Merge branch 'main' into dev/dotnet_workflow/fix_multimodel_sample

2026-06-16 21:04:09 +08:00 · 2026-04-03 13:11:32 -04:00 · 2026-04-03 12:23:36 -04:00 · 2026-04-03 11:19:28 -04:00 · 2026-04-03 08:27:30 -04:00
879 changed files with 9161 additions and 57526 deletions
@@ -21,7 +21,6 @@ ignorePatterns:
  - pattern: "http://host.docker.internal"
  - pattern: "https://openai.github.io/openai-agents-js/openai/agents/classes/"
  - pattern: "https:\/\/dotnet.microsoft.com\/download"
-  - pattern: "https://github.com/Rel1cx/eslint-react"
 # excludedDirs:
  # Folders which include links to localhost, since it's not ignored with regular expressions
 baseUrl: https://github.com/microsoft/agent-framework/
@@ -1,165 +0,0 @@
-name: DevFlow PR Review
-
-on:
-  pull_request_target:
-    types:
-      - opened
-      - reopened
-      - ready_for_review
-  workflow_dispatch:
-    inputs:
-      pr_number:
-        description: Pull request number to review
-        required: true
-        type: string
-
-permissions:
-  contents: read
-  issues: write
-  pull-requests: write
-
-concurrency:
-  group: devflow-pr-review-${{ github.repository }}-${{ github.event.pull_request.number || inputs.pr_number || github.run_id }}
-  cancel-in-progress: true
-
-env:
-  DEVFLOW_REPOSITORY: ${{ vars.DF_REPO }}
-  DEVFLOW_REF: main
-  TARGET_REPO_PATH: ${{ github.workspace }}/target-repo
-  DEVFLOW_PATH: ${{ github.workspace }}/devflow
-
-jobs:
-  team_check:
-    runs-on: ubuntu-latest
-    outputs:
-      is_team_member: ${{ steps.check.outputs.is_team_member }}
-      pr_number: ${{ steps.pr.outputs.pr_number }}
-      pr_url: ${{ steps.pr.outputs.pr_url }}
-      repo: ${{ steps.pr.outputs.repo }}
-    steps:
-      - name: Resolve PR metadata
-        id: pr
-        shell: bash
-        env:
-          PR_HTML_URL: ${{ github.event.pull_request.html_url }}
-          PR_NUMBER_EVENT: ${{ github.event.pull_request.number }}
-          PR_NUMBER_INPUT: ${{ inputs.pr_number }}
-        run: |
-          set -euo pipefail
-
-          if [[ "${GITHUB_EVENT_NAME}" == "pull_request_target" ]]; then
-            pr_number="${PR_NUMBER_EVENT}"
-            pr_url="${PR_HTML_URL}"
-          else
-            pr_number="${PR_NUMBER_INPUT}"
-            pr_url="https://github.com/${GITHUB_REPOSITORY}/pull/${pr_number}"
-          fi
-
-          if [[ ! "$pr_number" =~ ^[1-9][0-9]*$ ]]; then
-            echo "Could not determine PR number; for workflow_dispatch runs, the 'pr_number' input is required when not running on pull_request_target." >&2
-            exit 1
-          fi
-
-          echo "pr_url=${pr_url}" >> "$GITHUB_OUTPUT"
-          echo "pr_number=${pr_number}" >> "$GITHUB_OUTPUT"
-          echo "repo=${GITHUB_REPOSITORY}" >> "$GITHUB_OUTPUT"
-
-      - name: Check PR author team membership
-        id: check
-        uses: actions/github-script@v8
-        env:
-          TEAM_NAME: ${{ secrets.DEVELOPER_TEAM }}
-          PR_NUMBER: ${{ steps.pr.outputs.pr_number }}
-        with:
-          github-token: ${{ secrets.GH_ACTIONS_PR_WRITE }}
-          script: |
-            let author = context.payload.pull_request?.user?.login;
-            if (!author) {
-              const { data: pr } = await github.rest.pulls.get({
-                owner: context.repo.owner,
-                repo: context.repo.repo,
-                pull_number: Number(process.env.PR_NUMBER),
-              });
-              author = pr.user.login;
-            }
-
-            let isTeamMember = false;
-            try {
-              const teamMembership = await github.rest.teams.getMembershipForUserInOrg({
-                org: context.repo.owner,
-                team_slug: process.env.TEAM_NAME,
-                username: author,
-              });
-              isTeamMember = teamMembership.data.state === 'active';
-            } catch (error) {
-              console.log(`Team membership lookup failed for ${author}: ${error.message}`);
-              isTeamMember = false;
-            }
-
-            core.setOutput('is_team_member', isTeamMember ? 'true' : 'false');
-            if (isTeamMember) {
-              core.info(`Author ${author} is a team member; proceeding with review.`);
-            } else {
-              core.info(`Author ${author} is not a member of ${process.env.TEAM_NAME}; skipping review.`);
-            }
-
-  review:
-    runs-on: ubuntu-latest
-    needs: team_check
-    if: ${{ needs.team_check.outputs.is_team_member == 'true' }}
-    timeout-minutes: 60
-    # Advisory check: failures here should not block the PR. The reviewer
-    # posts comments as a best-effort signal; if the pipeline breaks, the
-    # PR author should still be able to merge without a red required check.
-    continue-on-error: true
-
-    steps:
-      # Safe checkout: base repo only, not the untrusted PR head.
-      - name: Checkout target repo base
-        uses: actions/checkout@v6
-        with:
-          ref: ${{ github.event_name == 'pull_request_target' && github.event.pull_request.base.sha || github.sha }}
-          fetch-depth: 0
-          persist-credentials: false
-          path: target-repo
-
-      # Private DevFlow checkout: the PAT/token grants access to this repo's code.
-      - name: Checkout DevFlow
-        uses: actions/checkout@v6
-        with:
-          repository: ${{ env.DEVFLOW_REPOSITORY }}
-          ref: ${{ env.DEVFLOW_REF }}
-          token: ${{ secrets.DEVFLOW_TOKEN }}
-          fetch-depth: 1
-          persist-credentials: false
-          path: devflow
-
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: "3.13"
-
-      - name: Set up uv
-        uses: astral-sh/setup-uv@v7
-        with:
-          version: "0.11.x"
-          enable-cache: true
-
-      - name: Install DevFlow dependencies
-        working-directory: ${{ env.DEVFLOW_PATH }}
-        run: uv sync --frozen
-
-      - name: Run PR review
-        id: review
-        working-directory: ${{ env.DEVFLOW_PATH }}
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-          GH_COPILOT_TOKEN: ${{ secrets.GH_COPILOT_TOKEN }}
-          SK_REPO_PATH: ${{ env.TARGET_REPO_PATH }}
-          AGENT_REPO_PATH: ${{ env.TARGET_REPO_PATH }}
-          PR_URL: ${{ needs.team_check.outputs.pr_url }}
-        run: |
-          uv run python scripts/trigger_pr_review.py \
-            --pr-url "$PR_URL" \
-            --github-username "$GITHUB_ACTOR" \
-            --no-require-comment-selection
@@ -48,8 +48,7 @@ jobs:
            .
            .github
            dotnet
-            python
-            declarative-agents
+            workflow-samples

      - name: Setup dotnet
        uses: actions/setup-dotnet@v5.2.0
@@ -64,20 +63,6 @@ jobs:
          tenant-id: ${{ secrets.AZURE_TENANT_ID }}
          subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}

-      - name: Generate filtered solution
-        shell: pwsh
-        run: |
-          ./dotnet/eng/scripts/New-FilteredSolution.ps1 `
-            -Solution dotnet/agent-framework-dotnet.slnx `
-            -TargetFramework net10.0 `
-            -Configuration Debug `
-            -OutputPath dotnet/filtered.slnx `
-            -Verbose
-
-      - name: Build solution
-        shell: bash
-        run: dotnet build dotnet/filtered.slnx -f net10.0 --warnaserror
-
      - name: Run verify-samples
        id: verify
        working-directory: dotnet
@@ -87,14 +87,6 @@ jobs:
          -n logical --dist worksteal
          --timeout=120 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
-          --junitxml=pytest.xml
-      - name: Upload test results
-        if: always()
-        uses: actions/upload-artifact@v7
-        with:
-          name: test-results-openai
-          path: ./python/pytest.xml
-          if-no-files-found: ignore

  # Azure OpenAI integration tests
  python-tests-azure-openai:
@@ -138,16 +130,8 @@ jobs:
          -n logical --dist worksteal
          --timeout=120 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
-          --junitxml=pytest.xml
-      - name: Upload test results
-        if: always()
-        uses: actions/upload-artifact@v7
-        with:
-          name: test-results-azure-openai
-          path: ./python/pytest.xml
-          if-no-files-found: ignore

-  # Misc integration tests (Anthropic, Hyperlight, Ollama, MCP)
+  # Misc integration tests (Anthropic, Ollama, MCP)
  python-tests-misc-integration:
    name: Python Integration Tests - Misc
    runs-on: ubuntu-latest
@@ -178,25 +162,16 @@ jobs:
          fallback_url: ${{ env.LOCAL_MCP_URL }}
      - name: Prefer local MCP URL when available
        run: echo "LOCAL_MCP_URL=${{ steps.local-mcp.outputs.effective_url }}" >> "$GITHUB_ENV"
-      - name: Test with pytest (Anthropic, Hyperlight, Ollama, MCP integration)
+      - name: Test with pytest (Anthropic, Ollama, MCP integration)
        run: >
          uv run pytest --import-mode=importlib
          packages/anthropic/tests
-          packages/hyperlight/tests
          packages/ollama/tests
          packages/core/tests/core/test_mcp.py
          -m integration
          -n logical --dist worksteal
          --timeout=120 --session-timeout=900 --timeout_method thread
-          --retries 2 --retry-delay 30
-          --junitxml=pytest.xml
-      - name: Upload test results
-        if: always()
-        uses: actions/upload-artifact@v7
-        with:
-          name: test-results-misc
-          path: ./python/pytest.xml
-          if-no-files-found: ignore
+          --retries 2 --retry-delay 5
      - name: Stop local MCP server
        if: always()
        shell: bash
@@ -273,14 +248,6 @@ jobs:
          -x
          --timeout=360 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
-          --junitxml=pytest.xml
-      - name: Upload test results
-        if: always()
-        uses: actions/upload-artifact@v7
-        with:
-          name: test-results-functions
-          path: ./python/pytest.xml
-          if-no-files-found: ignore

  # Foundry integration tests
  python-tests-foundry:
@@ -327,14 +294,6 @@ jobs:
          -n logical --dist worksteal
          --timeout=120 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
-          --junitxml=pytest.xml
-      - name: Upload test results
-        if: always()
-        uses: actions/upload-artifact@v7
-        with:
-          name: test-results-foundry
-          path: ./python/pytest.xml
-          if-no-files-found: ignore

  # Azure Cosmos integration tests
  python-tests-cosmos:
@@ -379,80 +338,7 @@ jobs:
          echo "Cosmos DB emulator did not become ready in time." >&2
          exit 1
      - name: Test with pytest (Cosmos integration)
-        run: uv run --directory packages/azure-cosmos poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5 --junitxml=${{ github.workspace }}/python/pytest.xml
-      - name: Upload test results
-        if: always()
-        uses: actions/upload-artifact@v7
-        with:
-          name: test-results-cosmos
-          path: ./python/pytest.xml
-          if-no-files-found: ignore
-
-  # Flaky test trend report (aggregates per-job JUnit XML results)
-  python-flaky-test-report:
-    name: Flaky Test Report
-    if: >
-      always() &&
-      (contains(join(needs.*.result, ','), 'success') ||
-       contains(join(needs.*.result, ','), 'failure'))
-    needs:
-      [
-        python-tests-openai,
-        python-tests-azure-openai,
-        python-tests-misc-integration,
-        python-tests-functions,
-        python-tests-foundry,
-        python-tests-cosmos,
-      ]
-    runs-on: ubuntu-latest
-    defaults:
-      run:
-        working-directory: python
-    steps:
-      - uses: actions/checkout@v6
-        with:
-          ref: ${{ inputs.checkout-ref }}
-          persist-credentials: false
-      - name: Set up python and install the project
-        uses: ./.github/actions/python-setup
-        with:
-          python-version: ${{ env.UV_PYTHON }}
-          os: ${{ runner.os }}
-      - name: Download all test results from current run
-        uses: actions/download-artifact@v4
-        with:
-          pattern: test-results-*
-          path: test-results/
-      - name: Restore flaky report history cache
-        uses: actions/cache/restore@v4
-        with:
-          path: python/flaky-report-history.json
-          key: flaky-report-history-integration-${{ github.run_id }}
-          restore-keys: |
-            flaky-report-history-integration-
-      - name: Generate trend report
-        run: >
-          uv run python scripts/flaky_report/aggregate.py
-          ../test-results/
-          flaky-report-history.json
-          flaky-test-report.md
-      - name: Post to Job Summary
-        if: always()
-        run: cat flaky-test-report.md >> $GITHUB_STEP_SUMMARY
-      - name: Save flaky report history cache
-        if: always()
-        uses: actions/cache/save@v4
-        with:
-          path: python/flaky-report-history.json
-          key: flaky-report-history-integration-${{ github.run_id }}
-      - name: Upload unified trend report
-        if: always()
-        uses: actions/upload-artifact@v7
-        with:
-          name: flaky-test-report
-          path: |
-            python/flaky-test-report.md
-            python/flaky-report-history.json
+        run: uv run --directory packages/azure-cosmos poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5

  python-integration-tests-check:
    if: always()
@@ -65,7 +65,6 @@ jobs:
              - 'python/samples/**/providers/azure/**'
            misc:
              - 'python/packages/anthropic/**'
-              - 'python/packages/hyperlight/**'
              - 'python/packages/ollama/**'
              - 'python/packages/core/agent_framework/_mcp.py'
              - 'python/packages/core/tests/core/test_mcp.py'
@@ -116,13 +115,12 @@ jobs:
          -m "not integration"
          --timeout=120 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
-          --junitxml=pytest.xml
        working-directory: ./python
      - name: Surface failing tests
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/pytest.xml
+          path: ./python/**.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
@@ -165,7 +163,6 @@ jobs:
          -n logical --dist worksteal
          --timeout=120 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
-          --junitxml=pytest.xml
        working-directory: ./python
      - name: Test OpenAI samples
        timeout-minutes: 10
@@ -176,18 +173,11 @@ jobs:
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/pytest.xml
+          path: ./python/**.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
          title: OpenAI integration test results
-      - name: Upload test results
-        if: always()
-        uses: actions/upload-artifact@v7
-        with:
-          name: test-results-openai
-          path: ./python/pytest.xml
-          if-no-files-found: ignore

  # Azure OpenAI integration tests
  python-tests-azure-openai:
@@ -235,7 +225,6 @@ jobs:
          -n logical --dist worksteal
          --timeout=120 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
-          --junitxml=pytest.xml
        working-directory: ./python
      - name: Test Azure samples
        timeout-minutes: 10
@@ -246,18 +235,11 @@ jobs:
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/pytest.xml
+          path: ./python/**.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
          title: Azure OpenAI integration test results
-      - name: Upload test results
-        if: always()
-        uses: actions/upload-artifact@v7
-        with:
-          name: test-results-azure-openai
-          path: ./python/pytest.xml
-          if-no-files-found: ignore

  # Misc integration tests (Anthropic, Ollama, MCP)
  python-tests-misc-integration:
@@ -293,18 +275,16 @@ jobs:
          fallback_url: ${{ env.LOCAL_MCP_URL }}
      - name: Prefer local MCP URL when available
        run: echo "LOCAL_MCP_URL=${{ steps.local-mcp.outputs.effective_url }}" >> "$GITHUB_ENV"
-      - name: Test with pytest (Anthropic, Hyperlight, Ollama, MCP integration)
+      - name: Test with pytest (Anthropic, Ollama, MCP integration)
        run: >
          uv run pytest --import-mode=importlib
          packages/anthropic/tests
-          packages/hyperlight/tests
          packages/ollama/tests
          packages/core/tests/core/test_mcp.py
          -m integration
          -n logical --dist worksteal
          --timeout=120 --session-timeout=900 --timeout_method thread
-          --retries 2 --retry-delay 30
-          --junitxml=pytest.xml
+          --retries 2 --retry-delay 5
        working-directory: ./python
      - name: Stop local MCP server
        if: always()
@@ -330,18 +310,11 @@ jobs:
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/pytest.xml
+          path: ./python/**.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
          title: Misc integration test results
-      - name: Upload test results
-        if: always()
-        uses: actions/upload-artifact@v7
-        with:
-          name: test-results-misc
-          path: ./python/pytest.xml
-          if-no-files-found: ignore

  # Azure Functions + Durable Task integration tests
  python-tests-functions:
@@ -402,24 +375,16 @@ jobs:
          -x
          --timeout=360 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
-          --junitxml=pytest.xml
        working-directory: ./python
      - name: Surface failing tests
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/pytest.xml
+          path: ./python/**.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
          title: Functions integration test results
-      - name: Upload test results
-        if: always()
-        uses: actions/upload-artifact@v7
-        with:
-          name: test-results-functions
-          path: ./python/pytest.xml
-          if-no-files-found: ignore

  python-tests-foundry:
    name: Python Integration Tests - Foundry
@@ -437,10 +402,6 @@ jobs:
      FOUNDRY_MODEL: ${{ vars.FOUNDRY_MODEL }}
      FOUNDRY_AGENT_NAME: ${{ vars.FOUNDRY_AGENT_NAME }}
      FOUNDRY_AGENT_VERSION: ${{ vars.FOUNDRY_AGENT_VERSION }}
-      FOUNDRY_MODELS_ENDPOINT: ${{ vars.FOUNDRY_MODELS_ENDPOINT || '' }}
-      FOUNDRY_MODELS_API_KEY: ${{ secrets.FOUNDRY_MODELS_API_KEY || '' }}
-      FOUNDRY_EMBEDDING_MODEL: ${{ vars.FOUNDRY_EMBEDDING_MODEL || '' }}
-      FOUNDRY_IMAGE_EMBEDDING_MODEL: ${{ vars.FOUNDRY_IMAGE_EMBEDDING_MODEL || '' }}
      LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
    defaults:
      run:
@@ -469,24 +430,16 @@ jobs:
          -n logical --dist worksteal
          --timeout=120 --session-timeout=900 --timeout_method thread
          --retries 2 --retry-delay 5
-          --junitxml=pytest.xml
        working-directory: ./python
      - name: Surface failing tests
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/pytest.xml
+          path: ./python/**.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
          title: Test results
-      - name: Upload test results
-        if: always()
-        uses: actions/upload-artifact@v7
-        with:
-          name: test-results-foundry
-          path: ./python/pytest.xml
-          if-no-files-found: ignore

