Capture meeting notes

Expanded the pipeline documentation to include details about the Dev Harness and added new features related to compaction strategies and test frameworks.

.github/.linkspector.yml

@@ -20,6 +20,7 @@ ignorePatterns:
   - pattern: "https://your-resource.openai.azure.com/"
   - pattern: "http://host.docker.internal"
   - pattern: "https://openai.github.io/openai-agents-js/openai/agents/classes/"
+  - pattern: "https:\/\/dotnet.microsoft.com\/download"
 # excludedDirs:
   # Folders which include links to localhost, since it's not ignored with regular expressions
 baseUrl: https://github.com/microsoft/agent-framework/

.github/actions/python-setup/action.yml

@@ -8,6 +8,10 @@ inputs:
     os:
       description: The operating system to set up
       required: true
+    exclude-packages:
+      description: Space-separated list of packages to exclude from uv sync
+      required: false
+      default: ''
 
 runs:
     using: "composite"
@@ -19,6 +23,20 @@ runs:
             enable-cache: true
             cache-suffix: ${{ inputs.os }}-${{ inputs.python-version }}
             cache-dependency-glob: "**/uv.lock"
+      - name: Exclude incompatible workspace packages
+        if: ${{ inputs.exclude-packages != '' }}
+        shell: bash
+        run: |
+          for pkg in ${{ inputs.exclude-packages }}; do
+            for f in python/packages/*/pyproject.toml; do
+              if grep -q "name = \"$pkg\"" "$f"; then
+                pkg_dir=$(dirname "$f" | sed 's|python/||')
+                echo "Excluding workspace package: $pkg ($pkg_dir)"
+                sed -i.bak '/\[tool\.uv\.workspace\]/a\exclude = ["'"$pkg_dir"'"]' python/pyproject.toml
+                sed -i.bak '/'"$pkg"' = { workspace = true }/d' python/pyproject.toml
+              fi
+            done
+          done
       - name: Install the project
         shell: bash
         run: |

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

@@ -59,20 +59,20 @@ jobs:
         if: steps.filter.outputs.dotnet != 'true'
         run: echo "NOT dotnet file"
 
-  dotnet-build-and-test:
+  # Build the full solution (including samples) on all TFMs. No tests.
+  dotnet-build:
     needs: paths-filter
     if: needs.paths-filter.outputs.dotnetChanges == 'true'
     strategy:
       fail-fast: false
       matrix:
         include:
-          - { targetFramework: "net10.0", os: "ubuntu-latest", configuration: Release, integration-tests: true, environment: "integration" }
+          - { targetFramework: "net10.0", os: "ubuntu-latest", configuration: Release }
           - { targetFramework: "net9.0", os: "windows-latest", configuration: Debug }
           - { targetFramework: "net8.0", os: "ubuntu-latest", configuration: Release }
-          - { targetFramework: "net472", os: "windows-latest", configuration: Release, integration-tests: true, environment: "integration" }
+          - { targetFramework: "net472", os: "windows-latest", configuration: Release }
 
     runs-on: ${{ matrix.os }}
-    environment: ${{ matrix.environment }}
     steps:
       - uses: actions/checkout@v6
         with:
@@ -84,16 +84,6 @@ jobs:
               python
               workflow-samples
 
-      # Start Cosmos DB Emulator for all integration tests and only for unit tests when CosmosDB changes happened)
-      - name: Start Azure Cosmos DB Emulator
-        if: ${{ runner.os == 'Windows' && (needs.paths-filter.outputs.cosmosDbChanges == 'true' || (github.event_name != 'pull_request' && matrix.integration-tests)) }}
-        shell: pwsh
-        run: |
-          Write-Host "Launching Azure Cosmos DB Emulator"
-          Import-Module "$env:ProgramFiles\Azure Cosmos DB Emulator\PSModules\Microsoft.Azure.CosmosDB.Emulator"
-          Start-CosmosDbEmulator -NoUI -Key "C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw=="
-          echo "COSMOSDB_EMULATOR_AVAILABLE=true" >> $env:GITHUB_ENV
-
       - name: Setup dotnet
         uses: actions/setup-dotnet@v5.1.0
         with:
@@ -140,25 +130,98 @@ jobs:
           popd
           rm -rf "$TEMP_DIR"
 
-      - name: Run Unit Tests
-        shell: bash
-        run: |
-          export UT_PROJECTS=$(find ./dotnet -type f -name "*.UnitTests.csproj" | tr '\n' ' ')
-          for project in $UT_PROJECTS; do
-            # Query the project's target frameworks using MSBuild with the current configuration
-            target_frameworks=$(dotnet msbuild $project -getProperty:TargetFrameworks -p:Configuration=${{ matrix.configuration }} -nologo 2>/dev/null | tr -d '\r')
+  # Build src+tests only (no samples) for a single TFM and run tests.
+  dotnet-test:
+    needs: paths-filter
+    if: needs.paths-filter.outputs.dotnetChanges == 'true'
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - { targetFramework: "net10.0", os: "ubuntu-latest", configuration: Release, integration-tests: true, environment: "integration" }
+          - { targetFramework: "net472", os: "windows-latest", configuration: Release, integration-tests: true, environment: "integration" }
 
-            # Check if the project supports the target framework
-            if [[ "$target_frameworks" == *"${{ matrix.targetFramework }}"* ]]; then
-              if [[ "${{ matrix.targetFramework }}" == "${{ env.COVERAGE_FRAMEWORK }}" ]]; 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
-                dotnet test -f ${{ matrix.targetFramework }} -c ${{ matrix.configuration }} $project --no-build -v Normal --logger trx
-              fi
-            else
-              echo "Skipping $project - does not support target framework ${{ matrix.targetFramework }} (supports: $target_frameworks)"
-            fi
-          done
+    runs-on: ${{ matrix.os }}
+    environment: ${{ matrix.environment }}
+    steps:
+      - uses: actions/checkout@v6
+        with:
+            persist-credentials: false
+            sparse-checkout: |
+              .
+              .github
+              dotnet
+              python
+              workflow-samples
+
+      # Start Cosmos DB Emulator for all integration tests and only for unit tests when CosmosDB changes happened)
+      - name: Start Azure Cosmos DB Emulator
+        if: ${{ runner.os == 'Windows' && (needs.paths-filter.outputs.cosmosDbChanges == 'true' || (github.event_name != 'pull_request' && matrix.integration-tests)) }}
+        shell: pwsh
+        run: |
+          Write-Host "Launching Azure Cosmos DB Emulator"
+          Import-Module "$env:ProgramFiles\Azure Cosmos DB Emulator\PSModules\Microsoft.Azure.CosmosDB.Emulator"
+          Start-CosmosDbEmulator -NoUI -Key "C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw=="
+          echo "COSMOSDB_EMULATOR_AVAILABLE=true" >> $env:GITHUB_ENV
+
+      - name: Setup dotnet
+        uses: actions/setup-dotnet@v5.1.0
+        with:
+          global-json-file: ${{ github.workspace }}/dotnet/global.json
+
+      - name: Generate test solution (no samples)
+        shell: pwsh
+        run: |
+          ./dotnet/eng/scripts/New-FilteredSolution.ps1 `
+            -Solution dotnet/agent-framework-dotnet.slnx `
+            -TargetFramework ${{ matrix.targetFramework }} `
+            -Configuration ${{ matrix.configuration }} `
+            -ExcludeSamples `
+            -OutputPath dotnet/filtered.slnx `
+            -Verbose
+
+      - name: Build src and tests
+        shell: bash
+        run: dotnet build dotnet/filtered.slnx -c ${{ matrix.configuration }} -f ${{ matrix.targetFramework }} --warnaserror
+
+      - name: Generate test-type filtered solutions
+        shell: pwsh
+        run: |
+          $commonArgs = @{
+            Solution       = "dotnet/filtered.slnx"
+            TargetFramework = "${{ matrix.targetFramework }}"
+            Configuration   = "${{ matrix.configuration }}"
+            Verbose         = $true
+          }
+          ./dotnet/eng/scripts/New-FilteredSolution.ps1 @commonArgs `
+            -TestProjectNameFilter "*UnitTests*" `
+            -OutputPath dotnet/filtered-unit.slnx
+          ./dotnet/eng/scripts/New-FilteredSolution.ps1 @commonArgs `
+            -TestProjectNameFilter "*IntegrationTests*" `
+            -OutputPath dotnet/filtered-integration.slnx
+
+      - name: Run Unit Tests
+        shell: pwsh
+        working-directory: dotnet
+        run: |
+          $coverageSettings = Join-Path $PWD "tests/coverage.runsettings"
+          $coverageArgs = @()
+          if ("${{ matrix.targetFramework }}" -eq "${{ env.COVERAGE_FRAMEWORK }}") {
+            $coverageArgs = @(
+              "--coverage",
+              "--coverage-output-format", "cobertura",
+              "--coverage-settings", $coverageSettings,
+              "--results-directory", "../TestResults/Coverage/"
+            )
+          }
+
+          dotnet test --solution ./filtered-unit.slnx `
+            -f ${{ matrix.targetFramework }} `
+            -c ${{ matrix.configuration }} `
+            --no-build -v Normal `
+            --report-xunit-trx `
+            --ignore-exit-code 8 `
+            @coverageArgs
         env:
           # Cosmos DB Emulator connection settings
           COSMOSDB_ENDPOINT: https://localhost:8081
@@ -185,21 +248,19 @@ jobs:
         id: azure-functions-setup
 
       - name: Run Integration Tests
-        shell: bash
+        shell: pwsh
+        working-directory: dotnet
         if: github.event_name != 'pull_request' && matrix.integration-tests
         run: |
-          export INTEGRATION_TEST_PROJECTS=$(find ./dotnet -type f -name "*IntegrationTests.csproj" | tr '\n' ' ')
-          for project in $INTEGRATION_TEST_PROJECTS; do
-            # Query the project's target frameworks using MSBuild with the current configuration
-            target_frameworks=$(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 --filter "Category!=IntegrationDisabled"
-            else
-              echo "Skipping $project - does not support target framework ${{ matrix.targetFramework }} (supports: $target_frameworks)"
-            fi
-          done
+          dotnet test --solution ./filtered-integration.slnx `
+            -f ${{ matrix.targetFramework }} `
+            -c ${{ matrix.configuration }} `
+            --no-build -v Normal `
+            --report-xunit-trx `
+            --ignore-exit-code 8 `
+            --filter-not-trait "Category=IntegrationDisabled" `
+            --parallel-algorithm aggressive `
+            --max-threads 2.0x
         env:
           # Cosmos DB Emulator connection settings
           COSMOSDB_ENDPOINT: https://localhost:8081
@@ -222,7 +283,7 @@ jobs:
         if: matrix.targetFramework == env.COVERAGE_FRAMEWORK
         uses: danielpalme/ReportGenerator-GitHub-Action@5.5.1
         with:
-          reports: "./TestResults/Coverage/**/coverage.cobertura.xml"
+          reports: "./TestResults/Coverage/**/*.cobertura.xml"
           targetdir: "./TestResults/Reports"
           reporttypes: "HtmlInline;JsonSummary"
 
@@ -236,13 +297,13 @@ jobs:
       - name: Check coverage
         if: matrix.targetFramework == env.COVERAGE_FRAMEWORK
         shell: pwsh
-        run: .github/workflows/dotnet-check-coverage.ps1 -JsonReportPath "TestResults/Reports/Summary.json" -CoverageThreshold $env:COVERAGE_THRESHOLD
+        run: ./dotnet/eng/scripts/dotnet-check-coverage.ps1 -JsonReportPath "TestResults/Reports/Summary.json" -CoverageThreshold $env:COVERAGE_THRESHOLD
 
   # This final job is required to satisfy the merge queue. It must only run (or succeed) if no tests failed
   dotnet-build-and-test-check:
     if: always()
     runs-on: ubuntu-latest
-    needs: [dotnet-build-and-test]
+    needs: [dotnet-build, dotnet-test]
     steps:
       - name: Get Date
         shell: bash

.github/workflows/dotnet-format.yml

@@ -86,11 +86,10 @@ jobs:
         run: docker pull mcr.microsoft.com/dotnet/sdk:${{ matrix.dotnet }}
 
       # This step will run dotnet format on each of the unique csproj files and fail if any changes are made
-      # exclude-diagnostics should be removed after fixes for IL2026 and IL3050 are out: https://github.com/dotnet/sdk/issues/51136
       - name: Run dotnet format
         if: steps.find-csproj.outputs.csproj_files != ''
         run: |
           for csproj in ${{ steps.find-csproj.outputs.csproj_files }}; do
             echo "Running dotnet format on $csproj"
-            docker run --rm -v $(pwd):/app -w /app mcr.microsoft.com/dotnet/sdk:${{ matrix.dotnet }} /bin/sh -c "dotnet format $csproj --verify-no-changes --verbosity diagnostic --exclude-diagnostics IL2026 IL3050"
+            docker run --rm -v $(pwd):/app -w /app mcr.microsoft.com/dotnet/sdk:${{ matrix.dotnet }} /bin/sh -c "dotnet format $csproj --verify-no-changes --verbosity diagnostic"
           done

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

@@ -18,7 +18,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.10"]
+        python-version: ["3.11"]
     runs-on: ubuntu-latest
     continue-on-error: true
     defaults:
@@ -55,7 +55,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.10"]
+        python-version: ["3.11"]
     runs-on: ubuntu-latest
     continue-on-error: true
     defaults:
@@ -84,7 +84,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.10"]
+        python-version: ["3.11"]
     runs-on: ubuntu-latest
     continue-on-error: true
     defaults:
@@ -117,7 +117,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.10"]
+        python-version: ["3.11"]
     runs-on: ubuntu-latest
     continue-on-error: true
     defaults:

.github/workflows/python-dependency-range-validation.yml

@@ -0,0 +1,216 @@
+# Probe the highest allowed dependency versions, then open issues/PRs from the passing updates.
+name: Python - Dependency Range Validation
+
+on:
+  workflow_dispatch:
+
+permissions:
+  contents: write
+  issues: write
+  pull-requests: write
+
+env:
+  UV_CACHE_DIR: /tmp/.uv-cache
+
+jobs:
+  dependency-range-validation:
+    name: Dependency Range Validation
+    runs-on: ubuntu-latest
+    env:
+      # For now only run 3.13, if we do encounter situations where there are mismatches between packages and python versions (other then 3.10 and 3.14 which are known to not be able to install everything)
+      # then we will have to reevaluate.
+      UV_PYTHON: "3.13"
+      GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+    steps:
+      - uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+
+      - name: Set up python and install the project
+        uses: ./.github/actions/python-setup
+        with:
+          python-version: ${{ env.UV_PYTHON }}
+          os: ${{ runner.os }}
+        env:
+          UV_CACHE_DIR: /tmp/.uv-cache
+
+      - name: Run dependency range validation
+        id: validate_ranges
+        # Keep workflow running so we can still publish diagnostics from this run.
+        continue-on-error: true
+        run: uv run poe validate-dependency-bounds-project --mode upper --project "*"
+        working-directory: ./python
+
+      - name: Upload dependency range report
+        # Always publish the report so failures are inspectable even when validation fails.
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: dependency-range-results
+          path: python/scripts/dependencies/dependency-range-results.json
+          if-no-files-found: warn
+
+      - name: Create issues for failed dependency candidates
+        # Always process the report so failed candidates create actionable tracking issues.
+        if: always()
+        uses: actions/github-script@v8
+        with:
+          script: |
+            const fs = require("fs")
+            const reportPath = "python/scripts/dependencies/dependency-range-results.json"
+
+            if (!fs.existsSync(reportPath)) {
+              core.warning(`No dependency range report found at ${reportPath}`)
+              return
+            }
+
+            const report = JSON.parse(fs.readFileSync(reportPath, "utf8"))
+            const dependencyFailures = []
+
+            for (const packageResult of report.packages ?? []) {
+              for (const dependency of packageResult.dependencies ?? []) {
+                const candidateVersions = new Set(dependency.candidate_versions ?? [])
+                const failedAttempts = (dependency.attempts ?? []).filter(
+                  (attempt) => attempt.status === "failed" && candidateVersions.has(attempt.trial_upper)
+                )
+                if (!failedAttempts.length) {
+                  continue
+                }
+
+                const failuresByVersion = new Map()
+                for (const attempt of failedAttempts) {
+                  const version = attempt.trial_upper || "unknown"
+                  if (!failuresByVersion.has(version)) {
+                    failuresByVersion.set(version, attempt.error || "No error output captured.")
+                  }
+                }
+
+                dependencyFailures.push({
+                  packageName: packageResult.package_name,
+                  projectPath: packageResult.project_path,
+                  dependencyName: dependency.name,
+                  originalRequirements: dependency.original_requirements ?? [],
+                  finalRequirements: dependency.final_requirements ?? [],
+                  failedVersions: [...failuresByVersion.entries()].map(([version, error]) => ({ version, error })),
+                })
+              }
+            }
+
+            if (!dependencyFailures.length) {
+              core.info("No failing dependency candidates found.")
+              return
+            }
+
+            const owner = context.repo.owner
+            const repo = context.repo.repo
+            const openIssues = await github.paginate(github.rest.issues.listForRepo, {
+              owner,
+              repo,
+              state: "open",
+              per_page: 100,
+            })
+            const openIssueTitles = new Set(
+              openIssues.filter((issue) => !issue.pull_request).map((issue) => issue.title)
+            )
+
+            const formatError = (message) => String(message || "No error output captured.").replace(/```/g, "'''")
+
+            for (const failure of dependencyFailures) {
+              const title = `Dependency validation failed: ${failure.dependencyName} (${failure.packageName})`
+              if (openIssueTitles.has(title)) {
+                core.info(`Issue already exists: ${title}`)
+                continue
+              }
+
+              const visibleFailures = failure.failedVersions.slice(0, 5)
+              const omittedCount = failure.failedVersions.length - visibleFailures.length
+              const failureDetails = visibleFailures
+                .map(
+                  (entry) =>
+                    `- \`${entry.version}\`\n\n\`\`\`\n${formatError(entry.error).slice(0, 3500)}\n\`\`\``
+                )
+                .join("\n\n")
+
+              const body = [
+                "Automated dependency range validation found candidate versions that failed checks.",
+                "",
+                `- Package: \`${failure.packageName}\``,
+                `- Project path: \`${failure.projectPath}\``,
+                `- Dependency: \`${failure.dependencyName}\``,
+                `- Original requirements: ${
+                  failure.originalRequirements.length
+                    ? failure.originalRequirements.map((value) => `\`${value}\``).join(", ")
+                    : "_none_"
+                }`,
+                `- Final requirements after run: ${
+                  failure.finalRequirements.length
+                    ? failure.finalRequirements.map((value) => `\`${value}\``).join(", ")
+                    : "_none_"
+                }`,
+                "",
+                "### Failed versions and errors",
+                failureDetails,
+                omittedCount > 0 ? `\n_Additional failed versions omitted: ${omittedCount}_` : "",
+                "",
+                `Workflow run: ${context.serverUrl}/${owner}/${repo}/actions/runs/${context.runId}`,
+              ].join("\n")
+
+              await github.rest.issues.create({
+                owner,
+                repo,
+                title,
+                body,
+              })
+              openIssueTitles.add(title)
+              core.info(`Created issue: ${title}`)
+            }
+
+      - name: Refresh lockfile
+        # Only refresh lockfile after a clean validation to avoid committing known-bad ranges.
+        if: steps.validate_ranges.outcome == 'success'
+        run: uv lock --upgrade
+        working-directory: ./python
+
+      - name: Commit and push dependency updates
+        id: commit_updates
+        if: steps.validate_ranges.outcome == 'success'
+        run: |
+          BRANCH="automation/python-dependency-range-updates"
+
+          git config user.name "github-actions[bot]"
+          git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
+          git checkout -B "${BRANCH}"
+
+          git add python/packages/*/pyproject.toml python/uv.lock
+          if git diff --cached --quiet; then
+            echo "has_changes=false" >> "$GITHUB_OUTPUT"
+            echo "No dependency updates to commit."
+            exit 0
+          fi
+
+          git commit -m "chore: update dependency ranges"
+          git push --force-with-lease --set-upstream origin "${BRANCH}"
+          echo "has_changes=true" >> "$GITHUB_OUTPUT"
+
+      - name: Create or update pull request with GitHub CLI
+        # Only open/update PRs for validated updates to keep automation branches trustworthy.
+        if: steps.validate_ranges.outcome == 'success' && steps.commit_updates.outputs.has_changes == 'true'
+        run: |
+          BRANCH="automation/python-dependency-range-updates"
+          PR_TITLE="Python: chore: update dependency ranges"
+          PR_BODY_FILE="$(mktemp)"
+
+          cat > "${PR_BODY_FILE}" <<'EOF'
+          This PR was generated by the dependency range validation workflow.
+
+          - Ran `uv run poe validate-dependency-bounds-project --mode upper --project "*"`
+          - Updated package dependency bounds
+          - Refreshed `python/uv.lock` with `uv lock --upgrade`
+          EOF
+
+          PR_NUMBER="$(gh pr list --head "${BRANCH}" --base main --state open --json number --jq '.[0].number')"
+          if [ -n "${PR_NUMBER}" ]; then
+            gh pr edit "${PR_NUMBER}" --title "${PR_TITLE}" --body-file "${PR_BODY_FILE}"
+          else
+            gh pr create --base main --head "${BRANCH}" --title "${PR_TITLE}" --body-file "${PR_BODY_FILE}"
+          fi

.github/workflows/python-dev-dependency-upgrade.yml

@@ -0,0 +1,91 @@
+name: Python - Dev Dependency Upgrade
+
+on:
+  workflow_dispatch:
+
+permissions:
+  contents: write
+  pull-requests: write
+
+env:
+  UV_CACHE_DIR: /tmp/.uv-cache
+
+jobs:
+  upgrade-dev-dependencies:
+    name: Upgrade Dev Dependencies
+    runs-on: ubuntu-latest
+    env:
+      UV_PYTHON: "3.13"
+      GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+    steps:
+      - uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+
+      - name: Set up python and install the project
+        uses: ./.github/actions/python-setup
+        with:
+          python-version: ${{ env.UV_PYTHON }}
+          os: ${{ runner.os }}
+        env:
+          UV_CACHE_DIR: /tmp/.uv-cache
+
+      - name: Upgrade dev dependencies and validate workspace
+        run: uv run poe upgrade-dev-dependencies
+        working-directory: ./python
+
+      - name: Commit and push dev dependency updates
+        id: commit_updates
+        run: |
+          BRANCH="automation/python-dev-dependency-updates"
+
+          git config user.name "github-actions[bot]"
+          git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
+          git checkout -B "${BRANCH}"
+
+          git add python/pyproject.toml python/packages/*/pyproject.toml python/uv.lock
+          if git diff --cached --quiet; then
+            echo "has_changes=false" >> "$GITHUB_OUTPUT"
+            echo "No dev dependency updates to commit."
+            exit 0
+          fi
+
+          git commit -F- <<'EOF'
+          Python: chore: upgrade dev dependencies
+          EOF
+          git push --force-with-lease --set-upstream origin "${BRANCH}"
+          echo "has_changes=true" >> "$GITHUB_OUTPUT"
+
+      - name: Create or update pull request with GitHub CLI
+        if: steps.commit_updates.outputs.has_changes == 'true'
+        run: |
+          BRANCH="automation/python-dev-dependency-updates"
+          PR_TITLE="Python: chore: upgrade dev dependencies"
+          PR_BODY_FILE="$(mktemp)"
+
+          cat > "${PR_BODY_FILE}" <<'EOF'
+          ### Motivation and Context
+
+          This automated update refreshes Python dev dependency pins across the workspace and reruns the repo validation gates before opening a pull request.
+
+          ### Description
+
+          - Ran `uv run poe upgrade-dev-dependencies`
+          - Refreshed dev dependency pins in workspace `pyproject.toml` files
+          - Refreshed `python/uv.lock` with `uv lock --upgrade`
+          - Reinstalled from the frozen lockfile and reran `check`, `typing`, and `test`
+
+          ### Contribution Checklist
+
+          - [x] The code builds clean without any errors or warnings
+          - [x] The PR follows the [Contribution Guidelines](https://github.com/microsoft/agent-framework/blob/main/CONTRIBUTING.md)
+          - [x] All unit tests pass, and I have added new tests where possible
+          - [ ] **Is this a breaking change?** If yes, add "[BREAKING]" prefix to the title of the PR.
+          EOF
+
+          PR_NUMBER="$(gh pr list --head "${BRANCH}" --base main --state open --json number --jq '.[0].number')"
+          if [ -n "${PR_NUMBER}" ]; then
+            gh pr edit "${PR_NUMBER}" --title "${PR_TITLE}" --body-file "${PR_BODY_FILE}"
+          else
+            gh pr create --base main --head "${BRANCH}" --title "${PR_TITLE}" --body-file "${PR_BODY_FILE}"
+          fi

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

@@ -170,7 +170,7 @@ jobs:
     environment: integration
     timeout-minutes: 60
     env:
-      UV_PYTHON: "3.10"
+      UV_PYTHON: "3.11"
       OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
       OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
       OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}

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

@@ -67,6 +67,7 @@ jobs:
         with:
           python-version: ${{ matrix.python-version }}
           os: ${{ runner.os }}
+          exclude-packages: ${{ matrix.python-version == '3.10' && 'agent-framework-github-copilot' || '' }}
         env:
           # Configure a constant location for the uv cache
           UV_CACHE_DIR: /tmp/.uv-cache
@@ -75,6 +76,9 @@ jobs:
       - name: Run lab tests
         run: cd packages/lab && uv run poe test
 
+      - name: Run resource-intensive lab tests
+        run: cd packages/lab && uv run pytest -m "resource_intensive and not integration" --junitxml=test-results-resource-intensive.xml
+
       - name: Run lab lint
         run: cd packages/lab && uv run poe lint
 

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

@@ -288,7 +288,7 @@ jobs:
     runs-on: ubuntu-latest
     environment: integration
     env:
-      UV_PYTHON: "3.10"
+      UV_PYTHON: "3.11"
       OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
       OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
       OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}

.github/workflows/python-test-coverage.yml

@@ -20,7 +20,7 @@ jobs:
       run:
         working-directory: python
     env:
-      UV_PYTHON: "3.10"
+      UV_PYTHON: "3.11"
     steps:
       - uses: actions/checkout@v6
       # Save the PR number to a file since the workflow_run event

.github/workflows/python-tests.yml

@@ -34,12 +34,13 @@ jobs:
         with:
           python-version: ${{ matrix.python-version }}
           os: ${{ runner.os }}
+          exclude-packages: ${{ matrix.python-version == '3.10' && 'agent-framework-github-copilot' || '' }}
         env:
           # Configure a constant location for the uv cache
           UV_CACHE_DIR: /tmp/.uv-cache
       # Unit tests
       - name: Run all tests
-        run: uv run poe all-tests
+        run: uv run poe all-tests ${{ matrix.python-version == '3.10' && '--ignore-glob=packages/github_copilot/**' || '' }}
         working-directory: ./python
 
       # Surface failing tests

.gitignore

@@ -205,6 +205,9 @@ WARP.md
 **/memory-bank/
 **/projectBrief.md
 **/tmpclaude*
+# Dependency-bound validation reports
+python/scripts/dependency-*-results.json
+python/scripts/dependencies/dependency-*-results.json
 
