.IsNullOrEmpty(endpoint) && !string.IsNullOrEmpty(agentId))
 }
 else if (!string.IsNullOrEmpty(apiKey))
 {
-    hostAgent = agentType.ToUpperInvariant() switch
+    (hostA2AAgent, hostA2AAgentCard) = agentType.ToUpperInvariant() switch
    {
        "INVOICE" => await HostAgentFactory.CreateChatCompletionHostAgentAsync(
            agentType, model, apiKey, "InvoiceAgent",
@@ -102,7 +104,10 @@ else
    throw new ArgumentException("Either A2AServer:ApiKey or A2AServer:ConnectionString & agentId must be provided");
 }

-app.MapA2A(hostAgent!.TaskManager!, "/");
-app.MapWellKnownAgentCard(hostAgent!.TaskManager!, "/");
+var a2aTaskManager = app.MapA2A(
+    hostA2AAgent,
+    path: "/",
+    agentCard: hostA2AAgentCard,
+    taskManager => app.MapWellKnownAgentCard(taskManager, "/"));

 await app.RunAsync();
@@ -0,0 +1,23 @@
+<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\Microsoft.Agents.AI.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.AGUI\Microsoft.Agents.AI.AGUI.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,12 @@
+// 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.Text.Json.Serialization;
+
+namespace AGUIClient;
+
+[JsonSerializable(typeof(SensorRequest))]
+[JsonSerializable(typeof(SensorResponse))]
+internal sealed partial class AGUIClientSerializerContext : JsonSerializerContext;
@@ -0,0 +1,213 @@
+// 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.ComponentModel;
+using System.Reflection;
+using System.Text;
+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)
+        };
+
+        var changeBackground = AIFunctionFactory.Create(
+            () =>
+            {
+                Console.ForegroundColor = ConsoleColor.DarkBlue;
+                Console.WriteLine("Changing color to blue");
+            },
+            name: "change_background_color",
+            description: "Change the console background color to dark blue."
+        );
+
+        var readClientClimateSensors = AIFunctionFactory.Create(
+            ([Description("The sensors measurements to include in the response")] SensorRequest request) =>
+            {
+                return new SensorResponse()
+                {
+                    Temperature = 22.5,
+                    Humidity = 45.0,
+                    AirQualityIndex = 75
+                };
+            },
+            name: "read_client_climate_sensors",
+            description: "Reads the climate sensor data from the client device.",
+            serializerOptions: AGUIClientSerializerContext.Default.Options
+        );
+
+        var chatClient = new AGUIChatClient(
+            httpClient,
+            serverUrl,
+            jsonSerializerOptions: AGUIClientSerializerContext.Default.Options);
+
+        AIAgent agent = chatClient.CreateAIAgent(
+            name: "agui-client",
+            description: "AG-UI Client Agent",
+            tools: [changeBackground, readClientClimateSensors]);
+
+        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;
+                var updates = new List<ChatResponseUpdate>();
+                await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(messages, thread, cancellationToken: cancellationToken))
+                {
+                    // Use AsChatResponseUpdate to access ChatResponseUpdate properties
+                    ChatResponseUpdate chatUpdate = update.AsChatResponseUpdate();
+                    updates.Add(chatUpdate);
+                    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($"\n[Run Started - Thread: {threadId}, Run: {update.ResponseId}]");
+                        Console.ResetColor();
+                        isFirstUpdate = false;
+                    }
+
+                    // Display different content types with appropriate formatting
+                    foreach (AIContent content in update.Contents)
+                    {
+                        switch (content)
+                        {
+                            case TextContent textContent:
+                                Console.ForegroundColor = ConsoleColor.Cyan;
+                                Console.Write(textContent.Text);
+                                Console.ResetColor();
+                                break;
+
+                            case FunctionCallContent functionCallContent:
+                                Console.ForegroundColor = ConsoleColor.Green;
+                                Console.WriteLine($"\n[Function Call - Name: {functionCallContent.Name}, Arguments: {PrintArguments(functionCallContent.Arguments)}]");
+                                Console.ResetColor();
+                                break;
+
+                            case FunctionResultContent functionResultContent:
+                                Console.ForegroundColor = ConsoleColor.Magenta;
+                                if (functionResultContent.Exception != null)
+                                {
+                                    Console.WriteLine($"\n[Function Result - Exception: {functionResultContent.Exception}]");
+                                }
+                                else
+                                {
+                                    Console.WriteLine($"\n[Function Result - Result: {functionResultContent.Result}]");
+                                }
+                                Console.ResetColor();
+                                break;
+
+                            case ErrorContent errorContent:
+                                Console.ForegroundColor = ConsoleColor.Red;
+                                string code = errorContent.AdditionalProperties?["Code"] as string ?? "Unknown";
+                                Console.WriteLine($"\n[Error - Code: {code}, Message: {errorContent.Message}]");
+                                Console.ResetColor();
+                                break;
+                        }
+                    }
+                }
+                if (updates.Count > 0 && !updates[^1].Contents.Any(c => c is TextContent))
+                {
+                    var lastUpdate = updates[^1];
+                    Console.ForegroundColor = ConsoleColor.Yellow;
+                    Console.WriteLine();
+                    Console.WriteLine($"[Run Ended - Thread: {threadId}, Run: {lastUpdate.ResponseId}]");
+                    Console.ResetColor();
+                }
+                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;
+        }
+    }
+
+    private static string PrintArguments(IDictionary<string, object?>? arguments)
+    {
+        if (arguments == null)
+        {
+            return "";
+        }
+        var builder = new StringBuilder();
+        builder.AppendLine();
+        foreach (var kvp in arguments)
+        {
+            builder.AppendLine($"   Name: {kvp.Key}");
+            builder.AppendLine($"   Value: {kvp.Value}");
+        }
+        return builder.ToString();
+    }
+}
@@ -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
@@ -0,0 +1,13 @@
+// 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.
+
+namespace AGUIClient;
+
+internal sealed class SensorRequest
+{
+    public bool IncludeTemperature { get; set; } = true;
+    public bool IncludeHumidity { get; set; } = true;
+    public bool IncludeAirQualityIndex { get; set; } = true;
+}
@@ -0,0 +1,13 @@
+// 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.
+
+namespace AGUIClient;
+
+internal sealed class SensorResponse
+{
+    public double Temperature { get; set; }
+    public double Humidity { get; set; }
+    public int AirQualityIndex { get; set; }
+}
@@ -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>b9c3f1e1-2fb4-5g29-0e52-53e2b7g9gf21</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>
@@ -0,0 +1,11 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Text.Json.Serialization;
+
+namespace AGUIDojoServer;
+
+[JsonSerializable(typeof(WeatherInfo))]
+[JsonSerializable(typeof(Recipe))]
+[JsonSerializable(typeof(Ingredient))]
+[JsonSerializable(typeof(RecipeResponse))]
+internal sealed partial class AGUIDojoServerSerializerContext : JsonSerializerContext;