  # TODO: Add python-tests-lab

@@ -536,87 +489,17 @@ jobs:
          echo "Cosmos DB emulator did not become ready in time." >&2
          exit 1
      - name: Test with pytest (Cosmos integration)
-        run: uv run --directory packages/azure-cosmos poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5 --junitxml=${{ github.workspace }}/python/pytest.xml
+        run: uv run --directory packages/azure-cosmos poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5
        working-directory: ./python
      - name: Surface failing tests
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/pytest.xml
+          path: ./python/**.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
          title: Cosmos integration test results
-      - name: Upload test results
-        if: always()
-        uses: actions/upload-artifact@v7
-        with:
-          name: test-results-cosmos
-          path: ./python/pytest.xml
-          if-no-files-found: ignore
-
-  # Flaky test trend report (aggregates per-job JUnit XML results)
-  python-flaky-test-report:
-    name: Flaky Test Report
-    if: >
-      always() &&
-      (contains(join(needs.*.result, ','), 'success') ||
-       contains(join(needs.*.result, ','), 'failure'))
-    needs:
-      [
-        python-tests-openai,
-        python-tests-azure-openai,
-        python-tests-misc-integration,
-        python-tests-functions,
-        python-tests-foundry,
-        python-tests-cosmos,
-      ]
-    runs-on: ubuntu-latest
-    defaults:
-      run:
-        working-directory: python
-    steps:
-      - uses: actions/checkout@v6
-      - name: Set up python and install the project
-        uses: ./.github/actions/python-setup
-        with:
-          python-version: ${{ env.UV_PYTHON }}
-          os: ${{ runner.os }}
-      - name: Download all test results from current run
-        uses: actions/download-artifact@v4
-        with:
-          pattern: test-results-*
-          path: test-results/
-      - name: Restore flaky report history cache
-        uses: actions/cache/restore@v4
-        with:
-          path: python/flaky-report-history.json
-          key: flaky-report-history-merge-${{ github.run_id }}
-          restore-keys: |
-            flaky-report-history-merge-
-      - name: Generate trend report
-        run: >
-          uv run python scripts/flaky_report/aggregate.py
-          ../test-results/
-          flaky-report-history.json
-          flaky-test-report.md
-      - name: Post to Job Summary
-        if: always()
-        run: cat flaky-test-report.md >> $GITHUB_STEP_SUMMARY
-      - name: Save flaky report history cache
-        if: always()
-        uses: actions/cache/save@v4
-        with:
-          path: python/flaky-report-history.json
-          key: flaky-report-history-merge-${{ github.run_id }}
-      - name: Upload unified trend report
-        if: always()
-        uses: actions/upload-artifact@v7
-        with:
-          name: flaky-test-report
-          path: |
-            python/flaky-test-report.md
-            python/flaky-report-history.json

  python-integration-tests-check:
    if: always()
@@ -40,7 +40,7 @@ jobs:
          UV_CACHE_DIR: /tmp/.uv-cache
      # Unit tests
      - name: Run all tests
-        run: uv run poe test -A --junitxml=pytest.xml
+        run: uv run poe test -A
        working-directory: ./python

      # Surface failing tests
@@ -48,7 +48,7 @@ jobs:
        if: always()
        uses: pmeier/pytest-results-action@v0.7.2
        with:
-          path: ./python/pytest.xml
+          path: ./python/**.xml
          summary: true
          display-options: fEX
          fail-on-empty: false
@@ -47,8 +47,6 @@ htmlcov/
 .cache
 nosetests.xml
 coverage.xml
-pytest.xml
-python-coverage.xml
 *.cover
 *.py,cover
 .hypothesis/
@@ -136,10 +134,6 @@ celerybeat.pid
 .venv
 env/
 venv/
-
-# Foundry agent CLI (contains secrets, auto-generated)
-.foundry-agent.json
-.foundry-agent-build.log
 ENV/
 env.bak/
 venv.bak/
@@ -207,8 +201,6 @@ temp*/

 # AI
 .claude/
-.omc/
-.omx/
 WARP.md
 **/memory-bank/
 **/projectBrief.md
@@ -241,4 +233,3 @@ python/dotnet-ref

 # Generated filtered solution files (created by eng/scripts/New-FilteredSolution.ps1)
 dotnet/filtered-*.slnx
-**/*.lscache
@@ -120,38 +120,38 @@ if __name__ == "__main__":
 ```

 ### Basic Agent - .NET
-Create a simple Agent, using Microsoft Foundry with token-based auth, that writes a haiku about the Microsoft Agent Framework
-
-```c#
-// dotnet add package Microsoft.Agents.AI.Foundry
-// Use `az login` to authenticate with Azure CLI
-using Azure.AI.Projects;
-using Azure.Identity;
-using System;
-using Azure.AI.Projects;
-using Azure.Identity;
-
-var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
-
-var agent = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
-    .AsAIAgent(model: deploymentName, name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
-
-Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
-```

 Create a simple Agent, using OpenAI Responses, that writes a haiku about the Microsoft Agent Framework

 ```c#
-// dotnet add package Microsoft.Agents.AI.OpenAI
-using System;
+// dotnet add package Microsoft.Agents.AI.OpenAI --prerelease
+using Microsoft.Agents.AI;
 using OpenAI;
 using OpenAI.Responses;

 // Replace the <apikey> with your OpenAI API key.
 var agent = new OpenAIClient("<apikey>")
-    .GetResponsesClient()
-    .AsAIAgent(model: "gpt-5.4-mini", name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
+    .GetResponsesClient("gpt-4o-mini")
+    .AsAIAgent(name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");
+
+Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
+```
+
+Create a simple Agent, using Microsoft Foundry with token-based auth, that writes a haiku about the Microsoft Agent Framework
+
+```c#
+// dotnet add package Microsoft.Agents.AI.AzureAI --prerelease
+// dotnet add package Azure.Identity
+// Use `az login` to authenticate with Azure CLI
+using Azure.AI.Projects;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+var agent = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
+    .AsAIAgent(model: deploymentName, name: "HaikuBot", instructions: "You are an upbeat assistant that writes beautifully.");

 Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Framework."));
 ```
@@ -207,9 +207,4 @@ The samples typically read configuration from environment variables. Common requ

 ## Important Notes

-> [!IMPORTANT]
-> If you use Microsoft Agent Framework to build applications that operate with any third-party servers, agents, code, or non-Azure Direct models (“Third-Party Systems”), you do so at your own risk. Third-Party Systems are Non-Microsoft Products under the Microsoft Product Terms and are governed by their own third-party license terms. You are responsible for any usage and associated costs.
->
->We recommend reviewing all data being shared with and received from Third-Party Systems and being cognizant of third-party practices for handling, sharing, retention and location of data. It is your responsibility to manage whether your data will flow outside of your organization’s Azure compliance and geographic boundaries and any related implications, and that appropriate permissions, boundaries and approvals are provisioned.
-> 
->You are responsible for carefully reviewing and testing applications you build using Microsoft Agent Framework in the context of your specific use cases, and making all appropriate decisions and customizations. This includes implementing your own responsible AI mitigations such as metaprompt, content filters, or other safety systems, and ensuring your applications meet appropriate quality, reliability, security, and trustworthiness standards. See also: [Transparency FAQ](./TRANSPARENCY_FAQ.md)
+If you use the Microsoft Agent Framework to build applications that operate with third-party servers or agents, you do so at your own risk. We recommend reviewing all data being shared with third-party servers or agents and being cognizant of third-party practices for retention and location of data. It is your responsibility to manage whether your data will flow outside of your organization's Azure compliance and geographic boundaries and any related implications.
@@ -1,233 +0,0 @@
---
-status: proposed
-contact: eavanvalkenburg
-date: 2026-04-07
-deciders: TBD
-consulted:
-informed:
---
-
-# CodeAct integration through backend-specific context providers and an `execute_code` tool
-
-## Introduction
-
-**CodeAct** is a pattern in which the model writes executable code — rather than emitting a fixed function-call JSON schema — to plan, transform data, and orchestrate tool calls inside a single sandbox invocation. Instead of requiring a separate model round-trip for every tool call, conditional branch, or data transformation, the model produces a short program that runs in a controlled runtime, calls host-provided tools through a `call_tool(...)` bridge, and returns structured results. This reduces latency, lowers token cost, and lets the model express richer multi-step logic that is difficult to capture in a flat tool-call sequence.
-
-Throughout this ADR, **CodeAct** is the primary term. **Code mode** and **programmatic tool calling** refer to the same capability.
-
-## Context and Problem Statement
-
-We need an architecture design that supports CodeAct in both Python and .NET. This is a necessary capability for the current generation of long-running agents, which need to plan, iterate, transform tool outputs, and execute bounded code inside a controlled runtime — for example, filtering a large result set, computing derived values, or chaining several tool calls with conditional logic — instead of requiring a separate model round-trip for each of those steps. The design should preserve the same behavioral contract across SDKs, but it does not need to use the same internal extension point in each runtime. We also want to standardize on Hyperlight as the initial backend, using the existing Python package and an anticipated .NET binding package once it is available.
-
-Throughout this ADR, **CodeAct** is the primary term. **Code mode** and **programmatic tool calling** refer to the same capability. This ADR uses **CodeAct** consistently.
-
-Model-generated code is treated as untrusted relative to the host process. This ADR assumes the selected backend provides the primary isolation boundary, while the framework is responsible for configuring approvals and capabilities, integrating telemetry, and translating outputs and failures into framework-native shapes. If a backend cannot provide isolation appropriate for its trust model, it is not a suitable CodeAct backend.
-
-The core design question is: **where should CodeAct integrate into the agent pipeline so that both SDKs can offer the same functionality without invasive changes to their core function-calling loops?**
-
-## Decision Drivers
-
- CodeAct must shape the model-facing surface before model invocation, not only after the model has already chosen tools.
- The design should let users control which tools are available through CodeAct and which remain regular tools only.
- The design must preserve existing session, approval, telemetry, and tool invocation behavior as much as possible.
- The design should define the minimum cross-SDK telemetry and failure semantics for `execute_code`, so Python and .NET do not diverge on basic observability or error handling.
- The design must fit naturally into the extension points that already exist in each SDK.
- The design must be safe for concurrent runs and must not rely on mutating shared agent configuration during invocation.
- The chosen structure should allow multiple backend-specific providers to fit under the same conceptual design over time, even though Hyperlight is the initial target.
- The abstraction should not assume that every backend is a VM-style sandbox; alternative execution models such as Pydantic's Monty should also fit.
- The design should allow `execute_code` to be reused both as a tool-enabled CodeAct runtime and as a standard code interpreter tool implementation.
- The design should remain open to alternative language/runtime modes, such as JavaScript on Hyperlight, rather than baking the abstraction to Python only.
- The design should provide a portable way to configure sandbox capabilities such as file access and network access, including allow-listed outbound domains.
- Using CodeAct should be optional, and installing its runtime or backend dependencies should also be optional.
- Backend-specific dependencies should be isolated behind a small adapter so SDK code is not tightly coupled to an unstable package surface.
-
-## Considered Options
-
- **Option 1**: Standardize on context provider-based CodeAct with a shared cross-SDK contract and backend-specific public types
- **Option 2**: Implement CodeAct as a dedicated chat-client decorator/wrapper
- **Option 3**: Integrate CodeAct directly into the function invocation layer/FunctionInvokingChatClient
-
-## Pros and Cons of the Options
-
-### Option 1: Standardize on context provider-based CodeAct with a shared cross-SDK contract and backend-specific public types
-
-This option uses `ContextProvider` in Python and `AIContextProvider` in .NET, but standardizes the public concept and behavior.
-In this option, the CodeAct tool set is provider-owned: only tools explicitly configured on the concrete CodeAct provider instance are available inside CodeAct, and the provider exposes direct CRUD-style management for tools, file mounts, and outbound network allow-list configuration rather than requiring a separate runtime setup object.
-The agent's direct tool surface remains separate. If a tool should be available both through CodeAct and as a normal direct tool, it is configured in both places.
-
- Good, because both SDKs already have first-class provider concepts intended for per-invocation context shaping.
- Good, because providers operate before model invocation, which is where CodeAct must add instructions and reshape tools.
- Good, because this lets us preserve existing function invocation behavior rather than rewriting it.
- Good, because slightly different internals are acceptable while the public behavior remains aligned.
- Good, because convenience builder/decorator helpers can still be added later on top of the provider model without changing the core design.
- Good, because backend-specific runtime logic can stay inside concrete provider implementations or internal helpers instead of being forced into a lowest-common-denominator public abstraction.
- Good, because the same provider structure can support either an all-or-nothing tool surface or a mixed side-by-side tool surface.
- Good, because users can keep some tools direct-only while allowing other tools to be used from inside CodeAct.
- Good, because a provider-owned CodeAct tool registry avoids mutating or inferring the agent's direct tool surface and can work consistently in both SDKs.
- Good, because the same conceptual design can remain open to `HyperlightCodeActProvider`, a future `MontyCodeActProvider`, and other backend-specific providers over time.
- Good, because `execute_code` can evolve into multiple backend-specific runtime modes rather than being hard-wired to one Python-plus-tools mode.
- Bad, because the provider indirection adds per-run overhead — snapshotting the tool registry, dispatching lifecycle hooks, and building instructions — that a deeper integration point could skip. In practice this overhead is negligible relative to model inference latency and sandbox startup cost.
-
-### Option 2: Implement CodeAct as a dedicated chat-client decorator/wrapper
-
-This option would introduce a CodeAct-specific chat-client decorator that injects instructions and tools directly into the chat request pipeline.
-
- Good, because this is a natural fit for .NET's `DelegatingChatClient` pipeline.
- Good, because it can also support advanced custom chat-client stacks.
- Good, because backend-specific runtime selection could be hidden inside the decorator implementation.
- Good, because the decorator could also encapsulate mode-specific instruction shaping for tool-enabled versus standalone interpreter behavior.
- Good, because the decorator can decide per request whether the tool surface is exclusive or mixed.
- Bad, because Python can support this by building a custom layering stack on top of a `Raw...Client` and swapping in a different `FunctionInvocationLayer`, but that composition path is more manual than the .NET `DelegatingChatClient` pipeline.
- Bad, because it duplicates responsibilities already handled by provider abstractions.
- Bad, because it makes CodeAct look more transport-specific than it really is.
- Bad, because swappable backends and reusable interpreter or language modes become coupled to chat-client composition rather than modeled as first-class CodeAct concepts.
-
-### Option 3: Integrate CodeAct directly into the function invocation layer/FunctionInvokingChatClient
-
-This option would push CodeAct into Python's `FunctionInvocationLayer` and .NET's `FunctionInvokingChatClient` or related middleware.
-
- Good, because it is close to tool execution and can observe concrete tool invocation behavior.
- Good, because function middleware may still be useful later for auxiliary auditing or policy around sandbox-originated tool calls.
- Bad, because this is the wrong layer for constructing the model-facing tool surface and prompt instructions.
- Bad, because it does not naturally control whether the model sees an exclusive CodeAct tool surface or a mixed side-by-side tool surface.
- Bad, because it would still require a second mechanism for hiding normal tools and advertising `execute_code`.
- Bad, because it is a weak fit for standalone interpreter modes where no tool-calling loop is needed.
- Bad, because backend selection and CodeAct mode behavior are orthogonal concerns that do not belong in the function invocation layer.
- Bad, because `.NET` would become more tightly coupled to `FunctionInvokingChatClient`, which sits below the agent framework abstraction and is not the natural cross-SDK design seam.
-
-## Approval Model Options
-
- **Option A**: Bundled approval for the `execute_code` invocation
- **Option B**: Pre-execution inspection of `call_tool(...)` references before approving `execute_code`
- **Option C**: Nested per-tool approvals during `execute_code`
-
-## Pros and Cons of the Approval Options
-
-### Option A: Bundled approval for the `execute_code` invocation
-
-This option grants approval once, before `execute_code` starts. Provider-owned tool calls made from inside that execution run under the same approval. The effective approval of `execute_code` is determined up front from the provider configuration rather than from inspecting which tools are actually called during execution.
-
- Good, because it is the simplest model to explain and implement consistently in both SDKs.
- Good, because it fits naturally with long-running CodeAct loops where repeated approval interruptions would be disruptive.
- Good, because it does not require static code analysis before execution begins.
- Good, because it keeps the first release focused on the provider integration rather than a more complex approval engine.
- Bad, because approval is coarse-grained and may cover more activity than the user expected.
- Bad, because it provides less visibility into which provider-owned tools or capabilities will be exercised during the run.
-
-### Option B: Pre-execution inspection of `call_tool(...)` references before approving `execute_code`
-
-This option inspects submitted code for statically discoverable `call_tool("tool_name", ...)` references before execution starts and uses that information to shape the approval request.
-
- Good, because it can show users more detail up front while still keeping approval at a single pre-execution moment.
- Good, because it matches the common case where tool names are spelled out directly in the generated code.
- Good, because it can coexist with bundled approval as a more informative variant of the same UX.
- Bad, because the analysis is inherently best-effort and cannot reliably predict dynamic behavior.
- Bad, because it requires duplicated parsing or inspection logic that does not replace runtime enforcement.
-
-### Option C: Nested per-tool approvals during `execute_code`
-
-This option requests approval when sandboxed code actually attempts to invoke a provider-owned tool that requires approval.
-
- Good, because it aligns approval with real behavior rather than predicted behavior.
- Good, because it gives precise visibility into which provider-owned tools are being used.
- Good, because it can allow some tool calls while rejecting others within the same execution.
- Bad, because it interrupts long-running CodeAct flows and can degrade the user experience significantly.
- Bad, because it requires more complex runtime plumbing and approval UX in both SDKs.
- Bad, because repeated approval pauses may make CodeAct less useful for the exact long-running scenarios that motivate this feature.
-
-## Decision Outcomes
-
-### Decision 1: Integration seam and public structure
-
-Chosen option: **Option 1: Standardize on provider-based CodeAct with a shared cross-SDK contract and backend-specific public types**, because it is the only option that maps cleanly to both SDKs, lets us reshape instructions and tools before model invocation, and avoids invasive changes to the existing function invocation loops while still allowing multiple backend-specific providers and multiple runtime modes to fit under the same structure later.
-
-### Decision 2: Initial approval model
-
-Chosen option: **Option A: Bundled approval for the `execute_code` invocation**, because it is the smallest approval model that fits both SDKs, works well for long-running CodeAct flows, and does not force us to standardize a more complex inspection or policy engine in the first release.
-
-This follows the spirit of the current Python tool approval flow, where `FunctionTool` uses `approval_mode="always_require" | "never_require"` and the auto-invocation loop escalates the whole batch when any called tool requires approval.
-
-### Design summary
-
-We standardize the **public concept** of CodeAct across SDKs while allowing each SDK to use the extension point that fits it best.
-
- Python uses a `ContextProvider`.
- .NET uses an `AIContextProvider`.
- The term **CodeAct context provider** is used throughout this ADR as a design concept, not as a required public base type. Public SDK APIs should prefer concrete backend-specific types such as `HyperlightCodeActProvider` rather than a public abstract `CodeActContextProvider` or a public `CodeActExecutor` parameter.
- CodeAct support should ship as an optional package in each SDK rather than as part of the core package, so users who do not need CodeAct do not take on its installation and dependency footprint. That optional package may still depend on a few small, backward-compatible hooks in the host SDK's core agent pipeline.
- There is no separate runtime setup object in the chosen design. Concrete providers manage their provider-owned CodeAct tool registry, file mounts, and outbound network allow-list configuration directly through CRUD-style methods on the provider itself.
- At a high level, CodeAct is exposed through backend-specific context providers that contribute an `execute_code` tool, own the CodeAct-specific tool registry, and carry backend capability configuration such as filesystem and network access.
- The initial approval model is bundled approval for `execute_code`, using the same `approval_mode="always_require" | "never_require"` vocabulary as regular tools.
- The CodeAct provider exposes a default `approval_mode` for `execute_code`. If the provider default is `always_require`, `execute_code` is always treated as `always_require` regardless of the provider-owned tool registry. If the provider default is `never_require`, the effective approval for `execute_code` is derived from the provider-owned CodeAct tool registry captured for the run.
- If every provider-owned CodeAct tool in that registry has `approval_mode="never_require"`, `execute_code` is treated as `never_require`. If any provider-owned CodeAct tool in that registry has `approval_mode="always_require"`, `execute_code` is treated as `always_require`, even if the generated code may not end up calling that tool.
- Approval is granted before `execute_code` starts, and provider-owned tool calls made from inside that execution run under the same approval.
- Direct-only agent tools do not affect the approval of `execute_code`; only the provider-owned CodeAct tool registry participates in that calculation.
- This approval model is intentionally conservative. If one sensitive provider-owned tool forces `execute_code` to require approval more often than desired, the mitigation is to keep that tool direct-only or split it into a different provider/tool surface rather than trying to infer per-run tool usage up front.
- Configuring filesystem and network capability state on the provider, including adding file mounts or outbound network allow-list entries, is itself the approval for those capabilities in the initial model.
- Each `execute_code` invocation must start from a clean execution state; in-memory variables and other ephemeral interpreter/runtime state must not persist across separate calls. When a provider exposes a workspace, mounted files, or a writable artifact/output area, those files are the supported persistence mechanism across calls and are treated as external state rather than interpreter state.
- Mutating the provider's tool registry or capability configuration while a run is in flight is allowed, but it only affects subsequent runs. Provider implementations must snapshot the effective state for each run and synchronize concurrent access so shared provider instances remain safe across concurrent runs.
- The minimum cross-SDK telemetry contract is that `execute_code` is traced as a normal tool invocation nested inside the surrounding agent run, and provider-owned tool calls made from inside CodeAct continue to emit ordinary tool-invocation telemetry. Backend-specific resource metrics are optional extensions, not a required new top-level cross-SDK event model.
- Timeout, out-of-memory, backend crash, and similar sandbox failures are all execution failures of `execute_code` and should surface as structured error results rather than backend-specific public DTOs. Partial textual or file outputs may be returned only when the backend can report them unambiguously; callers must not rely on partial-output recovery as a portable guarantee.