 # Azurite storage emulator files
 */__azurite_db_blob__.json*

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

@@ -4,8 +4,8 @@ status: accepted
 contact: westey-m
 date: 2025-07-10 {YYYY-MM-DD when the decision was last updated}
 deciders: sergeymenshykh, markwallace, rbarreto, dmytrostruk, westey-m, eavanvalkenburg, stephentoub
-consulted: 
-informed: 
+consulted:
+informed:
 ---
 
 # Agent Run Responses Design
@@ -64,7 +64,7 @@ Approaches observed from the compared SDKs:
 | AutoGen | **Approach 1** Separates messages into Agent-Agent (maps to Primary) and Internal (maps to Secondary) and these are returned as separate properties on the agent response object.  See [types of messages](https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/messages.html#types-of-messages) and [Response](https://microsoft.github.io/autogen/stable/reference/python/autogen_agentchat.base.html#autogen_agentchat.base.Response) | **Approach 2** Returns a stream of internal events and the last item is a Response object. See [ChatAgent.on_messages_stream](https://microsoft.github.io/autogen/stable/reference/python/autogen_agentchat.base.html#autogen_agentchat.base.ChatAgent.on_messages_stream) |
 | OpenAI Agent SDK | **Approach 1** Separates new_items (Primary+Secondary) from final output (Primary) as separate properties on the [RunResult](https://github.com/openai/openai-agents-python/blob/main/src/agents/result.py#L39) | **Approach 1** Similar to non-streaming, has a way of streaming updates via a method on the response object which includes all data, and then a separate final output property on the response object which is populated only when the run is complete. See [RunResultStreaming](https://github.com/openai/openai-agents-python/blob/main/src/agents/result.py#L136) |
 | Google ADK | **Approach 2** [Emits events](https://google.github.io/adk-docs/runtime/#step-by-step-breakdown) with [FinalResponse](https://github.com/google/adk-java/blob/main/core/src/main/java/com/google/adk/events/Event.java#L232) true (Primary) / false (Secondary) and callers have to filter out those with false to get just the final response message | **Approach 2** Similar to non-streaming except [events](https://google.github.io/adk-docs/runtime/#streaming-vs-non-streaming-output-partialtrue) are emitted with [Partial](https://github.com/google/adk-java/blob/main/core/src/main/java/com/google/adk/events/Event.java#L133) true to indicate that they are streaming messages. A final non partial event is also emitted. |
-| AWS (Strands) | **Approach 3** Returns an [AgentResult](https://strandsagents.com/latest/documentation/docs/api-reference/python/agent/agent_result/) (Primary) with messages and a reason for the run's completion. | **Approach 2** [Streams events](https://strandsagents.com/latest/documentation/docs/api-reference/python/agent/agent/#strands.agent.agent.Agent.stream_async) (Primary+Secondary) including, response text, current_tool_use, even data from "callbacks" (strands plugins) |
+| AWS (Strands) | **Approach 3** Returns an [AgentResult](https://strandsagents.com/docs/api/python/strands.agent.agent_result/) (Primary) with messages and a reason for the run's completion. | **Approach 2** [Streams events](https://strandsagents.com/docs/api/python/strands.agent.agent/) (Primary+Secondary) including, response text, current_tool_use, even data from "callbacks" (strands plugins) |
 | LangGraph | **Approach 2** A mixed list of all [messages](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) | **Approach 2** A mixed list of all [messages](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) |
 | Agno | **Combination of various approaches** Returns a [RunResponse](https://docs.agno.com/reference/agents/run-response) object with text content, messages (essentially chat history including inputs and instructions), reasoning and thinking text properties. Secondary events could potentially be extracted from messages. | **Approach 2** Returns [RunResponseEvent](https://docs.agno.com/reference/agents/run-response#runresponseevent-types-and-attributes) objects including tool call, memory update, etc, information, where the [RunResponseCompletedEvent](https://docs.agno.com/reference/agents/run-response#runresponsecompletedevent) has similar properties to RunResponse|
 | A2A | **Approach 3** Returns a [Task or Message](https://a2aproject.github.io/A2A/latest/specification/#71-messagesend) where the message is the final result (Primary) and task is a reference to a long running process. | **Approach 2** Returns a [stream](https://a2aproject.github.io/A2A/latest/specification/#72-messagestream) that contains task updates (Secondary) and a final message (Primary) |
@@ -496,7 +496,7 @@ We need to decide what AIContent types, each agent response type will be mapped
 |-|-|
 | AutoGen | **Approach 1** Supports [configuring an agent](https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/agents.html#structured-output) at agent creation. |
 | Google ADK | **Approach 1** Both [input and output schemas can be specified for LLM Agents](https://google.github.io/adk-docs/agents/llm-agents/#structuring-data-input_schema-output_schema-output_key) at construction time. This option is specific to this agent type and other agent types do not necessarily support |
-| AWS (Strands) | **Approach 2** Supports a special invocation method called [structured_output](https://strandsagents.com/latest/documentation/docs/api-reference/python/agent/agent/#strands.agent.agent.Agent.structured_output) |
+| AWS (Strands) | **Approach 2** Supports a special invocation method called [structured_output](https://strandsagents.com/docs/api/python/strands.agent.agent/) |
 | LangGraph | **Approach 1** Supports [configuring an agent](https://langchain-ai.github.io/langgraph/agents/agents/?h=structured#6-configure-structured-output) at agent construction time, and a [structured response](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) can be retrieved as a special property on the agent response |
 | Agno | **Approach 1** Supports [configuring an agent](https://docs.agno.com/input-output/structured-output/agent) at agent construction time |
 | A2A | **Informal Approach 2** Doesn't formally support schema negotiation, but [hints can be provided via metadata](https://a2a-protocol.org/latest/specification/#97-structured-data-exchange-requesting-and-providing-json) at invocation time |
@@ -508,7 +508,7 @@ We need to decide what AIContent types, each agent response type will be mapped
 |-|-|
 | AutoGen | Supports a [stop reason](https://microsoft.github.io/autogen/stable/reference/python/autogen_agentchat.base.html#autogen_agentchat.base.TaskResult.stop_reason) which is a freeform text string |
 | Google ADK | [No equivalent present](https://github.com/google/adk-python/blob/main/src/google/adk/events/event.py) |
-| AWS (Strands) | Exposes a [stop_reason](https://strandsagents.com/latest/documentation/docs/api-reference/python/types/event_loop/#strands.types.event_loop.StopReason) property on the [AgentResult](https://strandsagents.com/latest/documentation/docs/api-reference/python/agent/agent_result/) class with options that are tied closely to LLM operations. |
+| AWS (Strands) | Exposes a [stop_reason](https://strandsagents.com/docs/api/python/strands.types.event_loop/) property on the [AgentResult](https://strandsagents.com/docs/api/python/strands.agent.agent_result/) class with options that are tied closely to LLM operations. |
 | LangGraph | No equivalent present, output contains only [messages](https://langchain-ai.github.io/langgraph/agents/run_agents/#output-format) |
 | Agno | [No equivalent present](https://docs.agno.com/reference/agents/run-response) |
 | A2A | No equivalent present, response only contains a [message](https://a2a-protocol.org/latest/specification/#64-message-object) or [task](https://a2a-protocol.org/latest/specification/#61-task-object). |

docs/decisions/0019-python-context-compaction-strategy.md

@@ -1240,3 +1240,10 @@ class AttributionAwareStrategy(CompactionStrategy):
 
 - [ADR-0016: Unifying Context Management with ContextPlugin](0016-python-context-middleware.md) — Parent ADR that established `ContextProvider`, `HistoryProvider`, and `AgentSession` architecture.
 - [Context Compaction Limitations Analysis](https://gist.github.com/victordibia/ec3f3baf97345f7e47da025cf55b999f) — Detailed analysis of why current architecture cannot support in-run compaction, with attempted solutions and their failure modes. Option 4 in this ADR corresponds to "Option A: Middleware Access to Mutable Message Source" from that analysis; Options 1-3 correspond to "Option B: Tool Loop Hook", adapted here to a `BaseChatClient` hook instead of `FunctionInvocationConfiguration`.
+
+### Implementation Rollout Note
+
+Implementation is split into two phases:
+
+1. **Phase 1 (PR 1):** runtime compaction foundation in `agent_framework/_compaction.py`, in-run integration, and extensive core tests, plus in-run compaction samples (`basics`, `advanced`, `custom`).
+2. **Phase 2 (PR 2):** history/storage compaction (`upsert`-based full replacement), provider support, storage tests, and storage-focused sample (`storage`).

docs/harness/pipeline.md

@@ -0,0 +1,214 @@
+# MAF Brainstorming Session
+> March, 17th 2026
+
+## Reference Documents
+
+- [OpenClaw Agent Harness](https://microsoft-my.sharepoint.com/:w:/p/shahen/IQAU5F524RvtTpzjAZIjMf0BAQqMMPYCMRRPnX0eslRiPb0?e=MLF6CL)
+- [Agent Platform Comparison](https://m365.cloud.microsoft/chat/pages/eyJ1IjoiaHR0cHM6Ly9taWNyb3NvZnQuc2hhcmVwb2ludC5jb20vY29udGVudHN0b3JhZ2UveDhGTk8teHRza3VDUlgyX2ZNVEhMYmRXU2tHOE93Skt2VTBCX3pNTDFaVT9uYXY9Y3owbE1rWmpiMjUwWlc1MGMzUnZjbUZuWlNVeVJuZzRSazVQTFhoMGMydDFRMUpZTWw5bVRWUklUR0prVjFOclJ6aFBkMHBMZGxVd1FsOTZUVXd4V2xVbVpEMWlKVEl4TUhscVMzWlphRU5CVlVkV2IwUndhVlpzZUZKekxXTkNZMjltVm1jME1VSnlabVZpWWxKeVNXdFZlamd5YlRBelJtVnhXVlJaVmtwQlkzQlVkMnc0TUNabVBUQXhXVlJZVWxWVVNqSk1WbFV6UlZsWE4xTmFSek5JVDBGUFRWSkNXRWhLUzFFbVl6MGxNa1ltWVQxTWIyOXdRWEJ3Sm5BOUpUUXdabXgxYVdSNEpUSkdiRzl2Y0Mxd1lXZGxMV052Ym5SaGFXNWxjaVo0UFNVM1FpVXlNbmNsTWpJbE0wRWxNakpVTUZKVVZVaDRkR0ZYVG5saU0wNTJXbTVSZFdNeWFHaGpiVlozWWpKc2RXUkROV3BpTWpFNFdXbEZkMlZYY0V4a2JHeHZVVEJHVmxJeFduWlNTRUp3Vm0xNE5GVnVUWFJaTUVwcVlqSmFWMXA2VVhoUmJrcHRXbGRLYVZWdVNrcGhNVlkyVDBSS2RFMUVUa2RhV0VaYVZrWnNWMU5yUm1walJsSXpZa1JuZDJaRVFYaFhWbEpaVld4V1ZWUldUa0pPTUdSWlZGVk9SbFpVVWs5U2EydDVVMVJqZVZGc2FGWldSa3BDVFRGSkpUTkVKVEl5SlRKREpUSXlhU1V5TWlVelFTVXlNbU5oTkRSbFlUZGtMVEF5TWpjdE5ERm1OQzFpWVRsaUxUUm1OV1kyTlRWaVpEZGpPU1V5TWlVM1JBPT0ifQ?auth=2&ct=1773767195553&or=Teams-HL&LOF=1)
+- [LangChain Deep Agents](https://docs.langchain.com/oss/python/deepagents/overview)
+- [CodeAct](https://arxiv.org/abs/2402.01030)
+- [AI Accelerator - Foundry](https://microsoft.sharepoint.com/:p:/t/CoreAIStudioOutboundProduct/IQAFfbFIu5E7RLMcFmX_7C6EAU2xt1TxnGbR36EN6JTwX0Y?e=9UsKZ6)
+- [Foundry Developer Portal (Hosted Agents)](https://hosted-agents-builder.lemonriver-6a2ef1ee.westus2.azurecontainerapps.io/getting-started)
+
+
+## Next Steps
+
+Demo for MVP session on campus next week.
+
+1. Code Act: How to with MAF
+1. Harness Preview: Single agent with compaction, tools (including shell or file-system), and simple orchestration loop.
+
+Deploy agent with harness as _Foundry Hosted Agent_.
+
+
+## What Is the Agent Harness?
+
+The runtime control plane that enables reliable, long-running agent execution. Not a specific agent. Not a specific set of tools. It's the **infrastructure layer** that any agent can run within.
+
+What it provides:
+
+- **Outer loop** — model ↔ tools ↔ state ↔ repair, running as long as it needs to
+- **State & durability** — checkpoints, resume, memory
+- **Tool plumbing** — registry, schema, invocation, error handling
+- **Governance** — permissions, human-in-the-loop, policies
+- **Context management** — compaction, eviction, externalization
+- **Observability** — traces, transcripts, replay
+
+
+### Where We Stand
+
+MAF compared against DeepAgents, Amplifier, Opencode, Copilot CLI, OpenAI Codex, and Claude Code — every one of them has these capabilities. MAF has some partially, most not at all.
+
+| Priority | Capability | Layer | MAF Today |
+|---|:---|:---|:---|
+| **P0** | Agent/User Orchestration | Harness | 🟡 Workflows or part of `AIAgent`? |
+| **P0** | Session Persistence | Harness | 🟢 `AgentSession`/`AIContextProvider` |
+| **P0** | Context Compaction | Harness | 🟢 In preview |
+| **P0** | Memory | Environment | 🟡 Partial — Python core only |
+| **P0** | Permissions / Scoping | Harness | 🔴 Nothing |
+| **P0** | Tool: Composite Tool Calling | Harness | 🔴 Needs definition |
+| **P0** | Tool: Filesystem | Environment | 🟢 Local access |
+| **P0** | Tool: Shell Execution | Environment | 🟢 Local access |
+| **P0** | Tool: Todo / Planning | Harness | 🔴 Nothing |
+| **P0** | Sub-Agent Delegation | Harness | 🟡 Partial — orchestration exists, state isolation incomplete |
+| **P1** | Skills / Prompt Presets | Persona | 🔴 Nothing |
+| **P1** | Model Routing | Harness | 🔴 Nothing |
+| **P1** | Agent Budgets | Persona | 🔴 Nothing |
+| **P1** | Prompt Caching | Persona | 🔴 Nothing |
+
+### Open Issues
+
+- How does this look in DevUI?
+
+
+
+## Features
+
+### Agent/User Orchestration
+
+How does the harness manage structured, multi-turn data collection from the user? 
+What's the interaction model between the outer loop and user-facing slot-filling prompts? 
+How does it compose with compaction and task management? How does the agent re-ask or repair slot values after partial completion?
+
+### Session Persistence
+
+`AgentSession` is directly serializable and there is also a `ChatHistoryProvider` option for more complex storage needs. 
+
+Open questions: 
+- How to handle schema evolution? 
+- How to version `AgentSession`? 
+- How to support partial loading for long histories?
+- Does a session include more than conversation context (i.e. messages)?
+
+### Compaction Strategy
+
+Two API tiers — **simple for most developers, advanced for full control**.
+
+**Simple (menu-driven)** — developer picks from preset enums:
+```csharp
+builder.AddCompaction(Approach.Balanced, Size.Compact, summarizingChatClient);
+```
+
+**Advanced (pipeline)** — ordered stages, least to most aggressive:
+```csharp
+builder.AddCompaction(
+    new PipelineCompactionStrategy(
+        // 1. Gentle: collapse old tool-call groups into short summaries
+        new ToolResultCompactionStrategy(CompactionTriggers.MessagesExceed(7)),
+
+        // 2. Moderate: use an LLM to summarize older conversation spans into a concise message
+        new SummarizationCompactionStrategy(summarizerChatClient, CompactionTriggers.TokensExceed(0x6000)),
+
+        // 3. Aggressive: keep only the last N user turns and their responses
+        new SlidingWindowCompactionStrategy(CompactionTriggers.TurnsExceed(32)),
+
+        // 4. Emergency: drop oldest groups until under the token budget
+        new TruncationCompactionStrategy(CompactionTriggers.TokensExceed(0x8000))));
+```
+
+1. **Gentle:** Collapse old tool-call groups into short summaries (`ToolResultCompactionStrategy`)
+2. **Moderate:** LLM-based summarization of older conversation spans (`SummarizationCompactionStrategy`)
+3. **Aggressive:** Sliding window — keep only last N user turns (`SlidingWindowCompactionStrategy`)
+
+### Memories
+
+Loads from backend storage, injects into system prompt automatically.
+
+### Permissions / Scoping
+
+Agent Scopes define the explicit boundaries within which an agent is allowed to operate, constraining where it can act 
+(for example, a single folder or service) and what level of access it has (such as read‑only, write, or execute). 
+By enforcing scoped resources and permissions, this feature ensures the agent’s actions remain intentionally limited, 
+predictable, and aligned with least‑privilege principles—preventing overreach even when the agent could otherwise reason 
+about broader options.
+
+### Tools: File System / Shell
+
+Both should follow the same pattern: **interface-based, with pluggable backends**. Local is the default. Remote/sandboxed is supported.
+
+- **File System** — `FilesystemTool` with `read`, `write`, `edit`, `list`, `glob`, `grep`. Backed by a `FilesystemProtocol` with `LocalFilesystem` (direct access) and `HostedFilesystem` (remote sandbox). Must include path validation, traversal prevention, large-file pagination. Consider snapshot/restore for tracking changes during execution.
+
+- **Shell** — `LocalShellTool` / `HostedShellTool`. Configurable timeout, output truncation, working directory, environment variables. Open question: what sandboxing and permission model?
+
+- **Computer Use (TODO)** — same interface pattern for screen/mouse/keyboard interaction. Future work. Security and governance implications are significant.
+
+### Tools: Task Management
+
+`TodoTool` with `write_todos`. `TodoItem` has content + status (pending / in progress / completed). `TodoMiddleware` injects current todos into the system prompt — this is what gives the agent the ability to self-plan and track its own progress.
+
+Open debate: P0 or P1? "An agent _can_ work with only filesystem + shell. But for Claude Code-like complex multi-step tasks, this is P0."
+
+### Data Driven: Input Schema / Structured Data Output
+
+How does the harness support defining what data the agent needs (input schema) and what the agent produces (structured output)? Is this related to or distinct from slot filling? How does the developer define and validate schemas?
+### Sub-Agent Delegation
+
+MAF already has orchestration (Sequential, Concurrent, Group Chat, Magentic, Handoff, Human-in-the-loop). The gap is **state isolation**: sub-agents need their own message history and todo state, isolated from the parent, returning results as tool responses. "A lot of task planners and coding agents use sub-agents. This feels P0."
+
+### Skills / Prompt Presets (P1)
+
+`SkillsMiddleware` loads reusable instruction sets from `SKILL.md` files with YAML frontmatter (Anthropic Skills format). Progressive disclosure — metadata first, content on demand. Skill discovery from filesystem paths.
+
+### Model Routing (P1)
+
+`ModelRouterMiddleware` with strategies: cost-aware (minimize cost for task requirements) and heuristic (rule-based, e.g., stronger model for code tasks).
+
+### Agent Budgets
+
+Agent Budgets define a hard execution limit—such as a maximum number of tokens, turns, or tool calls—within which an agent must 
+decide whether to act and how far to pursue a task, directly shaping planning, delegation, and early stopping behavior. 
+Unlike a context‑management budget, which governs what information is retained or loaded, an agent budget constrains execution itself, 
+informing decisions like skipping steps, reducing depth, or terminating when the remaining budget cannot justify further action.
+
+### Prompt Caching (P1)
+
+Prompt caching is important for coding agents.  
+When an agent is iterating on a coding problem, the same or similar prompts are often repeated.
+We need a great caching story to speed up iteration and reduce costs.
+
+
+## Shape
+
+Everything hangs off a **fluent builder pattern**.  
+Ideally this builder is identical with the agent-builder pattern, so developers 
+can seamlessly transition from "building an agent" to "building a harness for that agent" without learning a new API. 
+
+Example:
+
+```
+builder
+    .AddCompaction(...)
+    .AddTool(filesystemTool)
+    .AddTool(shellTool)
+    .AddMemory(...)
+    .AddTodo(...)
+```
+
+- **Composability** — developers opt in/out of individual capabilities. Minimal harness = just the outer loop. Full harness = everything.
+- **Hosting** — must integrate cleanly with DI and hosting (ASP.NET, Azure Functions).
+- **Presets** — opinionated starters? (`HarnessPresets.CodingAgent`, `HarnessPresets.Conversational`, `HarnessPresets.Research`)
+- **Two-tier deployment** — "develop local, deploy remote":
+  - _Local:_ Direct filesystem/shell, fast iteration, debugging, human-in-the-loop
+  - _Production (Foundry Hosted Agents):_ Managed containers, autoscaling, identity, observability, Teams / M365 Copilot / Web
+- The interface-based tool abstractions (`LocalFilesystem` ↔ `HostedFilesystem`, `LocalShell` ↔ `HostedShell`) are what make the two-tier model work.
+
+
+## Validation
+
+- **Prompt evaluation** — test default harness prompts (compaction, slot filling, etc.) across OpenAI, Azure OpenAI, Anthropic, and other providers
+- **Custom prompt override** — developers can replace default prompts; need to document and validate the override mechanism
+- **Compaction testing** — verify different pipeline configurations produce correct and useful results
+- **Test strategy** — unit tests, integration tests, model-in-the-loop evaluation, benchmarks
+
+
+## Tutorials
+
+Suggested progression:
+
+1. Getting started — minimal harness setup
+2. Adding compaction to a long-running conversation
+3. Using tools (filesystem, shell) within the harness
+4. Slot filling / guided conversations
+5. Task management and structured output
+6. Advanced — custom compaction pipelines, memory, sub-agents
+

dotnet/.github/skills/build-and-test/SKILL.md

@@ -17,14 +17,17 @@ dotnet format             # Auto-fix formatting for all projects
 
 # Build/test/format a specific project (preferred for isolated/internal changes)
 dotnet build src/Microsoft.Agents.AI.<Package> --tl:off
-dotnet test tests/Microsoft.Agents.AI.<Package>.UnitTests
+dotnet test --project tests/Microsoft.Agents.AI.<Package>.UnitTests
 dotnet format src/Microsoft.Agents.AI.<Package>
 
 # Run a single test
-dotnet test --filter "FullyQualifiedName~Namespace.TestClassName.TestMethodName"
+# Replace the filter values with the appropriate assembly, namespace, class, and method names for the test you want to run and use * as a wildcard elsewhere, e.g. "/*/*/HttpClientTests/GetAsync_ReturnsSuccessStatusCode"
+# Use `--ignore-exit-code 8` to avoid failing the build when no tests are found for some projects
+dotnet test --filter-query "/<assemblyFilter>/<namespaceFilter>/<classFilter>/<methodFilter>" --ignore-exit-code 8
 
 # Run unit tests only
-dotnet test --filter FullyQualifiedName\~UnitTests
+# Use `--ignore-exit-code 8` to avoid failing the build when no tests are found for integration test projects
+dotnet test --filter-query "/*UnitTests*/*/*/*" --ignore-exit-code 8
 ```
 
 Use `--tl:off` when building to avoid flickering when running commands in the agent.
@@ -56,7 +59,7 @@ Example: Running tests for a single project using .NET 10.
 