@@ -0,0 +1,98 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.ComponentModel;
+using System.Text.Json;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+using ChatClient = OpenAI.Chat.ChatClient;
+
+namespace AGUIDojoServer;
+
+internal static class ChatClientAgentFactory
+{
+    private static AzureOpenAIClient? s_azureOpenAIClient;
+    private static string? s_deploymentName;
+
+    public static void Initialize(IConfiguration configuration)
+    {
+        string endpoint = configuration["AZURE_OPENAI_ENDPOINT"] ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+        s_deploymentName = configuration["AZURE_OPENAI_DEPLOYMENT_NAME"] ?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT_NAME is not set.");
+
+        s_azureOpenAIClient = new AzureOpenAIClient(
+            new Uri(endpoint),
+            new DefaultAzureCredential());
+    }
+
+    public static ChatClientAgent CreateAgenticChat()
+    {
+        ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
+
+        return chatClient.AsIChatClient().CreateAIAgent(
+            name: "AgenticChat",
+            description: "A simple chat agent using Azure OpenAI");
+    }
+
+    public static ChatClientAgent CreateBackendToolRendering()
+    {
+        ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
+
+        return chatClient.AsIChatClient().CreateAIAgent(
+            name: "BackendToolRenderer",
+            description: "An agent that can render backend tools using Azure OpenAI",
+            tools: [AIFunctionFactory.Create(
+                GetWeather,
+                name: "get_weather",
+                description: "Get the weather for a given location.",
+                AGUIDojoServerSerializerContext.Default.Options)]);
+    }
+
+    public static ChatClientAgent CreateHumanInTheLoop()
+    {
+        ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
+
+        return chatClient.AsIChatClient().CreateAIAgent(
+            name: "HumanInTheLoopAgent",
+            description: "An agent that involves human feedback in its decision-making process using Azure OpenAI");
+    }
+
+    public static ChatClientAgent CreateToolBasedGenerativeUI()
+    {
+        ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
+
+        return chatClient.AsIChatClient().CreateAIAgent(
+            name: "ToolBasedGenerativeUIAgent",
+            description: "An agent that uses tools to generate user interfaces using Azure OpenAI");
+    }
+
+    public static ChatClientAgent CreateAgenticUI()
+    {
+        ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
+
+        return chatClient.AsIChatClient().CreateAIAgent(
+            name: "AgenticUIAgent",
+            description: "An agent that generates agentic user interfaces using Azure OpenAI");
+    }
+
+    public static AIAgent CreateSharedState(JsonSerializerOptions options)
+    {
+        ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
+
+        var baseAgent = chatClient.AsIChatClient().CreateAIAgent(
+            name: "SharedStateAgent",
+            description: "An agent that demonstrates shared state patterns using Azure OpenAI");
+
+        return new SharedStateAgent(baseAgent, options);
+    }
+
+    [Description("Get the weather for a given location.")]
+    private static WeatherInfo GetWeather([Description("The location to get the weather for.")] string location) => new()
+    {
+        Temperature = 20,
+        Conditions = "sunny",
+        Humidity = 50,
+        WindSpeed = 10,
+        FeelsLike = 25
+    };
+}
@@ -0,0 +1,17 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Text.Json.Serialization;
+
+namespace AGUIDojoServer;
+
+internal sealed class Ingredient
+{
+    [JsonPropertyName("icon")]
+    public string Icon { get; set; } = string.Empty;
+
+    [JsonPropertyName("name")]
+    public string Name { get; set; } = string.Empty;
+
+    [JsonPropertyName("amount")]
+    public string Amount { get; set; } = string.Empty;
+}
@@ -0,0 +1,45 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using AGUIDojoServer;
+using Microsoft.Agents.AI.Hosting.AGUI.AspNetCore;
+using Microsoft.AspNetCore.HttpLogging;
+using Microsoft.Extensions.Options;
+
+WebApplicationBuilder builder = WebApplication.CreateBuilder(args);
+
+builder.Services.AddHttpLogging(logging =>
+{
+    logging.LoggingFields = HttpLoggingFields.RequestPropertiesAndHeaders | HttpLoggingFields.RequestBody
+        | HttpLoggingFields.ResponsePropertiesAndHeaders | HttpLoggingFields.ResponseBody;
+    logging.RequestBodyLogLimit = int.MaxValue;
+    logging.ResponseBodyLogLimit = int.MaxValue;
+});
+
+builder.Services.AddHttpClient().AddLogging();
+builder.Services.ConfigureHttpJsonOptions(options => options.SerializerOptions.TypeInfoResolverChain.Add(AGUIDojoServerSerializerContext.Default));
+builder.Services.AddAGUI();
+
+WebApplication app = builder.Build();
+
+app.UseHttpLogging();
+
+// Initialize the factory
+ChatClientAgentFactory.Initialize(app.Configuration);
+
+// Map the AG-UI agent endpoints for different scenarios
+app.MapAGUI("/agentic_chat", ChatClientAgentFactory.CreateAgenticChat());
+
+app.MapAGUI("/backend_tool_rendering", ChatClientAgentFactory.CreateBackendToolRendering());
+
+app.MapAGUI("/human_in_the_loop", ChatClientAgentFactory.CreateHumanInTheLoop());
+
+app.MapAGUI("/tool_based_generative_ui", ChatClientAgentFactory.CreateToolBasedGenerativeUI());
+
+app.MapAGUI("/agentic_generative_ui", ChatClientAgentFactory.CreateAgenticUI());
+
+var jsonOptions = app.Services.GetRequiredService<IOptions<Microsoft.AspNetCore.Http.Json.JsonOptions>>();
+app.MapAGUI("/shared_state", ChatClientAgentFactory.CreateSharedState(jsonOptions.Value.SerializerOptions));
+
+await app.RunAsync();
+
+public partial class Program { }
@@ -0,0 +1,12 @@
+{
+  "profiles": {
+    "AGUIDojoServer": {
+      "commandName": "Project",
+      "launchBrowser": true,
+      "environmentVariables": {
+        "ASPNETCORE_ENVIRONMENT": "Development"
+      },
+      "applicationUrl": "http://localhost:5018"
+    }
+  }
+}
@@ -0,0 +1,26 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Text.Json.Serialization;
+
+namespace AGUIDojoServer;
+
+internal sealed class Recipe
+{
+    [JsonPropertyName("title")]
+    public string Title { get; set; } = string.Empty;
+
+    [JsonPropertyName("skill_level")]
+    public string SkillLevel { get; set; } = string.Empty;
+
+    [JsonPropertyName("cooking_time")]
+    public string CookingTime { get; set; } = string.Empty;
+
+    [JsonPropertyName("special_preferences")]
+    public List<string> SpecialPreferences { get; set; } = [];
+
+    [JsonPropertyName("ingredients")]
+    public List<Ingredient> Ingredients { get; set; } = [];
+
+    [JsonPropertyName("instructions")]
+    public List<string> Instructions { get; set; } = [];
+}
@@ -0,0 +1,13 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Text.Json.Serialization;
+
+namespace AGUIDojoServer;
+
+#pragma warning disable CA1812 // Used for the JsonSchema response format
+internal sealed class RecipeResponse
+#pragma warning restore CA1812
+{
+    [JsonPropertyName("recipe")]
+    public Recipe Recipe { get; set; } = new();
+}
@@ -0,0 +1,106 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Diagnostics.CodeAnalysis;
+using System.Runtime.CompilerServices;
+using System.Text.Json;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+
+namespace AGUIDojoServer;
+
+[SuppressMessage("Performance", "CA1812:Avoid uninstantiated internal classes", Justification = "Instantiated by ChatClientAgentFactory.CreateSharedState")]
+internal sealed class SharedStateAgent : DelegatingAIAgent
+{
+    private readonly JsonSerializerOptions _jsonSerializerOptions;
+
+    public SharedStateAgent(AIAgent innerAgent, JsonSerializerOptions jsonSerializerOptions)
+        : base(innerAgent)
+    {
+        this._jsonSerializerOptions = jsonSerializerOptions;
+    }
+
+    public override Task<AgentRunResponse> RunAsync(IEnumerable<ChatMessage> messages, AgentThread? thread = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