- The provider-based structure preserves room for future pre-execution inspection and nested per-tool approvals if later experience shows they are needed.
- Concrete backend-specific providers may still use small SDK-local helpers or adapters internally, but that split is an implementation detail rather than a public API requirement.
-
-Detailed language-specific implementation notes are specified in:
-
- [Python implementation](../features/code_act/python-implementation.md)
- [.NET implementation](../features/code_act/dotnet-implementation.md)
-
-### Minimal core hooks required by the optional package
-
-CodeAct remains optional at the package level, but the optional package depends on a small number of hooks that must live in the host SDK because the agent pipeline owns model invocation and per-run tool resolution.
-
- Python depends on the existing `ContextProvider` lifecycle, `SessionContext.extend_instructions(...)`, `SessionContext.extend_tools(...)`, per-run runtime tool access via `SessionContext.options["tools"]`, and the shared `ApprovalMode` vocabulary used by `FunctionTool`.
- .NET depends on the existing `AIContextProvider` seam, agent/runtime support for applying providers before model invocation, and the existing chat-client or function-invocation seams that concrete implementations use to contribute `execute_code`.
-
-These hooks are backward-compatible because they only expose or forward per-run state that core already owns. Behavior changes only when a concrete CodeAct provider opts in and uses them.
-
-### Concrete provider implementation contract
-
-The design does not require a public abstract `CodeActContextProvider` base class, but it does require a stable implementation contract for concrete providers.
-
- Concrete providers should expose a standard capability surface at construction time, with SDK-appropriate naming for:
-  - approval mode
-  - workspace root
-  - file mounts
-  - allowed outbound targets plus any per-target method or policy restrictions needed by the backend
- Separate public `filesystem_mode` / `network_mode` flags are not required by the cross-SDK contract. Filesystem access may be disabled implicitly until a workspace or file mounts are configured, and outbound network may be disabled implicitly until an allow-list or equivalent outbound policy entry is configured.
- Concrete providers should expose direct CRUD-style methods for managing the provider-owned CodeAct tool registry, file mounts, and outbound network allow-list configuration, rather than requiring callers to construct a separate runtime setup object.
- Concrete providers should implement their host SDK's provider lifecycle hooks to:
-  - build CodeAct instructions,
-  - add `execute_code`,
-  - snapshot the effective CodeAct tool registry and capability settings for the run,
-  - compute the effective approval requirement for `execute_code`,
-  - configure file access and network access for the backend,
-  - prepare or restore execution state,
-  - execute code,
-  - and translate backend output into framework-native content.
- Any internal abstract/helper surface shared by multiple concrete providers should standardize responsibilities for:
-  - instruction construction,
-  - file-access configuration,
-  - network-access configuration,
-  - environment preparation/restoration,
-  - code execution,
-  - and output-to-content conversion.
- Backend execution output should reuse existing framework-native content/message primitives rather than introducing backend-specific public result DTOs.
-
-## More Information
-
-### Related artifacts
-
- Python implementation: [`docs/features/code_act/python-implementation.md`](../features/code_act/python-implementation.md)
- .NET implementation: [`docs/features/code_act/dotnet-implementation.md`](../features/code_act/dotnet-implementation.md)
- Python provider/session APIs: [`python/packages/core/agent_framework/_sessions.py`](../../python/packages/core/agent_framework/_sessions.py)
- Python function invocation loop: [`python/packages/core/agent_framework/_tools.py`](../../python/packages/core/agent_framework/_tools.py)
- .NET context provider abstraction: [`dotnet/src/Microsoft.Agents.AI.Abstractions/AIContextProvider.cs`](../../dotnet/src/Microsoft.Agents.AI.Abstractions/AIContextProvider.cs)
- .NET agent integration for context providers: [`dotnet/src/Microsoft.Agents.AI/ChatClient/ChatClientAgent.cs`](../../dotnet/src/Microsoft.Agents.AI/ChatClient/ChatClientAgent.cs)
- Optional .NET chat-client provider decorator: [`dotnet/src/Microsoft.Agents.AI/AIContextProviderDecorators/AIContextProviderChatClient.cs`](../../dotnet/src/Microsoft.Agents.AI/AIContextProviderDecorators/AIContextProviderChatClient.cs)
- .NET function invocation middleware seam: [`dotnet/src/Microsoft.Agents.AI/FunctionInvocationDelegatingAgentBuilderExtensions.cs`](../../dotnet/src/Microsoft.Agents.AI/FunctionInvocationDelegatingAgentBuilderExtensions.cs)
-
-### Related decisions
-
- [0015-agent-run-context](0015-agent-run-context.md)
- [0016-python-context-middleware](0016-python-context-middleware.md)
@@ -1,454 +0,0 @@
---
-status: proposed
-contact: evmattso
-date: 2026-04-10
-deciders: evmattso
---
-
-# Foundry Toolbox Support in FoundryChatClient
-
-## What is the goal of this feature?
-
-Enable Agent Framework users to consume Foundry **toolboxes** — named, versioned bundles of tool definitions stored server-side in an Azure AI Foundry project — directly from `FoundryChatClient`, without dropping to the raw `azure-ai-projects` SDK.
-
-A user who has configured a toolbox in the Foundry portal (or via the raw SDK) should be able to load it into an agent with a single call:
-
-```python
-toolbox = await client.get_toolbox("research_tools")
-agent = Agent(client=client, instructions="...", tools=toolbox)
-```
-
-**Success metric:** an agent can consume a toolbox with no manual handling of version-resolution logic on the user's side.
-
-## What is the problem being solved?
-
-`azure-ai-projects==2.1.0a20260409002` ships a new `BetaToolboxesOperations` surface, reachable as `AIProjectClient.beta.toolboxes` on the raw SDK client (and therefore as `FoundryChatClient.project_client.beta.toolboxes` through our wrapper), that lets teams:
- Group related hosted tools (code interpreter, file search, MCP, web search, etc.) under a named toolbox
- Version toolboxes immutably, so agents can pin to a specific configuration for production stability
- Share toolboxes across multiple agents in a project
-
-However, consuming a toolbox from the framework today requires:
-1. Knowing the raw SDK accessor path (`client.project_client.beta.toolboxes`)
-2. Making two calls for the common case — `.get(name)` to find the default version, then `.get_version(name, version)` to actually retrieve tools
-3. Manually unpacking `toolbox.tools` before passing them to `Agent(tools=...)`
-
-None of this is hard, but it's the kind of boilerplate that should live in the client. Every other hosted tool in `FoundryChatClient` (code interpreter, file search, web search, image generation, MCP) already has a factory method (`get_code_interpreter_tool()`, etc.). Toolbox support should fit the same shape on the chat-client composition surface.
-
-## API Changes
-
-### One new method on the FoundryChatClient surface
-
-The public toolbox-consumption surface lands on:
-
- `RawFoundryChatClient` (inherited by `FoundryChatClient`) in `_chat_client.py`
-
-The implementation delegates to shared helper functions in `_tools.py` so there is a single source of truth for the SDK calls.
-
-**Scope note:** `FoundryAgent` is intentionally not part of this design. `FoundryAgent` is the runtime surface for invoking an already-configured server-side Foundry agent; if that agent should use a toolbox, the toolbox/tools should already be configured on the Foundry side (UI or `azure-ai-projects` authoring flow) before MAF connects to it.
-
-**Scope note:** Authoring a server-side agent whose definition references a toolbox (via `PromptAgentDefinition(tools=toolbox.tools, ...)` + `client.agents.create_version(...)`) is deliberately outside MAF scope. That is an `azure-ai-projects` / service-resource authoring concern, not a future MAF feature. Users who need it should use the raw Azure SDK directly.
-
-```python
-async def get_toolbox(
-    self,
-    name: str,
-    *,
-    version: str | None = None,
-) -> ToolboxVersionObject:
-    """Fetch a Foundry toolbox by name.
-
-    If ``version`` is ``None``, resolves the toolbox's current default version
-    (two requests). If ``version`` is specified, fetches that version directly
-    (single request).
-
-    :param name: The name of the toolbox.
-    :param version: Optional immutable version identifier to pin to.
-    :return: A ``ToolboxVersionObject``. Pass its ``tools`` attribute to
-        ``Agent(tools=toolbox.tools)``.
-    :raises azure.core.exceptions.ResourceNotFoundError: If the toolbox or
-        version does not exist.
-    """
-
-```
-
-### Return types: raw SDK models, no custom wrappers
-
-Methods return the `azure.ai.projects.models` types directly:
-
- `get_toolbox()` → `ToolboxVersionObject` (has `.name`, `.version`, `.tools`, `.id`, `.created_at`, `.description`, `.metadata`, `.policies`)
-
-No custom wrapper classes are defined. Returning the SDK types directly:
- Eliminates maintenance overhead of keeping a custom wrapper aligned with SDK changes
- Matches the existing convention — `get_code_interpreter_tool()` returns the raw `CodeInterpreterTool` SDK type
- Means any new fields the SDK adds to these types flow through automatically
-
-`Agent(..., tools=...)` will accept the fetched toolbox object directly by flattening to `toolbox.tools` internally.
-
-### Design decisions
-
-**Instance methods, not `@staticmethod` factories.** Existing `get_code_interpreter_tool()` / `get_mcp_tool()` / etc. are `@staticmethod` because they're pure factories with no network I/O. Toolbox fetching requires the project client, so these new methods must be instance methods. This is a deliberate departure from the existing-factory pattern, justified by the async-with-I/O nature of the operation.
-
-**Raw SDK type passthrough (no custom wrappers).** There is only one toolbox type in the Foundry SDK and maintaining a shadow wrapper would create alignment risk as the SDK evolves. The raw `ToolboxVersionObject` and `ToolboxObject` carry all the fields users need. Individual tools inside `toolbox.tools` are the same `azure.ai.projects.models.Tool` subclasses returned by other factory methods.
-
-**Two-request default-version path.** When `version=None`, implementation calls `.get(name)` to find `default_version`, then `.get_version(name, default_version)` for the tools. Caching the default-version mapping was considered and rejected — default versions can change server-side via `update(default_version=...)`, and a stale cache would silently give callers the wrong tools. Two requests at agent setup is acceptable.
-
-**No discovery/listing surface in MAF.** Discovery is intentionally left to the raw `azure-ai-projects` client. MAF does not currently expose project-resource listing surfaces for many other Foundry resources (deployments, vector stores, agents, etc.), so the toolbox design stays narrowly focused on explicit retrieval by name/version.
-
-**Shared helpers in `_tools.py`.** The SDK-call helper function (`fetch_toolbox`) lives in a shared module so the chat-client surface stays thin and the request logic remains centralized.
-
-**`tools=toolbox` convenience, not a new wrapper type.** Although `get_toolbox()` returns the raw `ToolboxVersionObject`, Agent Framework can still support `tools=toolbox` / `tools=[toolbox]` by flattening the toolbox's `.tools` internally. That matches existing SDK ergonomics where some higher-level objects can be placed directly in `tools=` and unpacked underneath, without introducing a public `FoundryToolbox` wrapper.
-
-**Errors pass through unchanged.** `ResourceNotFoundError`, `HttpResponseError`, etc. from the SDK propagate as-is. No framework-specific exception hierarchy.
-
-## E2E Code Samples
-
-### Primary sample
-
-New file: `samples/02-agents/providers/foundry/foundry_chat_client_with_toolbox.py`
-
-```python
-import asyncio
-
-from agent_framework import Agent
-from agent_framework.foundry import FoundryChatClient
-from azure.identity import AzureCliCredential
-
-
-async def main() -> None:
-    client = FoundryChatClient(credential=AzureCliCredential())
-
-    toolbox = await client.get_toolbox("research_tools")
-    print(f"Loaded toolbox {toolbox.name}@{toolbox.version} ({len(toolbox.tools)} tools)")
-
-    agent = Agent(
-        client=client,
-        instructions="You are a research assistant.",
-        tools=toolbox,
-    )
-
-    result = await agent.run("What are the latest developments in quantum error correction?")
-    print(f"Result: {result}")
-
-
-if __name__ == "__main__":
-    asyncio.run(main())
-```
-
-### Version pinning
-
-```python
-toolbox = await client.get_toolbox("research_tools", version="v3")
-```
-
-### Combining multiple toolboxes
-
-```python
-toolbox_a = await client.get_toolbox("research_tools")
-toolbox_b = await client.get_toolbox("some_other_tools", version="v3")
-
-agent = Agent(
-    client=client,
-    instructions="...",
-    tools=[toolbox_a, toolbox_b],
-)
-```
-
-### Combining toolbox tools with locally defined tools
-
-```python
-toolbox = await client.get_toolbox("research_tools")
-
-def get_internal_metrics(metric_name: str) -> dict:
-    """Custom tool that reads from an internal dashboard."""
-    ...
-
-agent = Agent(
-    client=client,
-    instructions="...",
-    tools=[get_internal_metrics, toolbox],
-)
-```
-
-### Selecting only some tools from a toolbox
-
-Developers will not always want to pass the entire toolbox through unchanged. A
-small helper in the Foundry package provides local post-fetch selection without
-changing the raw return type of `get_toolbox()`.
-
-```python
-from agent_framework.foundry import select_toolbox_tools
-
-toolbox = await client.get_toolbox("research_tools")
-
-selected_tools = select_toolbox_tools(
-    toolbox,
-    include_names=["githubmcp", "code_interpreter"],
-)
-
-agent = Agent(
-    client=client,
-    instructions="Use only the selected toolbox tools.",
-    tools=selected_tools,
-)
-```
-
-Supported filters:
-
-```python
-from agent_framework.foundry import FoundryHostedToolType, select_toolbox_tools
-
-selected_tools = select_toolbox_tools(
-    toolbox,
-    include_types=["mcp", "code_interpreter"],  # type: Collection[FoundryHostedToolType]
-    exclude_names=["internal_admin_tool"],
-)
-```
-
-Helper signature:
-
-```python
-type FoundryHostedToolType = Literal[
-    "code_interpreter",
-    "file_search",
-    "image_generation",
-    "mcp",
-    "web_search",
-] | str
-
-def select_toolbox_tools(
-    tools: ToolboxVersionObject | Sequence[Tool | dict[str, Any]],
-    *,
-    include_names: Collection[str] | None = None,
-    exclude_names: Collection[str] | None = None,
-    include_types: Collection[FoundryHostedToolType] | None = None,
-    exclude_types: Collection[FoundryHostedToolType] | None = None,
-    predicate: Callable[[Tool | dict[str, Any]], bool] | None = None,
-) -> list[Tool | dict[str, Any]]:
-    ...
-```
-
-Normalized name precedence for `include_names` / `exclude_names`:
-
-1. MCP `server_label`
-2. generic tool `name`
-3. fallback tool `type`
-
-This keeps `get_toolbox()` as a thin fetch API and makes selection an explicit,
-local post-processing step, while still allowing the ergonomic
-`select_toolbox_tools(toolbox, ...)` call shape.
-
-## Native vs MCP consumption of a Foundry toolbox
-
-A Foundry toolbox can be consumed two ways. This design adds new implementation work only for the first:
-
-1. **Native consumption (in scope).** Tools execute inside Foundry's agent runtime. `get_toolbox()` returns the `ToolboxVersionObject` whose `.tools` attribute carries typed tool configs that the runtime interprets server-side. This design is specifically for `FoundryChatClient`-backed local agent composition.
-
-2. **MCP consumption (already supported through existing MCP abstractions).** A Foundry toolbox can also be exposed as an MCP server. In that case, use the existing `MCPStreamableHTTPTool(name=..., url=...)` — it already handles this path with any chat client (Foundry, OpenAI, Anthropic, etc.). No new Foundry-specific API is needed for MCP-exposed toolboxes in this design.
-
-### MCPStreamableHTTPTool example for a Foundry toolbox endpoint
-
-If Foundry gives you an MCP endpoint for the toolbox (for example from the
-toolbox details UI / endpoint surface), the existing MCP client path is:
-
-```python
-from agent_framework import Agent, MCPStreamableHTTPTool
-from agent_framework.openai import OpenAIChatClient
-
-toolbox_mcp = MCPStreamableHTTPTool(
-    name="research_tools",
-    url="https://<foundry-toolbox-mcp-endpoint>",
-)
-
-agent = Agent(
-    client=OpenAIChatClient(),
-    instructions="You are a research assistant.",
-    tools=[toolbox_mcp],
-)
-```
-
-This is a different integration shape than `get_toolbox(...).tools`:
-
- `get_toolbox(...).tools` = **native Foundry hosted-tool configs** interpreted by the
-  Foundry runtime
- `MCPStreamableHTTPTool(name=..., url=...)` = **live MCP server connection** to a
-  toolbox endpoint
-
-The design in this spec adds first-class support only for the native hosted-tool
-path. The MCP path is already served by the framework's existing MCP abstractions.
-
-These paths are not unified because they have fundamentally different execution models. Native toolbox tools are declarative configs the Foundry runtime executes; MCP consumption is a live wire protocol to a running server.
-
-**MCP authentication inside a toolbox** is handled server-side via `project_connection_id` on individual `MCPTool` entries (OAuth connection objects configured in the Foundry project). The client never holds bearer tokens. Consent flow handling (`CONSENT_REQUIRED` → user-visible consent URL) happens during `agent.run()`, not during toolbox fetching — see Non-goals.
-
-## Testing Strategy
-
-Unit tests in `packages/foundry/tests/test_toolbox.py` with mocked `project_client.beta.toolboxes`. A single opt-in live round-trip, `test_integration_get_toolbox_round_trip_against_real_project`, is marked `@pytest.mark.integration`; it is skipped by default and only runs when the required Foundry credentials are available.
-
-Coverage:
-
- `get_toolbox(name, version="v3")` — explicit version, single request. Assert `.get` not called, `.get_version` awaited once, returns `ToolboxVersionObject`.
- `get_toolbox(name)` — default-version resolution. Assert `.get` then `.get_version` called in order with correct args.
- Error propagation — `ResourceNotFoundError` from `.get` propagates unchanged.
- Tool passthrough — heterogeneous tool list (`CodeInterpreterTool`, `MCPTool(project_connection_id=...)`) passes through unchanged. Asserts `project_connection_id` survives.
- Agent integration smoke — `tools=toolbox` / `tools=[toolbox]` flatten to the underlying toolbox tools.
- Multiple toolbox composition smoke — `tools=[toolbox_a, toolbox_b]` flattens into a single agent tool list.
- `get_toolbox_tool_name()` — selection-name precedence is MCP `server_label`, then `name`, then `type`.
- `select_toolbox_tools(toolbox, include_names=...)` — selects by normalized tool names directly from a fetched toolbox object.
- `select_toolbox_tools(toolbox, include_types=...)` — selects by tool types with `Literal`-guided IDE completion.
- `select_toolbox_tools(..., exclude_names=..., predicate=...)` — supports exclusion + custom predicates.
-
-Deliberately **not** covered:
- Runtime consent-flow handling for OAuth MCP tools (see Non-goals).
- Toolbox discovery/listing (`list_toolboxes`, `list_toolbox_versions`) — deliberately left to the raw Azure SDK.
- Full CRUD (`create_version`, `update`, `delete`) and server-side agent authoring — see Non-goals.
-
-Live Foundry API integration is exercised only through the opt-in `@pytest.mark.integration` round-trip noted above; it is not part of the default test run.