 ```bash
 # From dotnet/ directory
-dotnet test ./tests/Microsoft.Agents.AI.Abstractions.UnitTests -f net10.0
+dotnet test --project ./tests/Microsoft.Agents.AI.Abstractions.UnitTests -f net10.0
 ```
 
 Example: Running a single test in a specific project using .NET 10.
@@ -64,7 +67,7 @@ Provide the full namespace, class name, and method name for the test you want to
 
 ```bash
 # From dotnet/ directory
-dotnet test ./tests/Microsoft.Agents.AI.Abstractions.UnitTests -f net10.0 --filter "FullyQualifiedName~Microsoft.Agents.AI.Abstractions.UnitTests.AgentRunOptionsTests.CloningConstructorCopiesProperties"
+dotnet test --project ./tests/Microsoft.Agents.AI.Abstractions.UnitTests -f net10.0 --filter-query "/*/Microsoft.Agents.AI.Abstractions.UnitTests/AgentRunOptionsTests/CloningConstructorCopiesProperties"
 ```
 
 ### Multi-target framework tip
@@ -83,3 +86,45 @@ Just remember to run `dotnet restore` after pulling changes, making changes to p
 Unit tests target both .NET Framework as well as .NET Core. When running on Linux, only the .NET Core tests can be run, as .NET Framework is not supported on Linux.
 
 To run only the .NET Core tests, use the `-f net10.0` option with `dotnet test`.
+
+### Microsoft Testing Platform (MTP)
+
+Tests use the [Microsoft Testing Platform](https://learn.microsoft.com/dotnet/core/testing/unit-testing-platform-intro) via xUnit v3. Key differences from the legacy VSTest runner:
+
+- **`dotnet test` requires `--project`** to specify a test project directly (positional arguments are no longer supported).
+- **Test output** uses the MTP format (e.g., `[✓112/x0/↓0]` progress and `Test run summary: Passed!`).
+- **TRX reports** use `--report-xunit-trx` instead of `--logger trx`.
+- **Code coverage** uses `Microsoft.Testing.Extensions.CodeCoverage` with `--coverage --coverage-output-format cobertura`.
+- **Running a test project directly** is supported via `dotnet run --project <test-project>`. This bypasses the `dotnet test` infrastructure and runs the test executable directly with the MTP command line.
+
+- **Running tests across the solution** with a filter may cause some projects to match zero tests, which MTP treats as a failure (exit code 8). Use `--ignore-exit-code 8` to suppress this:
+
+```bash
+# Run all unit tests across the solution, ignoring projects with no matching tests
+dotnet test --solution ./agent-framework-dotnet.slnx --no-build -f net10.0 --ignore-exit-code 8
+```
+
+- **Running tests with `--solution` for a specific TFM** requires all projects in the solution to support that TFM. Not all projects target every framework (e.g., some are `net10.0`-only). Use `./dotnet/eng/scripts/New-FilteredSolution.ps1` to generate a filtered solution:
+
+```powershell
+# Generate a filtered solution for net472 and run tests
+$filtered = ./dotnet/eng/scripts/New-FilteredSolution.ps1 -Solution dotnet/agent-framework-dotnet.slnx -TargetFramework net472
+dotnet test --solution $filtered --no-build -f net472 --ignore-exit-code 8
+
+# Exclude samples and keep only unit test projects
+./dotnet/eng/scripts/New-FilteredSolution.ps1 -Solution dotnet/agent-framework-dotnet.slnx -TargetFramework net10.0 -ExcludeSamples -TestProjectNameFilter "*UnitTests*" -OutputPath dotnet/filtered-unit.slnx
+```
+
+```bash
+# Run tests via dotnet test (uses MTP under the hood)
+dotnet test --project ./tests/Microsoft.Agents.AI.UnitTests -f net10.0
+
+# Run tests with code coverage (Cobertura format)
+dotnet test --project ./tests/Microsoft.Agents.AI.UnitTests -f net10.0 --coverage --coverage-output-format cobertura --coverage-settings ./tests/coverage.runsettings
+
+# Run tests directly via dotnet run (MTP native command line)
+dotnet run --project ./tests/Microsoft.Agents.AI.UnitTests -f net10.0
+
+# Show MTP command line help
+dotnet run --project ./tests/Microsoft.Agents.AI.UnitTests -f net10.0 -- -?
+```

dotnet/Directory.Packages.props

@@ -11,8 +11,8 @@
   </PropertyGroup>
   <ItemGroup>
     <!-- Aspire.* -->
-    <PackageVersion Include="Anthropic" Version="12.3.0" />
-    <PackageVersion Include="Anthropic.Foundry" Version="0.4.1" />
+    <PackageVersion Include="Anthropic" Version="12.8.0" />
+    <PackageVersion Include="Anthropic.Foundry" Version="0.4.2" />
     <PackageVersion Include="Aspire.Azure.AI.OpenAI" Version="13.0.0-preview.1.25560.3" />
     <PackageVersion Include="Aspire.Hosting.AppHost" Version="$(AspireAppHostSdkVersion)" />
     <PackageVersion Include="Aspire.Hosting.Azure.CognitiveServices" Version="$(AspireAppHostSdkVersion)" />
@@ -33,14 +33,15 @@
     <!-- Newtonsoft.Json -->
     <PackageVersion Include="Newtonsoft.Json" Version="13.0.4" />
     <!-- System.* -->
-    <PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.3" />
+    <PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.4" />
     <PackageVersion Include="Microsoft.Bcl.HashCode" Version="6.0.0" />
+    <PackageVersion Include="Microsoft.Bcl.Memory" Version="10.0.4" />
     <PackageVersion Include="System.ClientModel" Version="1.9.0" />
     <PackageVersion Include="System.CodeDom" Version="10.0.0" />
     <PackageVersion Include="System.Collections.Immutable" Version="10.0.1" />
     <PackageVersion Include="System.CommandLine" Version="2.0.0-rc.2.25502.107" />
     <PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="10.0.3" />
-    <PackageVersion Include="System.Linq.AsyncEnumerable" Version="10.0.0" />
+    <PackageVersion Include="System.Linq.AsyncEnumerable" Version="10.0.4" />
     <PackageVersion Include="System.Net.Http.Json" Version="10.0.0" />
     <PackageVersion Include="System.Net.ServerSentEvents" Version="10.0.3" />
     <PackageVersion Include="System.Text.Json" Version="10.0.3" />
@@ -101,13 +102,14 @@
     <PackageVersion Include="Microsoft.Agents.Authentication.Msal" Version="1.3.171-beta" />
     <PackageVersion Include="Microsoft.Agents.Hosting.AspNetCore" Version="1.3.171-beta" />
     <!-- A2A -->
-    <PackageVersion Include="A2A" Version="0.3.3-preview" />
-    <PackageVersion Include="A2A.AspNetCore" Version="0.3.3-preview" />
+    <PackageVersion Include="A2A" Version="0.3.4-preview" />
+    <PackageVersion Include="A2A.AspNetCore" Version="0.3.4-preview" />
     <!-- MCP -->
-    <PackageVersion Include="ModelContextProtocol" Version="0.8.0-preview.1" />
+    <PackageVersion Include="ModelContextProtocol" Version="1.1.0" />
     <!-- Inference SDKs -->
     <PackageVersion Include="AWSSDK.Extensions.Bedrock.MEAI" Version="4.0.5.1" />
     <PackageVersion Include="Microsoft.ML.OnnxRuntimeGenAI" Version="0.10.0" />
+    <PackageVersion Include="Microsoft.ML.Tokenizers" Version="2.0.0" />
     <PackageVersion Include="OllamaSharp" Version="5.4.8" />
     <PackageVersion Include="OpenAI" Version="2.8.0" />
     <!-- Identity -->
@@ -140,12 +142,10 @@
     <PackageVersion Include="Microsoft.AspNetCore.TestHost" Condition="'$(TargetFramework)' == 'net10.0'" Version="10.0.0" />
     <PackageVersion Include="Microsoft.NET.Test.Sdk" Version="18.0.0" />
     <PackageVersion Include="Moq" Version="[4.18.4]" />
-    <PackageVersion Include="xunit" Version="2.9.3" />
-    <PackageVersion Include="xunit.abstractions" Version="2.0.3" />
-    <PackageVersion Include="xunit.runner.visualstudio" Version="3.1.3" />
-    <PackageVersion Include="Xunit.SkippableFact" Version="1.5.23" />
-    <PackageVersion Include="xretry" Version="1.9.0" />
-    <PackageVersion Include="coverlet.collector" Version="6.0.4" />
+    <PackageVersion Include="xunit.v3.mtp-v2" Version="3.2.2" />
+    <PackageVersion Include="xunit.runner.visualstudio" Version="3.1.5" />
+    <PackageVersion Include="xRetry.v3" Version="1.0.0-rc3" />
+    <PackageVersion Include="Microsoft.Testing.Extensions.CodeCoverage" Version="18.4.1" />
     <!-- Symbols -->
     <PackageVersion Include="Microsoft.SourceLink.GitHub" Version="8.0.0" />
     <!-- Toolset -->

dotnet/agent-framework-dotnet.slnx

@@ -56,6 +56,7 @@
     <Project Path="samples/02-agents/Agents/Agent_Step15_DeepResearch/Agent_Step15_DeepResearch.csproj" />
     <Project Path="samples/02-agents/Agents/Agent_Step16_Declarative/Agent_Step16_Declarative.csproj" />
     <Project Path="samples/02-agents/Agents/Agent_Step17_AdditionalAIContext/Agent_Step17_AdditionalAIContext.csproj" />
+    <Project Path="samples/02-agents/Agents/Agent_Step18_CompactionPipeline/Agent_Step18_CompactionPipeline.csproj" />
   </Folder>
   <Folder Name="/Samples/02-agents/DeclarativeAgents/">
     <Project Path="samples/02-agents/DeclarativeAgents/ChatClient/DeclarativeChatClientAgents.csproj" />
@@ -103,6 +104,7 @@
     <Project Path="samples/02-agents/AgentWithMemory/AgentWithMemory_Step01_ChatHistoryMemory/AgentWithMemory_Step01_ChatHistoryMemory.csproj" />
     <Project Path="samples/02-agents/AgentWithMemory/AgentWithMemory_Step02_MemoryUsingMem0/AgentWithMemory_Step02_MemoryUsingMem0.csproj" />
     <Project Path="samples/02-agents/AgentWithMemory/AgentWithMemory_Step04_MemoryUsingFoundry/AgentWithMemory_Step04_MemoryUsingFoundry.csproj" />
+    <Project Path="samples/02-agents/AgentWithMemory/AgentWithMemory_Step05_BoundedChatHistory/AgentWithMemory_Step05_BoundedChatHistory.csproj" />
   </Folder>
   <Folder Name="/Samples/02-agents/AgentWithOpenAI/">
     <File Path="samples/02-agents/AgentWithOpenAI/README.md" />
@@ -284,8 +286,13 @@
   </Folder>
   <Folder Name="/Samples/05-end-to-end/HostedAgents/">
     <Project Path="samples/05-end-to-end/HostedAgents/AgentsInWorkflows/AgentsInWorkflows.csproj" />
+    <Project Path="samples/05-end-to-end/HostedAgents/AgentThreadAndHITL/AgentThreadAndHITL.csproj" />
     <Project Path="samples/05-end-to-end/HostedAgents/AgentWithHostedMCP/AgentWithHostedMCP.csproj" />
+    <Project Path="samples/05-end-to-end/HostedAgents/AgentWithLocalTools/AgentWithLocalTools.csproj" />
     <Project Path="samples/05-end-to-end/HostedAgents/AgentWithTextSearchRag/AgentWithTextSearchRag.csproj" />
+    <Project Path="samples/05-end-to-end/HostedAgents/AgentWithTools/AgentWithTools.csproj" />
+    <Project Path="samples/05-end-to-end/HostedAgents/FoundryMultiAgent/FoundryMultiAgent.csproj" />
+    <Project Path="samples/05-end-to-end/HostedAgents/FoundrySingleAgent/FoundrySingleAgent.csproj" />
   </Folder>
   <Folder Name="/Samples/05-end-to-end/AspNetAgentAuthorization/">
     <File Path="samples/05-end-to-end/AspNetAgentAuthorization/docker-compose.yml" />
@@ -311,7 +318,6 @@
   </Folder>
   <Folder Name="/Solution Items/.github/workflows/">
     <File Path="../.github/workflows/dotnet-build-and-test.yml" />
-    <File Path="../.github/workflows/dotnet-check-coverage.ps1" />
     <File Path="../.github/workflows/dotnet-format.yml" />
   </Folder>
   <Folder Name="/Solution Items/demos/">
@@ -348,6 +354,10 @@
     <File Path="eng/MSBuild/Shared.props" />
     <File Path="eng/MSBuild/Shared.targets" />
   </Folder>
+  <Folder Name="/Solution Items/eng/scripts/">
+    <File Path="eng/scripts/dotnet-check-coverage.ps1" />
+    <File Path="eng/scripts/New-FilteredSolution.ps1" />
+  </Folder>
   <Folder Name="/Solution Items/nuget/">
     <File Path="nuget/icon.png" />
     <File Path="nuget/nuget-package.props" />
@@ -413,6 +423,10 @@
     <File Path="src/Shared/IntegrationTests/OpenAIConfiguration.cs" />
     <File Path="src/Shared/IntegrationTests/README.md" />
   </Folder>
+  <Folder Name="/Solution Items/src/Shared/IntegrationTestsAzureCredentials/">
+    <File Path="src/Shared/IntegrationTestsAzureCredentials/README.md" />
+    <File Path="src/Shared/IntegrationTestsAzureCredentials/TestAzureCliCredentials.cs" />
+  </Folder>
   <Folder Name="/Solution Items/src/Shared/Samples/">
     <File Path="src/Shared/Samples/BaseSample.cs" />
     <File Path="src/Shared/Samples/README.md" />

dotnet/agent-framework-release.slnf

@@ -14,6 +14,7 @@
       "src\\Microsoft.Agents.AI.Declarative\\Microsoft.Agents.AI.Declarative.csproj",
       "src\\Microsoft.Agents.AI.DevUI\\Microsoft.Agents.AI.DevUI.csproj",
       "src\\Microsoft.Agents.AI.DurableTask\\Microsoft.Agents.AI.DurableTask.csproj",
+      "src\\Microsoft.Agents.AI.FoundryMemory\\Microsoft.Agents.AI.FoundryMemory.csproj",
       "src\\Microsoft.Agents.AI.Hosting.A2A.AspNetCore\\Microsoft.Agents.AI.Hosting.A2A.AspNetCore.csproj",
       "src\\Microsoft.Agents.AI.Hosting.A2A\\Microsoft.Agents.AI.Hosting.A2A.csproj",
       "src\\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore\\Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.csproj",

dotnet/eng/MSBuild/Shared.props

@@ -8,6 +8,9 @@
   <ItemGroup Condition="'$(InjectSharedIntegrationTestCode)' == 'true'">
     <Compile Include="$(MSBuildThisFileDirectory)\..\..\src\Shared\IntegrationTests\*.cs" LinkBase="Shared\IntegrationTests" />
   </ItemGroup>
+  <ItemGroup Condition="'$(InjectSharedIntegrationTestAzureCredentialsCode)' == 'true'">
+    <Compile Include="$(MSBuildThisFileDirectory)\..\..\src\Shared\IntegrationTestsAzureCredentials\*.cs" LinkBase="Shared\IntegrationTestsAzureCredentials" />
+  </ItemGroup>
   <ItemGroup Condition="'$(InjectSharedBuildTestCode)' == 'true'">
     <Compile Include="$(MSBuildThisFileDirectory)\..\..\src\Shared\CodeTests\*.cs" LinkBase="Shared\CodeTests" />
   </ItemGroup>

dotnet/eng/scripts/New-FilteredSolution.ps1

@@ -0,0 +1,145 @@
+#!/usr/bin/env pwsh
+# Copyright (c) Microsoft. All rights reserved.
+
+<#
+.SYNOPSIS
+    Generates a filtered .slnx solution file by removing projects that don't match the specified criteria.
+
+.DESCRIPTION
+    Parses a .slnx solution file and applies one or more filters:
+    - Removes projects that don't support the specified target framework (via MSBuild query).
+    - Optionally removes all sample projects (under samples/).
+    - Optionally filters test projects by name pattern (e.g., only *UnitTests*).
+    Writes the filtered solution to the specified output path and prints the path.
+
+.PARAMETER Solution
+    Path to the source .slnx solution file.
+
+.PARAMETER TargetFramework
+    The target framework to filter by (e.g., net10.0, net472).
+
+.PARAMETER Configuration
+    Optional MSBuild configuration used when querying TargetFrameworks. Defaults to Debug.
+
+.PARAMETER TestProjectNameFilter
+    Optional wildcard pattern to filter test project names (e.g., *UnitTests*, *IntegrationTests*).
+    When specified, only test projects whose filename matches this pattern are kept.
+
+.PARAMETER ExcludeSamples
+    When specified, removes all projects under the samples/ directory from the solution.
+
+.PARAMETER OutputPath
+    Optional output path for the filtered .slnx file. If not specified, a temp file is created.
+
+.EXAMPLE
+    # Generate a filtered solution and run tests
+    $filtered = ./dotnet/eng/scripts/New-FilteredSolution.ps1 -Solution dotnet/agent-framework-dotnet.slnx -TargetFramework net472
+    dotnet test --solution $filtered --no-build -f net472
+
+.EXAMPLE
+    # Generate a solution with only unit test projects
+    ./dotnet/eng/scripts/New-FilteredSolution.ps1 -Solution dotnet/agent-framework-dotnet.slnx -TargetFramework net10.0 -TestProjectNameFilter "*UnitTests*" -OutputPath filtered-unit.slnx
+
+.EXAMPLE
+    # Inline usage with dotnet test (PowerShell)
+    dotnet test --solution (./dotnet/eng/scripts/New-FilteredSolution.ps1 -Solution dotnet/agent-framework-dotnet.slnx -TargetFramework net472) --no-build -f net472
+#>
+
+[CmdletBinding()]
+param(
+    [Parameter(Mandatory)]
+    [string]$Solution,
+
+    [Parameter(Mandatory)]
+    [string]$TargetFramework,
+
+    [string]$Configuration = "Debug",
+
+    [string]$TestProjectNameFilter,
+
+    [switch]$ExcludeSamples,
+
+    [string]$OutputPath
+)
+
+$ErrorActionPreference = "Stop"
+
+# Resolve the solution path
+$solutionPath = Resolve-Path $Solution
+$solutionDir = Split-Path $solutionPath -Parent
+
+if (-not $OutputPath) {
+    $OutputPath = [System.IO.Path]::Combine([System.IO.Path]::GetTempPath(), "filtered-$(Split-Path $solutionPath -Leaf)")
+}
+
+# Parse the .slnx XML
+[xml]$slnx = Get-Content $solutionPath -Raw
+
+$removed = @()
+$kept = @()
+
+# Remove sample projects if requested
+if ($ExcludeSamples) {
+    $sampleProjects = $slnx.SelectNodes("//Project[contains(@Path, 'samples/')]")
+    foreach ($proj in $sampleProjects) {
+        $projRelPath = $proj.GetAttribute("Path")
+        Write-Verbose "Removing (sample): $projRelPath"
+        $removed += $projRelPath
+        $proj.ParentNode.RemoveChild($proj) | Out-Null
+    }
+    Write-Host "Removed $($sampleProjects.Count) sample project(s)." -ForegroundColor Yellow
+}
+
+# Filter all remaining projects by target framework
+$allProjects = $slnx.SelectNodes("//Project")
+
+foreach ($proj in $allProjects) {
+    $projRelPath = $proj.GetAttribute("Path")
+    $projFullPath = Join-Path $solutionDir $projRelPath
+    $projFileName = Split-Path $projRelPath -Leaf
+    $isTestProject = $projRelPath -like "*tests/*"
+
+    # Filter test projects by name pattern if specified
+    if ($isTestProject -and $TestProjectNameFilter -and ($projFileName -notlike $TestProjectNameFilter)) {
+        Write-Verbose "Removing (name filter): $projRelPath"
+        $removed += $projRelPath
+        $proj.ParentNode.RemoveChild($proj) | Out-Null
+        continue
+    }
+
+    if (-not (Test-Path $projFullPath)) {
+        Write-Verbose "Project not found, keeping in solution: $projRelPath"
+        $kept += $projRelPath
+        continue
+    }
+
+    # Query the project's target frameworks using MSBuild
+    $targetFrameworks = & dotnet msbuild $projFullPath -getProperty:TargetFrameworks -p:Configuration=$Configuration -nologo 2>$null
+    $targetFrameworks = $targetFrameworks.Trim()
+
+    if ($targetFrameworks -like "*$TargetFramework*") {
+        Write-Verbose "Keeping: $projRelPath (targets: $targetFrameworks)"
+        $kept += $projRelPath
+    }
+    else {
+        Write-Verbose "Removing: $projRelPath (targets: $targetFrameworks, missing: $TargetFramework)"
+        $removed += $projRelPath
+        $proj.ParentNode.RemoveChild($proj) | Out-Null
+    }
+}
+
+# Write the filtered solution
+$slnx.Save($OutputPath)
+
+# Report results to stderr so stdout is clean for piping
+Write-Host "Filtered solution written to: $OutputPath" -ForegroundColor Green
+if ($removed.Count -gt 0) {
+    Write-Host "Removed $($removed.Count) project(s):" -ForegroundColor Yellow
+    foreach ($r in $removed) {
+        Write-Host "  - $r" -ForegroundColor Yellow
+    }
+}
+Write-Host "Kept $($kept.Count) project(s)." -ForegroundColor Green
+
+# Output the path for piping
+Write-Output $OutputPath

dotnet/global.json

@@ -1,7 +1,10 @@
 {
     "sdk": {
-        "version": "10.0.100",
+        "version": "10.0.200",
         "rollForward": "minor",
         "allowPrerelease": false
+    },
+    "test": {
+        "runner": "Microsoft.Testing.Platform"
     }
 }

dotnet/nuget/nuget-package.props

@@ -2,11 +2,11 @@
   <PropertyGroup>
     <!-- Central version prefix - applies to all nuget packages. -->
     <VersionPrefix>1.0.0</VersionPrefix>
-    <RCNumber>3</RCNumber>
+    <RCNumber>4</RCNumber>
     <PackageVersion Condition="'$(IsReleaseCandidate)' == 'true'">$(VersionPrefix)-rc$(RCNumber)</PackageVersion>
-    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).260304.1</PackageVersion>
-    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' == ''">$(VersionPrefix)-preview.260304.1</PackageVersion>
-    <GitTag>1.0.0-rc3</GitTag>
+    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).260311.1</PackageVersion>
+    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' == ''">$(VersionPrefix)-preview.260311.1</PackageVersion>
+    <GitTag>1.0.0-rc4</GitTag>
 
     <Configurations>Debug;Release;Publish</Configurations>
     <IsPackable>true</IsPackable>

dotnet/samples/02-agents/AGUI/Step01_GettingStarted/Server/Program.cs

@@ -4,7 +4,6 @@ using Azure.AI.OpenAI;
 using Azure.Identity;
 using Microsoft.Agents.AI;
 using Microsoft.Agents.AI.Hosting.AGUI.AspNetCore;
-using Microsoft.Extensions.AI;
 using OpenAI.Chat;
 
 WebApplicationBuilder builder = WebApplication.CreateBuilder(args);
@@ -27,7 +26,7 @@ ChatClient chatClient = new AzureOpenAIClient(
         new DefaultAzureCredential())
     .GetChatClient(deploymentName);
 
-AIAgent agent = chatClient.AsIChatClient().AsAIAgent(
+AIAgent agent = chatClient.AsAIAgent(
     name: "AGUIAssistant",
     instructions: "You are a helpful assistant.");
 

dotnet/samples/02-agents/AGUI/Step01_GettingStarted/Server/Server.csproj

@@ -10,7 +10,6 @@
   <ItemGroup>
     <PackageReference Include="Azure.AI.OpenAI" />
     <PackageReference Include="Azure.Identity" />
-    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
   </ItemGroup>
 
   <ItemGroup>

dotnet/samples/02-agents/AGUI/Step02_BackendTools/Server/Program.cs

@@ -82,7 +82,7 @@ ChatClient chatClient = new AzureOpenAIClient(
         new DefaultAzureCredential())
     .GetChatClient(deploymentName);
 
-ChatClientAgent agent = chatClient.AsIChatClient().AsAIAgent(
+ChatClientAgent agent = chatClient.AsAIAgent(
     name: "AGUIAssistant",
     instructions: "You are a helpful assistant with access to restaurant information.",
     tools: tools);

dotnet/samples/02-agents/AGUI/Step02_BackendTools/Server/Server.csproj

@@ -10,7 +10,6 @@
   <ItemGroup>
     <PackageReference Include="Azure.AI.OpenAI" />
     <PackageReference Include="Azure.Identity" />
-    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
   </ItemGroup>
 
   <ItemGroup>

dotnet/samples/02-agents/AGUI/Step03_FrontendTools/Server/Program.cs

@@ -4,7 +4,6 @@ using Azure.AI.OpenAI;
 using Azure.Identity;
 using Microsoft.Agents.AI;
 using Microsoft.Agents.AI.Hosting.AGUI.AspNetCore;
-using Microsoft.Extensions.AI;
 using OpenAI.Chat;
 
 WebApplicationBuilder builder = WebApplication.CreateBuilder(args);
@@ -27,7 +26,7 @@ ChatClient chatClient = new AzureOpenAIClient(
         new DefaultAzureCredential())
     .GetChatClient(deploymentName);
 
-AIAgent agent = chatClient.AsIChatClient().AsAIAgent(
+AIAgent agent = chatClient.AsAIAgent(
     name: "AGUIAssistant",
     instructions: "You are a helpful assistant.");
 

dotnet/samples/02-agents/AGUI/Step03_FrontendTools/Server/Server.csproj

@@ -10,7 +10,6 @@
   <ItemGroup>
     <PackageReference Include="Azure.AI.OpenAI" />
     <PackageReference Include="Azure.Identity" />
-    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
   </ItemGroup>
 
   <ItemGroup>

dotnet/samples/02-agents/AGUI/Step04_HumanInLoop/Server/Program.cs

@@ -60,7 +60,7 @@ ChatClient openAIChatClient = new AzureOpenAIClient(
         new DefaultAzureCredential())
     .GetChatClient(deploymentName);
 
-ChatClientAgent baseAgent = openAIChatClient.AsIChatClient().AsAIAgent(
+ChatClientAgent baseAgent = openAIChatClient.AsAIAgent(
     name: "AGUIAssistant",
     instructions: "You are a helpful assistant in charge of approving expenses",
     tools: tools);

dotnet/samples/02-agents/AGUI/Step04_HumanInLoop/Server/Server.csproj

@@ -10,7 +10,6 @@
   <ItemGroup>
     <PackageReference Include="Azure.AI.OpenAI" />
     <PackageReference Include="Azure.Identity" />
-    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
   </ItemGroup>
 
   <ItemGroup>

dotnet/samples/02-agents/AGUI/Step05_StateManagement/Server/Program.cs

@@ -4,7 +4,6 @@ using Azure.AI.OpenAI;
 using Azure.Identity;
 using Microsoft.Agents.AI;
 using Microsoft.Agents.AI.Hosting.AGUI.AspNetCore;
-using Microsoft.Extensions.AI;
 using Microsoft.Extensions.Options;
 using OpenAI.Chat;
 using RecipeAssistant;
@@ -37,7 +36,7 @@ ChatClient chatClient = new AzureOpenAIClient(
         new DefaultAzureCredential())
     .GetChatClient(deploymentName);
 
-AIAgent baseAgent = chatClient.AsIChatClient().AsAIAgent(
+AIAgent baseAgent = chatClient.AsAIAgent(
     name: "RecipeAgent",
     instructions: """
         You are a helpful recipe assistant. When users ask you to create or suggest a recipe,

dotnet/samples/02-agents/AGUI/Step05_StateManagement/Server/Server.csproj

@@ -10,7 +10,6 @@
   <ItemGroup>
     <PackageReference Include="Azure.AI.OpenAI" />
     <PackageReference Include="Azure.Identity" />
-    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
   </ItemGroup>
 
   <ItemGroup>

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step05_BoundedChatHistory/AgentWithMemory_Step05_BoundedChatHistory.csproj

@@ -0,0 +1,22 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+    <PackageReference Include="Microsoft.SemanticKernel.Connectors.InMemory" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step05_BoundedChatHistory/BoundedChatHistoryProvider.cs

@@ -0,0 +1,133 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+using Microsoft.Extensions.VectorData;
+
+namespace SampleApp;
+
+/// <summary>
+/// A <see cref="ChatHistoryProvider"/> that keeps a bounded window of recent messages in session state
+/// (via <see cref="InMemoryChatHistoryProvider"/>) and overflows older messages to a vector store
+/// (via <see cref="ChatHistoryMemoryProvider"/>). When providing chat history, it searches the vector
+/// store for relevant older messages and prepends them as a memory context message.
+/// </summary>
+/// <remarks>
+/// Only non-system messages are counted towards the session state limit and overflow mechanism. System messages are always retained in session state and are not included in the vector store.
+/// Function calls and function results are also dropped when truncation happens, both from in-memory state, and they are also not persisted to the vector store.
+/// </remarks>
+internal sealed class BoundedChatHistoryProvider : ChatHistoryProvider, IDisposable
+{
+    private readonly InMemoryChatHistoryProvider _chatHistoryProvider;
+    private readonly ChatHistoryMemoryProvider _memoryProvider;
+    private readonly TruncatingChatReducer _reducer;
+    private readonly string _contextPrompt;
+    private IReadOnlyList<string>? _stateKeys;
+
+    /// <summary>
+    /// Initializes a new instance of the <see cref="BoundedChatHistoryProvider"/> class.
+    /// </summary>
+    /// <param name="maxSessionMessages">The maximum number of non-system messages to keep in session state before overflowing to the vector store.</param>
+    /// <param name="vectorStore">The vector store to use for storing and retrieving overflow chat history.</param>
+    /// <param name="collectionName">The name of the collection for storing overflow chat history in the vector store.</param>
+    /// <param name="vectorDimensions">The number of dimensions to use for the chat history vector store embeddings.</param>
+    /// <param name="stateInitializer">A delegate that initializes the memory provider state, providing the storage and search scopes.</param>
+    /// <param name="contextPrompt">Optional prompt to prefix memory search results. Defaults to a standard memory context prompt.</param>
+    public BoundedChatHistoryProvider(
+        int maxSessionMessages,
+        VectorStore vectorStore,
+        string collectionName,
+        int vectorDimensions,
+        Func<AgentSession?, ChatHistoryMemoryProvider.State> stateInitializer,
+        string? contextPrompt = null)
+    {
+        if (maxSessionMessages < 0)
+        {
+            throw new ArgumentOutOfRangeException(nameof(maxSessionMessages), "maxSessionMessages must be non-negative.");
+        }
+
+        this._reducer = new TruncatingChatReducer(maxSessionMessages);
+        this._chatHistoryProvider = new InMemoryChatHistoryProvider(new InMemoryChatHistoryProviderOptions
+        {
+            ChatReducer = this._reducer,
+            ReducerTriggerEvent = InMemoryChatHistoryProviderOptions.ChatReducerTriggerEvent.AfterMessageAdded,
+            StorageInputRequestMessageFilter = msgs => msgs,
+        });
+        this._memoryProvider = new ChatHistoryMemoryProvider(
+            vectorStore,
+            collectionName,
+            vectorDimensions,
+            stateInitializer,
+            options: new ChatHistoryMemoryProviderOptions
+            {
+                SearchInputMessageFilter = msgs => msgs,
+                StorageInputRequestMessageFilter = msgs => msgs,
+            });
+        this._contextPrompt = contextPrompt
+            ?? "The following are memories from earlier in this conversation. Use them to inform your responses:";
+    }
+
+    /// <inheritdoc />
+    public override IReadOnlyList<string> StateKeys => this._stateKeys ??= this._chatHistoryProvider.StateKeys.Concat(this._memoryProvider.StateKeys).ToArray();
+
+    /// <inheritdoc />
+    protected override async ValueTask<IEnumerable<ChatMessage>> ProvideChatHistoryAsync(
+        InvokingContext context,
+        CancellationToken cancellationToken = default)
+    {
+        // Delegate to the inner provider's full lifecycle (retrieve, filter, stamp, merge with request messages).
+        var chatHistoryProviderInputContext = new InvokingContext(context.Agent, context.Session, []);
+        var allMessages = await this._chatHistoryProvider.InvokingAsync(chatHistoryProviderInputContext, cancellationToken).ConfigureAwait(false);
+
+        // Search the vector store for relevant older messages.
+        var aiContext = new AIContext { Messages = context.RequestMessages.ToList() };
+        var invokingContext = new AIContextProvider.InvokingContext(
+            context.Agent, context.Session, aiContext);
+
+        var result = await this._memoryProvider.InvokingAsync(invokingContext, cancellationToken).ConfigureAwait(false);
+
+        // Extract only the messages added by the memory provider (stamped with AIContextProvider source type).
+        var memoryMessages = result.Messages?
+            .Where(m => m.GetAgentRequestMessageSourceType() == AgentRequestMessageSourceType.AIContextProvider)
+            .ToList();
+
+        if (memoryMessages is { Count: > 0 })
+        {
+            var memoryText = string.Join("\n", memoryMessages.Select(m => m.Text).Where(t => !string.IsNullOrWhiteSpace(t)));
+
+            if (!string.IsNullOrWhiteSpace(memoryText))
+            {
+                var contextMessage = new ChatMessage(ChatRole.User, $"{this._contextPrompt}\n{memoryText}");
+                return new[] { contextMessage }.Concat(allMessages);
+            }
+        }
+
+        return allMessages;
+    }
+
+    /// <inheritdoc />
+    protected override async ValueTask StoreChatHistoryAsync(
+        InvokedContext context,
+        CancellationToken cancellationToken = default)
+    {
+        // Delegate storage to the in-memory provider. Its TruncatingChatReducer (AfterMessageAdded trigger)
+        // will automatically truncate to the configured maximum and expose any removed messages.
+        var innerContext = new InvokedContext(
+            context.Agent, context.Session, context.RequestMessages, context.ResponseMessages!);
+        await this._chatHistoryProvider.InvokedAsync(innerContext, cancellationToken).ConfigureAwait(false);
+
+        // Archive any messages that the reducer removed to the vector store.
+        if (this._reducer.RemovedMessages is { Count: > 0 })
+        {
+            var overflowContext = new AIContextProvider.InvokedContext(
+                context.Agent, context.Session, this._reducer.RemovedMessages, []);
+            await this._memoryProvider.InvokedAsync(overflowContext, cancellationToken).ConfigureAwait(false);
+        }
+    }
+
+    /// <inheritdoc/>
+    public void Dispose()
+    {
+        this._memoryProvider.Dispose();
+    }
+}

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step05_BoundedChatHistory/Program.cs

@@ -0,0 +1,79 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create a bounded chat history provider that keeps a configurable number of
+// recent messages in session state and automatically overflows older messages to a vector store.
+// When the agent is invoked, it searches the vector store for relevant older messages and
+// prepends them as a "memory" context message before the recent session history.
+
+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.Chat;
+using SampleApp;
+
+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";
+
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+var credential = new DefaultAzureCredential();
+
+// Create a vector store to store overflow chat messages.
+// For demonstration purposes, we are using an in-memory vector store.
+// Replace this with a persistent vector store implementation for production scenarios.
+VectorStore vectorStore = new InMemoryVectorStore(new InMemoryVectorStoreOptions()
+{
+    EmbeddingGenerator = new AzureOpenAIClient(new Uri(endpoint), credential)
+        .GetEmbeddingClient(embeddingDeploymentName)
+        .AsIEmbeddingGenerator()
+});
+
+var sessionId = Guid.NewGuid().ToString();
+
+// Create the BoundedChatHistoryProvider with a maximum of 4 non-system messages in session state.
+// It internally creates an InMemoryChatHistoryProvider with a TruncatingChatReducer and a
+// ChatHistoryMemoryProvider with the correct configuration to ensure overflow messages are
+// automatically archived to the vector store and recalled via semantic search.
+var boundedProvider = new BoundedChatHistoryProvider(
+    maxSessionMessages: 4,
+    vectorStore,
+    collectionName: "chathistory-overflow",
+    vectorDimensions: 3072,
+    session => new ChatHistoryMemoryProvider.State(
+        storageScope: new() { UserId = "UID1", SessionId = sessionId },
+        searchScope: new() { UserId = "UID1" }));
+
+// Create the agent with the bounded chat history provider.
+AIAgent agent = new AzureOpenAIClient(new Uri(endpoint), credential)
+    .GetChatClient(deploymentName)
+    .AsAIAgent(new ChatClientAgentOptions
+    {
+        ChatOptions = new() { Instructions = "You are a helpful assistant. Answer questions concisely." },
+        Name = "Assistant",
+        ChatHistoryProvider = boundedProvider,
+    });
+
+// Start a conversation. The first several exchanges will fill up the session state window.
+AgentSession session = await agent.CreateSessionAsync();
+
+Console.WriteLine("--- Filling the session window (4 messages max) ---\n");
+
+Console.WriteLine(await agent.RunAsync("My favorite color is blue.", session));
+Console.WriteLine(await agent.RunAsync("I have a dog named Max.", session));
+
+// At this point the session state holds 4 messages (2 user + 2 assistant).
+// The next exchange will push the oldest messages into the vector store.
+Console.WriteLine("\n--- Next exchange will trigger overflow to vector store ---\n");
+
+Console.WriteLine(await agent.RunAsync("What is the capital of France?", session));
+
+// The oldest messages about favorite color have now been archived to the vector store.
+// Ask the agent something that requires recalling the overflowed information.
+Console.WriteLine("\n--- Asking about overflowed information (should recall from vector store) ---\n");
+
+Console.WriteLine(await agent.RunAsync("What is my favorite color?", session));

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step05_BoundedChatHistory/README.md

@@ -0,0 +1,40 @@
+# Bounded Chat History with Vector Store Overflow
+
+This sample demonstrates how to create a custom `ChatHistoryProvider` that keeps a bounded window of recent messages in session state and automatically overflows older messages to a vector store. When the agent is invoked, it searches the vector store for relevant older messages and prepends them as memory context.
+
+## Concepts
+
+- **`TruncatingChatReducer`**: A custom `IChatReducer` that keeps the most recent N messages and exposes removed messages via a `RemovedMessages` property.
+- **`BoundedChatHistoryProvider`**: A custom `ChatHistoryProvider` that composes:
+  - `InMemoryChatHistoryProvider` for fast session-state storage (bounded by the reducer)
+  - `ChatHistoryMemoryProvider` for vector-store overflow and semantic search of older messages
+
+## Prerequisites
+
+- [.NET 10 SDK](https://dotnet.microsoft.com/download/dotnet/10.0)
+- An Azure OpenAI resource with:
+  - A chat deployment (e.g., `gpt-4o-mini`)
+  - An embedding deployment (e.g., `text-embedding-3-large`)
+
+## Configuration
+
+Set the following environment variables:
+
+| Variable | Description | Default |
+|---|---|---|
+| `AZURE_OPENAI_ENDPOINT` | Your Azure OpenAI endpoint URL | *(required)* |
+| `AZURE_OPENAI_DEPLOYMENT_NAME` | Chat model deployment name | `gpt-4o-mini` |
+| `AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME` | Embedding model deployment name | `text-embedding-3-large` |
+
+## Running the Sample
+
+```bash
+dotnet run
+```
+
+## How it Works
+
+1. The agent starts a conversation with a bounded session window of 4 non-system, non-function messages (i.e., user/assistant turns). System messages are always preserved, and function call/result messages are truncated and not preserved.
+2. As messages accumulate beyond the limit, the `TruncatingChatReducer` removes the oldest messages.
+3. The `BoundedChatHistoryProvider` detects the removed messages and stores them in a vector store via `ChatHistoryMemoryProvider`.
+4. On subsequent invocations, the provider searches the vector store for relevant older messages and prepends them as memory context, allowing the agent to recall information from earlier in the conversation.

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step05_BoundedChatHistory/TruncatingChatReducer.cs

@@ -0,0 +1,65 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using Microsoft.Extensions.AI;
+
+namespace SampleApp;
+
+/// <summary>
+/// A truncating chat reducer that keeps the most recent messages up to a configured maximum,
+/// preserving any leading system message. Removed messages are exposed via <see cref="RemovedMessages"/>
+/// so that a caller can archive them (e.g. to a vector store).
+/// </summary>
+internal sealed class TruncatingChatReducer : IChatReducer
+{
+    private readonly int _maxMessages;
+
+    /// <summary>
+    /// Initializes a new instance of the <see cref="TruncatingChatReducer"/> class.
+    /// </summary>
+    /// <param name="maxMessages">The maximum number of non-system messages to retain.</param>
+    public TruncatingChatReducer(int maxMessages)
+    {
+        this._maxMessages = maxMessages > 0 ? maxMessages : throw new ArgumentOutOfRangeException(nameof(maxMessages));
+    }
+
+    /// <summary>
+    /// Gets the messages that were removed during the most recent call to <see cref="ReduceAsync"/>.
+    /// </summary>
+    public IReadOnlyList<ChatMessage> RemovedMessages { get; private set; } = [];
+
+    /// <inheritdoc />
+    public Task<IEnumerable<ChatMessage>> ReduceAsync(IEnumerable<ChatMessage> messages, CancellationToken cancellationToken)
+    {
+        _ = messages ?? throw new ArgumentNullException(nameof(messages));
+
+        ChatMessage? systemMessage = null;
+        Queue<ChatMessage> retained = new(capacity: this._maxMessages);
+        List<ChatMessage> removed = [];
+
+        foreach (var message in messages)
+        {
+            if (message.Role == ChatRole.System)
+            {
+                // Preserve the first system message outside the counting window.
+                systemMessage ??= message;
+            }
+            else if (!message.Contents.Any(c => c is FunctionCallContent or FunctionResultContent))
+            {
+                if (retained.Count >= this._maxMessages)
+                {
+                    removed.Add(retained.Dequeue());
+                }
+
+                retained.Enqueue(message);
+            }
+        }
+
+        this.RemovedMessages = removed;
+
+        IEnumerable<ChatMessage> result = systemMessage is not null
+            ? new[] { systemMessage }.Concat(retained)
+            : retained;
+
+        return Task.FromResult(result);
+    }
+}

dotnet/samples/02-agents/AgentWithMemory/README.md

@@ -8,5 +8,6 @@ These samples show how to create an agent with the Agent Framework that uses Mem
 |[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](../../01-get-started/04_memory/)|This sample demonstrates how to create a custom memory component and attach it to an agent.|
 |[Memory with Azure AI Foundry](./AgentWithMemory_Step04_MemoryUsingFoundry/)|This sample demonstrates how to create and run an agent that uses Azure AI Foundry's managed memory service to extract and retrieve individual memories.|
+|[Bounded Chat History with Overflow](./AgentWithMemory_Step05_BoundedChatHistory/)|This sample demonstrates how to create a bounded chat history provider that overflows older messages to a vector store and recalls them as memories.|
 
 > **See also**: [Memory Search with Foundry Agents](../FoundryAgents/FoundryAgents_Step22_MemorySearch/) - demonstrates using the built-in Memory Search tool with Azure Foundry Agents.

dotnet/samples/02-agents/Agents/Agent_Step18_CompactionPipeline/Agent_Step18_CompactionPipeline.csproj

@@ -0,0 +1,21 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/02-agents/Agents/Agent_Step18_CompactionPipeline/Program.cs

@@ -0,0 +1,120 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to use a CompactionProvider with a compaction pipeline
+// as an AIContextProvider for an agent's in-run context management. The pipeline chains multiple
+// compaction strategies from gentle to aggressive:
+//   1. ToolResultCompactionStrategy - Collapses old tool-call groups into concise summaries
+//   2. SummarizationCompactionStrategy - LLM-compresses older conversation spans
+//   3. SlidingWindowCompactionStrategy - Keeps only the most recent N user turns
+//   4. TruncationCompactionStrategy - Emergency token-budget backstop
+
+using System.ComponentModel;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.Compaction;
+using Microsoft.Extensions.AI;
+
+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";
+
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AzureOpenAIClient openAIClient = new(new Uri(endpoint), new DefaultAzureCredential());
+
+// Create a chat client for the agent and a separate one for the summarization strategy.
+// Using the same model for simplicity; in production, use a smaller/cheaper model for summarization.
+IChatClient agentChatClient = openAIClient.GetChatClient(deploymentName).AsIChatClient();
+IChatClient summarizerChatClient = openAIClient.GetChatClient(deploymentName).AsIChatClient();
+
+// Define a tool the agent can use, so we can see tool-result compaction in action.
+[Description("Look up the current price of a product by name.")]
+static string LookupPrice([Description("The product name to look up.")] string productName) =>
+    productName.ToUpperInvariant() switch
+    {
+        "LAPTOP" => "The laptop costs $999.99.",
+        "KEYBOARD" => "The keyboard costs $79.99.",
+        "MOUSE" => "The mouse costs $29.99.",
+        _ => $"Sorry, I don't have pricing for '{productName}'."
+    };
+
+// Configure the compaction pipeline with one of each strategy, ordered least to most aggressive.
+PipelineCompactionStrategy compactionPipeline =
+    new(// 1. Gentle: collapse old tool-call groups into short summaries
+        new ToolResultCompactionStrategy(CompactionTriggers.MessagesExceed(7)),
+
+        // 2. Moderate: use an LLM to summarize older conversation spans into a concise message
+        new SummarizationCompactionStrategy(summarizerChatClient, CompactionTriggers.TokensExceed(0x500)),
+
+        // 3. Aggressive: keep only the last N user turns and their responses
+        new SlidingWindowCompactionStrategy(CompactionTriggers.TurnsExceed(4)),
+
+        // 4. Emergency: drop oldest groups until under the token budget
+        new TruncationCompactionStrategy(CompactionTriggers.TokensExceed(0x8000)));
+
+// Create the agent with a CompactionProvider that uses the compaction pipeline.
+AIAgent agent =
+    agentChatClient
+        .AsBuilder()
+        // Note: Adding the CompactionProvider at the builder level means it will be applied to all agents
+        // built from this builder and will manage context for both agent messages and tool calls.
+        .UseAIContextProviders(new CompactionProvider(compactionPipeline))
+        .BuildAIAgent(
+            new ChatClientAgentOptions
+            {
+                Name = "ShoppingAssistant",
+                ChatOptions = new()
+                {
+                    Instructions =