+    {
+        return this.RunStreamingAsync(messages, thread, options, cancellationToken).ToAgentRunResponseAsync(cancellationToken);
+    }
+
+    public override async IAsyncEnumerable<AgentRunResponseUpdate> RunStreamingAsync(
+        IEnumerable<ChatMessage> messages,
+        AgentThread? thread = null,
+        AgentRunOptions? options = null,
+        [EnumeratorCancellation] CancellationToken cancellationToken = default)
+    {
+        if (options is not ChatClientAgentRunOptions { ChatOptions.AdditionalProperties: { } properties } chatRunOptions ||
+            !properties.TryGetValue("ag_ui_state", out JsonElement state))
+        {
+            await foreach (var update in this.InnerAgent.RunStreamingAsync(messages, thread, options, cancellationToken).ConfigureAwait(false))
+            {
+                yield return update;
+            }
+            yield break;
+        }
+
+        var firstRunOptions = new ChatClientAgentRunOptions
+        {
+            ChatOptions = chatRunOptions.ChatOptions.Clone(),
+            AllowBackgroundResponses = chatRunOptions.AllowBackgroundResponses,
+            ContinuationToken = chatRunOptions.ContinuationToken,
+            ChatClientFactory = chatRunOptions.ChatClientFactory,
+        };
+
+        // Configure JSON schema response format for structured state output
+        firstRunOptions.ChatOptions.ResponseFormat = ChatResponseFormat.ForJsonSchema<RecipeResponse>(
+            schemaName: "RecipeResponse",
+            schemaDescription: "A response containing a recipe with title, skill level, cooking time, preferences, ingredients, and instructions");
+
+        ChatMessage stateUpdateMessage = new(
+            ChatRole.System,
+            [
+                new TextContent("Here is the current state in JSON format:"),
+                    new TextContent(state.GetRawText()),
+                    new TextContent("The new state is:")
+            ]);
+
+        var firstRunMessages = messages.Append(stateUpdateMessage);
+
+        var allUpdates = new List<AgentRunResponseUpdate>();
+        await foreach (var update in this.InnerAgent.RunStreamingAsync(firstRunMessages, thread, firstRunOptions, cancellationToken).ConfigureAwait(false))
+        {
+            allUpdates.Add(update);
+
+            // Yield all non-text updates (tool calls, etc.)
+            bool hasNonTextContent = update.Contents.Any(c => c is not TextContent);
+            if (hasNonTextContent)
+            {
+                yield return update;
+            }
+        }
+
+        var response = allUpdates.ToAgentRunResponse();
+
+        if (response.TryDeserialize(this._jsonSerializerOptions, out JsonElement stateSnapshot))
+        {
+            byte[] stateBytes = JsonSerializer.SerializeToUtf8Bytes(
+                stateSnapshot,
+                this._jsonSerializerOptions.GetTypeInfo(typeof(JsonElement)));
+            yield return new AgentRunResponseUpdate
+            {
+                Contents = [new DataContent(stateBytes, "application/json")]
+            };
+        }
+        else
+        {
+            yield break;
+        }
+
+        var secondRunMessages = messages.Concat(response.Messages).Append(
+            new ChatMessage(
+                ChatRole.System,
+                [new TextContent("Please provide a concise summary of the state changes in at most two sentences.")]));
+
+        await foreach (var update in this.InnerAgent.RunStreamingAsync(secondRunMessages, thread, options, cancellationToken).ConfigureAwait(false))
+        {
+            yield return update;
+        }
+    }
+}
@@ -0,0 +1,23 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Text.Json.Serialization;
+
+namespace AGUIDojoServer;
+
+internal sealed class WeatherInfo
+{
+    [JsonPropertyName("temperature")]
+    public int Temperature { get; init; }
+
+    [JsonPropertyName("conditions")]
+    public string Conditions { get; init; } = string.Empty;
+
+    [JsonPropertyName("humidity")]
+    public int Humidity { get; init; }
+
+    [JsonPropertyName("wind_speed")]
+    public int WindSpeed { get; init; }
+
+    [JsonPropertyName("feelsLike")]
+    public int FeelsLike { get; init; }
+}
@@ -0,0 +1,9 @@
+{
+  "Logging": {
+    "LogLevel": {
+      "Default": "Information",
+      "Microsoft.AspNetCore": "Warning",
+      "Microsoft.AspNetCore.HttpLogging.HttpLoggingMiddleware": "Information"
+    }
+  }
+}
@@ -0,0 +1,10 @@
+{
+  "Logging": {
+    "LogLevel": {
+      "Default": "Information",
+      "Microsoft.AspNetCore": "Warning",
+      "Microsoft.AspNetCore.HttpLogging.HttpLoggingMiddleware": "Information"
+    }
+  },
+  "AllowedHosts": "*"
+}
@@ -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>
@@ -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": {}
+}
@@ -0,0 +1,9 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.Text.Json.Serialization;
+
+namespace AGUIServer;
+
+[JsonSerializable(typeof(ServerWeatherForecastRequest))]
+[JsonSerializable(typeof(ServerWeatherForecastResponse))]
+internal sealed partial class AGUIServerSerializerContext : JsonSerializerContext;
@@ -0,0 +1,51 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.ComponentModel;
+using AGUIServer;
+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();
+builder.Services.ConfigureHttpJsonOptions(options => options.SerializerOptions.TypeInfoResolverChain.Add(AGUIServerSerializerContext.Default));
+builder.Services.AddAGUI();
+
+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 with tools
+var agent = new AzureOpenAIClient(
+        new Uri(endpoint),
+        new DefaultAzureCredential())
+    .GetChatClient(deploymentName)
+    .CreateAIAgent(
+        name: "AGUIAssistant",
+        tools: [
+            AIFunctionFactory.Create(
+                () => DateTimeOffset.UtcNow,
+                name: "get_current_time",
+                description: "Get the current UTC time."
+            ),
+            AIFunctionFactory.Create(
+                ([Description("The weather forecast request")]ServerWeatherForecastRequest request) => {
+                    return new ServerWeatherForecastResponse()
+                    {
+                        Summary = "Sunny",
+                        TemperatureC = 25,
+                        Date = request.Date
+                    };
+                },
+                name: "get_server_weather_forecast",
+                description: "Gets the forecast for a specific location and date",
+                AGUIServerSerializerContext.Default.Options)
+        ]);
+
+// Map the AG-UI agent endpoint
+app.MapAGUI("/", agent);
+
+await app.RunAsync();
@@ -0,0 +1,12 @@
+{
+  "profiles": {
+    "AGUIServer": {
+      "commandName": "Project",
+      "launchBrowser": true,
+      "environmentVariables": {
+        "ASPNETCORE_ENVIRONMENT": "Development"
+      },
+      "applicationUrl": "http://localhost:5100;https://localhost:5101"
+    }
+  }
+}
@@ -0,0 +1,9 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+namespace AGUIServer;
+
+internal sealed class ServerWeatherForecastRequest
+{
+    public DateTime Date { get; set; }
+    public string Location { get; set; } = "Seattle";
+}
@@ -0,0 +1,12 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+namespace AGUIServer;
+
+internal sealed class ServerWeatherForecastResponse
+{
+    public string Summary { get; set; } = "";
+
+    public int TemperatureC { get; set; }
+
+    public DateTime Date { get; set; }
+}
@@ -0,0 +1,208 @@
+# 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 `AGUIChatClient` to connect to the remote server:
+
+```csharp
+using HttpClient httpClient = new();
+var chatClient = new AGUIChatClient(
+    httpClient,
+    endpoint: serverUrl,
+    modelId: "agui-client",
+    jsonSerializerOptions: null);
+
+AIAgent agent = chatClient.CreateAIAgent(
+    instructions: null,
+    name: "agui-client",
+    description: "AG-UI Client Agent",
+    tools: []);
+
+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`
@@ -1,4 +1,4 @@
-<Project Sdk="Microsoft.NET.Sdk.Web">
+<Project Sdk="Microsoft.NET.Sdk.Web">