-
-## Framework dependency: `normalize_tools` flattening
-
-The core `normalize_tools` function in `packages/core/agent_framework/_tools.py` already supports flattening composite tool inputs. Toolbox support extends that behavior so a fetched `ToolboxVersionObject` is treated as a composite tool source and flattened to its `.tools`.
-
-That enables:
-
- `tools=toolbox`
- `tools=[toolbox]`
- `tools=[local_tool, toolbox]`
- `tools=[toolbox_a, toolbox_b]`
-
-while still keeping `select_toolbox_tools(toolbox.tools, ...)` available for partial selection before the final agent construction step.
-
-## Telemetry
-
-Telemetry for toolbox support has two separate goals:
-
-1. **Observe toolbox API access** — `get_toolbox()`
-2. **Observe toolbox usage during agent runs** — when users pass toolbox-derived tools into `Agent(..., tools=...)`
-
-### Request telemetry for toolbox API access
-
-When Agent Framework constructs the `AIProjectClient` internally for `FoundryChatClient`, it already sets:
-
-```python
-user_agent=AGENT_FRAMEWORK_USER_AGENT
-```
-
-That means toolbox API requests made through:
-
- `project_client.beta.toolboxes.get(...)`
- `project_client.beta.toolboxes.get_version(...)`
-
-carry the standard MAF user-agent marker and can be queried in backend request logs the same way as other Foundry SDK calls made through framework-owned clients.
-
-Important constraint: if the caller passes an already-constructed `project_client`, Agent Framework does **not** mutate it to inject the MAF user-agent. In that case, toolbox API request telemetry reflects whatever user-agent behavior that external client was configured with.
-
-### Runtime telemetry for toolbox usage on agent runs
-
-Tool-level telemetry already captures which hosted Foundry tools are available / invoked during agent execution. The remaining gap is **toolbox provenance**: once the user writes `tools=toolbox` (or otherwise flattens the toolbox into tool configs), the framework sees only raw tool configs and no longer knows which toolbox name/version supplied them.
-
-The design for closing the **client-side** observability gap is **internal provenance tracking**, not user-supplied metadata and not a new public wrapper type.
-
-#### Provenance model
-
-Note: this section is still under investigation.
-
-When `get_toolbox()` or `list_toolbox_versions()` returns a `ToolboxVersionObject`, Agent Framework will attach private provenance metadata to:
-
- the returned toolbox object
- each tool inside `toolbox.tools`
-
-Recommended shape (private, internal-only):
-
-```python
-tool._maf_toolbox_sources = [
-    {
-        "id": toolbox.id,
-        "name": toolbox.name,
-        "version": toolbox.version,
-    }
-]
-```
-
-Key properties of this approach:
-
- **No new public API surface** — users still work with raw `ToolboxVersionObject` / `ToolboxObject`
- **No user burden** — callers do not need to stamp metadata manually
- **Provenance follows the tool objects** — works with:
-  - `tools=toolbox.tools`
-  - `tools=[toolbox_a.tools, toolbox_b.tools]`
-  - `tools=[*toolbox_a.tools, *toolbox_b.tools]`
- **Private attributes are not serialized** into the actual request payload sent to the model/service, so this metadata does not leak into the tool definition body
-
-This is intentionally preferred over introducing a new public `FoundryToolbox` wrapper purely for telemetry, and preferred over a separate global provenance registry. The provenance lives on the existing tool objects so list-copying and chat-option merging naturally preserve it.
-
-#### Span enrichment
-
-When Agent / chat telemetry computes span attributes for a run, it should inspect the final tool list and aggregate the private toolbox provenance from any tool objects that carry it. The aggregated values are then emitted as attributes on the existing run/chat spans.
-
-Suggested custom attributes:
-
- `agent_framework.foundry.toolbox.ids`
- `agent_framework.foundry.toolbox.names`
- `agent_framework.foundry.toolbox.versions`
- or a single compact attribute such as `agent_framework.foundry.toolbox.sources=["research_tools@1","some_other_tools@3"]`
-
-The single compact `toolbox.sources` form is preferred for initial implementation because it is easy to query and easy to render from combined tool lists.
-
-#### Scope of telemetry changes
-
-This design does **not** require new spans. It enriches existing telemetry:
-
- toolbox API access continues to rely on request logs + Azure SDK distributed tracing + MAF user-agent
- agent/chat execution spans gain toolbox provenance attributes when toolbox-derived tools are present
-
-Implementation-wise, this design most likely touches:
-
- `packages/foundry/agent_framework_foundry/_tools.py` — to stamp provenance on fetched toolbox objects / tools
- `packages/core/agent_framework/observability.py` — to aggregate provenance into span attributes
-
-#### Important limitation: no server-side toolbox telemetry solution yet
-
-Private provenance attached to tool objects is only useful on the client side. It
-does **not** go over the wire to the Foundry service because those private fields
-are intentionally not serialized into the request payload.
-
-That means this design can support:
-
- local OpenTelemetry / exporter spans emitted by Agent Framework
- local attribution of a run to one or more fetched toolboxes
-
-but it does **not** solve:
-
- server-side request-log attribution of a model/tool run back to a toolbox
- backend/database queries that need the service itself to know "this tool came from toolbox X"
-
-At the moment, we do not have a satisfactory design for server-side toolbox
-telemetry. The service would require additional structured information on the
-request, and there is no accepted mechanism in this design yet for projecting
-toolbox provenance into a server-visible field/header/metadata shape.
-
-So the telemetry story in this spec is explicitly limited to **client-side
-toolbox telemetry**. Server-side toolbox attribution remains an open question and
-requires either:
-
- new service/API support, or
- a later framework design for emitting additional server-visible request metadata.
-
-#### Deliberate non-goals for telemetry
-
- No requirement for users to pass explicit toolbox metadata in `default_options["metadata"]` or `run(..., options=...)`
- No new public `FoundryToolbox` wrapper type just to preserve attribution
- No attempted server-side attribution mechanism in this design (for example a custom request header or request metadata field) until there is a validated end-to-end contract for it
-
-## Non-goals / Future Work
-
-Explicitly out of scope for this design. Each is a separate design and PR when needed.
-
-1. **Create/update/delete toolboxes from code.** CRUD is rare in agent consumption flows. Users who need it drop to `client.project_client.beta.toolboxes.create_version(...)`, `.update(...)`, `.delete(...)` directly.
-
-2. **Server-side agent authoring from toolbox.** Creating a `PromptAgentDefinition(tools=toolbox.tools)` + `client.agents.create_version(...)` is a future feature covering agent authoring from code. The toolbox read API provides the building blocks; the authoring helpers are a separate design.
-
-3. **OAuth consent-flow runtime handling.** When a toolbox contains MCP tools with `project_connection_id` pointing to an OAuth connection, the runtime may return `CONSENT_REQUIRED` mid-run. This is a runtime concern separate from toolbox fetching.
-
-4. **Live integration tests.** This PR ships unit tests only.
-
-5. **Toolbox caching or refresh APIs.** Each `get_toolbox()` call hits the network. Users who want caching wrap the call themselves.
@@ -1,625 +0,0 @@
-# CodeAct .NET implementation
-
-This document describes the .NET realization of the CodeAct design in
-[`docs/decisions/0024-codeact-integration.md`](../../decisions/0024-codeact-integration.md).
-
-This document is intentionally focused on the .NET design and public API surface.
-The initial public .NET type described here is `HyperlightCodeActProvider`. Future .NET backends, such as Monty, should follow the same conceptual model with their own concrete provider types rather than through a public abstract base class or a public executor parameter.
-
-## What is the goal of this feature?
-
-Goals:
- .NET developers can enable CodeAct through an `AIContextProvider`-based integration.
- Developers can configure a provider-owned CodeAct tool set that is separate from the agent's direct tool surface.
- Developers can use the same `execute_code` concept for both tool-enabled CodeAct and a standard code interpreter tool implementation.
- Developers can swap execution backends over time, starting with Hyperlight while keeping room for alternatives.
- Developers can configure execution capabilities such as workspace mounts and outbound network allow lists in a portable way.
-
-Success Metric:
- .NET samples exist for both a tool-enabled CodeAct mode and a standard interpreter mode.
-
-Implementation-free outcome:
- A .NET developer can attach a backend-specific CodeAct provider, choose which tools are available inside CodeAct, and configure execution capabilities without rewriting the function invocation loop or ChatClient pipeline.
-
-## What is the problem being solved?
-
-The cross-SDK problem statement and decision rationale live in the [ADR](../../decisions/0024-codeact-integration.md). The items below narrow that statement to .NET-specific design concerns:
-
- Today, the easiest way to prototype CodeAct in .NET is to manually configure an `AIFunction` and wire instructions — this is fragile and requires understanding internal sandbox lifecycle details.
- There is no first-class .NET design that simultaneously covers Hyperlight-backed CodeAct now, future backend-specific providers, and both tool-enabled and interpreter modes.
- Sandbox capabilities such as mounted file access and outbound network access need a portable configuration model instead of ad hoc backend-specific wiring.
- Approval behavior needs to be explicit and configurable, mapping to .NET's existing `ApprovalRequiredAIFunction` wrapper mechanism.
-
-## API Changes
-
-### CodeAct contract
-
-#### Terminology
-
- **CodeAct** is the primary term.
- `execute_code` is the model-facing tool name used by the initial .NET provider in this spec.
- Tool-enabled versus interpreter behavior is derived from the presence of CodeAct-managed tools, not from a separate public profile object.
-
-#### Provider-owned CodeAct tool registry
-
-A concrete .NET CodeAct provider owns the set of tools available through `call_tool(...)` inside CodeAct.
-
-Rules:
- Only tools explicitly configured on the concrete provider instance are available inside CodeAct.
- The provider must not infer its CodeAct-managed tool set from the agent's direct tool configuration (`ChatClientAgentOptions.Tools` or `AIContext.Tools`).
- Exclusive versus mixed behavior is achieved by where tools are configured, not by rewriting the agent's direct tool list.
-
-Implications:
- **CodeAct-only tool**: configured on the concrete CodeAct provider only.
- **Direct-only tool**: configured on the agent only.
- **Tool available both ways**: configured on both the agent and the concrete CodeAct provider.
-
-#### Managing tools and capabilities after provider construction
-
-There is no separate runtime setup object in the .NET design. CodeAct tools, file mounts, and outbound network allow-list state are managed directly on the provider through CRUD-style registry methods.
-
-Preferred pattern:
- `AddTools(params AIFunction[] tools) -> void`
- `GetTools() -> IReadOnlyList<AIFunction>`
- `RemoveTools(params string[] names) -> void`
- `ClearTools() -> void`
- `AddFileMounts(params FileMount[] mounts) -> void`
- `GetFileMounts() -> IReadOnlyList<FileMount>`
- `RemoveFileMounts(params string[] mountPaths) -> void`
- `ClearFileMounts() -> void`
- `AddAllowedDomains(params AllowedDomain[] domains) -> void`
- `GetAllowedDomains() -> IReadOnlyList<AllowedDomain>`
- `RemoveAllowedDomains(params string[] targets) -> void`
- `ClearAllowedDomains() -> void`
-
-Requirements:
- The provider-owned CodeAct tool registry is keyed by tool name (from `AIFunction.Name`).
- `AddTools(...)` adds new tools and replaces an existing provider-owned registration when the same tool name is added again.
- `GetTools()` returns the provider's current configured CodeAct tool registry.
- `RemoveTools(...)` removes provider-owned CodeAct tools by name.
- `ClearTools()` removes all provider-owned CodeAct tools.
- File mounts are keyed by sandbox mount path.
- `AddFileMounts(...)` adds new file mounts and replaces an existing mount when the same mount path is added again.
- `GetFileMounts()` returns the provider's current configured file mounts.
- `RemoveFileMounts(...)` removes file mounts by mount path.
- `ClearFileMounts()` removes all configured file mounts.
- Allowed domains are keyed by normalized target string.
- `AddAllowedDomains(...)` adds allow-list entries and replaces an existing entry when the same target is added again.
- `GetAllowedDomains()` returns the current outbound allow-list entries.
- `RemoveAllowedDomains(...)` removes allow-list entries by target.
- `ClearAllowedDomains()` removes all configured allow-list entries.
- Tool, file-mount, and network-allow-list mutations affect subsequent runs only; runs already in progress keep the snapshot captured at run start.
- The provider must snapshot its effective tool registry and capability state at the start of each run so concurrent execution remains deterministic.
-
-#### Approval model
-
-The initial .NET design follows the ADR's bundled approval decision and maps to the existing `ApprovalRequiredAIFunction` wrapper from `Microsoft.Extensions.AI.Abstractions`:
-
- The provider exposes a default `ApprovalMode` for `execute_code` (enum: `CodeActApprovalMode.AlwaysRequire` / `CodeActApprovalMode.NeverRequire`).
-
-Effective `execute_code` approval is computed as follows:
-
- If the provider default is `AlwaysRequire`, `execute_code` requires approval.
- If the provider default is `NeverRequire`, the provider evaluates the provider-owned CodeAct tool registry snapshot for that run.
-  - If every provider-owned CodeAct tool in that snapshot is not an `ApprovalRequiredAIFunction`, `execute_code` does not require approval.
-  - If any provider-owned CodeAct tool in that snapshot is an `ApprovalRequiredAIFunction`, `execute_code` requires approval, even if the generated code may not call that tool.
- When the effective approval resolves to `AlwaysRequire`, the generated `execute_code` function is wrapped in `ApprovalRequiredAIFunction` before being added to the `AIContext.Tools`.
- Provider-owned tool calls made through `call_tool(...)` during that execution run use the approval already determined for `execute_code`.
- Direct-only agent tools are excluded from this calculation.
- File and network capabilities do not create a separate runtime approval check in the initial model; configuring them on the provider is itself the approval for those capabilities.
-
-This is intentionally conservative and matches the shape of the existing .NET function-tool approval flow, where `ApprovalRequiredAIFunction` signals to the `ChatClientAgent` that user approval is needed before invocation.
-
-#### Shared execution flow
-
-On each run:
-1. `ProvideAIContextAsync(...)` snapshots the current CodeAct-managed tool registry and capability settings.
-2. Computes the effective approval requirement for `execute_code` from the provider default plus the snapshotted tool registry.
-3. Builds provider-defined instructions.
-4. Builds a run-scoped `execute_code` `AIFunction` from the snapshot (optionally wrapped in `ApprovalRequiredAIFunction`).
-5. Returns an `AIContext` containing the instructions and `execute_code` tool.
-6. When `execute_code` is invoked by the model, the run-scoped function creates or reuses an execution environment.
-7. If the current provider mode exposes host tools, `call_tool(...)` is bound only to the provider-owned tool registry snapshot.
-8. Code is executed and results converted to a JSON result string.
-
-Caching rules:
- The Hyperlight backend supports snapshots: the provider caches a reusable clean snapshot after the first sandbox initialization.
- No mutable per-run execution state may be shared across concurrent runs.
- In-memory interpreter state does not persist across separate `execute_code` calls.
- Configured workspace files, mounted files, and any writable artifact/output area are the supported persistence mechanism across calls when the backend exposes them.
-
-### .NET public API
-
-#### Core types
-
-```csharp
-/// <summary>
-/// Represents a host-to-sandbox file mount configuration.
-/// </summary>
-/// <param name="HostPath">Absolute or relative path on the host filesystem.</param>
-/// <param name="MountPath">Path inside the sandbox (e.g. "/input/data.csv").</param>
-public sealed record FileMount(string HostPath, string MountPath);
-
-/// <summary>
-/// Represents an outbound network allow-list entry.
-/// </summary>
-/// <param name="Target">URL or domain (e.g. "https://api.github.com").</param>
-/// <param name="Methods">
-/// Optional HTTP methods to allow (e.g. ["GET", "POST"]).
-/// Null allows all methods supported by the backend.
-/// </param>
-public sealed record AllowedDomain(string Target, IReadOnlyList<string>? Methods = null);
-
-/// <summary>
-/// Controls the approval behavior for execute_code invocations.
-/// </summary>
-public enum CodeActApprovalMode
-{
-    /// <summary>execute_code always requires user approval.</summary>
-    AlwaysRequire,
-
-    /// <summary>
-    /// Approval is derived from the provider-owned tool registry:
-    /// if any tool is an ApprovalRequiredAIFunction, execute_code requires approval.
-    /// </summary>
-    NeverRequire,
-}
-```
-
-#### HyperlightCodeActProvider
-
-```csharp
-/// <summary>
-/// An AIContextProvider that enables CodeAct execution through the
-/// Hyperlight sandbox backend.
-/// </summary>
-/// <remarks>
-/// <para>
-/// This provider injects an <c>execute_code</c> tool into the model-facing
-/// tool surface and builds CodeAct guidance instructions. Guest code executed
-/// through <c>execute_code</c> runs in an isolated Hyperlight sandbox with
-/// snapshot/restore for clean state per invocation.
-/// </para>
-/// <para>
-/// If no CodeAct-managed tools are configured, the provider uses
-/// interpreter-style behavior. If one or more CodeAct-managed tools are
-/// configured, the provider uses tool-enabled behavior and exposes
-/// <c>call_tool(...)</c> inside the sandbox bound to the configured tools.
-/// </para>
-/// </remarks>
-public sealed class HyperlightCodeActProvider : AIContextProvider, IDisposable
-{
-    /// <summary>
-    /// Initializes a new HyperlightCodeActProvider.
-    /// </summary>
-    /// <param name="options">Configuration options for the provider.</param>
-    public HyperlightCodeActProvider(HyperlightCodeActProviderOptions options);
-
-    // ----- Tool registry -----
-
-    /// <summary>Adds tools to the provider-owned CodeAct tool registry.</summary>
-    public void AddTools(params AIFunction[] tools);
-
-    /// <summary>Returns the current CodeAct-managed tools.</summary>
-    public IReadOnlyList<AIFunction> GetTools();
-
-    /// <summary>Removes tools by name from the CodeAct tool registry.</summary>
-    public void RemoveTools(params string[] names);
-
-    /// <summary>Removes all CodeAct-managed tools.</summary>
-    public void ClearTools();
-
-    // ----- File mounts -----
-
-    /// <summary>Adds file mount configurations.</summary>
-    public void AddFileMounts(params FileMount[] mounts);
-
-    /// <summary>Returns the current file mount configurations.</summary>
-    public IReadOnlyList<FileMount> GetFileMounts();
-
-    /// <summary>Removes file mounts by sandbox mount path.</summary>
-    public void RemoveFileMounts(params string[] mountPaths);
-
-    /// <summary>Removes all file mount configurations.</summary>
-    public void ClearFileMounts();
-
-    // ----- Network allow-list -----
-
-    /// <summary>Adds outbound network allow-list entries.</summary>
-    public void AddAllowedDomains(params AllowedDomain[] domains);
-
-    /// <summary>Returns the current outbound allow-list entries.</summary>