+                        """
+                        You are a helpful, but long winded, shopping assistant.
+                        Help the user look up prices and compare products.
+                        When responding, Be sure to be extra descriptive and use as
+                        many words as possible without sounding ridiculous.
+                        """,
+                    Tools = [AIFunctionFactory.Create(LookupPrice)]
+                },
+                // Note: AIContextProviders may be specified here instead of ChatClientBuilder.UseAIContextProviders.
+                // Specifying compaction at the agent level skips compaction in the function calling loop.
+                //AIContextProviders = [new CompactionProvider(compactionPipeline)]
+            });
+
+AgentSession session = await agent.CreateSessionAsync();
+
+// Helper to print chat history size
+void PrintChatHistory()
+{
+    if (session.TryGetInMemoryChatHistory(out var history))
+    {
+        Console.ForegroundColor = ConsoleColor.Cyan;
+        Console.WriteLine($"\n[Messages: #{history.Count}]\n");
+        Console.ResetColor();
+    }
+}
+
+// Run a multi-turn conversation with tool calls to exercise the pipeline.
+string[] prompts =
+[
+    "What's the price of a laptop?",
+    "How about a keyboard?",
+    "And a mouse?",
+    "Which product is the cheapest?",
+    "Can you compare the laptop and the keyboard for me?",
+    "What was the first product I asked about?",
+    "Thank you!",
+];
+
+foreach (string prompt in prompts)
+{
+    Console.ForegroundColor = ConsoleColor.Cyan;
+    Console.Write("\n[User] ");
+    Console.ResetColor();
+    Console.WriteLine(prompt);
+    Console.ForegroundColor = ConsoleColor.Cyan;
+    Console.Write("\n[Agent] ");
+    Console.ResetColor();
+    Console.WriteLine(await agent.RunAsync(prompt, session));
+
+    PrintChatHistory();
+}

dotnet/samples/02-agents/Agents/Agent_Step18_CompactionPipeline/README.md

@@ -0,0 +1,132 @@
+# Compaction Pipeline
+
+This sample demonstrates how to use a `CompactionProvider` with a `PipelineCompactionStrategy` to manage long conversation histories in a token-efficient way. The pipeline chains four compaction strategies, ordered from gentle to aggressive, so that the least disruptive strategy runs first and more aggressive strategies only activate when necessary.
+
+## What This Sample Shows
+
+- **`CompactionProvider`** — an `AIContextProvider` that applies a compaction strategy before each agent invocation, keeping only the most relevant messages within the model's context window
+- **`PipelineCompactionStrategy`** — chains multiple compaction strategies into an ordered pipeline; each strategy evaluates its own trigger independently and operates on the output of the previous one
+- **`ToolResultCompactionStrategy`** — collapses older tool-call groups into concise inline summaries, activated by a message-count trigger
+- **`SummarizationCompactionStrategy`** — uses an LLM to compress older conversation spans into a single summary message, activated by a token-count trigger
+- **`SlidingWindowCompactionStrategy`** — retains only the most recent N user turns and their responses, activated by a turn-count trigger
+- **`TruncationCompactionStrategy`** — emergency backstop that drops the oldest groups until the conversation fits within a hard token budget
+- **`CompactionTriggers`** — factory methods (`MessagesExceed`, `TokensExceed`, `TurnsExceed`, `GroupsExceed`, `HasToolCalls`, `All`, `Any`) that control when each strategy activates
+
+## Concepts
+
+### Message groups
+
+The compaction engine organizes messages into atomic *groups* that are treated as indivisible units during compaction. A group is either:
+
+| Group kind | Contents |
+|---|---|
+| `System` | System prompt message(s) |
+| `User` | A single user message |
+| `ToolCall` | One assistant message with tool calls + the matching tool result messages |
+| `AssistantText` | A single assistant text-only message |
+| `Summary` | One or more messages summarizing earlier conversation spans, produced by compaction strategies |
+
+`Summary` groups (`CompactionGroupKind.Summary`) are created by compaction strategies (for example, `SummarizationCompactionStrategy`) and do not originate directly from user or assistant messages.
+Strategies exclude entire groups rather than individual messages, preserving the tool-call/result pairing required by most model APIs.
+
+### Compaction triggers
+
+A `CompactionTrigger` is a predicate evaluated against the current `MessageIndex`. When the trigger fires, the strategy performs compaction; when it does not fire, the strategy is skipped. Available triggers are:
+
+| Trigger | Activates when… |
+|---|---|
+| `CompactionTriggers.Always` | Always (unconditional) |
+| `CompactionTriggers.Never` | Never (disabled) |
+| `CompactionTriggers.MessagesExceed(n)` | Included message count > n |
+| `CompactionTriggers.TokensExceed(n)` | Included token count > n |
+| `CompactionTriggers.TurnsExceed(n)` | Included user-turn count > n |
+| `CompactionTriggers.GroupsExceed(n)` | Included group count > n |
+| `CompactionTriggers.HasToolCalls()` | At least one included tool-call group exists |
+| `CompactionTriggers.All(...)` | All supplied triggers fire (logical AND) |
+| `CompactionTriggers.Any(...)` | Any supplied trigger fires (logical OR) |
+
+### Pipeline ordering
+
+Order strategies from **least aggressive** to **most aggressive**. The pipeline runs every strategy whose trigger is met. Earlier strategies reduce the conversation gently so that later, more destructive strategies may not need to activate at all.
+
+```
+1. ToolResultCompactionStrategy  – gentle:    replaces verbose tool results with a short label
+2. SummarizationCompactionStrategy – moderate: LLM-summarizes older turns
+3. SlidingWindowCompactionStrategy – aggressive: drops turns beyond the window
+4. TruncationCompactionStrategy   – emergency:  hard token-budget enforcement
+```
+
+## Prerequisites
+
+- .NET 10 SDK or later
+- Azure OpenAI service endpoint and model deployment
+- Azure CLI installed and authenticated
+
+**Note**: This sample uses `DefaultAzureCredential`. Sign in with `az login` before running. For production, prefer a specific credential such as `ManagedIdentityCredential`. For more information, see the [Azure CLI authentication documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+
+## Environment Variables
+
+```powershell
+$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"  # Required
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"                       # Optional, defaults to gpt-4o-mini
+```
+
+## Running the Sample
+
+```powershell
+cd dotnet/samples/02-agents/Agents/Agent_Step18_CompactionPipeline
+dotnet run
+```
+
+## Expected Behavior
+
+The sample runs a seven-turn shopping-assistant conversation with tool calls. After each turn it prints the full message count so you can observe the pipeline compaction doesn't alter the source conversation.
+
+Each of the four compaction strategies has a deliberately low threshold so that it activates during the short demonstration conversation. In a production scenario you would raise the thresholds to match your model's context window and cost requirements.
+
+## Customizing the Pipeline
+
+### Using a single strategy
+
+If you only need one compaction strategy, pass it directly to `CompactionProvider` without wrapping it in a pipeline:
+
+```csharp
+CompactionProvider provider =
+    new(new SlidingWindowCompactionStrategy(CompactionTriggers.TurnsExceed(20)));
+```
+
+### Ad-hoc compaction outside the provider pipeline
+
+`CompactionProvider.CompactAsync` applies a strategy to an arbitrary list of messages without an active agent session:
+
+```csharp
+IEnumerable<ChatMessage> compacted = await CompactionProvider.CompactAsync(
+    new TruncationCompactionStrategy(CompactionTriggers.TokensExceed(8000)),
+    existingMessages);
+```
+
+### Using a different model for summarization
+
+The `SummarizationCompactionStrategy` accepts any `IChatClient`. Use a smaller, cheaper model to reduce summarization cost:
+
+```csharp
+IChatClient summarizerChatClient = openAIClient.GetChatClient("gpt-4o-mini").AsIChatClient();
+new SummarizationCompactionStrategy(summarizerChatClient, CompactionTriggers.TokensExceed(4000))
+```
+
+### Registering through `ChatClientAgentOptions`
+
+`CompactionProvider` can also be specified directly on `ChatClientAgentOptions` instead of calling `UseAIContextProviders` on the `ChatClientBuilder`:
+
+```csharp
+AIAgent agent = agentChatClient
+    .AsBuilder()
+    .BuildAIAgent(new ChatClientAgentOptions
+    {
+        AIContextProviders = [new CompactionProvider(compactionPipeline)]
+    });
+```
+
+This places the compaction provider at the agent level instead of the chat client level, which allows you to use different compaction strategies for different agents that share the same chat client.
+
+> Note: In this mode the `CompactionProvider` is not engaged during the tool calling loop. Agent-level `AIContextProviders` run before chat history is stored, so any synthetic summary messages produced by `CompactionProvider` can become part of the persisted history when using `ChatHistoryProvider`. If you want to compact only the request context while preserving the original stored history, register `CompactionProvider` on the `ChatClientBuilder` via `UseAIContextProviders(...)` instead of on `ChatClientAgentOptions`.

dotnet/samples/02-agents/Agents/README.md

@@ -44,6 +44,7 @@ Before you begin, ensure you have the following prerequisites:
 |[Deep research with an agent](./Agent_Step15_DeepResearch/)|This sample demonstrates how to use the Deep Research Tool to perform comprehensive research on complex topics|
 |[Declarative agent](./Agent_Step16_Declarative/)|This sample demonstrates how to declaratively define an agent.|
 |[Providing additional AI Context to an agent using multiple AIContextProviders](./Agent_Step17_AdditionalAIContext/)|This sample demonstrates how to inject additional AI context into a ChatClientAgent using multiple custom AIContextProvider components that are attached to the agent.|
+|[Using compaction pipeline with an agent](./Agent_Step18_CompactionPipeline/)|This sample demonstrates how to use a compaction pipeline to efficiently limit the size of the conversation history for an agent.|
 
 ## Running the samples from the console
 

dotnet/samples/02-agents/FoundryAgents/FoundryAgents_Step22_MemorySearch/Program.cs

@@ -12,11 +12,8 @@ using OpenAI.Responses;
 
 string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
 string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
-
-// Memory store configuration
-// NOTE: Memory stores must be created beforehand via Azure Portal or Python SDK.
-// The .NET SDK currently only supports using existing memory stores with agents.
-string memoryStoreName = Environment.GetEnvironmentVariable("AZURE_AI_MEMORY_STORE_ID") ?? throw new InvalidOperationException("AZURE_AI_MEMORY_STORE_ID is not set.");
+string embeddingModelName = Environment.GetEnvironmentVariable("AZURE_AI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-ada-002";
+string memoryStoreName = Environment.GetEnvironmentVariable("AZURE_AI_MEMORY_STORE_ID") ?? $"foundry-memory-sample-{Guid.NewGuid():N}";
 
 const string AgentInstructions = """
     You are a helpful assistant that remembers past conversations.
@@ -32,71 +29,57 @@ const string AgentNameNative = "MemorySearchAgent-NATIVE";
 string userScope = $"user_{Environment.MachineName}";
 
 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+DefaultAzureCredential credential = new();
+AIProjectClient aiProjectClient = new(new Uri(endpoint), credential);
+
+// Ensure the memory store exists and has memories to retrieve.
+await EnsureMemoryStoreAsync();
 
 // Create the Memory Search tool configuration
-MemorySearchPreviewTool memorySearchTool = new(memoryStoreName, userScope)
-{
-    // Optional: Configure how quickly new memories are indexed (in seconds)
-    UpdateDelay = 1,
-
-    // Optional: Configure search behavior
-    SearchOptions = new MemorySearchToolOptions
-    {
-        // Additional search options can be configured here if needed
-    }
-};
+MemorySearchPreviewTool memorySearchTool = new(memoryStoreName, userScope) { UpdateDelay = 0 };
 
 // Create agent using Option 1 (MEAI) or Option 2 (Native SDK)
 AIAgent agent = await CreateAgentWithMEAI();
 // AIAgent agent = await CreateAgentWithNativeSDK();
 
-Console.WriteLine("Agent created with Memory Search tool. Starting conversation...\n");
-
-// Conversation 1: Share some personal information
-Console.WriteLine("User: My name is Alice and I love programming in C#.");
-AgentResponse response1 = await agent.RunAsync("My name is Alice and I love programming in C#.");
-Console.WriteLine($"Agent: {response1.Messages.LastOrDefault()?.Text}\n");
-
-// Allow time for memory to be indexed
-await Task.Delay(2000);
-
-// Conversation 2: Test if the agent remembers
-Console.WriteLine("User: What's my name and what programming language do I prefer?");
-AgentResponse response2 = await agent.RunAsync("What's my name and what programming language do I prefer?");
-Console.WriteLine($"Agent: {response2.Messages.LastOrDefault()?.Text}\n");
-
-// Inspect memory search results if available in raw response items
-// Note: Memory search tool call results appear as AgentResponseItem types
-foreach (var message in response2.Messages)
+try
 {
-    if (message.RawRepresentation is AgentResponseItem agentResponseItem &&
-        agentResponseItem is MemorySearchToolCallResponseItem memorySearchResult)
-    {
-        Console.WriteLine($"Memory Search Status: {memorySearchResult.Status}");
-        Console.WriteLine($"Memory Search Results Count: {memorySearchResult.Results.Count}");
+    Console.WriteLine("Agent created with Memory Search tool. Starting conversation...\n");
 
-        foreach (var result in memorySearchResult.Results)
+    // The agent uses the memory search tool to recall stored information.
+    Console.WriteLine("User: What's my name and what programming language do I prefer?");
+    AgentResponse response = await agent.RunAsync("What's my name and what programming language do I prefer?");
+    Console.WriteLine($"Agent: {response.Messages.LastOrDefault()?.Text}\n");
+
+    // Inspect memory search results if available in raw response items.
+    foreach (var message in response.Messages)
+    {
+        if (message.RawRepresentation is MemorySearchToolCallResponseItem memorySearchResult)
         {
-            var memoryItem = result.MemoryItem;
-            Console.WriteLine($"  - Memory ID: {memoryItem.MemoryId}");
-            Console.WriteLine($"    Scope: {memoryItem.Scope}");
-            Console.WriteLine($"    Content: {memoryItem.Content}");
-            Console.WriteLine($"    Updated: {memoryItem.UpdatedAt}");
+            Console.WriteLine($"Memory Search Status: {memorySearchResult.Status}");
+            Console.WriteLine($"Memory Search Results Count: {memorySearchResult.Results.Count}");
+
+            foreach (var result in memorySearchResult.Results)
+            {
+                var memoryItem = result.MemoryItem;
+                Console.WriteLine($"  - Memory ID: {memoryItem.MemoryId}");
+                Console.WriteLine($"    Scope: {memoryItem.Scope}");
+                Console.WriteLine($"    Content: {memoryItem.Content}");
+                Console.WriteLine($"    Updated: {memoryItem.UpdatedAt}");
+            }
         }
     }
 }
+finally
+{
+    // Cleanup: Delete the agent and memory store.
+    Console.WriteLine("\nCleaning up...");
+    await aiProjectClient.Agents.DeleteAgentAsync(agent.Name);
+    Console.WriteLine("Agent deleted.");
+    await aiProjectClient.MemoryStores.DeleteMemoryStoreAsync(memoryStoreName);
+    Console.WriteLine("Memory store deleted.");
+}
 
-// Cleanup: Delete the agent (memory store persists and should be cleaned up separately if needed)
-Console.WriteLine("\nCleaning up agent...");
-await aiProjectClient.Agents.DeleteAgentAsync(agent.Name);
-Console.WriteLine("Agent deleted successfully.");
-
-// NOTE: Memory stores are long-lived resources and are NOT deleted with the agent.
-// To delete a memory store, use the Azure Portal or Python SDK:
-// await project_client.memory_stores.delete(memory_store.name)
-
-// --- Agent Creation Options ---
 #pragma warning disable CS8321 // Local function is declared but never used
 
 // Option 1 - Using MemorySearchTool wrapped as MEAI AITool
@@ -122,3 +105,36 @@ async Task<AIAgent> CreateAgentWithNativeSDK()
             })
     );
 }
+
+// Helpers — kept at the bottom so the main agent flow above stays clean.
+async Task EnsureMemoryStoreAsync()
+{
+    Console.WriteLine($"Creating memory store '{memoryStoreName}'...");
+    try
+    {
+        await aiProjectClient.MemoryStores.GetMemoryStoreAsync(memoryStoreName);
+        Console.WriteLine("Memory store already exists.");
+    }
+    catch (System.ClientModel.ClientResultException ex) when (ex.Status == 404)
+    {
+        MemoryStoreDefaultDefinition definition = new(deploymentName, embeddingModelName);
+        await aiProjectClient.MemoryStores.CreateMemoryStoreAsync(memoryStoreName, definition, "Sample memory store for Memory Search demo");
+        Console.WriteLine("Memory store created.");
+    }
+
+    Console.WriteLine("Storing memories from a prior conversation...");
+    MemoryUpdateOptions memoryOptions = new(userScope) { UpdateDelay = 0 };
+    memoryOptions.Items.Add(ResponseItem.CreateUserMessageItem("My name is Alice and I love programming in C#."));
+
+    MemoryUpdateResult updateResult = await aiProjectClient.MemoryStores.WaitForMemoriesUpdateAsync(
+        memoryStoreName: memoryStoreName,
+        options: memoryOptions,
+        pollingInterval: 500);
+
+    if (updateResult.Status == MemoryStoreUpdateStatus.Failed)
+    {
+        throw new InvalidOperationException($"Memory update failed: {updateResult.ErrorDetails}");
+    }
+
+    Console.WriteLine($"Memory update completed (status: {updateResult.Status}).\n");
+}

dotnet/samples/04-hosting/DurableAgents/AzureFunctions/06_LongRunningTools/Tools.cs

@@ -17,7 +17,7 @@ internal sealed class Tools(ILogger<Tools> logger)
     [Description("Starts a content generation workflow and returns the instance ID for tracking.")]
     public string StartContentGenerationWorkflow([Description("The topic for content generation")] string topic)
     {
-        this._logger.LogInformation("Starting content generation workflow for topic: {Topic}", topic);
+        this._logger.LogInformation("Starting content generation workflow for topic: {Topic}", SanitizeLogValue(topic));
 
         const int MaxReviewAttempts = 3;
         const float ApprovalTimeoutHours = 72;
@@ -34,7 +34,7 @@ internal sealed class Tools(ILogger<Tools> logger)
 
         this._logger.LogInformation(
             "Content generation workflow scheduled to be started for topic '{Topic}' with instance ID: {InstanceId}",
-            topic,
+            SanitizeLogValue(topic),
             instanceId);
 
         return $"Workflow started with instance ID: {instanceId}";
@@ -45,7 +45,7 @@ internal sealed class Tools(ILogger<Tools> logger)
         [Description("The instance ID of the workflow to check")] string instanceId,
         [Description("Whether to include detailed information")] bool includeDetails = true)
     {
-        this._logger.LogInformation("Getting status for workflow instance: {InstanceId}", instanceId);
+        this._logger.LogInformation("Getting status for workflow instance: {InstanceId}", SanitizeLogValue(instanceId));
 
         // Get the current agent context using the session-static property
         OrchestrationMetadata? status = await DurableAgentContext.Current.GetOrchestrationStatusAsync(
@@ -54,7 +54,7 @@ internal sealed class Tools(ILogger<Tools> logger)
 
         if (status is null)
         {
-            this._logger.LogInformation("Workflow instance '{InstanceId}' not found.", instanceId);
+            this._logger.LogInformation("Workflow instance '{InstanceId}' not found.", SanitizeLogValue(instanceId));
             return new
             {
                 instanceId,
@@ -78,7 +78,16 @@ internal sealed class Tools(ILogger<Tools> logger)
         [Description("The instance ID of the workflow to submit feedback for")] string instanceId,
         [Description("Feedback to submit")] HumanApprovalResponse feedback)
     {
-        this._logger.LogInformation("Submitting human approval for workflow instance: {InstanceId}", instanceId);
+        this._logger.LogInformation("Submitting human approval for workflow instance: {InstanceId}", SanitizeLogValue(instanceId));
         await DurableAgentContext.Current.RaiseOrchestrationEventAsync(instanceId, "HumanApproval", feedback);
     }
+
+    /// <summary>
+    /// Sanitizes a user-provided value for safe inclusion in log entries
+    /// by removing control characters that could be used for log forging.
+    /// </summary>
+    private static string SanitizeLogValue(string value) =>
+        value
+            .Replace("\r", string.Empty, StringComparison.Ordinal)
+            .Replace("\n", string.Empty, StringComparison.Ordinal);
 }

dotnet/samples/04-hosting/DurableAgents/AzureFunctions/08_ReliableStreaming/FunctionTriggers.cs

@@ -157,8 +157,8 @@ public sealed class FunctionTriggers
 
         this._logger.LogInformation(
             "Resuming stream for conversation {ConversationId} from cursor: {Cursor}",
-            conversationId,
-            cursor ?? "(beginning)");
+            SanitizeLogValue(conversationId),
+            SanitizeLogValue(cursor) ?? "(beginning)");
 
         // Check Accept header to determine response format
         // text/plain = raw text output (ideal for terminals)
@@ -205,7 +205,7 @@ public sealed class FunctionTriggers
             {
                 if (chunk.Error != null)
                 {
-                    this._logger.LogWarning("Stream error for conversation {ConversationId}: {Error}", conversationId, chunk.Error);
+                    this._logger.LogWarning("Stream error for conversation {ConversationId}: {Error}", SanitizeLogValue(conversationId), chunk.Error);
                     await WriteErrorAsync(httpContext.Response, chunk.Error, useSseFormat, cancellationToken);
                     break;
                 }
@@ -224,7 +224,7 @@ public sealed class FunctionTriggers
         }
         catch (OperationCanceledException)
         {
-            this._logger.LogInformation("Client disconnected from stream {ConversationId}", conversationId);
+            this._logger.LogInformation("Client disconnected from stream {ConversationId}", SanitizeLogValue(conversationId));
         }
 
         return new EmptyResult();
@@ -316,4 +316,20 @@ public sealed class FunctionTriggers
 
         await response.WriteAsync(sb.ToString());
     }
+
+    /// <summary>
+    /// Sanitizes a user-provided value for safe inclusion in log entries
+    /// by removing control characters that could be used for log forging.
+    /// </summary>
+    private static string? SanitizeLogValue(string? value)
+    {
+        if (value is null)
+        {
+            return null;
+        }
+
+        return value
+            .Replace("\r", string.Empty, StringComparison.Ordinal)
+            .Replace("\n", string.Empty, StringComparison.Ordinal);
+    }
 }

dotnet/samples/05-end-to-end/AGUIClientServer/AGUIDojoServer/ChatClientAgentFactory.cs

@@ -10,7 +10,7 @@ using Azure.AI.OpenAI;
 using Azure.Identity;
 using Microsoft.Agents.AI;
 using Microsoft.Extensions.AI;
-using ChatClient = OpenAI.Chat.ChatClient;
+using OpenAI.Chat;
 
 namespace AGUIDojoServer;
 
@@ -36,7 +36,7 @@ internal static class ChatClientAgentFactory
     {
         ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
 
-        return chatClient.AsIChatClient().AsAIAgent(
+        return chatClient.AsAIAgent(
             name: "AgenticChat",
             description: "A simple chat agent using Azure OpenAI");
     }
@@ -45,7 +45,7 @@ internal static class ChatClientAgentFactory
     {
         ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
 
-        return chatClient.AsIChatClient().AsAIAgent(
+        return chatClient.AsAIAgent(
             name: "BackendToolRenderer",
             description: "An agent that can render backend tools using Azure OpenAI",
             tools: [AIFunctionFactory.Create(
@@ -59,7 +59,7 @@ internal static class ChatClientAgentFactory
     {
         ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
 
-        return chatClient.AsIChatClient().AsAIAgent(
+        return chatClient.AsAIAgent(
             name: "HumanInTheLoopAgent",
             description: "An agent that involves human feedback in its decision-making process using Azure OpenAI");
     }
@@ -68,7 +68,7 @@ internal static class ChatClientAgentFactory
     {
         ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
 
-        return chatClient.AsIChatClient().AsAIAgent(
+        return chatClient.AsAIAgent(
             name: "ToolBasedGenerativeUIAgent",
             description: "An agent that uses tools to generate user interfaces using Azure OpenAI");
     }
@@ -76,7 +76,7 @@ internal static class ChatClientAgentFactory
     public static AIAgent CreateAgenticUI(JsonSerializerOptions options)
     {
         ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
-        var baseAgent = chatClient.AsIChatClient().AsAIAgent(new ChatClientAgentOptions
+        var baseAgent = chatClient.AsAIAgent(new ChatClientAgentOptions
         {
             Name = "AgenticUIAgent",
             Description = "An agent that generates agentic user interfaces using Azure OpenAI",
@@ -119,7 +119,7 @@ internal static class ChatClientAgentFactory
     {
         ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
 
-        var baseAgent = chatClient.AsIChatClient().AsAIAgent(
+        var baseAgent = chatClient.AsAIAgent(
             name: "SharedStateAgent",
             description: "An agent that demonstrates shared state patterns using Azure OpenAI");
 
@@ -130,7 +130,7 @@ internal static class ChatClientAgentFactory
     {
         ChatClient chatClient = s_azureOpenAIClient!.GetChatClient(s_deploymentName!);
 
-        var baseAgent = chatClient.AsIChatClient().AsAIAgent(new ChatClientAgentOptions
+        var baseAgent = chatClient.AsAIAgent(new ChatClientAgentOptions
         {
             Name = "PredictiveStateUpdatesAgent",
             Description = "An agent that demonstrates predictive state updates using Azure OpenAI",

dotnet/samples/05-end-to-end/AGUIWebChat/README.md

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

dotnet/samples/05-end-to-end/AGUIWebChat/Server/Program.cs

@@ -6,7 +6,6 @@ using Azure.AI.OpenAI;
 using Azure.Identity;
 using Microsoft.Agents.AI;
 using Microsoft.Agents.AI.Hosting.AGUI.AspNetCore;
-using Microsoft.Extensions.AI;
 using OpenAI.Chat;
 
 WebApplicationBuilder builder = WebApplication.CreateBuilder(args);
@@ -28,7 +27,7 @@ AzureOpenAIClient azureOpenAIClient = new(
 
 ChatClient chatClient = azureOpenAIClient.GetChatClient(deploymentName);
 
-ChatClientAgent agent = chatClient.AsIChatClient().AsAIAgent(
+ChatClientAgent agent = chatClient.AsAIAgent(
     name: "ChatAssistant",
     instructions: "You are a helpful assistant.");
 

dotnet/samples/05-end-to-end/AspNetAgentAuthorization/Service/Program.cs

@@ -12,6 +12,7 @@ using Microsoft.AspNetCore.Authentication.JwtBearer;
 using Microsoft.AspNetCore.Authorization;
 using Microsoft.Extensions.AI;
 using OpenAI;
+using OpenAI.Chat;
 
 WebApplicationBuilder builder = WebApplication.CreateBuilder(args);
 
@@ -75,16 +76,20 @@ string apiKey = builder.Configuration["OPENAI_API_KEY"]
     ?? throw new InvalidOperationException("Set the OPENAI_API_KEY environment variable.");
 string model = builder.Configuration["OPENAI_MODEL"] ?? "gpt-4.1-mini";
 
+// Here we are using Singleton lifetime, since none of the services, function tools and user context classes in the sample have state that are per request.
+// You should evaluate the appropriate lifetime for your own services and tools based on their behavior and dependencies.
+// E.g. if any of the service instances or tools maintain state that is specific to a user, and each request may be from a different user,
+// you should use Scoped lifetime instead, so that a new instance is created for each request.
+// Note that if you use Scoped lifetime for any dependencies, you must also use Scoped lifetime for any class that uses it, including the agent itself.
 builder.Services.AddHttpContextAccessor();
-builder.Services.AddScoped<IUserContext, KeycloakUserContext>();
-builder.Services.AddScoped<ExpenseService>();
-builder.Services.AddScoped<AIAgent>(sp =>
+builder.Services.AddSingleton<IUserContext, KeycloakUserContext>();
+builder.Services.AddSingleton<ExpenseService>();
+builder.Services.AddSingleton<AIAgent>(sp =>
 {
     var expenseService = sp.GetRequiredService<ExpenseService>();
 
     return new OpenAIClient(apiKey)
         .GetChatClient(model)
-        .AsIChatClient()
         .AsAIAgent(
             name: "ExpenseApprovalAgent",
             instructions: "You are an expense approval assistant. You can list pending expenses "

dotnet/samples/05-end-to-end/AspNetAgentAuthorization/Service/Service.csproj

@@ -10,7 +10,6 @@
 
   <ItemGroup>
     <PackageReference Include="Microsoft.AspNetCore.Authentication.JwtBearer" />
-    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
   </ItemGroup>
 
   <ItemGroup>

dotnet/samples/05-end-to-end/AspNetAgentAuthorization/Service/UserContext.cs

@@ -27,43 +27,73 @@ public interface IUserContext
 /// Keycloak uses <c>sub</c> for the user ID, <c>preferred_username</c>
 /// for the login name, <c>given_name</c>/<c>family_name</c> for the
 /// display name, and <c>scope</c> (space-delimited) for granted scopes.
-/// Registered as a scoped service so it is resolved once per request.
+/// Registered as a singleton — claims are parsed once per request and
+/// cached in <see cref="HttpContext.Items"/>.
 /// </summary>
 public sealed class KeycloakUserContext : IUserContext
 {
-    public string UserId { get; }
+    private static readonly object s_cacheKey = new();
 
-    public string UserName { get; }
-
-    public string DisplayName { get; }
-
-    public IReadOnlySet<string> Scopes { get; }
+    private readonly IHttpContextAccessor _httpContextAccessor;
 
     public KeycloakUserContext(IHttpContextAccessor httpContextAccessor)
     {
-        ClaimsPrincipal? user = httpContextAccessor.HttpContext?.User;
+        this._httpContextAccessor = httpContextAccessor;
+    }
 
-        this.UserId = user?.FindFirstValue(ClaimTypes.NameIdentifier)
-                   ?? user?.FindFirstValue("sub")
-                   ?? "anonymous";
+    public string UserId => this.GetOrCreateCachedInfo().UserId;
 
-        this.UserName = user?.FindFirstValue("preferred_username")
-                     ?? user?.FindFirstValue(ClaimTypes.Name)
-                     ?? "unknown";
+    public string UserName => this.GetOrCreateCachedInfo().UserName;
+
+    public string DisplayName => this.GetOrCreateCachedInfo().DisplayName;
+
+    public IReadOnlySet<string> Scopes => this.GetOrCreateCachedInfo().Scopes;
+
+    private CachedUserInfo GetOrCreateCachedInfo()
+    {
+        HttpContext? httpContext = this._httpContextAccessor.HttpContext;
+        if (httpContext is not null && httpContext.Items.TryGetValue(s_cacheKey, out object? cached) && cached is CachedUserInfo info)
+        {
+            return info;
+        }
+
+        info = ParseClaims(httpContext?.User);
+
+        if (httpContext is not null)
+        {
+            httpContext.Items[s_cacheKey] = info;
+        }
+
+        return info;
+    }
+
+    private static CachedUserInfo ParseClaims(ClaimsPrincipal? user)
+    {
+        string userId = user?.FindFirstValue(ClaimTypes.NameIdentifier)
+                     ?? user?.FindFirstValue("sub")
+                     ?? "anonymous";
+
+        string userName = user?.FindFirstValue("preferred_username")
+                       ?? user?.FindFirstValue(ClaimTypes.Name)
+                       ?? "unknown";
 
         string? givenName = user?.FindFirstValue("given_name") ?? user?.FindFirstValue(ClaimTypes.GivenName);
         string? familyName = user?.FindFirstValue("family_name") ?? user?.FindFirstValue(ClaimTypes.Surname);
-        this.DisplayName = (givenName, familyName) switch
+        string displayName = (givenName, familyName) switch
         {
             (not null, not null) => $"{givenName} {familyName}",
             (not null, null) => givenName,
             (null, not null) => familyName,
-            _ => this.UserName,
+            _ => userName,
         };
 
         string? scopeClaim = user?.FindFirstValue("scope");
-        this.Scopes = scopeClaim is not null
+        IReadOnlySet<string> scopes = scopeClaim is not null
             ? new HashSet<string>(scopeClaim.Split(' ', StringSplitOptions.RemoveEmptyEntries), StringComparer.OrdinalIgnoreCase)
             : new HashSet<string>(StringComparer.OrdinalIgnoreCase);
+
+        return new CachedUserInfo(userId, userName, displayName, scopes);
     }
+
+    private sealed record CachedUserInfo(string UserId, string UserName, string DisplayName, IReadOnlySet<string> Scopes);
 }

dotnet/samples/05-end-to-end/HostedAgents/AgentThreadAndHITL/AgentThreadAndHITL.csproj

@@ -1,4 +1,4 @@
-<Project Sdk="Microsoft.NET.Sdk">
+<Project Sdk="Microsoft.NET.Sdk">
 
   <PropertyGroup>
     <OutputType>Exe</OutputType>
@@ -36,11 +36,10 @@
   </ItemGroup>
 
   <ItemGroup>
-    <PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.8" />
+    <PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.9" />
     <PackageReference Include="Azure.AI.OpenAI" Version="2.8.0-beta.1" />
     <PackageReference Include="Azure.Identity" Version="1.17.1" />
-    <PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-preview.251219.1" />
-    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" Version="10.1.1-preview.1.25612.2" />
+    <PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc1" />
   </ItemGroup>
 
   <!-- Add analyzers with compatible versions -->

dotnet/samples/05-end-to-end/HostedAgents/AgentThreadAndHITL/Program.cs

@@ -11,9 +11,10 @@ using Azure.AI.OpenAI;
 using Azure.Identity;
 using Microsoft.Agents.AI;
 using Microsoft.Extensions.AI;
+using OpenAI.Chat;
 
-var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
 
 [Description("Get the weather for a given location.")]
 static string GetWeather([Description("The location to get the weather for.")] string location)
@@ -22,17 +23,19 @@ static string GetWeather([Description("The location to get the weather for.")] s
 // Create the chat client and agent.
 // Note: ApprovalRequiredAIFunction wraps the tool to require user approval before invocation.
 // User should reply with 'approve' or 'reject' when prompted.
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 #pragma warning disable MEAI001 // Type is for evaluation purposes only
 AIAgent agent = new AzureOpenAIClient(
     new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
     .GetChatClient(deploymentName)
-    .AsIChatClient()
-    .CreateAIAgent(
+    .AsAIAgent(
         instructions: "You are a helpful assistant",
         tools: [new ApprovalRequiredAIFunction(AIFunctionFactory.Create(GetWeather))]
     );
 #pragma warning restore MEAI001
 
-var threadRepository = new InMemoryAgentThreadRepository(agent);
+InMemoryAgentThreadRepository threadRepository = new(agent);
 await agent.RunAIAgentAsync(telemetrySourceName: "Agents", threadRepository: threadRepository);

dotnet/samples/05-end-to-end/HostedAgents/AgentWithHostedMCP/AgentWithHostedMCP.csproj

@@ -35,10 +35,10 @@
   </ItemGroup>
 
   <ItemGroup>
-    <PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.6" />
+    <PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.9" />
     <PackageReference Include="Azure.AI.OpenAI" Version="2.8.0-beta.1" />
     <PackageReference Include="Azure.Identity" Version="1.17.1" />
-    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" Version="10.3.0" />
+    <PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc1" />
   </ItemGroup>
 
   <!-- Add analyzers with compatible versions -->

dotnet/samples/05-end-to-end/HostedAgents/AgentWithHostedMCP/Program.cs

@@ -4,14 +4,18 @@
 // 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 demonstrates how to use MCP tools with auto approval by setting ApprovalMode to NeverRequire.
 
+#pragma warning disable MEAI001 // HostedMcpServerTool, HostedMcpServerToolApprovalMode are experimental
+#pragma warning disable OPENAI001 // GetResponsesClient is experimental
+
 using Azure.AI.AgentServer.AgentFramework.Extensions;
 using Azure.AI.OpenAI;
 using Azure.Identity;
 using Microsoft.Agents.AI;
 using Microsoft.Extensions.AI;
+using OpenAI.Responses;
 
-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";
+string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
 
 // Create an MCP tool that can be called without approval.
 AITool mcpTool = new HostedMcpServerTool(serverName: "microsoft_learn", serverAddress: "https://learn.microsoft.com/api/mcp")
@@ -28,8 +32,7 @@ AIAgent agent = new AzureOpenAIClient(
     new Uri(endpoint),
     new DefaultAzureCredential())
     .GetResponsesClient(deploymentName)
-    .AsIChatClient()
-    .CreateAIAgent(
+    .AsAIAgent(
         instructions: "You answer questions by searching the Microsoft Learn content only.",
         name: "MicrosoftLearnAgent",
         tools: [mcpTool]);

dotnet/samples/05-end-to-end/HostedAgents/AgentWithHostedMCP/README.md

@@ -18,7 +18,7 @@ Before running this sample, ensure you have:
 2. A deployment of a chat model (e.g., gpt-4o-mini)
 3. Azure CLI installed and authenticated
 
-**Note**: This sample uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource.
+**Note**: This sample uses `DefaultAzureCredential` for authentication, which probes multiple sources automatically. For local development, make sure you're logged in with `az login` and have access to the Azure OpenAI resource.
 
 ## Environment Variables
 

dotnet/samples/05-end-to-end/HostedAgents/AgentWithLocalTools/AgentWithLocalTools.csproj

@@ -36,11 +36,11 @@
   </ItemGroup>
 
   <ItemGroup>
-    <PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.8" />
+    <PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.9" />
     <PackageReference Include="Azure.AI.Projects" Version="1.2.0-beta.5" />
     <PackageReference Include="Azure.AI.OpenAI" Version="2.8.0-beta.1" />
     <PackageReference Include="Azure.Identity" Version="1.17.1" />
-    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" Version="10.3.0" />
+    <PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc1" />
   </ItemGroup>
 
   <!-- Add analyzers with compatible versions -->

dotnet/samples/05-end-to-end/HostedAgents/AgentWithLocalTools/Program.cs

@@ -15,21 +15,21 @@ using Azure.Identity;
 using Microsoft.Agents.AI;
 using Microsoft.Extensions.AI;
 
-var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT")
+string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT")
     ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string deploymentName = Environment.GetEnvironmentVariable("MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
 Console.WriteLine($"Project Endpoint: {endpoint}");
 Console.WriteLine($"Model Deployment: {deploymentName}");
 
-var seattleHotels = new[]
-{
+Hotel[] seattleHotels =
+[
     new Hotel("Contoso Suites", 189, 4.5, "Downtown"),
     new Hotel("Fabrikam Residences", 159, 4.2, "Pike Place Market"),
     new Hotel("Alpine Ski House", 249, 4.7, "Seattle Center"),
     new Hotel("Margie's Travel Lodge", 219, 4.4, "Waterfront"),
     new Hotel("Northwind Inn", 139, 4.0, "Capitol Hill"),
     new Hotel("Relecloud Hotel", 99, 3.8, "University District"),
-};
+];
 
 [Description("Get available hotels in Seattle for the specified dates. This simulates a call to a hotel availability API.")]
 string GetAvailableHotels(
@@ -54,21 +54,21 @@ string GetAvailableHotels(
             return "Error: Check-out date must be after check-in date.";
         }
 
-        var nights = (checkOut - checkIn).Days;
-        var availableHotels = seattleHotels.Where(h => h.PricePerNight <= maxPrice).ToList();
+        int nights = (checkOut - checkIn).Days;
+        List<Hotel> availableHotels = seattleHotels.Where(h => h.PricePerNight <= maxPrice).ToList();
 
         if (availableHotels.Count == 0)
         {
             return $"No hotels found in Seattle within your budget of ${maxPrice}/night.";
         }
 
-        var result = new StringBuilder();
+        StringBuilder result = new();
         result.AppendLine($"Available hotels in Seattle from {checkInDate} to {checkOutDate} ({nights} nights):");
         result.AppendLine();
 
-        foreach (var hotel in availableHotels)
+        foreach (Hotel hotel in availableHotels)
         {
-            var totalCost = hotel.PricePerNight * nights;
+            int totalCost = hotel.PricePerNight * nights;
             result.AppendLine($"**{hotel.Name}**");
             result.AppendLine($"   Location: {hotel.Location}");
             result.AppendLine($"   Rating: {hotel.Rating}/5");
@@ -84,7 +84,10 @@ string GetAvailableHotels(
     }
 }
 
-var credential = new AzureCliCredential();
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+DefaultAzureCredential credential = new();
 AIProjectClient projectClient = new(new Uri(endpoint), credential);
 
 ClientConnection connection = projectClient.GetConnection(typeof(AzureOpenAIClient).FullName!);
@@ -96,14 +99,14 @@ if (!connection.TryGetLocatorAsUri(out Uri? openAiEndpoint) || openAiEndpoint is
 openAiEndpoint = new Uri($"https://{openAiEndpoint.Host}");
 Console.WriteLine($"OpenAI Endpoint: {openAiEndpoint}");
 
-var chatClient = new AzureOpenAIClient(openAiEndpoint, credential)
+IChatClient chatClient = new AzureOpenAIClient(openAiEndpoint, credential)
     .GetChatClient(deploymentName)
     .AsIChatClient()
     .AsBuilder()
     .UseOpenTelemetry(sourceName: "Agents", configure: cfg => cfg.EnableSensitiveData = false)
     .Build();
 
-var agent = new ChatClientAgent(chatClient,
+AIAgent agent = chatClient.AsAIAgent(
     name: "SeattleHotelAgent",
     instructions: """
         You are a helpful travel assistant specializing in finding hotels in Seattle, Washington.

dotnet/samples/05-end-to-end/HostedAgents/AgentWithTextSearchRag/AgentWithTextSearchRag.csproj

@@ -35,11 +35,10 @@
   </ItemGroup>
 
   <ItemGroup>
-    <PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.5" />
+    <PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.9" />
     <PackageReference Include="Azure.AI.OpenAI" Version="2.7.0-beta.2" />
     <PackageReference Include="Azure.Identity" Version="1.17.1" />
-    <PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-preview.251219.1" />
-    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" Version="10.1.1-preview.1.25612.2" />
+    <PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc1" />
   </ItemGroup>
 
   <!-- Add analyzers with compatible versions -->

dotnet/samples/05-end-to-end/HostedAgents/AgentWithTextSearchRag/Program.cs

@@ -11,8 +11,8 @@ using Microsoft.Agents.AI;
 using Microsoft.Extensions.AI;
 using OpenAI.Chat;
 
-var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
 
 TextSearchProviderOptions textSearchOptions = new()
 {
@@ -28,13 +28,13 @@ AIAgent agent = new AzureOpenAIClient(
     new Uri(endpoint),
     new DefaultAzureCredential())
     .GetChatClient(deploymentName)
-    .CreateAIAgent(new ChatClientAgentOptions
+    .AsAIAgent(new ChatClientAgentOptions
     {
         ChatOptions = new ChatOptions
         {
             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)
+        AIContextProviders = [new TextSearchProvider(MockSearchAsync, textSearchOptions)]
     });
 
 await agent.RunAIAgentAsync();

dotnet/samples/05-end-to-end/HostedAgents/AgentWithTools/AgentWithTools.csproj

@@ -35,11 +35,10 @@
   </ItemGroup>
 