  <PropertyGroup>
    <TargetFramework>net9.0</TargetFramework>
@@ -13,7 +13,7 @@
    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting\Microsoft.Agents.AI.Hosting.csproj" />
    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.A2A.AspNetCore\Microsoft.Agents.AI.Hosting.A2A.AspNetCore.csproj" />
-	  <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.OpenAI\Microsoft.Agents.AI.Hosting.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.OpenAI\Microsoft.Agents.AI.Hosting.OpenAI.csproj" />
    <ProjectReference Include="..\AgentWebChat.ServiceDefaults\AgentWebChat.ServiceDefaults.csproj" />
  </ItemGroup>

@@ -37,4 +37,4 @@
  </ItemGroup>
  <!-- A2A dependency -->

-</Project>
+</Project>
@@ -0,0 +1,17 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using Microsoft.Extensions.AI;
+
+namespace AgentWebChat.AgentHost.Custom;
+
+public class CustomAITool : AITool
+{
+}
+
+public class CustomFunctionTool : AIFunction
+{
+    protected override ValueTask<object?> InvokeCoreAsync(AIFunctionArguments arguments, CancellationToken cancellationToken)
+    {
+        return new ValueTask<object?>(arguments.Context?.Count ?? 0);
+    }
+}
@@ -2,11 +2,10 @@

 using A2A.AspNetCore;
 using AgentWebChat.AgentHost;
+using AgentWebChat.AgentHost.Custom;
 using AgentWebChat.AgentHost.Utilities;
 using Microsoft.Agents.AI;
 using Microsoft.Agents.AI.Hosting;
-using Microsoft.Agents.AI.Hosting.A2A.AspNetCore;
-using Microsoft.Agents.AI.Hosting.OpenAI;
 using Microsoft.Agents.AI.Workflows;
 using Microsoft.Extensions.AI;

@@ -22,13 +21,16 @@ 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");
+    chatClientServiceKey: "chat-model")
+    .WithAITool(new CustomAITool())
+    .WithAITool(new CustomFunctionTool())
+    .WithInMemoryThreadStore();

-builder.AddAIAgent("knights-and-knaves", (sp, key) =>
+var knightsKnavesAgentBuilder = builder.AddAIAgent("knights-and-knaves", (sp, key) =>
 {
    var chatClient = sp.GetRequiredKeyedService<IChatClient>("chat-model");

@@ -60,10 +62,7 @@ builder.AddAIAgent("knights-and-knaves", (sp, key) =>
        If the user asks a general question about their surrounding, make something up which is consistent with the scenario.
        """, "Narrator");

-    // TODO: How to avoid sync-over-async here?
-#pragma warning disable VSTHRD002 // Avoid problematic synchronous waits
-    return AgentWorkflowBuilder.BuildConcurrent([knight, knave, narrator]).AsAgentAsync(name: key).AsTask().GetAwaiter().GetResult();
-#pragma warning restore VSTHRD002
+    return AgentWorkflowBuilder.BuildConcurrent([knight, knave, narrator]).AsAgent(name: key);
 });

 // Workflow consisting of multiple specialized agents
@@ -82,8 +81,22 @@ var literatureAgent = builder.AddAIAgent("literator",
    description: "An agent that helps with literature.",
    chatClientServiceKey: "chat-model");

-builder.AddSequentialWorkflow("science-sequential-workflow", [chemistryAgent, mathsAgent, literatureAgent]).AddAsAIAgent();
-builder.AddConcurrentWorkflow("science-concurrent-workflow", [chemistryAgent, mathsAgent, literatureAgent]).AddAsAIAgent();
+var scienceSequentialWorkflow = builder.AddWorkflow("science-sequential-workflow", (sp, key) =>
+{
+    List<IHostedAgentBuilder> usedAgents = [chemistryAgent, mathsAgent, literatureAgent];
+    var agents = usedAgents.Select(ab => sp.GetRequiredKeyedService<AIAgent>(ab.Name));
+    return AgentWorkflowBuilder.BuildSequential(workflowName: key, agents: agents);
+}).AddAsAIAgent();
+
+var scienceConcurrentWorkflow = builder.AddWorkflow("science-concurrent-workflow", (sp, key) =>
+{
+    List<IHostedAgentBuilder> usedAgents = [chemistryAgent, mathsAgent, literatureAgent];
+    var agents = usedAgents.Select(ab => sp.GetRequiredKeyedService<AIAgent>(ab.Name));
+    return AgentWorkflowBuilder.BuildConcurrent(workflowName: key, agents: agents);
+}).AddAsAIAgent();
+
+builder.AddOpenAIChatCompletions();
+builder.AddOpenAIResponses();

 var app = builder.Build();

@@ -94,8 +107,8 @@ app.UseSwaggerUI(options => options.SwaggerEndpoint("/openapi/v1.json", "Agents
 app.UseExceptionHandler();

 // attach a2a with simple message communication
-app.MapA2A(agentName: "pirate", path: "/a2a/pirate");
-app.MapA2A(agentName: "knights-and-knaves", path: "/a2a/knights-and-knaves", agentCard: new()
+app.MapA2A(pirateAgentBuilder, path: "/a2a/pirate");
+app.MapA2A(knightsKnavesAgentBuilder, path: "/a2a/knights-and-knaves", agentCard: new()
 {
    Name = "Knights and Knaves",
    Description = "An agent that helps you solve the knights and knaves puzzle.",
@@ -105,15 +118,10 @@ app.MapA2A(agentName: "knights-and-knaves", path: "/a2a/knights-and-knaves", age
    // Url = "http://localhost:5390/a2a/knights-and-knaves"
 });

-app.MapOpenAIResponses("pirate");
-app.MapOpenAIResponses("knights-and-knaves");
+app.MapOpenAIResponses();

-app.MapOpenAIChatCompletions("pirate");
-app.MapOpenAIChatCompletions("knights-and-knaves");
-
-// workflow-agents
-app.MapOpenAIResponses("science-sequential-workflow");
-app.MapOpenAIResponses("science-concurrent-workflow");
+app.MapOpenAIChatCompletions(pirateAgentBuilder);
+app.MapOpenAIChatCompletions(knightsKnavesAgentBuilder);

 // Map the agents HTTP endpoints
 app.MapAgentDiscovery("/agents");
@@ -58,7 +58,7 @@ internal sealed class A2AAgentClient : AgentClientBase
            if (a2aResponse is AgentMessage message)
            {
                var responseMessage = message.ToChatMessage();
-                if (responseMessage is not null)
+                if (responseMessage is { Contents.Count: > 0 })
                {
                    results.Add(new AgentRunResponseUpdate(responseMessage.Role, responseMessage.Contents)
                    {
@@ -78,11 +78,7 @@ internal sealed class A2AAgentClient : AgentClientBase

                        foreach (var part in artifact.Parts)
                        {
-                            var aiContent = ConvertPartToAIContent(part);
-                            if (aiContent != null)
-                            {
-                                (aiContents ??= []).Add(aiContent);
-                            }
+                            (aiContents ??= []).Add(part.ToAIContent());
                        }