-    public IReadOnlyList<AllowedDomain> GetAllowedDomains();
-
-    /// <summary>Removes allow-list entries by target.</summary>
-    public void RemoveAllowedDomains(params string[] targets);
-
-    /// <summary>Removes all outbound allow-list entries.</summary>
-    public void ClearAllowedDomains();
-
-    // ----- Lifecycle -----
-
-    /// <summary>Releases the sandbox and all associated native resources.</summary>
-    public void Dispose();
-}
-```
-
-#### HyperlightCodeActProviderOptions
-
-```csharp
-/// <summary>
-/// Configuration options for <see cref="HyperlightCodeActProvider"/>.
-/// </summary>
-public sealed class HyperlightCodeActProviderOptions
-{
-    /// <summary>
-    /// The sandbox backend to use. Default is <c>Wasm</c>.
-    /// </summary>
-    public SandboxBackend Backend { get; set; } = SandboxBackend.Wasm;
-
-    /// <summary>
-    /// Path to the guest module (.wasm or .aot file).
-    /// Required for the Wasm backend; not needed for JavaScript.
-    /// When null, the provider attempts to locate the default packaged
-    /// Python guest module.
-    /// </summary>
-    public string? ModulePath { get; set; }
-
-    /// <summary>
-    /// Guest heap size. Accepts human-readable strings ("50Mi", "2Gi")
-    /// or raw byte values. Null uses the backend default.
-    /// </summary>
-    public string? HeapSize { get; set; }
-
-    /// <summary>
-    /// Guest stack size. Accepts human-readable strings ("35Mi")
-    /// or raw byte values. Null uses the backend default.
-    /// </summary>
-    public string? StackSize { get; set; }
-
-    /// <summary>
-    /// Initial set of CodeAct-managed tools available inside the sandbox.
-    /// </summary>
-    public IEnumerable<AIFunction>? Tools { get; set; }
-
-    /// <summary>
-    /// Default approval mode for the execute_code tool.
-    /// Default is <see cref="CodeActApprovalMode.NeverRequire"/>.
-    /// </summary>
-    public CodeActApprovalMode ApprovalMode { get; set; } = CodeActApprovalMode.NeverRequire;
-
-    /// <summary>
-    /// Optional workspace root directory on the host.
-    /// When set, it is exposed as the sandbox's input directory.
-    /// </summary>
-    public string? WorkspaceRoot { get; set; }
-
-    /// <summary>
-    /// Initial file mount configurations.
-    /// </summary>
-    public IEnumerable<FileMount>? FileMounts { get; set; }
-
-    /// <summary>
-    /// Initial outbound network allow-list entries.
-    /// </summary>
-    public IEnumerable<AllowedDomain>? AllowedDomains { get; set; }
-
-    /// <summary>
-    /// State key used to store provider state in AgentSession.StateBag.
-    /// Defaults to "HyperlightCodeActProvider". Override when using
-    /// multiple provider instances on the same agent.
-    /// </summary>
-    public string? StateKey { get; set; }
-}
-```
-
-#### Provider implementation contract
-
-The concrete provider plugs into the existing .NET `AIContextProvider` surface from `Microsoft.Agents.AI.Abstractions`.
-
-Required override:
- `ProvideAIContextAsync(InvokingContext, CancellationToken) -> ValueTask<AIContext>`
-
-`ProvideAIContextAsync(...)` is responsible for:
- snapshotting the current CodeAct-managed tool registry and capability settings for the run,
- computing the effective approval requirement for `execute_code` from the provider default and the snapshotted tool registry,
- building a short CodeAct guidance instruction string,
- building a run-scoped `execute_code` `AIFunction` from the snapshot,
- optionally wrapping it in `ApprovalRequiredAIFunction` when approval is required,
- and returning an `AIContext` with `Instructions` and `Tools` set.
-
-These steps run on every invocation rather than once at construction time because the provider supports CRUD mutations between runs, concurrent runs need independent snapshots, and the effective approval and instructions depend on the tool registry state captured at run start.
-
-The provider overrides `StateKeys` to return the configured `StateKey` from options, enabling multiple provider instances on the same agent without key collisions.
-
-Mutating the provider after `ProvideAIContextAsync(...)` has captured a run-scoped snapshot is allowed, but it affects subsequent runs only. Provider implementations synchronize state capture and CRUD operations so shared provider instances remain safe across concurrent runs.
-
-#### AIFunction-to-sandbox tool bridging
-
-The Hyperlight sandbox's `RegisterTool(name, Func<string, string>)` accepts a synchronous JSON-in / JSON-out delegate. Provider-owned CodeAct tools are `AIFunction` instances that are async and cancellation-aware.
-
-Bridging strategy:
- At sandbox initialization time, the provider registers each CodeAct-managed tool with the sandbox using the raw JSON overload: `RegisterTool(name, Func<string, string>)`.
- When the sandbox guest calls `call_tool("name", ...)`, the bridge delegate:
-  1. Deserializes the JSON arguments.
-  2. Invokes `AIFunction.InvokeAsync(...)` synchronously (via `GetAwaiter().GetResult()`) since the sandbox FFI callback is inherently synchronous.
-  3. Serializes the result back to JSON.
- This sync-over-async bridge is a known pragmatic trade-off constrained by the Hyperlight FFI boundary. It is safe because:
-  - Sandbox execution already runs on the thread pool (via `Task.Run`).
-  - The FFI callback runs on a worker thread with no synchronization context.
- If the Hyperlight .NET SDK later adds async tool registration, the bridge should migrate to that.
-
-#### Runtime behavior
-
- `ProvideAIContextAsync(...)` adds a short CodeAct guidance block through `AIContext.Instructions`.
- `ProvideAIContextAsync(...)` adds `execute_code` through `AIContext.Tools`.
- The detailed `call_tool(...)`, sandbox-tool, and capability guidance is carried by the `execute_code` function's `Description`.
- `execute_code` invokes the configured Hyperlight sandbox guest.
- If the current CodeAct tool registry snapshot is non-empty, the runtime injects `call_tool(...)` bound to the provider-owned tool registry.
- The provider does not inspect or mutate the agent's `ChatClientAgentOptions.Tools` or the incoming `AIContext.Tools` to determine its CodeAct tool set.
- The provider snapshots the current CodeAct tool registry and capability state at run start, so later registry and allow-list mutations only affect future runs.
- Interpreter versus tool-enabled behavior is derived from the presence of CodeAct-managed tools.
- `execute_code` is traced like a normal tool invocation within the surrounding agent run.
-
-#### Backend integration
-
-Initial public provider:
- `HyperlightCodeActProvider`
-
-Backend-specific notes:
- **Hyperlight**
-  - The provider internally creates a `SandboxBuilder` from the options and uses the `Sandbox` API from `HyperlightSandbox.Api`.
-  - The provider uses snapshot/restore to ensure clean execution state per `execute_code` invocation: a "warm" snapshot is taken after the first no-op initialization run, and restored before each subsequent execution.
-  - File access maps to Hyperlight Sandbox's `WithInputDir()` / `WithOutputDir()` / `WithTempOutput()` capability model.
-  - Network access is denied by default and is enabled through `Sandbox.AllowDomain(...)` per-target allow-list entries.
-  - Guest module resolution: if `ModulePath` is null for the Wasm backend, the provider attempts to locate a packaged Python guest module (equivalent to the Python SDK's `python_guest.path` resolution).
-
-#### Capability handling
-
-Capabilities are first-class `HyperlightCodeActProviderOptions` properties and provider-managed CRUD surfaces:
- `WorkspaceRoot`
- `FileMounts`
- `AllowedDomains`
-
-Enabling access means:
- Configuring `WorkspaceRoot` or any `FileMounts` enables the sandbox filesystem surface exposed through `/input` and `/output`.
- Leaving both `WorkspaceRoot` and `FileMounts` unset means no filesystem surface is configured.
- Adding any `AllowedDomains` entry enables outbound access only for the configured targets; leaving it empty means network access is disabled without a separate network mode flag.
-
-Backends may implement stricter semantics than these top-level settings.
-
-#### Execution output representation
-
-Backend execution output maps to a JSON result string returned from the `execute_code` `AIFunction`:
-
-```json
-{
-  "stdout": "Hello world\n",
-  "stderr": "",
-  "exit_code": 0,
-  "success": true
-}
-```
-
-Execution failures should surface readable error text in the `stderr` field and a non-zero `exit_code`. Timeouts, out-of-memory conditions, backend crashes, and similar sandbox failures are all `execute_code` failures and should surface as structured error results. Partial textual or file outputs may be returned only when the backend can report them unambiguously.
-
-#### `execute_code` input contract
-
-```json
-{
-  "type": "object",
-  "properties": {
-    "code": {
-      "type": "string",
-      "description": "Code to execute using the provider's configured backend/runtime behavior."
-    }
-  },
-  "required": ["code"]
-}
-```
-
-#### Thread safety and concurrency
-
- All CRUD methods (`AddTools`, `RemoveTools`, `AddFileMounts`, etc.) are synchronized via an internal lock.
- `ProvideAIContextAsync(...)` acquires the lock to snapshot current state, then releases it before building the run-scoped function. The run-scoped function closes over the immutable snapshot, not mutable provider state.
- Concurrent `execute_code` invocations from different runs use independent sandbox instances or synchronized access to a shared sandbox with snapshot/restore.
- Workspace directories (`WorkspaceRoot`, `FileMounts`) are external shared state: concurrent runs against the same workspace can race on files. This is the user's responsibility to manage (e.g., by using per-run output directories or separate provider instances).
-
-### HyperlightExecuteCodeFunction
-
-The provider package also exports a standalone `HyperlightExecuteCodeFunction` for direct-tool scenarios where a provider lifecycle is not needed. This is the .NET equivalent of the Python `HyperlightExecuteCodeTool`.
-
-```csharp
-/// <summary>
-/// A standalone execute_code AIFunction backed by a Hyperlight sandbox.
-/// Use this for manual/static wiring when the AIContextProvider lifecycle
-/// is not needed.
-/// </summary>
-public sealed class HyperlightExecuteCodeFunction : IDisposable
-{
-    /// <summary>
-    /// Creates a new standalone code execution function.
-    /// </summary>
-    /// <param name="options">Configuration options.</param>
-    public HyperlightExecuteCodeFunction(HyperlightCodeActProviderOptions options);
-
-    /// <summary>
-    /// Returns this as an AIFunction for direct registration on an agent.
-    /// When approval is required, the returned function is wrapped in
-    /// ApprovalRequiredAIFunction.
-    /// </summary>
-    public AIFunction AsAIFunction();
-
-    /// <summary>
-    /// Builds a CodeAct instruction string describing the available
-    /// tools and capabilities.
-    /// </summary>
-    /// <param name="toolsVisibleToModel">
-    /// When false, the instructions include full tool descriptions
-    /// (for use when tools are only accessible through CodeAct).
-    /// When true, instructions are abbreviated (tools are already
-    /// visible to the model as direct tools).
-    /// </param>
-    public string BuildInstructions(bool toolsVisibleToModel = false);
-
-    /// <summary>Releases sandbox resources.</summary>
-    public void Dispose();
-}
-```
-
-### Internal implementation structure
-
-The provider and standalone function share internal helpers:
-
-```
-Microsoft.Agents.AI.Hyperlight/
-├── HyperlightCodeActProvider.cs        // AIContextProvider implementation
-├── HyperlightCodeActProviderOptions.cs // Options record
-├── HyperlightExecuteCodeFunction.cs    // Standalone AIFunction for manual wiring
-├── FileMount.cs                        // File mount record
-├── AllowedDomain.cs                    // Network allow-list record
-├── CodeActApprovalMode.cs              // Approval enum
-├── Internal/
-│   ├── SandboxExecutor.cs              // Manages sandbox lifecycle, snapshot/restore
-│   ├── InstructionBuilder.cs           // Builds CodeAct instruction strings
-│   └── ToolBridge.cs                   // AIFunction ↔ Sandbox.RegisterTool adapter
-```
-
-`SandboxExecutor` encapsulates:
- Creating and configuring a `Sandbox` from options.
- Performing the initial no-op warm-up and snapshot.
- Registering bridged tools via `ToolBridge`.
- Restoring to the clean snapshot before each execution.
- Translating `ExecutionResult` to a JSON string.
-
-`InstructionBuilder` generates:
- A short CodeAct guidance block for `AIContext.Instructions`.
- A detailed `execute_code` description including `call_tool(...)` signatures and capability documentation.
-
-`ToolBridge` handles:
- Reflecting `AIFunction` metadata to build the sandbox tool registration.
- The sync-over-async invocation bridge.
-
-## E2E Code Samples
-
-### Tool-enabled CodeAct mode
-
-```csharp
-var fetchDocs = AIFunctionFactory.Create(FetchDocs, name: "fetch_docs");
-var queryData = AIFunctionFactory.Create(QueryData, name: "query_data");
-var lookupUser = AIFunctionFactory.Create(LookupUser, name: "lookup_user");
-
-var codeact = new HyperlightCodeActProvider(new HyperlightCodeActProviderOptions
-{
-    Tools = [fetchDocs, queryData],
-    WorkspaceRoot = "./workdir",
-    AllowedDomains = [new AllowedDomain("api.github.com", ["GET"])],
-});
-codeact.AddTools(lookupUser);
-
-var sendEmail = AIFunctionFactory.Create(SendEmail, name: "send_email");
-
-var agent = chatClient.AsAIAgent(
-    instructions: "You are a helpful assistant.",
-    options: new ChatClientAgentOptions
-    {
-        Tools = [sendEmail],  // direct-only tool
-        AIContextProviders = [codeact],
-    });
-
-await using var session = await agent.CreateSessionAsync();
-var response = await agent.InvokeAsync("Analyze the latest docs", session);
-```
-
-### Standard code interpreter mode
-
-```csharp
-var codeact = new HyperlightCodeActProvider(new HyperlightCodeActProviderOptions
-{
-    WorkspaceRoot = "./data",
-});
-
-var agent = chatClient.AsAIAgent(
-    instructions: "You are a code interpreter.",
-    options: new ChatClientAgentOptions
-    {
-        AIContextProviders = [codeact],
-    });
-```
-
-### Manual static wiring (no provider lifecycle)
-
-When the tool registry and capability configuration are fixed, the provider lifecycle can be skipped entirely. Build the `execute_code` function and instructions once and pass them directly to the agent:
-
-```csharp
-using var executeCode = new HyperlightExecuteCodeFunction(
-    new HyperlightCodeActProviderOptions
-    {
-        Tools = [fetchDocs, queryData],
-        WorkspaceRoot = "./workdir",
-        AllowedDomains = [new AllowedDomain("api.github.com", ["GET"])],
-    });
-
-var codeactInstructions = executeCode.BuildInstructions(toolsVisibleToModel: false);
-
-var agent = chatClient.AsAIAgent(
-    instructions: $"You are a helpful assistant.\n\n{codeactInstructions}",
-    options: new ChatClientAgentOptions
-    {
-        Tools = [sendEmail, executeCode.AsAIFunction()],
-    });
-```
-
-### With approval required
-
-```csharp
-var sensitiveAction = new ApprovalRequiredAIFunction(
-    AIFunctionFactory.Create(DeleteRecords, name: "delete_records"));
-
-var codeact = new HyperlightCodeActProvider(new HyperlightCodeActProviderOptions
-{
-    Tools = [fetchDocs, sensitiveAction],  // sensitiveAction triggers approval
-});
-
-// execute_code will be wrapped in ApprovalRequiredAIFunction because
-// at least one managed tool (delete_records) requires approval.
-var agent = chatClient.AsAIAgent(
-    instructions: "You are a helpful assistant.",
-    options: new ChatClientAgentOptions
-    {
-        AIContextProviders = [codeact],
-    });
-```
-
-## Relationship to hyperlight-sandbox .NET SDK
-
-This design depends on the .NET SDK being added in [hyperlight-dev/hyperlight-sandbox#46](https://github.com/hyperlight-dev/hyperlight-sandbox/pull/46). Key types consumed from that SDK:
-
-| hyperlight-sandbox type | Used for |
-|---|---|
-| `Sandbox` | Core sandbox lifecycle: `Run()`, `RegisterTool()`, `AllowDomain()`, `Snapshot()`, `Restore()` |
-| `SandboxBuilder` | Fluent sandbox construction from provider options |
-| `SandboxBackend` | Backend selection (Wasm, JavaScript) |
-| `ExecutionResult` | Capturing stdout, stderr, exit code from guest execution |
-| `SandboxSnapshot` | Checkpoint/restore for clean state per execution |
-
-The provider package (`Microsoft.Agents.AI.Hyperlight`) takes a NuGet dependency on `Hyperlight.HyperlightSandbox.Api` and `Microsoft.Extensions.AI.Abstractions`. It does **not** depend on `HyperlightSandbox.Extensions.AI` (`CodeExecutionTool`) — the provider implements its own sandbox lifecycle management with run-scoped snapshots to support concurrent invocations safely.
-
-## Package structure
-
-The CodeAct Hyperlight provider ships as an optional NuGet package:
- **Package**: `Microsoft.Agents.AI.Hyperlight`
- **Dependencies**:
-  - `Microsoft.Agents.AI.Abstractions` (for `AIContextProvider`, `AIContext`)
-  - `Microsoft.Extensions.AI.Abstractions` (for `AIFunction`, `ApprovalRequiredAIFunction`)
-  - `Hyperlight.HyperlightSandbox.Api` (for sandbox API)
- **Target framework**: `net8.0`
-
-This keeps CodeAct and its native sandbox dependencies optional — users who do not need CodeAct do not take on the Hyperlight installation and dependency footprint.
-
-## Open questions
-
-1. **Guest module distribution**: How should the default Python guest module (`.aot` file) be distributed for .NET consumers? Options include a separate NuGet package with native assets, a runtime download, or requiring users to build/provide their own.
-2. **Async tool registration**: If the Hyperlight .NET SDK adds async tool callback support in a future release, the sync-over-async bridge should be replaced. This is tracked as a known technical debt item.
-3. **Output file access**: The Hyperlight sandbox exposes `GetOutputFiles()` and `OutputPath` for retrieving files written by guest code. The initial design returns these as part of the JSON result. A future iteration could surface output files as framework-native content (e.g., `DataContent` or URI references).
-4. **Multiple sandbox instances for concurrency**: The current design uses synchronized access to a single sandbox with snapshot/restore. An alternative pooling strategy (one sandbox per concurrent run) could improve throughput at the cost of memory. This is deferred to implementation time.
@@ -1,385 +0,0 @@
-# CodeAct Python implementation
-
-This document describes the Python realization of the CodeAct design in
-[`docs/decisions/0024-codeact-integration.md`](../../decisions/0024-codeact-integration.md).
-
-This document is intentionally focused on the Python design and public API surface.
-The initial public Python type described here is `HyperlightCodeActProvider`. Future Python backends, such as Monty, should follow the same conceptual model with their own concrete provider types rather than through a public abstract base class or a public executor parameter.
-
-## What is the goal of this feature?
-
-Goals:
- Python developers can enable CodeAct through a `ContextProvider`-based integration.
- Developers can configure a provider-owned CodeAct tool set that is separate from the agent's direct `tools=` surface.
- Developers can use the same `execute_code` concept for both tool-enabled CodeAct and a standard code interpreter tool implementation.
- Developers can swap execution backends over time, starting with Hyperlight while keeping room for alternatives such as Pydantic's Monty.
- Developers can configure execution capabilities such as workspace mounts and outbound network allow lists in a portable way.
-
-Success Metric:
- Python samples exist for both a tool-enabled CodeAct mode and a standard interpreter mode.
-
-Implementation-free outcome:
- A Python developer can attach a backend-specific CodeAct provider, choose which tools are available inside CodeAct, and configure execution capabilities without rewriting the function invocation loop.
-
-## What is the problem being solved?
-