   <ItemGroup>
-    <PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.8" />
+    <PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.9" />
     <PackageReference Include="Azure.AI.OpenAI" Version="2.8.0-beta.1" />
     <PackageReference Include="Azure.Identity" Version="1.17.1" />
-    <PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-preview.251219.1" />
-    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" Version="10.3.0" />
+    <PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc1" />
   </ItemGroup>
 
   <!-- Add analyzers with compatible versions -->

dotnet/samples/05-end-to-end/HostedAgents/AgentWithTools/Program.cs

@@ -9,13 +9,16 @@ using Azure.Identity;
 using Microsoft.Agents.AI;
 using Microsoft.Extensions.AI;
 
-var openAiEndpoint = 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 toolConnectionId = Environment.GetEnvironmentVariable("MCP_TOOL_CONNECTION_ID") ?? throw new InvalidOperationException("MCP_TOOL_CONNECTION_ID is not set.");
+string openAiEndpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string toolConnectionId = Environment.GetEnvironmentVariable("MCP_TOOL_CONNECTION_ID") ?? throw new InvalidOperationException("MCP_TOOL_CONNECTION_ID is not set.");
 
-var credential = new AzureCliCredential();
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+DefaultAzureCredential credential = new();
 
-var chatClient = new AzureOpenAIClient(new Uri(openAiEndpoint), credential)
+IChatClient chatClient = new AzureOpenAIClient(new Uri(openAiEndpoint), credential)
     .GetChatClient(deploymentName)
     .AsIChatClient()
     .AsBuilder()
@@ -23,7 +26,7 @@ var chatClient = new AzureOpenAIClient(new Uri(openAiEndpoint), credential)
     .UseOpenTelemetry(sourceName: "Agents", configure: (cfg) => cfg.EnableSensitiveData = true)
     .Build();
 
-var agent = new ChatClientAgent(chatClient,
+AIAgent agent = chatClient.AsAIAgent(
       name: "AgentWithTools",
       instructions: @"You are a helpful assistant with access to tools for fetching Microsoft documentation.
 

dotnet/samples/05-end-to-end/HostedAgents/AgentWithTools/README.md

@@ -6,7 +6,7 @@ Key features:
 
 - Configuring Foundry tools using `UseFoundryTools` with MCP and code interpreter
 - Connecting to an external MCP tool via a Foundry project connection
-- Using `AzureCliCredential` for Azure authentication
+- Using `DefaultAzureCredential` for Azure authentication
 - OpenTelemetry instrumentation for both the chat client and agent
 
 > For common prerequisites and setup instructions, see the [Hosted Agent Samples README](../README.md).
@@ -36,7 +36,7 @@ $env:MCP_TOOL_CONNECTION_ID="SampleMCPTool"
 
 ## How It Works
 
-1. An `AzureOpenAIClient` is created with `AzureCliCredential` and used to get a chat client
+1. An `AzureOpenAIClient` is created with `DefaultAzureCredential` and used to get a chat client
 2. The chat client is wrapped with `UseFoundryTools` which registers two Foundry tool types:
    - **MCP connection**: Connects to an external MCP server (Microsoft Learn) via the project connection name, providing documentation fetch and search capabilities
    - **Code interpreter**: Allows the agent to execute code snippets when needed

dotnet/samples/05-end-to-end/HostedAgents/AgentsInWorkflows/AgentsInWorkflows.csproj

@@ -1,4 +1,4 @@
-<Project Sdk="Microsoft.NET.Sdk">
+<Project Sdk="Microsoft.NET.Sdk">
 
   <PropertyGroup>
     <OutputType>Exe</OutputType>
@@ -35,11 +35,10 @@
   </ItemGroup>
 
   <ItemGroup>
-    <PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.5" />
+    <PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.9" />
     <PackageReference Include="Azure.AI.OpenAI" Version="2.7.0-beta.2" />
     <PackageReference Include="Azure.Identity" Version="1.17.1" />
-    <PackageReference Include="Microsoft.Agents.AI.Workflows" Version="1.0.0-preview.251219.1" />
-    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" Version="10.1.0-preview.1.25608.1" />
+    <PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-rc1" />
   </ItemGroup>
 
   <!-- Add analyzers with compatible versions -->

dotnet/samples/05-end-to-end/HostedAgents/AgentsInWorkflows/Program.cs

@@ -12,8 +12,8 @@ using Microsoft.Agents.AI.Workflows;
 using Microsoft.Extensions.AI;
 
 // Set up the Azure OpenAI client
-var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
@@ -32,9 +32,9 @@ AIAgent agent = new WorkflowBuilder(frenchAgent)
     .AddEdge(frenchAgent, spanishAgent)
     .AddEdge(spanishAgent, englishAgent)
     .Build()
-    .AsAgent();
+    .AsAIAgent();
 
 await agent.RunAIAgentAsync();
 
-static ChatClientAgent GetTranslationAgent(string targetLanguage, IChatClient chatClient) =>
-    new(chatClient, $"You are a translation assistant that translates the provided text to {targetLanguage}.");
+static AIAgent GetTranslationAgent(string targetLanguage, IChatClient chatClient) =>
+    chatClient.AsAIAgent($"You are a translation assistant that translates the provided text to {targetLanguage}.");

dotnet/samples/05-end-to-end/HostedAgents/AgentsInWorkflows/README.md

@@ -19,7 +19,7 @@ Before you begin, ensure you have the following prerequisites:
 - 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).
+**Note**: This demo uses `DefaultAzureCredential` for authentication, which probes multiple sources automatically. For local development, make sure you're logged in with `az login` and have access to the Azure OpenAI resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
 
 Set the following environment variables:
 

dotnet/samples/05-end-to-end/HostedAgents/FoundryMultiAgent/Dockerfile

@@ -0,0 +1,20 @@
+# Build the application
+FROM mcr.microsoft.com/dotnet/sdk:10.0-alpine AS build
+WORKDIR /src
+
+# Copy files from the current directory on the host to the working directory in the container
+COPY . .
+
+RUN dotnet restore
+RUN dotnet build -c Release --no-restore
+RUN dotnet publish -c Release --no-build -o /app -f net10.0
+
+# Run the application
+FROM mcr.microsoft.com/dotnet/aspnet:10.0-alpine AS final
+WORKDIR /app
+
+# Copy everything needed to run the app from the "build" stage.
+COPY --from=build /app .
+
+EXPOSE 8088
+ENTRYPOINT ["dotnet", "FoundryMultiAgent.dll"]

dotnet/samples/05-end-to-end/HostedAgents/FoundryMultiAgent/FoundryMultiAgent.csproj

@@ -0,0 +1,76 @@
+<Project Sdk="Microsoft.NET.Sdk">
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+
+    <!-- 
+      Disable central package management for this project.
+      This project requires explicit package references with versions specified inline rather than 
+      inheriting them from Directory.Packages.props. This is necessary because a Docker image will 
+      be created from this project, and the Docker build process only has access to this folder 
+      and cannot access parent folders where Directory.Packages.props resides.
+    -->
+    <ManagePackageVersionsCentrally>false</ManagePackageVersionsCentrally>
+  </PropertyGroup>
+
+  <!-- 
+    Remove analyzer PackageReference items inherited from Directory.Packages.props.
+    Note: ManagePackageVersionsCentrally only controls PackageVersion items, not PackageReference items.
+    Directory.Packages.props contains both PackageVersion and PackageReference entries for analyzers,
+    and the PackageReference items are always inherited through MSBuild imports regardless of the 
+    ManagePackageVersionsCentrally setting. We must explicitly remove them before adding our own versions.
+  -->
+  <ItemGroup>
+    <PackageReference Remove="Microsoft.CodeAnalysis.NetAnalyzers" />
+    <PackageReference Remove="Microsoft.VisualStudio.Threading.Analyzers" />
+    <PackageReference Remove="xunit.analyzers" />
+    <PackageReference Remove="Moq.Analyzers" />
+    <PackageReference Remove="Roslynator.Analyzers" />
+    <PackageReference Remove="Roslynator.CodeAnalysis.Analyzers" />
+    <PackageReference Remove="Roslynator.Formatting.Analyzers" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.8" />
+    <PackageReference Include="Azure.AI.Projects" Version="1.2.0-beta.5" />
+    <PackageReference Include="Azure.Identity" Version="1.17.1" />
+    <PackageReference Include="Microsoft.Agents.AI" Version="1.0.0-preview.251219.1" />
+    <PackageReference Include="Microsoft.Agents.AI.AzureAI" Version="1.0.0-preview.251219.1" />
+    <PackageReference Include="Microsoft.Agents.AI.Workflows" Version="1.0.0-preview.251219.1" />
+    <PackageReference Include="OpenTelemetry" Version="1.12.0" />
+    <PackageReference Include="OpenTelemetry.Exporter.OpenTelemetryProtocol" Version="1.12.0" />
+  </ItemGroup>
+
+  <!-- Add analyzers with compatible versions -->
+  <ItemGroup>
+    <PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="10.0.100">
+      <PrivateAssets>all</PrivateAssets>
+      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
+    </PackageReference>
+    <PackageReference Include="Microsoft.VisualStudio.Threading.Analyzers" Version="17.14.15">
+      <PrivateAssets>all</PrivateAssets>
+      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
+    </PackageReference>
+    <PackageReference Include="Roslynator.Analyzers" Version="4.14.1">
+      <PrivateAssets>all</PrivateAssets>
+      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
+    </PackageReference>
+    <PackageReference Include="Roslynator.CodeAnalysis.Analyzers" Version="4.14.1">
+      <PrivateAssets>all</PrivateAssets>
+      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
+    </PackageReference>
+    <PackageReference Include="Roslynator.Formatting.Analyzers" Version="4.14.1">
+      <PrivateAssets>all</PrivateAssets>
+      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
+    </PackageReference>
+  </ItemGroup>
+
+  <ItemGroup>
+    <None Update="appsettings.Development.json">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+  </ItemGroup>
+
+</Project>

dotnet/samples/05-end-to-end/HostedAgents/FoundryMultiAgent/Program.cs

@@ -0,0 +1,51 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates a multi-agent workflow with Writer and Reviewer agents
+// using Azure AI Foundry AIProjectClient and the Agent Framework WorkflowBuilder.
+
+#pragma warning disable CA2252 // AIProjectClient and Agents API require opting into preview features
+
+using Azure.AI.AgentServer.AgentFramework.Extensions;
+using Azure.AI.Projects;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.Workflows;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT")
+    ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+Console.WriteLine($"Using Azure AI endpoint: {endpoint}");
+Console.WriteLine($"Using model deployment: {deploymentName}");
+
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
+
+// Create Foundry agents
+AIAgent writerAgent = await aiProjectClient.CreateAIAgentAsync(
+    name: "Writer",
+    model: deploymentName,
+    instructions: "You are an excellent content writer. You create new content and edit contents based on the feedback.");
+
+AIAgent reviewerAgent = await aiProjectClient.CreateAIAgentAsync(
+    name: "Reviewer",
+    model: deploymentName,
+    instructions: "You are an excellent content reviewer. Provide actionable feedback to the writer about the provided content. Provide the feedback in the most concise manner possible.");
+
+try
+{
+    var workflow = new WorkflowBuilder(writerAgent)
+        .AddEdge(writerAgent, reviewerAgent)
+        .Build();
+
+    Console.WriteLine("Starting Writer-Reviewer Workflow Agent Server on http://localhost:8088");
+    await workflow.AsAgent().RunAIAgentAsync();
+}
+finally
+{
+    // Cleanup server-side agents
+    await aiProjectClient.Agents.DeleteAgentAsync(writerAgent.Name);
+    await aiProjectClient.Agents.DeleteAgentAsync(reviewerAgent.Name);
+}

dotnet/samples/05-end-to-end/HostedAgents/FoundryMultiAgent/README.md

@@ -0,0 +1,168 @@
+**IMPORTANT!** All samples and other resources made available in this GitHub repository ("samples") are designed to assist in accelerating development of agents, solutions, and agent workflows for various scenarios. Review all provided resources and carefully test output behavior in the context of your use case. AI responses may be inaccurate and AI actions should be monitored with human oversight. Learn more in the transparency documents for [Agent Service](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/agents/transparency-note) and [Agent Framework](https://github.com/microsoft/agent-framework/blob/main/TRANSPARENCY_FAQ.md).
+
+Agents, solutions, or other output you create may be subject to legal and regulatory requirements, may require licenses, or may not be suitable for all industries, scenarios, or use cases. By using any sample, you are acknowledging that any output created using those samples are solely your responsibility, and that you will comply with all applicable laws, regulations, and relevant safety standards, terms of service, and codes of conduct.
+
+Third-party samples contained in this folder are subject to their own designated terms, and they have not been tested or verified by Microsoft or its affiliates.
+
+Microsoft has no responsibility to you or others with respect to any of these samples or any resulting output.
+
+# What this sample demonstrates
+
+This sample demonstrates a **key advantage of code-based hosted agents**:
+
+- **Multi-agent workflows** - Orchestrate multiple agents working together
+
+Code-based agents can execute **any C# code** you write. This sample includes a Writer-Reviewer workflow where two agents collaborate: a Writer creates content and a Reviewer provides feedback.
+
+The agent is hosted using the [Azure AI AgentServer SDK](https://www.nuget.org/packages/Azure.AI.AgentServer.AgentFramework/) and can be deployed to Microsoft Foundry.
+
+## How It Works
+
+### Multi-Agent Workflow
+
+In [Program.cs](Program.cs), the sample creates two agents using `AIProjectClient.CreateAIAgentAsync()` from the [Microsoft.Agents.AI.AzureAI](https://www.nuget.org/packages/Microsoft.Agents.AI.AzureAI/) package:
+
+- **Writer** - An agent that creates and edits content based on feedback
+- **Reviewer** - An agent that provides actionable feedback on the content
+
+The `WorkflowBuilder` from the [Microsoft.Agents.AI.Workflows](https://www.nuget.org/packages/Microsoft.Agents.AI.Workflows/) package connects these agents in a sequential flow:
+
+1. The Writer receives the initial request and generates content
+2. The Reviewer evaluates the content and provides feedback
+3. Both agent responses are output to the user
+
+### Agent Hosting
+
+The agent is hosted using the [Azure AI AgentServer SDK](https://www.nuget.org/packages/Azure.AI.AgentServer.AgentFramework/),
+which provisions a REST API endpoint compatible with the OpenAI Responses protocol.
+
+## Running the Agent Locally
+
+### Prerequisites
+
+Before running this sample, ensure you have:
+
+1. **Azure AI Foundry Project**
+   - Project created.
+   - Chat model deployed (e.g., `gpt-4o` or `gpt-4.1`)
+   - Note your project endpoint URL and model deployment name
+     > **Note**: You can right-click the project in the Microsoft Foundry VS Code extension and select `Copy Project Endpoint URL` to get the endpoint.
+
+2. **Azure CLI**
+   - Installed and authenticated
+   - Run `az login` and verify with `az account show`
+   - Your identity needs the **Azure AI Developer** role on the Foundry resource (for `agents/write` data action required by `CreateAIAgentAsync`)
+
+3. **.NET 10.0 SDK or later**
+   - Verify your version: `dotnet --version`
+   - Download from [https://dotnet.microsoft.com/download](https://dotnet.microsoft.com/download)
+
+### Environment Variables
+
+Set the following environment variables:
+
+**PowerShell:**
+
+```powershell
+# Replace with your actual values
+$env:AZURE_AI_PROJECT_ENDPOINT="https://<your-resource>.services.ai.azure.com/api/projects/<your-project>"
+$env:MODEL_DEPLOYMENT_NAME="gpt-4o-mini"
+```
+
+**Bash:**
+
+```bash
+export AZURE_AI_PROJECT_ENDPOINT="https://<your-resource>.services.ai.azure.com/api/projects/<your-project>"
+export MODEL_DEPLOYMENT_NAME="gpt-4o-mini"
+```
+
+### Running the Sample
+
+To run the agent, execute the following command in your terminal:
+
+```bash
+dotnet restore
+dotnet build
+dotnet run
+```
+
+This will start the hosted agent locally on `http://localhost:8088/`.
+
+### Interacting with the Agent
+
+**VS Code:**
+
+1. Open the Visual Studio Code Command Palette and execute the `Microsoft Foundry: Open Container Agent Playground Locally` command.
+2. Execute the following commands to start the containerized hosted agent.
+   ```bash
+   dotnet restore
+   dotnet build
+   dotnet run
+   ```
+3. Submit a request to the agent through the playground interface. For example, you may enter a prompt such as: "Create a slogan for a new electric SUV that is affordable and fun to drive."
+4. Review the agent's response in the playground interface.
+
+> **Note**: Open the local playground before starting the container agent to ensure the visualization functions correctly.
+
+**PowerShell (Windows):**
+
+```powershell
+$body = @{
+    input = "Create a slogan for a new electric SUV that is affordable and fun to drive"
+    stream = $false
+} | ConvertTo-Json
+
+Invoke-RestMethod -Uri http://localhost:8088/responses -Method Post -Body $body -ContentType "application/json"
+```
+
+**Bash/curl (Linux/macOS):**
+
+```bash
+curl -sS -H "Content-Type: application/json" -X POST http://localhost:8088/responses \
+   -d '{"input": "Create a slogan for a new electric SUV that is affordable and fun to drive","stream":false}'
+```
+
+You can also use the `run-requests.http` file in this directory with the VS Code REST Client extension.
+
+The Writer agent will generate content based on your prompt, and the Reviewer agent will provide feedback on the output.
+
+## Deploying the Agent to Microsoft Foundry
+
+**Preparation (required)**
+
+Please check the environment_variables section in [agent.yaml](agent.yaml) and ensure the variables there are set in your target Microsoft Foundry Project.
+
+To deploy the hosted agent:
+
+1. Open the VS Code Command Palette and run the `Microsoft Foundry: Deploy Hosted Agent` command.
+
+2. Follow the interactive deployment prompts. The extension will help you select or create the container files it needs.
+
+3. After deployment completes, the hosted agent appears under the `Hosted Agents (Preview)` section of the extension tree. You can select the agent there to view details and test it using the integrated playground.
+
+**What the deploy flow does for you:**
+
+- Creates or obtains an Azure Container Registry for the target project.
+- Builds and pushes a container image from your workspace (the build packages the workspace respecting `.dockerignore`).
+- Creates an agent version in Microsoft Foundry using the built image. If a `.env` file exists at the workspace root, the extension will parse it and include its key/value pairs as the hosted agent's environment variables in the create request (these variables will be available to the agent runtime).
+- Starts the agent container on the project's capability host. If the capability host is not provisioned, the extension will prompt you to enable it and will guide you through creating it.
+
+## MSI Configuration in the Azure Portal
+
+This sample requires the Microsoft Foundry Project to authenticate using a Managed Identity when running remotely in Azure. Grant the project's managed identity the required permissions by assigning the built-in [Azure AI User](https://aka.ms/foundry-ext-project-role) role.
+
+To configure the Managed Identity:
+
+1. In the Azure Portal, open the Foundry Project.
+2. Select "Access control (IAM)" from the left-hand menu.
+3. Click "Add" and choose "Add role assignment".
+4. In the role selection, search for and select "Azure AI User", then click "Next".
+5. For "Assign access to", choose "Managed identity".
+6. Click "Select members", locate the managed identity associated with your Foundry Project (you can search by the project name), then click "Select".
+7. Click "Review + assign" to complete the assignment.
+8. Allow a few minutes for the role assignment to propagate before running the application.
+
+## Additional Resources
+
+- [Microsoft Agents Framework](https://learn.microsoft.com/en-us/agent-framework/overview/agent-framework-overview)
+- [Managed Identities for Azure Resources](https://learn.microsoft.com/en-us/entra/identity/managed-identities-azure-resources/)

dotnet/samples/05-end-to-end/HostedAgents/FoundryMultiAgent/agent.yaml

@@ -0,0 +1,31 @@
+# yaml-language-server: $schema=https://raw.githubusercontent.com/microsoft/AgentSchema/refs/heads/main/schemas/v1.0/ContainerAgent.yaml
+
+name: FoundryMultiAgent
+displayName: "Foundry Multi-Agent Workflow"
+description: >
+  A multi-agent workflow featuring a Writer and Reviewer that collaborate
+  to create and refine content using Azure AI Foundry PersistentAgentsClient.
+metadata:
+  authors:
+    - Microsoft Agent Framework Team
+  tags:
+    - Azure AI AgentServer
+    - Microsoft Agent Framework
+    - Multi-Agent Workflow
+    - Writer-Reviewer
+    - Content Creation
+template:
+  kind: hosted
+  name: FoundryMultiAgent
+  protocols:
+    - protocol: responses
+      version: v1
+  environment_variables:
+    - name: AZURE_AI_PROJECT_ENDPOINT
+      value: ${AZURE_AI_PROJECT_ENDPOINT}
+    - name: MODEL_DEPLOYMENT_NAME
+      value: gpt-4o-mini
+resources:
+  - name: "gpt-4o-mini"
+    kind: model
+    id: gpt-4o-mini

dotnet/samples/05-end-to-end/HostedAgents/FoundryMultiAgent/appsettings.Development.json

@@ -0,0 +1,4 @@
+{
+    "AZURE_AI_PROJECT_ENDPOINT": "https://<your-resource>.services.ai.azure.com/api/projects/<your-project>",
+    "MODEL_DEPLOYMENT_NAME": "gpt-4o-mini"
+}

dotnet/samples/05-end-to-end/HostedAgents/FoundryMultiAgent/run-requests.http

@@ -0,0 +1,34 @@
+@host = http://localhost:8088
+@endpoint = {{host}}/responses
+
+### Health Check
+GET {{host}}/readiness
+
+### Simple string input - Content creation request
+POST {{endpoint}}
+Content-Type: application/json
+
+{
+    "input": "Create a slogan for a new electric SUV that is affordable and fun to drive",
+    "stream": false
+}
+
+### Explicit input format
+POST {{endpoint}}
+Content-Type: application/json
+
+{
+    "input": [
+        {
+            "type": "message",
+            "role": "user",
+            "content": [
+                {
+                    "type": "input_text",
+                    "text": "Write a short product description for a smart water bottle that tracks hydration"
+                }
+            ]
+        }
+    ],
+    "stream": false
+}

dotnet/samples/05-end-to-end/HostedAgents/FoundrySingleAgent/Dockerfile

@@ -0,0 +1,20 @@
+# Build the application
+FROM mcr.microsoft.com/dotnet/sdk:10.0-alpine AS build
+WORKDIR /src
+
+# Copy files from the current directory on the host to the working directory in the container
+COPY . .
+
+RUN dotnet restore
+RUN dotnet build -c Release --no-restore
+RUN dotnet publish -c Release --no-build -o /app -f net10.0
+
+# Run the application
+FROM mcr.microsoft.com/dotnet/aspnet:10.0-alpine AS final
+WORKDIR /app
+
+# Copy everything needed to run the app from the "build" stage.
+COPY --from=build /app .
+
+EXPOSE 8088
+ENTRYPOINT ["dotnet", "FoundrySingleAgent.dll"]

dotnet/samples/05-end-to-end/HostedAgents/FoundrySingleAgent/FoundrySingleAgent.csproj

@@ -0,0 +1,67 @@
+<Project Sdk="Microsoft.NET.Sdk">
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+
+    <!-- 
+      Disable central package management for this project.
+      This project requires explicit package references with versions specified inline rather than 
+      inheriting them from Directory.Packages.props. This is necessary because a Docker image will 
+      be created from this project, and the Docker build process only has access to this folder 
+      and cannot access parent folders where Directory.Packages.props resides.
+    -->
+    <ManagePackageVersionsCentrally>false</ManagePackageVersionsCentrally>
+  </PropertyGroup>
+
+  <!-- 
+    Remove analyzer PackageReference items inherited from Directory.Packages.props.
+    Note: ManagePackageVersionsCentrally only controls PackageVersion items, not PackageReference items.
+    Directory.Packages.props contains both PackageVersion and PackageReference entries for analyzers,
+    and the PackageReference items are always inherited through MSBuild imports regardless of the 
+    ManagePackageVersionsCentrally setting. We must explicitly remove them before adding our own versions.
+  -->
+  <ItemGroup>
+    <PackageReference Remove="Microsoft.CodeAnalysis.NetAnalyzers" />
+    <PackageReference Remove="Microsoft.VisualStudio.Threading.Analyzers" />
+    <PackageReference Remove="xunit.analyzers" />
+    <PackageReference Remove="Moq.Analyzers" />
+    <PackageReference Remove="Roslynator.Analyzers" />
+    <PackageReference Remove="Roslynator.CodeAnalysis.Analyzers" />
+    <PackageReference Remove="Roslynator.Formatting.Analyzers" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.8" />
+    <PackageReference Include="Azure.AI.Projects" Version="1.2.0-beta.5" />
+    <PackageReference Include="Azure.Identity" Version="1.17.1" />
+    <PackageReference Include="Microsoft.Agents.AI" Version="1.0.0-preview.251219.1" />
+    <PackageReference Include="Microsoft.Agents.AI.AzureAI" Version="1.0.0-preview.251219.1" />
+  </ItemGroup>
+
+  <!-- Add analyzers with compatible versions -->
+  <ItemGroup>
+    <PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="10.0.100">
+      <PrivateAssets>all</PrivateAssets>
+      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
+    </PackageReference>
+    <PackageReference Include="Microsoft.VisualStudio.Threading.Analyzers" Version="17.14.15">
+      <PrivateAssets>all</PrivateAssets>
+      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
+    </PackageReference>
+    <PackageReference Include="Roslynator.Analyzers" Version="4.14.1">
+      <PrivateAssets>all</PrivateAssets>
+      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
+    </PackageReference>
+    <PackageReference Include="Roslynator.CodeAnalysis.Analyzers" Version="4.14.1">
+      <PrivateAssets>all</PrivateAssets>
+      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
+    </PackageReference>
+    <PackageReference Include="Roslynator.Formatting.Analyzers" Version="4.14.1">
+      <PrivateAssets>all</PrivateAssets>
+      <IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
+    </PackageReference>
+  </ItemGroup>
+
+</Project>

dotnet/samples/05-end-to-end/HostedAgents/FoundrySingleAgent/Program.cs

@@ -0,0 +1,130 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// Seattle Hotel Agent - A simple agent with a tool to find hotels in Seattle.
+// Uses Microsoft Agent Framework with Azure AI Foundry.
+// Ready for deployment to Foundry Hosted Agent service.
+
+#pragma warning disable CA2252 // AIProjectClient and Agents API require opting into preview features
+
+using System.ComponentModel;
+using System.Globalization;
+using System.Text;
+
+using Azure.AI.AgentServer.AgentFramework.Extensions;
+using Azure.AI.Projects;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+
+// Get configuration from environment variables
+var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT")
+    ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+Console.WriteLine($"Project Endpoint: {endpoint}");
+Console.WriteLine($"Model Deployment: {deploymentName}");
+// Simulated hotel data for Seattle
+var seattleHotels = new[]
+{
+    new Hotel("Contoso Suites", 189, 4.5, "Downtown"),
+    new Hotel("Fabrikam Residences", 159, 4.2, "Pike Place Market"),
+    new Hotel("Alpine Ski House", 249, 4.7, "Seattle Center"),
+    new Hotel("Margie's Travel Lodge", 219, 4.4, "Waterfront"),
+    new Hotel("Northwind Inn", 139, 4.0, "Capitol Hill"),
+    new Hotel("Relecloud Hotel", 99, 3.8, "University District"),
+};
+
+[Description("Get available hotels in Seattle for the specified dates. This simulates a call to a hotel availability API.")]
+string GetAvailableHotels(
+    [Description("Check-in date in YYYY-MM-DD format")] string checkInDate,
+    [Description("Check-out date in YYYY-MM-DD format")] string checkOutDate,
+    [Description("Maximum price per night in USD (optional, defaults to 500)")] int maxPrice = 500)
+{
+    try
+    {
+        // Parse dates
+        if (!DateTime.TryParseExact(checkInDate, "yyyy-MM-dd", CultureInfo.InvariantCulture, DateTimeStyles.None, out var checkIn))
+        {
+            return "Error parsing check-in date. Please use YYYY-MM-DD format.";
+        }
+
+        if (!DateTime.TryParseExact(checkOutDate, "yyyy-MM-dd", CultureInfo.InvariantCulture, DateTimeStyles.None, out var checkOut))
+        {
+            return "Error parsing check-out date. Please use YYYY-MM-DD format.";
+        }
+
+        // Validate dates
+        if (checkOut <= checkIn)
+        {
+            return "Error: Check-out date must be after check-in date.";
+        }
+
+        var nights = (checkOut - checkIn).Days;
+
+        // Filter hotels by price
+        var availableHotels = seattleHotels.Where(h => h.PricePerNight <= maxPrice).ToList();
+
+        if (availableHotels.Count == 0)
+        {
+            return $"No hotels found in Seattle within your budget of ${maxPrice}/night.";
+        }
+
+        // Build response
+        var result = new StringBuilder();
+        result.AppendLine($"Available hotels in Seattle from {checkInDate} to {checkOutDate} ({nights} nights):");
+        result.AppendLine();
+
+        foreach (var hotel in availableHotels)
+        {
+            var totalCost = hotel.PricePerNight * nights;
+            result.AppendLine($"**{hotel.Name}**");
+            result.AppendLine($"   Location: {hotel.Location}");
+            result.AppendLine($"   Rating: {hotel.Rating}/5");
+            result.AppendLine($"   ${hotel.PricePerNight}/night (Total: ${totalCost})");
+            result.AppendLine();
+        }
+
+        return result.ToString();
+    }
+    catch (Exception ex)
+    {
+        return $"Error processing request. Details: {ex.Message}";
+    }
+}
+
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
+
+// Create Foundry agent with hotel search tool
+AIAgent agent = await aiProjectClient.CreateAIAgentAsync(
+    name: "SeattleHotelAgent",
+    model: deploymentName,
+    instructions: """
+        You are a helpful travel assistant specializing in finding hotels in Seattle, Washington.
+
+        When a user asks about hotels in Seattle:
+        1. Ask for their check-in and check-out dates if not provided
+        2. Ask about their budget preferences if not mentioned
+        3. Use the GetAvailableHotels tool to find available options
+        4. Present the results in a friendly, informative way
+        5. Offer to help with additional questions about the hotels or Seattle
+
+        Be conversational and helpful. If users ask about things outside of Seattle hotels,
+        politely let them know you specialize in Seattle hotel recommendations.
+        """,
+    tools: [AIFunctionFactory.Create(GetAvailableHotels)]);
+
+try
+{
+    Console.WriteLine("Seattle Hotel Agent Server running on http://localhost:8088");
+    await agent.RunAIAgentAsync(telemetrySourceName: "Agents");
+}
+finally
+{
+    // Cleanup server-side agent
+    await aiProjectClient.Agents.DeleteAgentAsync(agent.Name);
+}
+
+// Hotel record for simulated data
+internal sealed record Hotel(string Name, int PricePerNight, double Rating, string Location);

dotnet/samples/05-end-to-end/HostedAgents/FoundrySingleAgent/README.md

@@ -0,0 +1,167 @@
+**IMPORTANT!** All samples and other resources made available in this GitHub repository ("samples") are designed to assist in accelerating development of agents, solutions, and agent workflows for various scenarios. Review all provided resources and carefully test output behavior in the context of your use case. AI responses may be inaccurate and AI actions should be monitored with human oversight. Learn more in the transparency documents for [Agent Service](https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-ai/agents/transparency-note) and [Agent Framework](https://github.com/microsoft/agent-framework/blob/main/TRANSPARENCY_FAQ.md).
+
+Agents, solutions, or other output you create may be subject to legal and regulatory requirements, may require licenses, or may not be suitable for all industries, scenarios, or use cases. By using any sample, you are acknowledging that any output created using those samples are solely your responsibility, and that you will comply with all applicable laws, regulations, and relevant safety standards, terms of service, and codes of conduct.
+
+Third-party samples contained in this folder are subject to their own designated terms, and they have not been tested or verified by Microsoft or its affiliates.
+
+Microsoft has no responsibility to you or others with respect to any of these samples or any resulting output.
+
+# What this sample demonstrates
+
+This sample demonstrates a **key advantage of code-based hosted agents**:
+
+- **Local C# tool execution** - Run custom C# methods as agent tools
+
+Code-based agents can execute **any C# code** you write. This sample includes a Seattle Hotel Agent with a `GetAvailableHotels` tool that searches for available hotels based on check-in/check-out dates and budget preferences.
+
+The agent is hosted using the [Azure AI AgentServer SDK](https://learn.microsoft.com/en-us/dotnet/api/overview/azure/ai.agentserver.agentframework-readme) and can be deployed to Microsoft Foundry.
+
+## How It Works
+
+### Local Tools Integration
+
+In [Program.cs](Program.cs), the agent uses `AIProjectClient.CreateAIAgentAsync()` from the [Microsoft.Agents.AI.AzureAI](https://www.nuget.org/packages/Microsoft.Agents.AI.AzureAI/) package to create a Foundry agent with a local C# method (`GetAvailableHotels`) that simulates a hotel availability API. This demonstrates how code-based agents can execute custom server-side logic that prompt agents cannot access.
+
+The tool accepts:
+
+- **checkInDate** - Check-in date in YYYY-MM-DD format
+- **checkOutDate** - Check-out date in YYYY-MM-DD format
+- **maxPrice** - Maximum price per night in USD (optional, defaults to $500)
+
+### Agent Hosting
+
+The agent is hosted using the [Azure AI AgentServer SDK](https://learn.microsoft.com/en-us/dotnet/api/overview/azure/ai.agentserver.agentframework-readme),
+which provisions a REST API endpoint compatible with the OpenAI Responses protocol.
+
+## Running the Agent Locally
+
+### Prerequisites
+
+Before running this sample, ensure you have:
+
+1. **Azure AI Foundry Project**
+   - Project created.
+   - Chat model deployed (e.g., `gpt-4o` or `gpt-4.1`)
+   - Note your project endpoint URL and model deployment name
+
+2. **Azure CLI**
+   - Installed and authenticated
+   - Run `az login` and verify with `az account show`
+   - Your identity needs the **Azure AI Developer** role on the Foundry resource (for `agents/write` data action required by `CreateAIAgentAsync`)
+
+3. **.NET 10.0 SDK or later**
+   - Verify your version: `dotnet --version`
+   - Download from [https://dotnet.microsoft.com/download](https://dotnet.microsoft.com/download)
+
+### Environment Variables
+
+Set the following environment variables (matching `agent.yaml`):
+
+- `AZURE_AI_PROJECT_ENDPOINT` - Your Azure AI Foundry project endpoint URL (required)
+- `MODEL_DEPLOYMENT_NAME` - The deployment name for your chat model (defaults to `gpt-4o-mini`)
+
+**PowerShell:**
+
+```powershell
+# Replace with your actual values
+$env:AZURE_AI_PROJECT_ENDPOINT="https://<your-resource>.services.ai.azure.com/api/projects/<your-project>"
+$env:MODEL_DEPLOYMENT_NAME="gpt-4o-mini"
+```
+
+**Bash:**
+
+```bash
+export AZURE_AI_PROJECT_ENDPOINT="https://<your-resource>.services.ai.azure.com/api/projects/<your-project>"
+export MODEL_DEPLOYMENT_NAME="gpt-4o-mini"
+```
+
+### Running the Sample
+
+To run the agent, execute the following command in your terminal:
+
+```bash
+dotnet restore
+dotnet build
+dotnet run
+```
+
+This will start the hosted agent locally on `http://localhost:8088/`.
+
+### Interacting with the Agent
+
+**VS Code:**
+
+1. Open the Visual Studio Code Command Palette and execute the `Microsoft Foundry: Open Container Agent Playground Locally` command.
+2. Execute the following commands to start the containerized hosted agent.
+
+   ```bash
+   dotnet restore
+   dotnet build
+   dotnet run
+   ```
+
+3. Submit a request to the agent through the playground interface. For example, you may enter a prompt such as: "I need a hotel in Seattle from 2025-03-15 to 2025-03-18, budget under $200 per night."
+4. The agent will use the GetAvailableHotels tool to search for available hotels matching your criteria.
+
+> **Note**: Open the local playground before starting the container agent to ensure the visualization functions correctly.
+
+**PowerShell (Windows):**
+
+```powershell
+$body = @{
+    input = "I need a hotel in Seattle from 2025-03-15 to 2025-03-18, budget under `$200 per night"
+    stream = $false
+} | ConvertTo-Json
+
+Invoke-RestMethod -Uri http://localhost:8088/responses -Method Post -Body $body -ContentType "application/json"
+```
+
+**Bash/curl (Linux/macOS):**
+
+```bash
+curl -sS -H "Content-Type: application/json" -X POST http://localhost:8088/responses \
+   -d '{"input": "Find me hotels in Seattle for March 20-23, 2025 under $200 per night","stream":false}'
+```
+
+You can also use the `run-requests.http` file in this directory with the VS Code REST Client extension.
+
+The agent will use the `GetAvailableHotels` tool to search for available hotels matching your criteria.
+
+## Deploying the Agent to Microsoft Foundry
+
+**Preparation (required)**
+
+Please check the environment_variables section in [agent.yaml](agent.yaml) and ensure the variables there are set in your target Microsoft Foundry Project.
+
+To deploy the hosted agent:
+
+1. Open the VS Code Command Palette and run the `Microsoft Foundry: Deploy Hosted Agent` command.
+2. Follow the interactive deployment prompts. The extension will help you select or create the container files it needs.
+3. After deployment completes, the hosted agent appears under the `Hosted Agents (Preview)` section of the extension tree. You can select the agent there to view details and test it using the integrated playground.
+
+**What the deploy flow does for you:**
+
+- Creates or obtains an Azure Container Registry for the target project.
+- Builds and pushes a container image from your workspace (the build packages the workspace respecting `.dockerignore`).
+- Creates an agent version in Microsoft Foundry using the built image. If a `.env` file exists at the workspace root, the extension will parse it and include its key/value pairs as the hosted agent's environment variables in the create request (these variables will be available to the agent runtime).
+- Starts the agent container on the project's capability host. If the capability host is not provisioned, the extension will prompt you to enable it and will guide you through creating it.
+
+## MSI Configuration in the Azure Portal
+
+This sample requires the Microsoft Foundry Project to authenticate using a Managed Identity when running remotely in Azure. Grant the project's managed identity the required permissions by assigning the built-in [Azure AI User](https://aka.ms/foundry-ext-project-role) role.
+
+To configure the Managed Identity:
+
+1. In the Azure Portal, open the Foundry Project.
+2. Select "Access control (IAM)" from the left-hand menu.
+3. Click "Add" and choose "Add role assignment".
+4. In the role selection, search for and select "Azure AI User", then click "Next".
+5. For "Assign access to", choose "Managed identity".
+6. Click "Select members", locate the managed identity associated with your Foundry Project (you can search by the project name), then click "Select".
+7. Click "Review + assign" to complete the assignment.
+8. Allow a few minutes for the role assignment to propagate before running the application.
+
+## Additional Resources
+
+- [Microsoft Agents Framework](https://learn.microsoft.com/en-us/agent-framework/overview/agent-framework-overview)
+- [Managed Identities for Azure Resources](https://learn.microsoft.com/en-us/entra/identity/managed-identities-azure-resources/)

dotnet/samples/05-end-to-end/HostedAgents/FoundrySingleAgent/agent.yaml

@@ -0,0 +1,32 @@
+# yaml-language-server: $schema=https://raw.githubusercontent.com/microsoft/AgentSchema/refs/heads/main/schemas/v1.0/ContainerAgent.yaml
+
+name: FoundrySingleAgent
+displayName: "Foundry Single Agent with Local Tools"
+description: >
+  A travel assistant agent that helps users find hotels in Seattle.
+  Demonstrates local C# tool execution - a key advantage of code-based 
+  hosted agents over prompt agents.
+metadata:
+  authors:
+    - Microsoft Agent Framework Team
+  tags:
+    - Azure AI AgentServer
+    - Microsoft Agent Framework
+    - Local Tools
+    - Travel Assistant
+    - Hotel Search
+template:
+  kind: hosted
+  name: FoundrySingleAgent
+  protocols:
+    - protocol: responses
+      version: v1
+  environment_variables:
+    - name: AZURE_AI_PROJECT_ENDPOINT
+      value: ${AZURE_AI_PROJECT_ENDPOINT}
+    - name: MODEL_DEPLOYMENT_NAME
+      value: gpt-4o-mini
+resources:
+  - name: "gpt-4o-mini"
+    kind: model
+    id: gpt-4o-mini

dotnet/samples/05-end-to-end/HostedAgents/FoundrySingleAgent/run-requests.http

@@ -0,0 +1,52 @@
+@host = http://localhost:8088
+@endpoint = {{host}}/responses
+
+### Health Check
+GET {{host}}/readiness
+
+### Simple hotel search - budget under $200
+POST {{endpoint}}
+Content-Type: application/json
+
+{
+    "input": "I need a hotel in Seattle from 2025-03-15 to 2025-03-18, budget under $200 per night",
+    "stream": false
+}
+
+### Hotel search with higher budget
+POST {{endpoint}}
+Content-Type: application/json
+
+{
+    "input": "Find me hotels in Seattle for March 20-23, 2025 under $250 per night",
+    "stream": false
+}
+
+### Ask for recommendations without dates (agent should ask for clarification)
+POST {{endpoint}}
+Content-Type: application/json
+
+{
+    "input": "What hotels do you recommend in Seattle?",
+    "stream": false
+}
+
+### Explicit input format
+POST {{endpoint}}
+Content-Type: application/json
+
+{
+    "input": [
+        {
+            "type": "message",
+            "role": "user",
+            "content": [
+                {
+                    "type": "input_text",
+                    "text": "I'm looking for a hotel in Seattle from 2025-04-01 to 2025-04-05, my budget is $150 per night maximum"
+                }
+            ]
+        }
+    ],
+    "stream": false
+}

dotnet/samples/05-end-to-end/HostedAgents/README.md

@@ -12,6 +12,8 @@ These samples demonstrate how to build and host AI agents using the [Azure AI Ag
 | [`AgentWithHostedMCP`](./AgentWithHostedMCP/) | Hosted MCP server tool (Microsoft Learn search) |
 | [`AgentWithTextSearchRag`](./AgentWithTextSearchRag/) | RAG with `TextSearchProvider` (Contoso Outdoors) |
 | [`AgentsInWorkflows`](./AgentsInWorkflows/) | Sequential workflow pipeline (translation chain) |
+| [`FoundryMultiAgent`](./FoundryMultiAgent/) | Multi-agent Writer-Reviewer workflow using `AIProjectClient.CreateAIAgentAsync()` from [Microsoft.Agents.AI.AzureAI](https://www.nuget.org/packages/Microsoft.Agents.AI.AzureAI/) |
+| [`FoundrySingleAgent`](./FoundrySingleAgent/) | Single agent with local C# tool execution (hotel search) using `AIProjectClient.CreateAIAgentAsync()` from [Microsoft.Agents.AI.AzureAI](https://www.nuget.org/packages/Microsoft.Agents.AI.AzureAI/) |
 
 ## Common Prerequisites
 
@@ -23,7 +25,7 @@ Before running any sample, ensure you have:
 
 ### Authenticate with Azure CLI
 
-All samples use `AzureCliCredential` for authentication. Make sure you're logged in:
+All samples use `DefaultAzureCredential` for authentication, which automatically probes multiple credential sources (environment variables, managed identity, Azure CLI, etc.). For local development, the simplest approach is to authenticate via Azure CLI:
 