                        if (aiContents is not null)
@@ -155,20 +151,6 @@ internal sealed class A2AAgentClient : AgentClientBase
            return (a2aClient, a2aCardResolver);
        });

-    private static AIContent? ConvertPartToAIContent(Part part) =>
-        part switch
-        {
-            TextPart textPart => new TextContent(textPart.Text)
-            {
-                RawRepresentation = textPart
-            },
-            FilePart filePart when filePart.File is FileWithUri fileWithUrl => new HostedFileContent(fileWithUrl.Uri)
-            {
-                RawRepresentation = filePart
-            },
-            _ => null
-        };
-
    private static AdditionalPropertiesDictionary? ConvertMetadataToAdditionalProperties(Dictionary<string, JsonElement>? metadata)
    {
        if (metadata is not { Count: > 0 })
@@ -184,22 +166,3 @@ internal sealed class A2AAgentClient : AgentClientBase
        return additionalProperties;
    }
 }
-
-// Extension method to convert multiple chat messages to A2A messages
-internal static class ChatMessageExtensions
-{
-    public static List<AgentMessage> ToA2AMessages(this IList<ChatMessage> chatMessages)
-    {
-        if (chatMessages is null || chatMessages.Count == 0)
-        {
-            return [];
-        }
-
-        var result = new List<AgentMessage>();
-        foreach (var chatMessage in chatMessages)
-        {
-            result.Add(chatMessage.ToA2AMessage());
-        }
-        return result;
-    }
-}
@@ -23,11 +23,11 @@ internal sealed class OpenAIResponsesAgentClient(HttpClient httpClient) : AgentC
    {
        OpenAIClientOptions options = new()
        {
-            Endpoint = new Uri(httpClient.BaseAddress!, $"/{agentName}/v1/"),
+            Endpoint = new Uri(httpClient.BaseAddress!, "/v1/"),
            Transport = new HttpClientPipelineTransport(httpClient)
        };

-        var openAiClient = new OpenAIResponseClient(model: "myModel!", credential: new ApiKeyCredential("dummy-key"), options: options).AsIChatClient();
+        var openAiClient = new OpenAIResponseClient(model: agentName, credential: new ApiKeyCredential("dummy-key"), options: options).AsIChatClient();
        var chatOptions = new ChatOptions()
        {
            ConversationId = threadId
@@ -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(
@@ -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))
@@ -142,11 +142,11 @@ You:
 Besides the Aspire Dashboard and the Application Insights native UI, you can also use Grafana to visualize the telemetry data in Application Insights. There are two tailored dashboards for you to get started quickly:

 ### Agent Overview dashboard
-Grafana Dashboard Gallery link: <https://aka.ms/amg/dash/af-agent>
+Open dashboard in Azure portal: <https://aka.ms/amg/dash/af-agent>
 ![Agent Overview dashboard](https://github.com/Azure/azure-managed-grafana/raw/main/samples/assets/grafana-af-agent.gif)

 ### Workflow Overview dashboard
-Grafana Dashboard Gallery link: <https://aka.ms/amg/dash/af-workflow>
+Open dashboard in Azure portal: <https://aka.ms/amg/dash/af-workflow>
 ![Workflow Overview dashboard](https://github.com/Azure/azure-managed-grafana/raw/main/samples/assets/grafana-af-workflow.gif)

 ## Key Features Demonstrated
@@ -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>
@@ -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" />
+    <PackageReference Include="Microsoft.SemanticKernel.Connectors.InMemory" />
+    <PackageReference Include="System.Linq.Async" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,60 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent that stores chat messages in a vector store using the ChatHistoryMemoryProvider.
+// It can then use the chat history from prior conversations to inform responses in new conversations.
+
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+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";
+
+// Create a vector store to store the chat messages in.
+// For demonstration purposes, we are using an in-memory vector store.
+// Replace this with a vector store implementation of your choice that can persist the chat history long term.
+VectorStore vectorStore = new InMemoryVectorStore(new InMemoryVectorStoreOptions()
+{
+    EmbeddingGenerator = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
+        .GetEmbeddingClient(embeddingDeploymentName)
+        .AsIEmbeddingGenerator()
+});
+
+// Create the agent and add the ChatHistoryMemoryProvider to store chat messages in the vector store.
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+    .GetChatClient(deploymentName)
+    .CreateAIAgent(new ChatClientAgentOptions
+    {
+        Instructions = "You are good at telling jokes.",
+        Name = "Joker",
+        AIContextProviderFactory = (ctx) => new ChatHistoryMemoryProvider(
+            vectorStore,
+            collectionName: "chathistory",
+            vectorDimensions: 3072,
+            // Configure the scope values under which chat messages will be stored.
+            // In this case, we are using a fixed user ID and a unique thread ID for each new thread.
+            storageScope: new() { UserId = "UID1", ThreadId = new Guid().ToString() },
+            // Configure the scope which would be used to search for relevant prior messages.
+            // In this case, we are searching for any messages for the user across all threads.
+            searchScope: new() { UserId = "UID1" })
+    });
+
+// Start a new thread for the agent conversation.
+AgentThread thread = agent.GetNewThread();
+
+// Run the agent with the thread that stores conversation history in the vector store.
+Console.WriteLine(await agent.RunAsync("I like jokes about Pirates. Tell me a joke about a pirate.", thread));
+
+// Start a second thread. Since we configured the search scope to be across all threads for the user,
+// the agent should remember that the user likes pirate jokes.
+AgentThread thread2 = agent.GetNewThread();
+
+// Run the agent with the second thread.
+Console.WriteLine(await agent.RunAsync("Tell me a joke that I might like.", thread2));
@@ -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>
@@ -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));
@@ -0,0 +1,9 @@
+# Agent Framework Retrieval Augmented Generation (RAG)
+
+These samples show how to create an agent with the Agent Framework that uses Memory to remember previous conversations or facts from previous conversations.
+
+|Sample|Description|
+|---|---|
+|[Chat History memory](./AgentWithMemory_Step01_ChatHistoryMemory/)|This sample demonstrates how to enable an agent to remember messages from previous conversations.|
+|[Memory with MemoryStore](./AgentWithMemory_Step02_MemoryUsingMem0/)|This sample demonstrates how to create and run an agent that uses the Mem0 service to extract and retrieve individual memories.|
+|[Custom Memory Implementation](./AgentWithMemory_Step03_CustomMemory/)|This sample demonstrates how to create a custom memory component and attach it to an agent.|
@@ -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>
@@ -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."
+    };
+}
@@ -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; }
+}
@@ -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);
+    }
+}
@@ -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; }
+    }
+}
@@ -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; }
+}
@@ -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>
@@ -0,0 +1,132 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to use Qdrant with a custom schema 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;
+}
@@ -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.
@@ -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>
@@ -0,0 +1,84 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to use TextSearchProvider to add retrieval augmented generation (RAG)
+// capabilities to an AI agent. This shows a mock implementation of a search function,
+// which can be replaced with any custom search logic to query any external knowledge base.
+// The provider invokes the custom search function
+// 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);
+}
@@ -0,0 +1,9 @@
+# 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 Vector Store and custom schema](./AgentWithRAG_Step02_CustomVectorStoreRAG/)|This sample demonstrates how to create and run an agent that uses Retrieval Augmented Generation (RAG) with a vector store. It also uses a custom schema for the documents stored in the vector store.|
+|[RAG with custom RAG data source](./AgentWithRAG_Step03_CustomRAGDataSource/)|This sample demonstrates how to create and run an agent that uses Retrieval Augmented Generation (RAG) with a custom RAG data source.|
@@ -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>
@@ -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>
@@ -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;
+}
@@ -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
+```
@@ -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>
@@ -0,0 +1,70 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to use background responses with ChatClientAgent and Azure OpenAI Responses.
+
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.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";
+
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+     .GetOpenAIResponseClient(deploymentName)
+     .CreateAIAgent();
+
+// Enable background responses (only supported by 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 otters in space.", thread, options);
+
+// Poll until the response is complete.
+while (response.ContinuationToken is { } token)
+{
+    // Wait before polling again.
+    await Task.Delay(TimeSpan.FromSeconds(2));
+
+    // Continue with the token.
+    options.ContinuationToken = token;
+
+    response = await agent.RunAsync(thread, options);
+}
+
+// Display the result.
+Console.WriteLine(response.Text);
+
+// Reset options and thread for streaming.
+options = new() { AllowBackgroundResponses = true };
+thread = agent.GetNewThread();
+
+AgentRunResponseUpdate? lastReceivedUpdate = null;
+// Start streaming.
+await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync("Write a very long novel about otters in space.", thread, options))
+{
+    // Output each update.
+    Console.Write(update.Text);
+
+    // Track last update.
+    lastReceivedUpdate = update;
+
+    // Simulate connection loss after first piece of content received.
+    if (update.Text.Length > 0)
+    {
+        break;
+    }
+}
+
+// Resume from interruption point.
+options.ContinuationToken = lastReceivedUpdate?.ContinuationToken;
+
+await foreach (AgentRunResponseUpdate update in agent.RunStreamingAsync(thread, options))
+{
+    // Output each update.
+    Console.Write(update.Text);
+}
@@ -0,0 +1,27 @@
+# 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.
+- **Resuming after interruption** - Streaming APIs can be interrupted and resumed from the last update using the continuation token.
+
+> **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-4o-mini"  # Optional, defaults to gpt-4o-mini
+```
@@ -29,6 +29,7 @@ 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 OpenAPI function tools with a simple agent](https://github.com/microsoft/semantic-kernel/tree/main/dotnet/samples/AgentFrameworkMigration/AzureOpenAI/Step04_ToolCall_WithOpenAPI)|This sample demonstrates how to create function tools from an OpenAPI spec and use them with a simple agent (note that this sample is in the Semantic Kernel repository)|
 |[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|
@@ -38,10 +39,11 @@ Before you begin, ensure you have the following prerequisites:
 |[Exposing a simple agent as MCP tool](./Agent_Step10_AsMcpTool/)|This sample demonstrates how to expose an agent as an MCP tool|
 |[Using images with a simple agent](./Agent_Step11_UsingImages/)|This sample demonstrates how to use image multi-modality with an AI agent|
 |[Exposing a simple agent as a function tool](./Agent_Step12_AsFunctionTool/)|This sample demonstrates how to expose an agent as a function tool|
-|[Using memory with an agent](./Agent_Step13_Memory/)|This sample demonstrates how to create a simple memory component and use it with an agent|
+|[Background responses with tools and persistence](./Agent_Step13_BackgroundResponsesWithToolsAndPersistence/)|This sample demonstrates advanced background response scenarios including function calling during background operations and state persistence|
 |[Using middleware with an agent](./Agent_Step14_Middleware/)|This sample demonstrates how to use middleware with an agent|
 |[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|