-The cross-SDK problem statement and decision rationale live in the [ADR](../../decisions/0024-codeact-integration.md). The items below narrow that statement to Python-specific design concerns:
-
- Today, the easiest way to prototype CodeAct is to infer or reshape the agent's direct tool surface, which is fragile and hard to reason about.
- In Python, inferring a CodeAct tool surface from generic agent tool configuration is fragile and hard to reason about.
- There is no first-class Python design that simultaneously covers Hyperlight-backed CodeAct now, future backend-specific providers such as Monty, and both tool-enabled and interpreter modes.
- Sandbox capabilities such as mounted file access and outbound network access need a portable configuration model instead of ad hoc backend-specific wiring.
- Approval behavior needs to be explicit and configurable, especially when CodeAct and direct tool calling may both be available.
-
-## API Changes
-
-### CodeAct contract
-
-#### Terminology
-
- **CodeAct** is the primary term.
- **Code mode**, **codemode**, and **programmatic tool calling** refer to the same concept in this document.
- `execute_code` is the model-facing tool name used by the initial Python providers in this spec.
-
-#### Provider-owned CodeAct tool registry
-
-A concrete Python CodeAct provider owns the set of tools available through `call_tool(...)` inside CodeAct.
-
-Rules:
- Only tools explicitly configured on the concrete provider instance are available inside CodeAct.
- The provider must not infer its CodeAct-managed tool set from the agent's direct `tools=` configuration.
- Exclusive versus mixed behavior is achieved by where tools are configured, not by rewriting the agent's direct tool list.
-
-Implications:
- **CodeAct-only tool**: configured on the concrete CodeAct provider only.
- **Direct-only tool**: configured on the agent only.
- **Tool available both ways**: configured on both the agent and the concrete CodeAct provider.
-
-#### Managing tools and capabilities after provider construction
-
-There is no separate runtime setup object in the Python design. CodeAct tools, file mounts, and outbound network allow-list state are managed directly on the provider through CRUD-style registry methods.
-
-Preferred pattern:
- `add_tools(...) -> None`
- `get_tools() -> Sequence[ToolTypes]`
- `remove_tool(...) -> None`
- `clear_tools() -> None`
- `add_file_mounts(...) -> None`
- `get_file_mounts() -> Sequence[FileMount]`
- `remove_file_mount(...) -> None`
- `clear_file_mounts() -> None`
- `add_allowed_domains(...) -> None`
- `get_allowed_domains() -> Sequence[AllowedDomain]`
- `remove_allowed_domain(...) -> None`
- `clear_allowed_domains() -> None`
-
-Requirements:
- The provider-owned CodeAct tool registry is keyed by tool name.
- `add_tools(...)` adds new tools and replaces an existing provider-owned registration when the same tool name is added again.
- `get_tools()` returns the provider's current configured CodeAct tool registry.
- `remove_tool(...)` removes provider-owned CodeAct tools by name.
- `clear_tools()` removes all provider-owned CodeAct tools.
- File mounts are keyed by sandbox mount path.
- `add_file_mounts(...)` adds new file mounts and replaces an existing mount when the same mount path is added again.
- `get_file_mounts()` returns the provider's current configured file mounts.
- `remove_file_mount(...)` removes file mounts by mount path.
- `clear_file_mounts()` removes all configured file mounts.
- Allowed domains are keyed by normalized target string.
- `add_allowed_domains(...)` adds allow-list entries and replaces an existing entry when the same target is added again.
- `get_allowed_domains()` returns the current outbound allow-list entries.
- `remove_allowed_domain(...)` removes allow-list entries by target.
- `clear_allowed_domains()` removes all configured allow-list entries.
- Tool, file-mount, and network-allow-list mutations affect subsequent runs only; runs already in progress keep the snapshot captured at run start.
- The provider must snapshot its effective tool registry and capability state at the start of each run so concurrent execution remains deterministic.
-
-#### Approval model
-
-The initial Python design follows the ADR's initial approval decision and reuses the existing tool approval vocabulary from `agent_framework._tools`:
-
- `approval_mode="always_require"`
- `approval_mode="never_require"`
-
-The provider exposes a default `approval_mode` for `execute_code`.
-
-Effective `execute_code` approval is computed as follows:
-
- If the provider default is `always_require`, `execute_code` requires approval.
- If the provider default is `never_require`, the provider evaluates the provider-owned CodeAct tool registry snapshot for that run.
- If every provider-owned CodeAct tool in that snapshot is `never_require`, `execute_code` is `never_require`.
- If any provider-owned CodeAct tool in that snapshot is `always_require`, `execute_code` is `always_require`, even if the generated code may not call that tool.
- Provider-owned tool calls made through `call_tool(...)` during that execution run use the approval already determined for `execute_code`.
- Direct-only agent tools are excluded from this calculation.
- File and network capabilities do not create a separate runtime approval check in the initial model; configuring them on the provider, including adding file mounts or outbound network allow-list entries, is itself the approval for those capabilities.
-
-This is intentionally conservative and matches the shape of the current function-tool approval flow, where `FunctionTool` uses `always_require` / `never_require` and the auto-invocation loop escalates the whole batch if any called tool requires approval.
-
-If one sensitive provider-owned tool causes `execute_code` to require approval more often than desired, the mitigation is to keep that tool direct-only or expose it through a different CodeAct provider/tool surface. The initial model does not try to infer whether generated code will actually call that tool before approval.
-
-If the framework later standardizes pre-execution inspection or nested per-tool approvals, the Python provider surface can grow to expose that explicitly. The initial design does not assume that those extra modes are required.
-
-#### Shared execution flow
-
-On each run:
-1. Resolve the provider's backend/runtime behavior, capabilities, provider default `approval_mode`, and provider-owned tool registry.
-2. Compute the effective approval requirement for `execute_code` from the provider default plus the provider-owned tool registry snapshot.
-3. Build provider-defined instructions.
-4. Add `execute_code` to the model-facing tool surface.
-5. Invoke the underlying model.
-6. When `execute_code` is called, create or reuse an execution environment keyed by provider type, backend setup identity, capability configuration, and provider-owned tool signature.
-7. If the current provider mode exposes host tools, expose `call_tool(...)` bound only to the provider-owned tool registry.
-8. Execute code and convert results to framework-native content objects.
-
-Caching rules:
- Backends that support snapshots may cache a reusable clean snapshot.
- Backends that do not support snapshots may still cache warm initialization artifacts.
- No mutable per-run execution state may be shared across concurrent runs.
- In-memory interpreter state does not persist across separate `execute_code` calls.
- Configured workspace files, mounted files, and any writable artifact/output area are the supported persistence mechanism across calls when the backend exposes them.
-
-### Python public API
-
-#### Core types
-
-```python
-class FileMount(NamedTuple):
-    host_path: str | Path
-    mount_path: str
-
-FileMountInput = str | tuple[str | Path, str] | FileMount
-
-
-class AllowedDomain(NamedTuple):
-    target: str
-    methods: tuple[str, ...] | None = None
-
-
-AllowedDomainInput = str | tuple[str, str | Sequence[str]] | AllowedDomain
-
-
-class HyperlightCodeActProvider(ContextProvider):
-    def __init__(
-        self,
-        source_id: str = "hyperlight_codeact",
-        *,
-        backend: str = "wasm",
-        module: str | None = "python_guest.path",
-        module_path: str | None = None,
-        tools: ToolTypes | None = None,
-        approval_mode: Literal["always_require", "never_require"] = "never_require",
-        workspace_root: Path | None = None,
-        file_mounts: Sequence[FileMountInput] = (),
-        allowed_domains: Sequence[AllowedDomainInput] = (),
-    ) -> None: ...
-
-    def add_tools(self, tools: ToolTypes | Sequence[ToolTypes]) -> None: ...
-    def get_tools(self) -> Sequence[ToolTypes]: ...
-    def remove_tool(self, name: str) -> None: ...
-    def clear_tools(self) -> None: ...
-    def add_file_mounts(self, mounts: FileMountInput | Sequence[FileMountInput]) -> None: ...
-    def get_file_mounts(self) -> Sequence[FileMount]: ...
-    def remove_file_mount(self, mount_path: str) -> None: ...
-    def clear_file_mounts(self) -> None: ...
-    def add_allowed_domains(self, domains: AllowedDomainInput | Sequence[AllowedDomainInput]) -> None: ...
-    def get_allowed_domains(self) -> Sequence[AllowedDomain]: ...
-    def remove_allowed_domain(self, domain: str) -> None: ...
-    def clear_allowed_domains(self) -> None: ...
-```
-
-`file_mounts` accepts three equivalent input forms:
- `"data/report.csv"` uses the same relative path on the host and in the sandbox.
- `("fixtures/users.json", "data/users.json")` or `(Path("fixtures/users.json"), "data/users.json")` uses distinct host and sandbox paths.
- `FileMount(Path("fixtures/users.json"), "data/users.json")` is the named-tuple form of the explicit pair.
-
-`allowed_domains` accepts three equivalent input forms:
- `"github.com"` allows that target with all backend-supported methods.
- `("github.com", "GET")` or `("github.com", ["GET", "HEAD"])` uses an explicit per-target method list.
- `AllowedDomain("github.com", ("GET", "HEAD"))` is the named-tuple form of the explicit entry.
-
-No public abstract `CodeActContextProvider` base or public `executor=` parameter is required for the initial Python API.
-
-The initial alpha package also exports a standalone `HyperlightExecuteCodeTool`
-for direct-tool scenarios where a provider is not needed. That standalone tool
-should advertise `call_tool(...)`, the registered sandbox tools, and capability
-state through its own `description` rather than requiring separate agent
-instructions.
-
-Provider modes:
- If no CodeAct-managed tools are configured, `HyperlightCodeActProvider` uses interpreter-style behavior.
- If one or more CodeAct-managed tools are configured, `HyperlightCodeActProvider` uses tool-enabled behavior.
-
-#### Python provider implementation contract
-
-The concrete provider plugs into the existing Python `ContextProvider` surface from `agent_framework._sessions`.
-
-The Hyperlight package also depends on a small set of core hooks that must remain available from `agent-framework-core`:
- `ContextProvider.before_run(...)`
- `SessionContext.extend_instructions(...)`
- `SessionContext.extend_tools(...)`
- per-run runtime tool access via `SessionContext.options["tools"]`
- the shared `ApprovalMode` vocabulary used by `FunctionTool`
-
-Required lifecycle hook:
- `before_run(*, agent, session, context, state) -> None`
-
-Optional lifecycle hook:
- `after_run(*, agent, session, context, state) -> None`
-
-`before_run(...)` is responsible for:
- snapshotting the current CodeAct-managed tool registry and capability settings for the run,
- computing the effective approval requirement for `execute_code` from the provider default and the snapshotted tool registry,
- adding a short CodeAct guidance block,
- adding `execute_code` to the run through `SessionContext.extend_tools(...)`,
- and wiring any backend-specific execution state needed for the run.
-
-These steps run on every invocation rather than once at construction time because the provider supports CRUD mutations between runs, concurrent runs need independent snapshots, and the effective approval and instructions depend on the tool registry state captured at run start. When the tool registry and capability configuration are fixed for the lifetime of the agent, the manual wiring pattern (see `codeact_manual_wiring.py`) can be used instead, which passes the tool and instructions directly to the `Agent` constructor and avoids the per-run provider lifecycle entirely.
-
-If the provider stores anything in `state`, that value must stay JSON-serializable.
-
-Mutating the provider after `before_run(...)` has captured a run-scoped snapshot is allowed, but it affects subsequent runs only. Provider implementations should synchronize state capture and CRUD operations so shared provider instances remain safe across concurrent runs.
-
-`after_run(...)` is responsible for any backend-specific cleanup or post-processing that must happen after the model invocation completes.
-
-If shared internal helpers are introduced later for multiple concrete providers, they should standardize responsibilities for:
- building instructions,
- computing effective approval,
- configuring file access,
- configuring network access,
- preparing or restoring execution state,
- executing code,
- and converting backend output into framework-native `Content`.
-
-#### Runtime behavior
-
- `before_run(...)` adds a short CodeAct guidance block through `SessionContext.extend_instructions(...)`.
- `before_run(...)` adds `execute_code` through `SessionContext.extend_tools(...)`.
- The detailed `call_tool(...)`, sandbox-tool, and capability guidance is carried by `execute_code.description`.
- `execute_code` invokes the configured Hyperlight sandbox guest.
- If the current CodeAct tool registry is non-empty, the runtime injects `call_tool(...)` bound to the provider-owned tool registry.
- The provider does not inspect or mutate `Agent.default_options["tools"]` or `context.options["tools"]` to determine its CodeAct tool set.
- The provider snapshots the current CodeAct tool registry and capability state at run start, so later registry and allow-list mutations only affect future runs.
- Interpreter versus tool-enabled behavior is derived from the concrete provider and the presence of CodeAct-managed tools, not from a separate public profile object.
- `execute_code` should be traced like a normal tool invocation within the surrounding agent run, and provider-owned tool calls executed through `call_tool(...)` should continue to emit ordinary tool invocation telemetry.
-
-#### Backend integration
-
-Initial public provider:
- `HyperlightCodeActProvider`
-
-Backend-specific notes:
- **Hyperlight**
-  - Provider construction needs a guest artifact via `module`, which may be a packaged guest module name or a path to a compiled guest artifact.
-  - File access maps naturally to Hyperlight Sandbox's read-only `/input` and writable `/output` capability model.
-  - Network access is denied by default and is enabled through per-target allow-list entries.
- **Monty**
-  - A future `MontyCodeActProvider` should be a separate public type rather than a `HyperlightCodeActProvider` mode.
-  - Monty does not expose built-in filesystem or network access directly inside the interpreter.
-  - File and URL access are mediated through host-provided external functions, so a Monty provider would need to translate provider settings into virtual files and allow-checked callbacks.
-  - Monty setup may also include backend-specific inputs such as `script_name`, optional type-check stubs, or restored snapshots.
-
-#### Capability handling
-
-Capabilities are first-class `HyperlightCodeActProvider` init parameters and provider-managed CRUD surfaces:
- `workspace_root`
- `file_mounts`
- `allowed_domains`
-
-Concrete providers should normalize these settings internally. Hyperlight can map them directly to sandbox capabilities, while Monty must enforce them through host-mediated file and network functions and may apply stricter URL-level checks than the public provider surface expresses.
-
-Expected management split:
- `workspace_root` remains a direct configuration value on the provider,
- file mounts are managed through provider CRUD methods,
- outbound allow-list entries are managed through provider CRUD methods.
-
-Enabling access means:
- Configuring `workspace_root` or any `file_mounts` enables the sandbox filesystem surface exposed through `/input` and `/output`.
- Leaving both `workspace_root` and `file_mounts` unset means no filesystem surface is configured.
- Adding any `allowed_domains` entry enables outbound access only for the configured targets; leaving it empty means network access is disabled without a separate `network_mode` flag.
- A string target allows all backend-supported methods for that target; an explicit tuple or `AllowedDomain` entry narrows the methods for that target.
-
-Backends may implement stricter semantics than these top-level settings. For example, Hyperlight naturally maps file access to `/input` and `/output`, while Monty would enforce equivalent policy through host-provided callbacks rather than direct interpreter I/O.
-
-#### Execution output representation
-
-Backend execution output should be translated into existing AF `Content` values rather than a custom `CodeActExecutionResult` type.
-
-Use the existing content model from `agent_framework._types`, for example:
- `Content.from_code_interpreter_tool_result(outputs=[...])` to surface the overall result of sandboxed code execution,
- `Content.from_text(...)` for plain textual output,
- `Content.from_data(...)` or `Content.from_uri(...)` for generated files or binary artifacts,
- `Content.from_error(...)` for execution failures,
- and `Content.from_function_result(..., result=list[Content])` when surfacing the final result of `execute_code` through the normal tool result path.
-
-#### `execute_code` input contract
-
-```json
-{
-  "type": "object",
-  "properties": {
-    "code": {
-      "type": "string",
-      "description": "Code to execute using the provider's configured backend/runtime behavior."
-    }
-  },
-  "required": ["code"]
-}
-```
-
-Execution failures should surface readable error text and structured error `Content`, not a custom backend result object.
-
-Timeouts, out-of-memory conditions, backend crashes, and similar sandbox failures are all `execute_code` failures and should surface as structured error content. Partial textual or file outputs may be returned only when the backend can report them unambiguously; callers should not rely on partial-output recovery as a portable contract.
-
-## E2E Code Samples
-
-### Tool-enabled CodeAct mode
-
-```python
-codeact = HyperlightCodeActProvider(
-    tools=[fetch_docs, query_data],
-    workspace_root="./workdir",
-    allowed_domains=[("api.github.com", "GET")],
-)
-codeact.add_tools([lookup_user])
-
-agent = Agent(
-    client=client,
-    name="assistant",
-    tools=[send_email],  # direct-only tool
-    context_providers=[codeact],
-)
-```
-
-### Standard code interpreter mode
-
-```python
-codeact = HyperlightCodeActProvider(
-    workspace_root="./data",
-)
-
-agent = Agent(
-    client=client,
-    name="interpreter",
-    context_providers=[codeact],
-)
-```
-
-### Manual static wiring (no per-run provider lifecycle)
-
-When the tool registry and capability configuration are fixed, the provider lifecycle can be skipped entirely. Build the `execute_code` tool and instructions once and pass them directly to the agent:
-
-```python
-execute_code = HyperlightExecuteCodeTool(
-    tools=[fetch_docs, query_data],
-    workspace_root="./workdir",
-    allowed_domains=[("api.github.com", "GET")],
-    approval_mode="never_require",
-)
-
-codeact_instructions = execute_code.build_instructions(tools_visible_to_model=False)
-
-agent = Agent(
-    client=client,
-    name="assistant",
-    instructions=f"You are a helpful assistant.\n\n{codeact_instructions}",
-    tools=[send_email, execute_code],
-)
-```
@@ -9,16 +9,9 @@ The `verify-samples` project (`dotnet/eng/verify-samples/`) is an automated tool

 ## Running verify-samples

-**Important:** By default, samples must be pre-built before running verify-samples. Build the solution first, or pass `--build` to build samples during the run:
-
 ```bash
 cd dotnet
-dotnet build agent-framework-dotnet.slnx -f net10.0
-```