 ```powershell
 az login
@@ -38,9 +40,9 @@ Most samples require one or more of these environment variables:
 |----------|---------|-------------|
 | `AZURE_OPENAI_ENDPOINT` | Most samples | Your Azure OpenAI resource endpoint URL |
 | `AZURE_OPENAI_DEPLOYMENT_NAME` | Most samples | Chat model deployment name (defaults to `gpt-4o-mini`) |
-| `AZURE_AI_PROJECT_ENDPOINT` | AgentWithTools, AgentWithLocalTools | Azure AI Foundry project endpoint |
+| `AZURE_AI_PROJECT_ENDPOINT` | AgentWithTools, AgentWithLocalTools, FoundryMultiAgent, FoundrySingleAgent | Azure AI Foundry project endpoint |
 | `MCP_TOOL_CONNECTION_ID` | AgentWithTools | Foundry MCP tool connection name |
-| `MODEL_DEPLOYMENT_NAME` | AgentWithLocalTools | Chat model deployment name (defaults to `gpt-4o-mini`) |
+| `MODEL_DEPLOYMENT_NAME` | AgentWithLocalTools, FoundryMultiAgent, FoundrySingleAgent | Chat model deployment name (defaults to `gpt-4o-mini`) |
 
 See each sample's README for the specific variables required.
 