 ## Running the samples from the console

@@ -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>
@@ -0,0 +1,86 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates basic usage of the DevUI in an ASP.NET Core application with AI agents.
+
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.DevUI;
+using Microsoft.Agents.AI.Hosting;
+using Microsoft.Agents.AI.Workflows;
+using Microsoft.Extensions.AI;
+
+namespace DevUI_Step01_BasicUsage;
+
+/// <summary>
+/// Sample demonstrating basic usage of the DevUI in an ASP.NET Core application.
+/// </summary>
+/// <remarks>
+/// This sample shows how to:
+/// 1. Set up Azure OpenAI as the chat client
+/// 2. Register agents and workflows using the hosting packages
+/// 3. Map the DevUI endpoint which automatically configures the middleware
+/// 4. Map the dynamic OpenAI Responses API for Python DevUI compatibility
+/// 5. Access the DevUI in a web browser
+///
+/// The DevUI provides an interactive web interface for testing and debugging AI agents.
+/// DevUI assets are served from embedded resources within the assembly.
+/// Simply call MapDevUI() to set up everything needed.
+///
+/// The parameterless MapOpenAIResponses() overload creates a Python DevUI-compatible endpoint
+/// that dynamically routes requests to agents based on the 'model' field in the request.
+/// </remarks>
+internal static class Program
+{
+    /// <summary>
+    /// Entry point that starts an ASP.NET Core web server with the DevUI.
+    /// </summary>
+    /// <param name="args">Command line arguments.</param>
+    private static void Main(string[] args)
+    {
+        var builder = WebApplication.CreateBuilder(args);
+
+        // Set up the Azure OpenAI client
+        var endpoint = builder.Configuration["AZURE_OPENAI_ENDPOINT"] ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+        var deploymentName = builder.Configuration["AZURE_OPENAI_DEPLOYMENT_NAME"] ?? "gpt-4o-mini";
+
+        var chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
+            .GetChatClient(deploymentName)
+            .AsIChatClient();
+
+        builder.Services.AddChatClient(chatClient);
+
+        // Register sample agents
+        builder.AddAIAgent("assistant", "You are a helpful assistant. Answer questions concisely and accurately.");
+        builder.AddAIAgent("poet", "You are a creative poet. Respond to all requests with beautiful poetry.");
+        builder.AddAIAgent("coder", "You are an expert programmer. Help users with coding questions and provide code examples.");
+
+        // Register sample workflows
+        var assistantBuilder = builder.AddAIAgent("workflow-assistant", "You are a helpful assistant in a workflow.");
+        var reviewerBuilder = builder.AddAIAgent("workflow-reviewer", "You are a reviewer. Review and critique the previous response.");
+        builder.AddWorkflow("review-workflow", (sp, key) =>
+        {
+            var agents = new List<IHostedAgentBuilder>() { assistantBuilder, reviewerBuilder }.Select(ab => sp.GetRequiredKeyedService<AIAgent>(ab.Name));
+            return AgentWorkflowBuilder.BuildSequential(workflowName: key, agents: agents);
+        }).AddAsAIAgent();
+
+        builder.Services.AddOpenAIResponses();
+        builder.Services.AddOpenAIConversations();
+
+        var app = builder.Build();
+
+        app.MapOpenAIResponses();
+        app.MapOpenAIConversations();
+
+        if (builder.Environment.IsDevelopment())
+        {
+            app.MapDevUI();
+        }
+
+        Console.WriteLine("DevUI is available at: https://localhost:50516/devui");
+        Console.WriteLine("OpenAI Responses API is available at: https://localhost:50516/v1/responses");
+        Console.WriteLine("Press Ctrl+C to stop the server.");
+
+        app.Run();
+    }
+}
@@ -0,0 +1,13 @@
+{
+  "profiles": {
+    "DevUI_Step01_BasicUsage": {
+      "commandName": "Project",
+      "launchUrl": "devui",
+      "launchBrowser": true,
+      "environmentVariables": {
+        "ASPNETCORE_ENVIRONMENT": "Development"
+      },
+      "applicationUrl": "https://localhost:50516;http://localhost:50518"
+    }
+  }
+}
@@ -0,0 +1,87 @@
+# DevUI Step 01 - Basic Usage
+
+This sample demonstrates how to add the DevUI to an ASP.NET Core application with AI agents.
+
+## What is DevUI?
+
+The DevUI provides an interactive web interface for testing and debugging AI agents during development.
+
+## Configuration
+
+Set the following environment variables:
+
+- `AZURE_OPENAI_ENDPOINT` - Your Azure OpenAI endpoint URL (required)
+- `AZURE_OPENAI_DEPLOYMENT_NAME` - Your deployment name (defaults to "gpt-4o-mini")
+
+## Running the Sample
+
+1. Set your Azure OpenAI credentials as environment variables
+2. Run the application:
+   ```bash
+   dotnet run
+   ```
+3. Open your browser to https://localhost:50516/devui
+4. Select an agent or workflow from the dropdown and start chatting!
+
+## Sample Agents and Workflows
+
+This sample includes:
+
+**Agents:**
+- **assistant** - A helpful assistant
+- **poet** - A creative poet
+- **coder** - An expert programmer
+
+**Workflows:**
+- **review-workflow** - A sequential workflow that generates a response and then reviews it
+
+## Adding DevUI to Your Own Project
+
+To add DevUI to your ASP.NET Core application:
+
+1. Add the DevUI package and hosting packages:
+   ```bash
+   dotnet add package Microsoft.Agents.AI.DevUI
+   dotnet add package Microsoft.Agents.AI.Hosting
+   dotnet add package Microsoft.Agents.AI.Hosting.OpenAI
+   ```
+
+2. Register your agents and workflows:
+   ```csharp
+   var builder = WebApplication.CreateBuilder(args);
+   
+   // Set up your chat client
+   builder.Services.AddChatClient(chatClient);
+   
+   // Register agents
+   builder.AddAIAgent("assistant", "You are a helpful assistant.");
+   