dotnet/src/Microsoft.Agents.AI.A2A/A2AAgent.cs

@@ -127,6 +127,7 @@ public sealed class A2AAgent : AIAgent
             {
                 AgentId = this.Id,
                 ResponseId = message.MessageId,
+                FinishReason = ChatFinishReason.Stop,
                 RawRepresentation = message,
                 Messages = [message.ToChatMessage()],
                 AdditionalProperties = message.Metadata?.ToAdditionalProperties(),
@@ -141,6 +142,7 @@ public sealed class A2AAgent : AIAgent
             {
                 AgentId = this.Id,
                 ResponseId = agentTask.Id,
+                FinishReason = MapTaskStateToFinishReason(agentTask.Status.State),
                 RawRepresentation = agentTask,
                 Messages = agentTask.ToChatMessages() ?? [],
                 ContinuationToken = CreateContinuationToken(agentTask.Id, agentTask.Status.State),
@@ -328,6 +330,7 @@ public sealed class A2AAgent : AIAgent
         {
             AgentId = this.Id,
             ResponseId = message.MessageId,
+            FinishReason = ChatFinishReason.Stop,
             RawRepresentation = message,
             Role = ChatRole.Assistant,
             MessageId = message.MessageId,
@@ -342,6 +345,7 @@ public sealed class A2AAgent : AIAgent
         {
             AgentId = this.Id,
             ResponseId = task.Id,
+            FinishReason = MapTaskStateToFinishReason(task.Status.State),
             RawRepresentation = task,
             Role = ChatRole.Assistant,
             Contents = task.ToAIContents(),
@@ -365,7 +369,16 @@ public sealed class A2AAgent : AIAgent
             responseUpdate.Contents = artifactUpdateEvent.Artifact.ToAIContents();
             responseUpdate.RawRepresentation = artifactUpdateEvent;
         }
+        else if (taskUpdateEvent is TaskStatusUpdateEvent statusUpdateEvent)
+        {
+            responseUpdate.FinishReason = MapTaskStateToFinishReason(statusUpdateEvent.Status.State);
+        }
 
         return responseUpdate;
     }
+
+    private static ChatFinishReason? MapTaskStateToFinishReason(TaskState state)
+    {
+        return state == TaskState.Completed ? ChatFinishReason.Stop : null;
+    }
 }

dotnet/src/Microsoft.Agents.AI.A2A/Extensions/A2AMetadataExtensions.cs

@@ -1,36 +0,0 @@
-// Copyright (c) Microsoft. All rights reserved.
-
-using System.Collections.Generic;
-using System.Text.Json;
-using Microsoft.Extensions.AI;
-
-namespace A2A;
-
-/// <summary>
-/// Extension methods for A2A metadata dictionary.
-/// </summary>
-internal static class A2AMetadataExtensions
-{
-    /// <summary>
-    /// Converts a dictionary of metadata to an <see cref="AdditionalPropertiesDictionary"/>.
-    /// </summary>
-    /// <remarks>
-    /// This method can be replaced by the one from A2A SDK once it is public.
-    /// </remarks>
-    /// <param name="metadata">The metadata dictionary to convert.</param>
-    /// <returns>The converted <see cref="AdditionalPropertiesDictionary"/>, or null if the input is null or empty.</returns>
-    internal static AdditionalPropertiesDictionary? ToAdditionalProperties(this Dictionary<string, JsonElement>? metadata)
-    {
-        if (metadata is not { Count: > 0 })
-        {
-            return null;
-        }
-
-        var additionalProperties = new AdditionalPropertiesDictionary();
-        foreach (var kvp in metadata)
-        {
-            additionalProperties[kvp.Key] = kvp.Value;
-        }
-        return additionalProperties;
-    }
-}

dotnet/src/Microsoft.Agents.AI.A2A/Extensions/AdditionalPropertiesDictionaryExtensions.cs