+   // Register workflows
+   var agent1Builder = builder.AddAIAgent("workflow-agent1", "You are agent 1.");
+   var agent2Builder = builder.AddAIAgent("workflow-agent2", "You are agent 2.");
+   builder.AddSequentialWorkflow("my-workflow", [agent1Builder, agent2Builder])
+       .AddAsAIAgent();
+   ```
+
+3. Add OpenAI services and map the endpoints for OpenAI and DevUI:
+   ```csharp
+   // Register services for OpenAI responses and conversations (also required for DevUI)
+   builder.Services.AddOpenAIResponses();
+   builder.Services.AddOpenAIConversations();
+
+   var app = builder.Build();
+
+   // Map endpoints for OpenAI responses and conversations (also required for DevUI)
+   app.MapOpenAIResponses();
+   app.MapOpenAIConversations();
+
+   if (builder.Environment.IsDevelopment())
+   {
+       // Map DevUI endpoint to /devui
+       app.MapDevUI();
+   }
+   
+   app.Run();
+   ```
+
+4. Navigate to `/devui` in your browser
@@ -0,0 +1,60 @@
+# DevUI Samples
+
+This folder contains samples demonstrating how to use the DevUI in ASP.NET Core applications.
+
+## What is DevUI?
+
+The DevUI provides an interactive web interface for testing and debugging AI agents during development.
+
+## Samples
+
+### [DevUI_Step01_BasicUsage](./DevUI_Step01_BasicUsage)
+
+Shows how to add DevUI to an ASP.NET Core application with multiple agents and workflows.
+
+**Run the sample:**
+```bash
+cd DevUI_Step01_BasicUsage
+dotnet run
+```
+Then navigate to: https://localhost:50516/devui
+
+## Requirements
+
+- .NET 8.0 or later
+- ASP.NET Core
+- Azure OpenAI credentials
+
+## Quick Start
+
+To add DevUI to your application:
+
+```csharp
+var builder = WebApplication.CreateBuilder(args);
+
+// Set up the chat client
+builder.Services.AddChatClient(chatClient);
+
+// Register your agents
+builder.AddAIAgent("my-agent", "You are a helpful assistant.");
+
+// Register services for OpenAI responses and conversations (also required for DevUI)
+builder.Services.AddOpenAIResponses();
+builder.Services.AddOpenAIConversations();
+
+var app = builder.Build();
+
+// Map endpoints for OpenAI responses and conversations (also required for DevUI)
+app.MapOpenAIResponses();
+app.MapOpenAIConversations();
+
+if (builder.Environment.IsDevelopment())
+{
+    // Map DevUI endpoint to /devui
+    app.MapDevUI();
+}
+
+app.Run();
+```
+
+Then navigate to `/devui` in your browser.
@@ -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>
@@ -1,52 +1,106 @@
 // 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.
+// This sample shows how to create and use a simple AI agent with Azure Foundry Agents as the backend, that uses a Hosted MCP Tool.
+// In this case the Azure Foundry Agents service will invoke any MCP tools as required. MCP tools are not invoked by the Agent Framework.
+// The sample first shows how to use MCP tools with auto approval, and then how to set up a tool that requires approval before it can be invoked and how to approve such a tool.

 using Azure.AI.Agents.Persistent;
 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 model = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_MODEL_ID") ?? "gpt-4.1-mini";
+var model = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4.1-mini";

 // Get a client to create/retrieve server side agents with.
 var persistentAgentsClient = new PersistentAgentsClient(endpoint, new AzureCliCredential());

+// **** MCP Tool with Auto Approval ****
+// *************************************
+
 // Create an MCP tool definition that the agent can use.
-var mcpTool = new MCPToolDefinition(
-    serverLabel: "microsoft_learn",
-    serverUrl: "https://learn.microsoft.com/api/mcp");
-mcpTool.AllowedTools.Add("microsoft_docs_search");
-
-// Create a server side persistent agent with the Azure.AI.Agents.Persistent SDK.
-var agentMetadata = await persistentAgentsClient.Administration.CreateAgentAsync(
-    model: model,
-    name: "MicrosoftLearnAgent",
-    instructions: "You answer questions by searching the Microsoft Learn content only.",
-    tools: [mcpTool]);
-
-// Retrieve an already created server side persistent agent as an AIAgent.
-AIAgent agent = await persistentAgentsClient.GetAIAgentAsync(agentMetadata.Value.Id);
-
-// Create run options to configure the agent invocation.
-var runOptions = new ChatClientAgentRunOptions()
+// In this case we allow the tool to always be called without approval.
+var mcpTool = new HostedMcpServerTool(
+    serverName: "microsoft_learn",
+    serverAddress: "https://learn.microsoft.com/api/mcp")
 {
-    ChatOptions = new()
-    {
-        RawRepresentationFactory = (_) => new ThreadAndRunOptions()
-        {
-            ToolResources = new MCPToolResource(serverLabel: "microsoft_learn")
-            {
-                RequireApproval = new MCPApproval("never"),
-            }.ToToolResources()
-        }
-    }
+    AllowedTools = ["microsoft_docs_search"],
+    ApprovalMode = HostedMcpServerToolApprovalMode.NeverRequire
 };

+// Create a server side persistent agent with the mcp tool, and expose it as an AIAgent.
+AIAgent agent = await persistentAgentsClient.CreateAIAgentAsync(
+    model: model,
+    options: new()
+    {
+        Name = "MicrosoftLearnAgent",
+        Instructions = "You answer questions by searching the Microsoft Learn content only.",
+        ChatOptions = new()
+        {
+            Tools = [mcpTool]
+        },
+    });
+
 // You can then invoke the agent like any other AIAgent.
 AgentThread thread = agent.GetNewThread();
-var response = await agent.RunAsync("Please summarize the Azure AI Agent documentation related to MCP Tool calling?", thread, runOptions);
-Console.WriteLine(response);
+Console.WriteLine(await agent.RunAsync("Please summarize the Azure AI Agent documentation related to MCP Tool calling?", thread));