@@ -1,44 +0,0 @@
-// Copyright (c) Microsoft. All rights reserved.
-
-using System.Collections.Generic;
-using System.Text.Json;
-using Microsoft.Agents.AI;
-
-namespace Microsoft.Extensions.AI;
-
-/// <summary>
-/// Extension methods for AdditionalPropertiesDictionary.
-/// </summary>
-internal static class AdditionalPropertiesDictionaryExtensions
-{
-    /// <summary>
-    /// Converts an <see cref="AdditionalPropertiesDictionary"/> to a dictionary of <see cref="JsonElement"/> values suitable for A2A metadata.
-    /// </summary>
-    /// <remarks>
-    /// This method can be replaced by the one from A2A SDK once it is available.
-    /// </remarks>
-    /// <param name="additionalProperties">The additional properties dictionary to convert, or <c>null</c>.</param>
-    /// <returns>A dictionary of JSON elements representing the metadata, or <c>null</c> if the input is null or empty.</returns>
-    internal static Dictionary<string, JsonElement>? ToA2AMetadata(this AdditionalPropertiesDictionary? additionalProperties)
-    {
-        if (additionalProperties is not { Count: > 0 })
-        {
-            return null;
-        }
-
-        var metadata = new Dictionary<string, JsonElement>();
-
-        foreach (var kvp in additionalProperties)
-        {
-            if (kvp.Value is JsonElement)
-            {
-                metadata[kvp.Key] = (JsonElement)kvp.Value!;
-                continue;
-            }
-
-            metadata[kvp.Key] = JsonSerializer.SerializeToElement(kvp.Value, A2AJsonUtilities.DefaultOptions.GetTypeInfo(typeof(object)));
-        }
-
-        return metadata;
-    }
-}

dotnet/src/Microsoft.Agents.AI.Abstractions/AIAgent.cs

@@ -20,6 +20,19 @@ namespace Microsoft.Agents.AI;
 /// <see cref="AIAgent"/> serves as the foundational class for implementing AI agents that can participate in conversations
 /// and process user requests. An agent instance may participate in multiple concurrent conversations, and each conversation
 /// may involve multiple agents working together.
+/// <para>
+/// <strong>Security considerations:</strong> An <see cref="AIAgent"/> orchestrates data flow across trust boundaries —
+/// messages are sent to external AI services, context providers, chat history stores, and function tools. Agent Framework
+/// passes messages through as-is without validation or sanitization. Developers must be aware that:
+/// <list type="bullet">
+/// <item><description>User-supplied messages may contain prompt injection attempts designed to manipulate LLM behavior.</description></item>
+/// <item><description>LLM responses should be treated as untrusted output — they may contain hallucinations, malicious payloads (e.g., scripts, SQL),
+/// or content influenced by indirect prompt injection. Always validate and sanitize LLM output before rendering in HTML, executing as code,
+/// or using in database queries.</description></item>
+/// <item><description>Messages with different roles carry different trust levels: <c>system</c> messages have the highest trust and must be developer-controlled;
+/// <c>user</c>, <c>assistant</c>, and <c>tool</c> messages should be treated as untrusted.</description></item>
+/// </list>
+/// </para>
 /// </remarks>
 [DebuggerDisplay("{DebuggerDisplay,nq}")]
 public abstract partial class AIAgent
@@ -165,6 +178,11 @@ public abstract partial class AIAgent
     /// This method enables saving conversation sessions to persistent storage,
     /// allowing conversations to resume across application restarts or be migrated between
     /// different agent instances. Use <see cref="DeserializeSessionAsync"/> to restore the session.
+    /// <para>
+    /// <strong>Security consideration:</strong> Serialized sessions may contain conversation content, session identifiers,
+    /// and other potentially sensitive data including PII. Ensure that serialized session data is stored securely with
+    /// appropriate access controls and encryption at rest.
+    /// </para>
     /// </remarks>
     public ValueTask<JsonElement> SerializeSessionAsync(AgentSession session, JsonSerializerOptions? jsonSerializerOptions = null, CancellationToken cancellationToken = default)
         => this.SerializeSessionCoreAsync(session, jsonSerializerOptions, cancellationToken);
@@ -194,6 +212,12 @@ public abstract partial class AIAgent
     /// This method enables restoration of conversation sessions from previously saved state,
     /// allowing conversations to resume across application restarts or be migrated between
     /// different agent instances.
+    /// <para>
+    /// <strong>Security consideration:</strong> Restoring a session from an untrusted source is equivalent to accepting untrusted input.
+    /// Serialized sessions may contain conversation content, session identifiers, and potentially sensitive data. A compromised
+    /// storage backend could alter message roles to escalate trust, or inject adversarial content that influences LLM behavior.
+    /// Treat serialized session data as sensitive and ensure it is stored and transmitted securely.
+    /// </para>
     /// </remarks>
     public ValueTask<AgentSession> DeserializeSessionAsync(JsonElement serializedState, JsonSerializerOptions? jsonSerializerOptions = null, CancellationToken cancellationToken = default)
         => this.DeserializeSessionCoreAsync(serializedState, jsonSerializerOptions, cancellationToken);
@@ -301,6 +325,11 @@ public abstract partial class AIAgent
     /// The messages are processed in the order provided and become part of the conversation history.
     /// The agent's response will also be added to <paramref name="session"/> if one is provided.
     /// </para>
+    /// <para>
+    /// <strong>Security consideration:</strong> Agent Framework does not validate or sanitize message content — it is passed through
+    /// to the underlying AI service as-is. If input messages include untrusted user content, developers should be aware of prompt injection risks.
+    /// System-role messages must be developer-controlled and should never contain end-user input.
+    /// </para>
     /// </remarks>
     public Task<AgentResponse> RunAsync(
         IEnumerable<ChatMessage> messages,
@@ -426,6 +455,11 @@ public abstract partial class AIAgent
     /// Each <see cref="AgentResponseUpdate"/> represents a portion of the complete response, allowing consumers
     /// to display partial results, implement progressive loading, or provide immediate feedback to users.
     /// </para>
+    /// <para>
+    /// <strong>Security consideration:</strong> Agent Framework does not validate or sanitize message content — it is passed through
+    /// to the underlying AI service as-is. If input messages include untrusted user content, developers should be aware of prompt injection risks.
+    /// System-role messages must be developer-controlled and should never contain end-user input.
+    /// </para>
     /// </remarks>
     public async IAsyncEnumerable<AgentResponseUpdate> RunStreamingAsync(
         IEnumerable<ChatMessage> messages,

dotnet/src/Microsoft.Agents.AI.Abstractions/AIContextProvider.cs

@@ -28,6 +28,14 @@ namespace Microsoft.Agents.AI;
 /// <see cref="InvokingAsync"/> to provide context, and optionally called at the end of invocation via
 /// <see cref="InvokedAsync"/> to process results.
 /// </para>
+/// <para>
+/// <strong>Security considerations:</strong> Context providers may inject messages with any role, including <c>system</c>, which
+/// has the highest trust level and directly shapes LLM behavior. Developers must ensure that all providers attached to an agent
+/// are trusted. Agent Framework does not validate or filter the data returned by providers — it is accepted as-is and merged into
+/// the request context. If a provider retrieves data from an external source (e.g., a vector database or memory service), be aware
+/// that a compromised data source could introduce adversarial content designed to manipulate LLM behavior via indirect prompt injection.
+/// Implementers should validate and sanitize data retrieved from external sources before returning it.
+/// </para>
 /// </remarks>
 public abstract class AIContextProvider
 {
@@ -96,6 +104,11 @@ public abstract class AIContextProvider
     /// <item><description>Injecting contextual messages from conversation history</description></item>
     /// </list>
     /// </para>
+    /// <para>
+    /// <strong>Security consideration:</strong> Data retrieved from external sources (e.g., vector databases, memory services, or
+    /// knowledge bases) may contain adversarial content designed to influence LLM behavior via indirect prompt injection.
+    /// Implementers should validate data integrity and consider the trustworthiness of the data source.
+    /// </para>
     /// </remarks>
     public ValueTask<AIContext> InvokingAsync(InvokingContext context, CancellationToken cancellationToken = default)
         => this.InvokingCoreAsync(Throw.IfNull(context), cancellationToken);
@@ -195,6 +208,11 @@ public abstract class AIContextProvider
     /// In contrast with <see cref="InvokingCoreAsync"/>, this method only returns additional context to be merged with the input,
     /// while <see cref="InvokingCoreAsync"/> is responsible for returning the full merged <see cref="AIContext"/> for the invocation.
     /// </para>
+    /// <para>
+    /// <strong>Security consideration:</strong> Any messages, tools, or instructions returned by this method will be merged into the
+    /// AI request context. If data is retrieved from external or untrusted sources, implementers should validate and sanitize it
+    /// to prevent indirect prompt injection attacks.
+    /// </para>
     /// </remarks>
     /// <param name="context">Contains the request context including the caller provided messages that will be used by the agent for this invocation.</param>
     /// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
@@ -299,6 +317,10 @@ public abstract class AIContextProvider
     /// <para>
     /// The default implementation of <see cref="InvokedCoreAsync"/> only calls this method if the invocation succeeded.
     /// </para>
+    /// <para>
+    /// <strong>Security consideration:</strong> Messages being processed/stored may contain PII and sensitive conversation content.
+    /// Implementers should ensure appropriate encryption at rest and access controls for the storage backend.
+    /// </para>
     /// </remarks>
     protected virtual ValueTask StoreAIContextAsync(InvokedContext context, CancellationToken cancellationToken = default) =>
         default;

dotnet/src/Microsoft.Agents.AI.Abstractions/AgentResponse.cs

@@ -61,6 +61,7 @@ public class AgentResponse
 
         this.AdditionalProperties = response.AdditionalProperties;
         this.CreatedAt = response.CreatedAt;
+        this.FinishReason = response.FinishReason;
         this.Messages = response.Messages;
         this.RawRepresentation = response;
         this.ResponseId = response.ResponseId;
@@ -84,6 +85,7 @@ public class AgentResponse
 
         this.AdditionalProperties = response.AdditionalProperties;
         this.CreatedAt = response.CreatedAt;
+        this.FinishReason = response.FinishReason;
         this.Messages = response.Messages;
         this.RawRepresentation = response;
         this.ResponseId = response.ResponseId;
@@ -190,6 +192,21 @@ public class AgentResponse
     /// </remarks>
     public DateTimeOffset? CreatedAt { get; set; }
 
+    /// <summary>
+    /// Gets or sets the reason for the agent response finishing.
+    /// </summary>
+    /// <value>
+    /// A <see cref="ChatFinishReason"/> value indicating why the response finished (e.g., stop, length, content filter, tool calls),
+    /// or <see langword="null"/> if the finish reason is not available.
+    /// </value>
+    /// <remarks>
+    /// <para>
+    /// This property is particularly useful for detecting non-normal completions, such as content filtering
+    /// or token limit truncation, which may require special handling by the caller.
+    /// </para>
+    /// </remarks>
+    public ChatFinishReason? FinishReason { get; set; }
+
     /// <summary>
     /// Gets or sets the resource usage information for generating this response.
     /// </summary>
@@ -276,6 +293,7 @@ public class AgentResponse
                 RawRepresentation = message.RawRepresentation,
                 Role = message.Role,
 
+                FinishReason = this.FinishReason,
                 AgentId = this.AgentId,
                 ResponseId = this.ResponseId,
                 MessageId = message.MessageId,

dotnet/src/Microsoft.Agents.AI.Abstractions/AgentResponseExtensions.cs

@@ -38,6 +38,7 @@ public static class AgentResponseExtensions
             {
                 AdditionalProperties = response.AdditionalProperties,
                 CreatedAt = response.CreatedAt,
+                FinishReason = response.FinishReason,
                 Messages = response.Messages,
                 RawRepresentation = response,
                 ResponseId = response.ResponseId,
@@ -71,6 +72,7 @@ public static class AgentResponseExtensions
                 AuthorName = responseUpdate.AuthorName,
                 Contents = responseUpdate.Contents,
                 CreatedAt = responseUpdate.CreatedAt,
+                FinishReason = responseUpdate.FinishReason,
                 MessageId = responseUpdate.MessageId,
                 RawRepresentation = responseUpdate,
                 ResponseId = responseUpdate.ResponseId,

dotnet/src/Microsoft.Agents.AI.Abstractions/AgentResponseUpdate.cs

@@ -70,6 +70,7 @@ public class AgentResponseUpdate
         this.AuthorName = chatResponseUpdate.AuthorName;
         this.Contents = chatResponseUpdate.Contents;
         this.CreatedAt = chatResponseUpdate.CreatedAt;
+        this.FinishReason = chatResponseUpdate.FinishReason;
         this.MessageId = chatResponseUpdate.MessageId;
         this.RawRepresentation = chatResponseUpdate;
         this.ResponseId = chatResponseUpdate.ResponseId;
@@ -153,6 +154,15 @@ public class AgentResponseUpdate
     /// </remarks>
     public ResponseContinuationToken? ContinuationToken { get; set; }
 
+    /// <summary>
+    /// Gets or sets the reason for the agent response finishing.
+    /// </summary>
+    /// <value>
+    /// A <see cref="ChatFinishReason"/> value indicating why the response finished (e.g., stop, length, content filter, tool calls),
+    /// or <see langword="null"/> if the finish reason is not available or not yet determined (mid-stream).
+    /// </value>
+    public ChatFinishReason? FinishReason { get; set; }
+
     /// <inheritdoc/>
     public override string ToString() => this.Text;
 

dotnet/src/Microsoft.Agents.AI.Abstractions/AgentSession.cs

@@ -42,6 +42,15 @@ namespace Microsoft.Agents.AI;
 /// <see cref="JsonElement"/> and the <see cref="AIAgent.DeserializeSessionAsync(JsonElement, JsonSerializerOptions?, System.Threading.CancellationToken)"/> method
 /// can be used to deserialize the session.
 /// </para>
+/// <para>
+/// <strong>Security considerations:</strong> Serialized sessions may contain conversation content, session identifiers,
+/// and other potentially sensitive data including PII. Developers should:
+/// <list type="bullet">
+/// <item><description>Treat serialized session data as sensitive and store it securely with appropriate access controls and encryption at rest.</description></item>
+/// <item><description>Treat restoring a session from an untrusted source as equivalent to accepting untrusted input. A compromised storage backend
+/// could alter message roles to escalate trust, or inject adversarial content that influences LLM behavior.</description></item>
+/// </list>
+/// </para>
 /// </remarks>
 /// <seealso cref="AIAgent"/>
 /// <seealso cref="AIAgent.CreateSessionAsync(System.Threading.CancellationToken)"/>
@@ -67,6 +76,11 @@ public abstract class AgentSession
     /// <summary>
     /// Gets any arbitrary state associated with this session.
     /// </summary>
+    /// <remarks>
+    /// Data stored in the <see cref="StateBag"/> will be included when the session is serialized.
+    /// Avoid storing secrets, credentials, or highly sensitive data in the state bag without appropriate encryption,
+    /// as this data may be persisted to external storage.
+    /// </remarks>
     [JsonPropertyName("stateBag")]
     public AgentSessionStateBag StateBag { get; protected set; } = new();
 

dotnet/src/Microsoft.Agents.AI.Abstractions/ChatHistoryProvider.cs

@@ -37,6 +37,14 @@ namespace Microsoft.Agents.AI;
 /// A <see cref="ChatHistoryProvider"/> is only relevant for scenarios where the underlying AI service that the agent is using
 /// does not use in-service chat history storage.
 /// </para>
+/// <para>
+/// <strong>Security considerations:</strong> Agent Framework does not validate or filter the messages returned by the provider
+/// during load — they are accepted as-is and treated identically to user-supplied messages. Implementers must ensure that only
+/// trusted data is returned. If the underlying storage is compromised, adversarial content could influence LLM behavior via
+/// indirect prompt injection — for example, injected messages could alter the conversation context or impersonate different roles.
+/// Messages stored in chat history may contain PII and sensitive conversation content; implementers should consider encryption
+/// at rest and appropriate access controls for the storage backend.
+/// </para>
 /// </remarks>
 public abstract class ChatHistoryProvider
 {
@@ -159,6 +167,11 @@ public abstract class ChatHistoryProvider
     /// Messages are returned in chronological order to maintain proper conversation flow and context for the agent.
     /// The oldest messages appear first in the collection, followed by more recent messages.
     /// </para>
+    /// <para>
+    /// <strong>Security consideration:</strong> Messages loaded from storage should be treated with the same caution as user-supplied
+    /// messages. A compromised storage backend could alter message roles to escalate trust (e.g., changing <c>user</c> messages to
+    /// <c>system</c> messages) or inject adversarial content that influences LLM behavior.
+    /// </para>
     /// </remarks>
     /// <param name="context">Contains the request context including the caller provided messages that will be used by the agent for this invocation.</param>
     /// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
@@ -273,6 +286,10 @@ public abstract class ChatHistoryProvider
     /// <para>
     /// The default implementation of <see cref="InvokedCoreAsync"/> only calls this method if the invocation succeeded.
     /// </para>
+    /// <para>
+    /// <strong>Security consideration:</strong> Messages being stored may contain PII and sensitive conversation content.
+    /// Implementers should ensure appropriate encryption at rest and access controls for the storage backend.
+    /// </para>
     /// </remarks>
     protected virtual ValueTask StoreChatHistoryAsync(InvokedContext context, CancellationToken cancellationToken = default) =>
         default;

dotnet/src/Microsoft.Agents.AI.Abstractions/InMemoryChatHistoryProvider.cs

@@ -79,20 +79,21 @@ public sealed class InMemoryChatHistoryProvider : ChatHistoryProvider
     /// <exception cref="ArgumentNullException"><paramref name="messages"/> is <see langword="null"/>.</exception>
     public void SetMessages(AgentSession? session, List<ChatMessage> messages)
     {
-        _ = Throw.IfNull(messages);
+        Throw.IfNull(messages);
 
-        var state = this._sessionState.GetOrInitializeState(session);
+        State state = this._sessionState.GetOrInitializeState(session);
         state.Messages = messages;
     }
 
     /// <inheritdoc />
     protected override async ValueTask<IEnumerable<ChatMessage>> ProvideChatHistoryAsync(InvokingContext context, CancellationToken cancellationToken = default)
     {
-        var state = this._sessionState.GetOrInitializeState(context.Session);
+        State state = this._sessionState.GetOrInitializeState(context.Session);
 
         if (this.ReducerTriggerEvent is InMemoryChatHistoryProviderOptions.ChatReducerTriggerEvent.BeforeMessagesRetrieval && this.ChatReducer is not null)
         {
-            state.Messages = (await this.ChatReducer.ReduceAsync(state.Messages, cancellationToken).ConfigureAwait(false)).ToList();
+            // Apply pre-retrieval reduction if configured
+            await ReduceMessagesAsync(this.ChatReducer, state, cancellationToken).ConfigureAwait(false);
         }
 
         return state.Messages;
@@ -101,7 +102,7 @@ public sealed class InMemoryChatHistoryProvider : ChatHistoryProvider
     /// <inheritdoc />
     protected override async ValueTask StoreChatHistoryAsync(InvokedContext context, CancellationToken cancellationToken = default)
     {
-        var state = this._sessionState.GetOrInitializeState(context.Session);
+        State state = this._sessionState.GetOrInitializeState(context.Session);
 
         // Add request and response messages to the provider
         var allNewMessages = context.RequestMessages.Concat(context.ResponseMessages ?? []);
@@ -109,10 +110,16 @@ public sealed class InMemoryChatHistoryProvider : ChatHistoryProvider
 
         if (this.ReducerTriggerEvent is InMemoryChatHistoryProviderOptions.ChatReducerTriggerEvent.AfterMessageAdded && this.ChatReducer is not null)
         {
-            state.Messages = (await this.ChatReducer.ReduceAsync(state.Messages, cancellationToken).ConfigureAwait(false)).ToList();
+            // Apply pre-write reduction strategy if configured
+            await ReduceMessagesAsync(this.ChatReducer, state, cancellationToken).ConfigureAwait(false);
         }
     }
 
+    private static async Task ReduceMessagesAsync(IChatReducer reducer, State state, CancellationToken cancellationToken = default)
+    {
+        state.Messages = [.. await reducer.ReduceAsync(state.Messages, cancellationToken).ConfigureAwait(false)];
+    }
+
     /// <summary>
     /// Represents the state of a <see cref="InMemoryChatHistoryProvider"/> stored in the <see cref="AgentSession.StateBag"/>.
     /// </summary>

dotnet/src/Microsoft.Agents.AI.CosmosNoSql/CosmosChatHistoryProvider.cs

@@ -17,6 +17,24 @@ namespace Microsoft.Agents.AI;
 /// <summary>
 /// Provides a Cosmos DB implementation of the <see cref="ChatHistoryProvider"/> abstract class.
 /// </summary>
+/// <remarks>
+/// <para>
+/// <strong>Security considerations:</strong>
+/// <list type="bullet">
+/// <item><description><strong>PII and sensitive data:</strong> Chat history stored in Cosmos DB may contain PII, sensitive conversation
+/// content, and system instructions. Ensure the Cosmos DB account is configured with appropriate access controls, encryption at rest,
+/// and network security (e.g., private endpoints, virtual network rules). The <see cref="MessageTtlSeconds"/> property can be used to
+/// automatically expire messages and limit data retention.</description></item>
+/// <item><description><strong>Compromised store risks:</strong> Agent Framework does not validate or filter messages loaded from the
+/// store — they are accepted as-is. If the Cosmos DB store is compromised, adversarial content could be injected into the conversation
+/// context, potentially influencing LLM behavior via indirect prompt injection. Altered message roles (e.g., changing <c>user</c> to
+/// <c>system</c>) could escalate trust levels.</description></item>
+/// <item><description><strong>Authentication:</strong> Agent Framework does not manage authentication or encryption for the Cosmos DB
+/// connection — these are the responsibility of the <see cref="CosmosClient"/> configuration. Use managed identity
+/// or token-based authentication where possible, and avoid embedding connection strings with keys in source code.</description></item>
+/// </list>
+/// </para>
+/// </remarks>
 [RequiresUnreferencedCode("The CosmosChatHistoryProvider uses JSON serialization which is incompatible with trimming.")]
 [RequiresDynamicCode("The CosmosChatHistoryProvider uses JSON serialization which is incompatible with NativeAOT.")]
 public sealed class CosmosChatHistoryProvider : ChatHistoryProvider, IDisposable

dotnet/src/Microsoft.Agents.AI.DurableTask/CHANGELOG.md

@@ -4,6 +4,12 @@
 
 ### Changed
 
+- Filter empty `AIContent` from durable agent state responses ([#4670](https://github.com/microsoft/agent-framework/pull/4670))
+
+## v1.0.0-preview.260311.1
+
+### Changed
+
 - Added TTL configuration for durable agent entities ([#2679](https://github.com/microsoft/agent-framework/pull/2679))
 - Switch to new "Run" method name ([#2843](https://github.com/microsoft/agent-framework/pull/2843))
 - Removed AgentThreadMetadata and used AgentSessionId directly instead ([#3067](https://github.com/microsoft/agent-framework/pull/3067));
@@ -16,6 +22,8 @@
 - Marked all `RunAsync<T>` overloads as `new`, added missing ones, and added support for primitives and arrays ([#3803](https://github.com/microsoft/agent-framework/pull/3803))
 - Improve session cast error message quality and consistency ([#3973](https://github.com/microsoft/agent-framework/pull/3973))
 
+NOTE: Some of the above changes may have been part of earlier releases not mentioned in this file.
+
 ## v1.0.0-preview.251204.1
 
 - Added orchestration ID to durable agent entity state ([#2137](https://github.com/microsoft/agent-framework/pull/2137))

dotnet/src/Microsoft.Agents.AI.DurableTask/State/DurableAgentStateResponse.cs

@@ -1,6 +1,7 @@
 // Copyright (c) Microsoft. All rights reserved.
 
 using System.Text.Json.Serialization;
+using Microsoft.Extensions.AI;
 
 namespace Microsoft.Agents.AI.DurableTask.State;
 
@@ -28,7 +29,10 @@ internal sealed class DurableAgentStateResponse : DurableAgentStateEntry
         {
             CorrelationId = correlationId,
             CreatedAt = response.CreatedAt ?? response.Messages.Max(m => m.CreatedAt) ?? DateTimeOffset.UtcNow,
-            Messages = response.Messages.Select(DurableAgentStateMessage.FromChatMessage).ToList(),
+            Messages = response.Messages
+                .Where(HasSerializableContent)
+                .Select(DurableAgentStateMessage.FromChatMessage)
+                .ToList(),
             Usage = DurableAgentStateUsage.FromUsage(response.Usage)
         };
     }
@@ -46,4 +50,18 @@ internal sealed class DurableAgentStateResponse : DurableAgentStateEntry
             Usage = this.Usage?.ToUsageDetails(),
         };
     }
+
+    // Checks whether a ChatMessage has any content that will produce meaningful serialized data.
+    // Known derived AIContent types (TextContent, FunctionCallContent, etc.) are always serializable.
+    // Base AIContent instances only carry RawRepresentation (which is [JsonIgnore]), Annotations, and
+    // AdditionalProperties. We keep the message if any base AIContent has annotations or additional
+    // properties set. NOTE: if AIContent gains new serializable properties in the future, this check
+    // should be updated accordingly.
+    private static bool HasSerializableContent(ChatMessage message)
+    {
+        return message.Contents.Any(c =>
+            c.GetType() != typeof(AIContent) ||
+            c.Annotations?.Count > 0 ||
+            c.AdditionalProperties?.Count > 0);
+    }
 }

dotnet/src/Microsoft.Agents.AI.FoundryMemory/Microsoft.Agents.AI.FoundryMemory.csproj

@@ -13,10 +13,6 @@
   </PropertyGroup>
 
   <Import Project="$(RepoRoot)/dotnet/nuget/nuget-package.props" />
-  <PropertyGroup>
-    <!-- Disable packing until we are ready to release this as a nuget -->
-    <IsPackable>false</IsPackable>
-  </PropertyGroup>
 
   <ItemGroup>
     <ProjectReference Include="..\Microsoft.Agents.AI.Abstractions\Microsoft.Agents.AI.Abstractions.csproj" />

dotnet/src/Microsoft.Agents.AI.GitHub.Copilot/GitHubCopilotAgent.cs

@@ -346,14 +346,14 @@ public sealed class GitHubCopilotAgent : AIAgent, IAsyncDisposable
         };
     }
 
-    private AgentResponseUpdate ConvertToAgentResponseUpdate(AssistantMessageEvent assistantMessage)
+    internal AgentResponseUpdate ConvertToAgentResponseUpdate(AssistantMessageEvent assistantMessage)
     {
-        TextContent textContent = new(assistantMessage.Data?.Content ?? string.Empty)
+        AIContent content = new()
         {
             RawRepresentation = assistantMessage
         };
 
-        return new AgentResponseUpdate(ChatRole.Assistant, [textContent])
+        return new AgentResponseUpdate(ChatRole.Assistant, [content])
         {
             AgentId = this.Id,
             ResponseId = assistantMessage.Data?.MessageId,

dotnet/src/Microsoft.Agents.AI.Hosting.A2A/Converters/A2AMetadataExtensions.cs

@@ -1,36 +0,0 @@
-// Copyright (c) Microsoft. All rights reserved.
-
-using System.Collections.Generic;
-using System.Text.Json;
-using Microsoft.Extensions.AI;
-
-namespace Microsoft.Agents.AI.Hosting.A2A.Converters;
-
-/// <summary>
-/// Extension methods for A2A metadata dictionary.
-/// </summary>
-internal static class A2AMetadataExtensions
-{
-    /// <summary>
-    /// Converts a dictionary of metadata to an <see cref="AdditionalPropertiesDictionary"/>.
-    /// </summary>
-    /// <remarks>
-    /// This method can be replaced by the one from A2A SDK once it is public.
-    /// </remarks>
-    /// <param name="metadata">The metadata dictionary to convert.</param>
-    /// <returns>The converted <see cref="AdditionalPropertiesDictionary"/>, or null if the input is null or empty.</returns>
-    internal static AdditionalPropertiesDictionary? ToAdditionalProperties(this Dictionary<string, JsonElement>? metadata)
-    {
-        if (metadata is not { Count: > 0 })
-        {
-            return null;
-        }
-
-        var additionalProperties = new AdditionalPropertiesDictionary();
-        foreach (var kvp in metadata)
-        {
-            additionalProperties[kvp.Key] = kvp.Value;
-        }
-        return additionalProperties;
-    }
-}