 // Cleanup for sample purposes.
 await persistentAgentsClient.Administration.DeleteAgentAsync(agent.Id);
+
+// **** MCP Tool with Approval Required ****
+// *****************************************
+
+// Create an MCP tool definition that the agent can use.
+// In this case we require approval before the tool can be called.
+var mcpToolWithApproval = new HostedMcpServerTool(
+    serverName: "microsoft_learn",
+    serverAddress: "https://learn.microsoft.com/api/mcp")
+{
+    AllowedTools = ["microsoft_docs_search"],
+    ApprovalMode = HostedMcpServerToolApprovalMode.AlwaysRequire
+};
+
+// Create an agent based on Azure OpenAI Responses as the backend.
+AIAgent agentWithRequiredApproval = await persistentAgentsClient.CreateAIAgentAsync(
+    model: model,
+    options: new()
+    {
+        Name = "MicrosoftLearnAgentWithApproval",
+        Instructions = "You answer questions by searching the Microsoft Learn content only.",
+        ChatOptions = new()
+        {
+            Tools = [mcpToolWithApproval]
+        },
+    });
+
+// You can then invoke the agent like any other AIAgent.
+var threadWithRequiredApproval = agentWithRequiredApproval.GetNewThread();
+var response = await agentWithRequiredApproval.RunAsync("Please summarize the Azure AI Agent documentation related to MCP Tool calling?", threadWithRequiredApproval);
+var userInputRequests = response.UserInputRequests.ToList();
+
+while (userInputRequests.Count > 0)
+{
+    // Ask the user to approve each MCP call request.
+    // For simplicity, we are assuming here that only MCP approval requests are being made.
+    var userInputResponses = userInputRequests
+        .OfType<McpServerToolApprovalRequestContent>()
+        .Select(approvalRequest =>
+        {
+            Console.WriteLine($"""
+                The agent would like to invoke the following MCP Tool, please reply Y to approve.
+                ServerName: {approvalRequest.ToolCall.ServerName}
+                Name: {approvalRequest.ToolCall.ToolName}
+                Arguments: {string.Join(", ", approvalRequest.ToolCall.Arguments?.Select(x => $"{x.Key}: {x.Value}") ?? [])}
+                """);
+            return new ChatMessage(ChatRole.User, [approvalRequest.CreateResponse(Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false)]);
+        })
+        .ToList();
+
+    // Pass the user input responses back to the agent for further processing.
+    response = await agentWithRequiredApproval.RunAsync(userInputResponses, threadWithRequiredApproval);
+
+    userInputRequests = response.UserInputRequests.ToList();
+}
+
+Console.WriteLine($"\nAgent: {response}");
@@ -21,6 +21,7 @@ Before you begin, ensure you have the following prerequisites:
 |---|---|
 |[Agent with MCP server tools](./Agent_MCP_Server/)|This sample demonstrates how to use MCP server tools with a simple agent|
 |[Agent with MCP server tools and authorization](./Agent_MCP_Server_Auth/)|This sample demonstrates how to use MCP Server tools from a protected MCP server with a simple agent|
+|[Responses Agent with Hosted MCP tool](./ResponseAgent_Hosted_MCP/)|This sample demonstrates how to use the Hosted MCP tool with the Responses Service, where the service invokes any MCP tools directly|

 ## Running the samples from the console

@@ -0,0 +1,95 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with OpenAI Responses as the backend, that uses a Hosted MCP Tool.
+// In this case the OpenAI responses service will invoke any MCP tools as required. MCP tools are not invoked by the Agent Framework.
+// The sample first shows how to use MCP tools with auto approval, and then how to set up a tool that requires approval before it can be invoked and how to approve such a tool.
+
+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-4o-mini";
+
+// **** MCP Tool with Auto Approval ****
+// *************************************
+
+// Create an MCP tool definition that the agent can use.
+// In this case we allow the tool to always be called without approval.
+var mcpTool = new HostedMcpServerTool(
+    serverName: "microsoft_learn",
+    serverAddress: "https://learn.microsoft.com/api/mcp")
+{
+    AllowedTools = ["microsoft_docs_search"],
+    ApprovalMode = HostedMcpServerToolApprovalMode.NeverRequire
+};
+
+// Create an agent based on Azure OpenAI Responses as the backend.
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+     .GetOpenAIResponseClient(deploymentName)
+     .CreateAIAgent(
+        instructions: "You answer questions by searching the Microsoft Learn content only.",
+        name: "MicrosoftLearnAgent",
+        tools: [mcpTool]);
+
+// You can then invoke the agent like any other AIAgent.
+AgentThread thread = agent.GetNewThread();
+Console.WriteLine(await agent.RunAsync("Please summarize the Azure AI Agent documentation related to MCP Tool calling?", thread));
+
+// **** MCP Tool with Approval Required ****
+// *****************************************
+
+// Create an MCP tool definition that the agent can use.
+// In this case we require approval before the tool can be called.
+var mcpToolWithApproval = new HostedMcpServerTool(
+    serverName: "microsoft_learn",
+    serverAddress: "https://learn.microsoft.com/api/mcp")
+{
+    AllowedTools = ["microsoft_docs_search"],
+    ApprovalMode = HostedMcpServerToolApprovalMode.AlwaysRequire
+};
+
+// Create an agent based on Azure OpenAI Responses as the backend.
+AIAgent agentWithRequiredApproval = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+    .GetOpenAIResponseClient(deploymentName)
+    .CreateAIAgent(
+        instructions: "You answer questions by searching the Microsoft Learn content only.",
+        name: "MicrosoftLearnAgentWithApproval",
+        tools: [mcpToolWithApproval]);
+
+// You can then invoke the agent like any other AIAgent.
+var threadWithRequiredApproval = agentWithRequiredApproval.GetNewThread();
+var response = await agentWithRequiredApproval.RunAsync("Please summarize the Azure AI Agent documentation related to MCP Tool calling?", threadWithRequiredApproval);
+var userInputRequests = response.UserInputRequests.ToList();
+
+while (userInputRequests.Count > 0)
+{
+    // Ask the user to approve each MCP call request.
+    // For simplicity, we are assuming here that only MCP approval requests are being made.
+    var userInputResponses = userInputRequests
+        .OfType<McpServerToolApprovalRequestContent>()
+        .Select(approvalRequest =>
+        {
+            Console.WriteLine($"""
+                The agent would like to invoke the following MCP Tool, please reply Y to approve.
+                ServerName: {approvalRequest.ToolCall.ServerName}
+                Name: {approvalRequest.ToolCall.ToolName}
+                Arguments: {string.Join(", ", approvalRequest.ToolCall.Arguments?.Select(x => $"{x.Key}: {x.Value}") ?? [])}
+                """);
+            return new ChatMessage(ChatRole.User, [approvalRequest.CreateResponse(Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false)]);
+        })
+        .ToList();
+
+    // Pass the user input responses back to the agent for further processing.
+    response = await agentWithRequiredApproval.RunAsync(userInputResponses, threadWithRequiredApproval);
+
+    userInputRequests = response.UserInputRequests.ToList();
+}
+
+Console.WriteLine($"\nAgent: {response}");
@@ -0,0 +1,17 @@
+# 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)
+- User has the `Cognitive Services OpenAI Contributor` role for the Azure OpenAI resource.
+
+**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-4.1-mini"  # Optional, defaults to gpt-4.1-mini
+```
@@ -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>
--- a/Show More
+++ b/Show More