-Then run verify-samples:
-
-```bash
 # Run all samples across all categories
 dotnet run --project eng/verify-samples -- --log results.log --csv results.csv

@@ -31,10 +24,6 @@ dotnet run --project eng/verify-samples -- Agent_Step02_StructuredOutput Agent_S
 # Control parallelism (default 8)
 dotnet run --project eng/verify-samples -- --parallel 8 --log results.log

-# Build samples during run (skips the need for a prior build step)
-# This may cause build conflicts as multiple samples are built in parallel, so use with caution
-dotnet run --project eng/verify-samples -- --build --log results.log
-
 # Combine options
 dotnet run --project eng/verify-samples -- --category 03-workflows --parallel 4 --log results.log --csv results.csv --md results.md
 ```
@@ -402,11 +402,4 @@ FodyWeavers.xsd
 *.msp

 # JetBrains Rider
-*.sln.iml
-
-# Foundry agent CLI config (contains secrets, auto-generated)
-.foundry-agent.json
-.foundry-agent-build.log
-
-# Pre-published output for Docker builds
-out/
+*.sln.iml
@@ -4,9 +4,8 @@
  <!-- https://learn.microsoft.com/en-us/nuget/consume-packages/Central-Package-Management -->
  <Sdk Name="Microsoft.Build.CentralPackageVersions" Version="2.1.3" />
  <!-- Only run 'dotnet format' on dev machines, Release builds. Skip on GitHub Actions -->
-  <!-- as this runs in its own Actions job. Only run for net10.0 target frameworks since the dotnet format command -->
-  <!-- already formats all target frameworks in project. Otherwise it will run format x times x where x is the number of target frameworks -->
-  <Target Name="DotnetFormatOnBuild" BeforeTargets="Build" Condition=" '$(Configuration)' == 'Release' AND '$(GITHUB_ACTIONS)' == '' AND '$(TargetFramework)' == 'net10.0' ">
+  <!-- as this runs in its own Actions job. -->
+  <Target Name="DotnetFormatOnBuild" BeforeTargets="Build" Condition=" '$(Configuration)' == 'Release' AND '$(GITHUB_ACTIONS)' == '' ">
    <Message Text="Running dotnet format" Importance="high" />
    <Exec Command="dotnet format --no-restore -v diag $(ProjectFileName)" />
  </Target>
@@ -7,31 +7,23 @@
  </PropertyGroup>
  <PropertyGroup>
    <!-- Aspire -->
-    <AspireAppHostSdkVersion>13.1.0</AspireAppHostSdkVersion>
+    <AspireAppHostSdkVersion>13.0.2</AspireAppHostSdkVersion>
  </PropertyGroup>
  <ItemGroup>
    <!-- Aspire.* -->
-    <PackageVersion Include="Anthropic" Version="12.13.0" />
-    <PackageVersion Include="Anthropic.Foundry" Version="0.5.0" />
-    <PackageVersion Include="Aspire.Hosting" Version="$(AspireAppHostSdkVersion)" />
+    <PackageVersion Include="Anthropic" Version="12.11.0" />
+    <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.Azure.AI.Inference" Version="13.1.0-preview.1.25616.3" />
-    <PackageVersion Include="Aspire.Hosting.Azure.AIFoundry" Version="13.1.0-preview.1.25616.3" />
    <PackageVersion Include="Aspire.Hosting.AppHost" Version="$(AspireAppHostSdkVersion)" />
    <PackageVersion Include="Aspire.Hosting.Azure.CognitiveServices" Version="$(AspireAppHostSdkVersion)" />
    <PackageVersion Include="Aspire.Microsoft.Azure.Cosmos" Version="$(AspireAppHostSdkVersion)" />
    <PackageVersion Include="CommunityToolkit.Aspire.OllamaSharp" Version="13.0.0" />
    <!-- Azure.* -->
-    <PackageVersion Include="Azure.AI.AgentServer.Core" Version="1.0.0-beta.22" />
-    <PackageVersion Include="Azure.AI.AgentServer.Invocations" Version="1.0.0-beta.1" />
-    <PackageVersion Include="Azure.AI.AgentServer.Responses" Version="1.0.0-beta.3" />
    <PackageVersion Include="Azure.AI.Projects" Version="2.0.0" />
    <PackageVersion Include="Azure.AI.Agents.Persistent" Version="1.2.0-beta.10" />
    <PackageVersion Include="Azure.AI.OpenAI" Version="2.9.0-beta.1" />
-    <PackageVersion Include="Azure.Core" Version="1.53.0" />
-    <PackageVersion Include="Azure.Identity" Version="1.21.0" />
-    <PackageVersion Include="DotNetEnv" Version="3.1.1" />
-    <PackageVersion Include="Azure.Monitor.OpenTelemetry.Exporter" Version="1.5.0" />
+    <PackageVersion Include="Azure.Identity" Version="1.20.0" />
+    <PackageVersion Include="Azure.Monitor.OpenTelemetry.Exporter" Version="1.4.0" />
    <!-- Google Gemini  -->
    <PackageVersion Include="Google.GenAI" Version="1.6.0" />
    <PackageVersion Include="Mscc.GenerativeAI.Microsoft" Version="2.9.3" />
@@ -40,62 +32,68 @@
    <!-- Newtonsoft.Json -->
    <PackageVersion Include="Newtonsoft.Json" Version="13.0.4" />
    <!-- System.* -->
-    <PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.6" />
+    <PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.4" />
    <PackageVersion Include="Microsoft.Bcl.HashCode" Version="6.0.0" />
-    <PackageVersion Include="Microsoft.Bcl.Memory" Version="10.0.5" />
+    <PackageVersion Include="Microsoft.Bcl.Memory" Version="10.0.4" />
    <PackageVersion Include="System.ClientModel" Version="1.10.0" />
    <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="10.0.6" />
-    <PackageVersion Include="System.Linq.AsyncEnumerable" Version="10.0.5" />
+    <PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="10.0.4" />
+    <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="10.0.5" />
-    <PackageVersion Include="System.Text.Json" Version="10.0.6" />
-    <PackageVersion Include="System.Threading.Channels" Version="10.0.6" />
+    <PackageVersion Include="System.Net.ServerSentEvents" Version="10.0.4" />
+    <PackageVersion Include="System.Text.Json" Version="10.0.4" />
+    <PackageVersion Include="System.Threading.Channels" Version="10.0.4" />
    <PackageVersion Include="System.Threading.Tasks.Extensions" Version="4.6.3" />
    <PackageVersion Include="System.Net.Security" Version="4.3.2" />
    <!-- OpenTelemetry -->
-    <PackageVersion Include="OpenTelemetry" Version="1.15.0" />
-    <PackageVersion Include="OpenTelemetry.Api" Version="1.15.0" />
-    <PackageVersion Include="OpenTelemetry.Exporter.Console" Version="1.15.0" />
-    <PackageVersion Include="OpenTelemetry.Exporter.InMemory" Version="1.15.0" />
-    <PackageVersion Include="OpenTelemetry.Exporter.OpenTelemetryProtocol" Version="1.15.0" />
-    <PackageVersion Include="OpenTelemetry.Extensions.Hosting" Version="1.14.0" />
-    <PackageVersion Include="OpenTelemetry.Instrumentation.AspNetCore" Version="1.14.0" />
-    <PackageVersion Include="OpenTelemetry.Instrumentation.Http" Version="1.14.0" />
-    <PackageVersion Include="OpenTelemetry.Instrumentation.Runtime" Version="1.14.0" />
+    <PackageVersion Include="OpenTelemetry" Version="1.13.1" />
+    <PackageVersion Include="OpenTelemetry.Api" Version="1.13.1" />
+    <PackageVersion Include="OpenTelemetry.Exporter.Console" Version="1.13.1" />
+    <PackageVersion Include="OpenTelemetry.Exporter.InMemory" Version="1.13.1" />
+    <PackageVersion Include="OpenTelemetry.Exporter.OpenTelemetryProtocol" Version="1.13.1" />
+    <PackageVersion Include="OpenTelemetry.Extensions.Hosting" Version="1.13.1" />
+    <PackageVersion Include="OpenTelemetry.Instrumentation.AspNetCore" Version="1.13.0" />
+    <PackageVersion Include="OpenTelemetry.Instrumentation.Http" Version="1.13.0" />
+    <PackageVersion Include="OpenTelemetry.Instrumentation.Runtime" Version="1.13.0" />
    <!-- Microsoft.AspNetCore.* -->
    <PackageVersion Include="Microsoft.AspNetCore.Authentication.JwtBearer" Version="10.0.0" />
    <PackageVersion Include="Microsoft.AspNetCore.Authentication.OpenIdConnect" Version="10.0.0" />
    <PackageVersion Include="Microsoft.AspNetCore.OpenApi" Version="10.0.0" />
    <PackageVersion Include="Swashbuckle.AspNetCore.SwaggerUI" Version="10.0.0" />
    <!-- Microsoft.Extensions.* -->
-    <PackageVersion Include="Microsoft.Extensions.AI" Version="10.5.0" />
-    <PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.5.0" />
+    <PackageVersion Include="Microsoft.Extensions.AI" Version="10.4.0" />
+    <PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.4.0" />
    <PackageVersion Include="Microsoft.Extensions.AI.Evaluation" Version="10.4.0" />
    <PackageVersion Include="Microsoft.Extensions.AI.Evaluation.Quality" Version="10.4.0" />
    <PackageVersion Include="Microsoft.Extensions.AI.Evaluation.Safety" Version="10.3.0-preview.1.26109.11" />
-    <PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.5.0" />
+    <PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.4.0" />
    <PackageVersion Include="Microsoft.Extensions.Caching.Memory" Version="10.0.0" />
-    <PackageVersion Include="Microsoft.Extensions.Compliance.Abstractions" Version="10.5.0" />
-    <PackageVersion Include="Microsoft.Extensions.Configuration" Version="10.0.1" />
-    <PackageVersion Include="Microsoft.Extensions.Configuration.Binder" Version="10.0.1" />
-    <PackageVersion Include="Microsoft.Extensions.Configuration.EnvironmentVariables" Version="10.0.1" />
-    <PackageVersion Include="Microsoft.Extensions.Configuration.Json" Version="10.0.1" />
-    <PackageVersion Include="Microsoft.Extensions.Configuration.UserSecrets" Version="10.0.1" />
-    <PackageVersion Include="Microsoft.Extensions.DependencyInjection" Version="10.0.1" />
-    <PackageVersion Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="10.0.6" />
-    <PackageVersion Include="Microsoft.Extensions.Hosting" Version="10.0.1" />
+    <PackageVersion Include="Microsoft.Extensions.Compliance.Abstractions" Version="10.4.0" />
+    <PackageVersion Include="Microsoft.Extensions.Configuration" Version="10.0.0" />
+    <PackageVersion Include="Microsoft.Extensions.Configuration.Binder" Version="10.0.0" />
+    <PackageVersion Include="Microsoft.Extensions.Configuration.EnvironmentVariables" Version="10.0.0" />
+    <PackageVersion Include="Microsoft.Extensions.Configuration.Json" Version="10.0.0" />
+    <PackageVersion Include="Microsoft.Extensions.Configuration.UserSecrets" Version="10.0.0" />
+    <PackageVersion Include="Microsoft.Extensions.DependencyInjection" Version="10.0.0" />
+    <PackageVersion Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="10.0.4" />
+    <PackageVersion Include="Microsoft.Extensions.Hosting" Version="10.0.0" />
    <PackageVersion Include="Microsoft.Extensions.Http.Resilience" Version="10.0.0" />
-    <PackageVersion Include="Microsoft.Extensions.Logging" Version="10.0.1" />
-    <PackageVersion Include="Microsoft.Extensions.Logging.Abstractions" Version="10.0.6" />
-    <PackageVersion Include="Microsoft.Extensions.Logging.Console" Version="10.0.1" />
+    <PackageVersion Include="Microsoft.Extensions.Logging" Version="10.0.0" />
+    <PackageVersion Include="Microsoft.Extensions.Logging.Abstractions" Version="10.0.4" />
+    <PackageVersion Include="Microsoft.Extensions.Logging.Console" Version="10.0.0" />
    <PackageVersion Include="Microsoft.Extensions.ServiceDiscovery" Version="10.0.0" />
    <PackageVersion Include="Microsoft.Extensions.VectorData.Abstractions" Version="9.7.0" />
    <!-- Vector Stores -->
    <PackageVersion Include="Microsoft.SemanticKernel.Connectors.InMemory" Version="1.67.0-preview" />
    <PackageVersion Include="Microsoft.SemanticKernel.Connectors.Qdrant" Version="1.67.0-preview" />
+    <!-- Semantic Kernel -->
+    <PackageVersion Include="Microsoft.SemanticKernel" Version="1.67.0" />
+    <PackageVersion Include="Microsoft.SemanticKernel.Agents.Core" Version="1.67.0" />
+    <PackageVersion Include="Microsoft.SemanticKernel.Agents.OpenAI" Version="1.67.0-preview" />
+    <PackageVersion Include="Microsoft.SemanticKernel.Agents.AzureAI" Version="1.67.0-preview" />
+    <PackageVersion Include="Microsoft.SemanticKernel.Plugins.OpenApi" Version="1.67.0" />
    <!-- Agent SDKs -->
    <PackageVersion Include="GitHub.Copilot.SDK" Version="0.1.29" />
    <PackageVersion Include="Microsoft.Agents.CopilotStudio.Client" Version="1.3.171-beta" />
@@ -104,15 +102,16 @@
    <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="1.0.0-preview2" />
-    <PackageVersion Include="A2A.AspNetCore" Version="1.0.0-preview2" />
+    <PackageVersion Include="A2A" Version="0.3.4-preview" />
+    <PackageVersion Include="A2A.AspNetCore" Version="0.3.4-preview" />
    <!-- MCP -->
    <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="2.10.0" />
+    <PackageVersion Include="OpenAI" Version="2.9.1" />
    <!-- Identity -->
    <PackageVersion Include="Microsoft.Identity.Client.Extensions.Msal" Version="4.83.1" />
    <!-- Workflows -->
@@ -127,6 +126,7 @@
    <PackageVersion Include="Microsoft.DurableTask.Worker.AzureManaged" Version="1.18.0" />
    <!-- Azure Functions -->
    <PackageVersion Include="Microsoft.Azure.Functions.Worker" Version="2.50.0" />
+    <PackageVersion Include="Microsoft.Azure.Functions.Worker.ApplicationInsights" Version="2.50.0" />
    <PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" Version="1.12.1" />
    <PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" Version="1.0.1" />
    <PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Http" Version="3.3.0" />
@@ -1,12 +1,9 @@
-<Solution>
+<Solution>
  <Configurations>
    <BuildType Name="Debug" />
    <BuildType Name="Publish" />
    <BuildType Name="Release" />
  </Configurations>
-  <Folder Name="/src/Aspire.Hosting.AgentFramework.DevUI/">
-    <Project Path="src/Aspire.Hosting.AgentFramework.DevUI/Aspire.Hosting.AgentFramework.DevUI.csproj" />
-  </Folder>
  <Folder Name="/Samples/">
    <File Path="samples/AGENTS.md" />
    <File Path="samples/README.md" />
@@ -40,12 +37,6 @@
    <Project Path="samples/02-agents/AgentProviders/Agent_With_OpenAIChatCompletion/Agent_With_OpenAIChatCompletion.csproj" />
    <Project Path="samples/02-agents/AgentProviders/Agent_With_OpenAIResponses/Agent_With_OpenAIResponses.csproj" />
  </Folder>
-  <Folder Name="/Samples/05-end-to-end/DevUIAspireIntegration/">
-    <Project Path="samples/05-end-to-end/DevUIAspireIntegration/DevUIIntegration.AppHost/DevUIIntegration.AppHost.csproj" />
-    <Project Path="samples/05-end-to-end/DevUIAspireIntegration/DevUIIntegration.ServiceDefaults/DevUIIntegration.ServiceDefaults.csproj" />
-    <Project Path="samples/05-end-to-end/DevUIAspireIntegration/EditorAgent/EditorAgent.csproj" />
-    <Project Path="samples/05-end-to-end/DevUIAspireIntegration/WriterAgent/WriterAgent.csproj" />
-  </Folder>
  <Folder Name="/Samples/02-agents/Agents/">
    <File Path="samples/02-agents/Agents/README.md" />
    <Project Path="samples/02-agents/Agents/Agent_Step01_UsingFunctionToolsWithApprovals/Agent_Step01_UsingFunctionToolsWithApprovals.csproj" />
@@ -161,13 +152,6 @@
    <Project Path="samples/02-agents/AgentsWithFoundry/Agent_Step21_WebSearch/Agent_Step21_WebSearch.csproj" />
    <Project Path="samples/02-agents/AgentsWithFoundry/Agent_Step22_MemorySearch/Agent_Step22_MemorySearch.csproj" />
    <Project Path="samples/02-agents/AgentsWithFoundry/Agent_Step23_LocalMCP/Agent_Step23_LocalMCP.csproj" />
-    <Project Path="samples/02-agents/AgentsWithFoundry/Agent_Step24_CodeInterpreterFileDownload/Agent_Step24_CodeInterpreterFileDownload.csproj" />
-  </Folder>
-  <Folder Name="/Samples/02-agents/Evaluation/">
-    <Project Path="samples/02-agents/Evaluation/Evaluation_SimpleEval/Evaluation_SimpleEval.csproj" />
-    <Project Path="samples/02-agents/Evaluation/Evaluation_CustomEvals/Evaluation_CustomEvals.csproj" />
-    <Project Path="samples/02-agents/Evaluation/Evaluation_ExpectedOutputs/Evaluation_ExpectedOutputs.csproj" />
-    <Project Path="samples/02-agents/Evaluation/Evaluation_Multimodal/Evaluation_Multimodal.csproj" />
  </Folder>
  <Folder Name="/Samples/02-agents/AgentWithMemory/">
    <File Path="samples/02-agents/AgentWithMemory/README.md" />
@@ -183,7 +167,6 @@
    <Project Path="samples/02-agents/AgentWithOpenAI/Agent_OpenAI_Step03_CreateFromChatClient/Agent_OpenAI_Step03_CreateFromChatClient.csproj" />
    <Project Path="samples/02-agents/AgentWithOpenAI/Agent_OpenAI_Step04_CreateFromOpenAIResponseClient/Agent_OpenAI_Step04_CreateFromOpenAIResponseClient.csproj" />
    <Project Path="samples/02-agents/AgentWithOpenAI/Agent_OpenAI_Step05_Conversation/Agent_OpenAI_Step05_Conversation.csproj" />
-    <Project Path="samples/02-agents/AgentWithOpenAI/Agent_OpenAI_Step06_CodeInterpreterFileDownload/Agent_OpenAI_Step06_CodeInterpreterFileDownload.csproj" />
  </Folder>
  <Folder Name="/Samples/02-agents/AgentWithRAG/">
    <File Path="samples/02-agents/AgentWithRAG/README.md" />
@@ -260,9 +243,6 @@
  <Folder Name="/Samples/03-workflows/HumanInTheLoop/">
    <Project Path="samples/03-workflows/HumanInTheLoop/HumanInTheLoopBasic/HumanInTheLoopBasic.csproj" />
  </Folder>
-  <Folder Name="/Samples/03-workflows/Orchestration/">
-    <Project Path="samples/03-workflows/Orchestration/Handoff/Handoff.csproj" />
-  </Folder>
  <Folder Name="/Samples/03-workflows/Observability/">
    <Project Path="samples/03-workflows/Observability/ApplicationInsights/ApplicationInsights.csproj" />
    <Project Path="samples/03-workflows/Observability/AspireDashboard/AspireDashboard.csproj" />
@@ -280,47 +260,7 @@
    <Project Path="samples/03-workflows/_StartHere/06_MixedWorkflowAgentsAndExecutors/06_MixedWorkflowAgentsAndExecutors.csproj" />
    <Project Path="samples/03-workflows/_StartHere/07_WriterCriticWorkflow/07_WriterCriticWorkflow.csproj" />
  </Folder>
-  <Folder Name="/Samples/03-workflows/Evaluation/">
-    <Project Path="samples/03-workflows/Evaluation/Evaluation_WorkflowEval/Evaluation_WorkflowEval.csproj" />
-  </Folder>
-  <Folder Name="/Samples/04-hosting/">
-  </Folder>
-  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/" />
-  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/invocations/" />
-  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/invocations/Hosted-Invocations-EchoAgent/">
-    <Project Path="samples/04-hosting/FoundryHostedAgents/invocations/Hosted-Invocations-EchoAgent/Hosted-Invocations-EchoAgent.csproj" />
-  </Folder>
-  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/invocations/Using-Samples/">
-    <Project Path="samples/04-hosting/FoundryHostedAgents/invocations/Using-Samples/SimpleInvocationsAgent/SimpleInvocationsAgent.csproj" />
-  </Folder>
-  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/" />
-  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-ChatClientAgent/">
-    <Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-ChatClientAgent/HostedChatClientAgent.csproj" />
-  </Folder>
-  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-FoundryAgent/">
-    <Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-FoundryAgent/HostedFoundryAgent.csproj" />
-  </Folder>
-  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-LocalTools/">
-    <Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-LocalTools/HostedLocalTools.csproj" />
-  </Folder>
-  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-McpTools/">
-    <Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-McpTools/HostedMcpTools.csproj" />
-  </Folder>
-  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-Toolbox/">
-    <Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-Toolbox/HostedToolbox.csproj" />
-  </Folder>
-  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-TextRag/">
-    <Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-TextRag/HostedTextRag.csproj" />
-  </Folder>
-  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-Workflow-Simple/">
-    <Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-Workflow-Simple/HostedWorkflowSimple.csproj" />
-  </Folder>
-  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Using-Samples/">
-    <Project Path="samples/04-hosting/FoundryHostedAgents/responses/Using-Samples/SimpleAgent/SimpleAgent.csproj" />
-  </Folder>
-  <Folder Name="/Samples/04-hosting/FoundryHostedAgents/responses/Hosted-Workflow-Handoff/">
-    <Project Path="samples/04-hosting/FoundryHostedAgents/responses/Hosted-Workflow-Handoff/HostedWorkflowHandoff.csproj" />
-  </Folder>
+  <Folder Name="/Samples/04-hosting/" />
  <Folder Name="/Samples/04-hosting/DurableAgents/" />
  <Folder Name="/Samples/04-hosting/DurableAgents/AzureFunctions/">
    <File Path="samples/04-hosting/DurableAgents/AzureFunctions/.editorconfig" />
@@ -344,22 +284,15 @@
    <Project Path="samples/04-hosting/DurableAgents/ConsoleApps/06_LongRunningTools/06_LongRunningTools.csproj" />
    <Project Path="samples/04-hosting/DurableAgents/ConsoleApps/07_ReliableStreaming/07_ReliableStreaming.csproj" />
  </Folder>
-  <Folder Name="/Samples/02-agents/A2A/">
-    <File Path="samples/02-agents/A2A/README.md" />
-    <Project Path="samples/02-agents/A2A/A2AAgent_AsFunctionTools/A2AAgent_AsFunctionTools.csproj" />
-    <Project Path="samples/02-agents/A2A/A2AAgent_PollingForTaskCompletion/A2AAgent_PollingForTaskCompletion.csproj" />
-    <Project Path="samples/02-agents/A2A/A2AAgent_StreamReconnection/A2AAgent_StreamReconnection.csproj" />
-    <Project Path="samples/02-agents/A2A/A2AAgent_ProtocolSelection/A2AAgent_ProtocolSelection.csproj" />
+  <Folder Name="/Samples/04-hosting/A2A/">
+    <File Path="samples/04-hosting/A2A/README.md" />
+    <Project Path="samples/04-hosting/A2A/A2AAgent_AsFunctionTools/A2AAgent_AsFunctionTools.csproj" />
+    <Project Path="samples/04-hosting/A2A/A2AAgent_PollingForTaskCompletion/A2AAgent_PollingForTaskCompletion.csproj" />
  </Folder>  
  <Folder Name="/Samples/05-end-to-end/">
    <Project Path="samples/05-end-to-end/AgentWithPurview/AgentWithPurview.csproj" />
    <Project Path="samples/05-end-to-end/M365Agent/M365Agent.csproj" />
  </Folder>
-  <Folder Name="/Samples/05-end-to-end/Evaluation/">
-    <Project Path="samples/05-end-to-end/Evaluation/Evaluation_FoundryQuality/Evaluation_FoundryQuality.csproj" />
-    <Project Path="samples/05-end-to-end/Evaluation/Evaluation_MixedProviders/Evaluation_MixedProviders.csproj" />
-    <Project Path="samples/05-end-to-end/Evaluation/Evaluation_ConversationSplits/Evaluation_ConversationSplits.csproj" />
-  </Folder>
  <Folder Name="/Samples/05-end-to-end/A2AClientServer/">
    <File Path="samples/05-end-to-end/A2AClientServer/README.md" />
    <Project Path="samples/05-end-to-end/A2AClientServer/A2AClient/A2AClient.csproj" />
@@ -377,6 +310,15 @@
    <Project Path="samples/05-end-to-end/AGUIClientServer/AGUIDojoServer/AGUIDojoServer.csproj" />
    <Project Path="samples/05-end-to-end/AGUIClientServer/AGUIServer/AGUIServer.csproj" />
  </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/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" />
    <File Path="samples/05-end-to-end/AspNetAgentAuthorization/README.md" />
@@ -538,13 +480,13 @@
    <Project Path="src/Microsoft.Agents.AI.AGUI/Microsoft.Agents.AI.AGUI.csproj" />
    <Project Path="src/Microsoft.Agents.AI.Anthropic/Microsoft.Agents.AI.Anthropic.csproj" />
    <Project Path="src/Microsoft.Agents.AI.AzureAI.Persistent/Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
+    <Project Path="src/Microsoft.Agents.AI.Foundry/Microsoft.Agents.AI.Foundry.csproj" />
    <Project Path="src/Microsoft.Agents.AI.CopilotStudio/Microsoft.Agents.AI.CopilotStudio.csproj" />
    <Project Path="src/Microsoft.Agents.AI.CosmosNoSql/Microsoft.Agents.AI.CosmosNoSql.csproj" />
    <Project Path="src/Microsoft.Agents.AI.Declarative/Microsoft.Agents.AI.Declarative.csproj" />
    <Project Path="src/Microsoft.Agents.AI.DevUI/Microsoft.Agents.AI.DevUI.csproj" />
    <Project Path="src/Microsoft.Agents.AI.DurableTask/Microsoft.Agents.AI.DurableTask.csproj" />
-    <Project Path="src/Microsoft.Agents.AI.Foundry/Microsoft.Agents.AI.Foundry.csproj" />
-    <Project Path="src/Microsoft.Agents.AI.Foundry.Hosting/Microsoft.Agents.AI.Foundry.Hosting.csproj" />
+
    <Project Path="src/Microsoft.Agents.AI.GitHub.Copilot/Microsoft.Agents.AI.GitHub.Copilot.csproj" />
    <Project Path="src/Microsoft.Agents.AI.Hosting.A2A.AspNetCore/Microsoft.Agents.AI.Hosting.A2A.AspNetCore.csproj" />
    <Project Path="src/Microsoft.Agents.AI.Hosting.A2A/Microsoft.Agents.AI.Hosting.A2A.csproj" />
@@ -566,10 +508,11 @@
  <Folder Name="/Tests/IntegrationTests/">
    <Project Path="tests/AgentConformance.IntegrationTests/AgentConformance.IntegrationTests.csproj" />
    <Project Path="tests/AnthropicChatCompletion.IntegrationTests/AnthropicChatCompletion.IntegrationTests.csproj" />
+    <Project Path="tests/Foundry.IntegrationTests/Foundry.IntegrationTests.csproj" />
    <Project Path="tests/AzureAIAgentsPersistent.IntegrationTests/AzureAIAgentsPersistent.IntegrationTests.csproj" />
    <Project Path="tests/CopilotStudio.IntegrationTests/CopilotStudio.IntegrationTests.csproj" />
-    <Project Path="tests/Foundry.IntegrationTests/Foundry.IntegrationTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.DurableTask.IntegrationTests/Microsoft.Agents.AI.DurableTask.IntegrationTests.csproj" />
+
    <Project Path="tests/Microsoft.Agents.AI.GitHub.Copilot.IntegrationTests/Microsoft.Agents.AI.GitHub.Copilot.IntegrationTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.IntegrationTests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.IntegrationTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests/Microsoft.Agents.AI.Hosting.AzureFunctions.IntegrationTests.csproj" />
@@ -580,17 +523,17 @@
    <Project Path="tests/OpenAIResponse.IntegrationTests/OpenAIResponse.IntegrationTests.csproj" />
  </Folder>
  <Folder Name="/Tests/UnitTests/">
-    <Project Path="tests/Aspire.Hosting.AgentFramework.DevUI.UnitTests/Aspire.Hosting.AgentFramework.DevUI.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.A2A.UnitTests/Microsoft.Agents.AI.A2A.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.Abstractions.UnitTests/Microsoft.Agents.AI.Abstractions.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.AGUI.UnitTests/Microsoft.Agents.AI.AGUI.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.Anthropic.UnitTests/Microsoft.Agents.AI.Anthropic.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.AzureAI.Persistent.UnitTests/Microsoft.Agents.AI.AzureAI.Persistent.UnitTests.csproj" />
+    <Project Path="tests/Microsoft.Agents.AI.Foundry.UnitTests/Microsoft.Agents.AI.Foundry.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.CosmosNoSql.UnitTests/Microsoft.Agents.AI.CosmosNoSql.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.Declarative.UnitTests/Microsoft.Agents.AI.Declarative.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.DevUI.UnitTests/Microsoft.Agents.AI.DevUI.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.DurableTask.UnitTests/Microsoft.Agents.AI.DurableTask.UnitTests.csproj" />
-    <Project Path="tests/Microsoft.Agents.AI.Foundry.UnitTests/Microsoft.Agents.AI.Foundry.UnitTests.csproj" />
+
    <Project Path="tests/Microsoft.Agents.AI.GitHub.Copilot.UnitTests/Microsoft.Agents.AI.GitHub.Copilot.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.Hosting.A2A.UnitTests/Microsoft.Agents.AI.Hosting.A2A.UnitTests.csproj" />
    <Project Path="tests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.UnitTests/Microsoft.Agents.AI.Hosting.AGUI.AspNetCore.UnitTests.csproj" />
@@ -9,7 +9,6 @@
      "src\\Microsoft.Agents.AI.GitHub.Copilot\\Microsoft.Agents.AI.GitHub.Copilot.csproj",
      "src\\Microsoft.Agents.AI.AzureAI.Persistent\\Microsoft.Agents.AI.AzureAI.Persistent.csproj",
      "src\\Microsoft.Agents.AI.Foundry\\Microsoft.Agents.AI.Foundry.csproj",
-      "src\\Microsoft.Agents.AI.Foundry.Hosting\\Microsoft.Agents.AI.Foundry.Hosting.csproj",
      "src\\Microsoft.Agents.AI.CopilotStudio\\Microsoft.Agents.AI.CopilotStudio.csproj",
      "src\\Microsoft.Agents.AI.CosmosNoSql\\Microsoft.Agents.AI.CosmosNoSql.csproj",
      "src\\Microsoft.Agents.AI.Declarative\\Microsoft.Agents.AI.Declarative.csproj",
@@ -29,8 +28,7 @@
      "src\\Microsoft.Agents.AI.Workflows.Declarative\\Microsoft.Agents.AI.Workflows.Declarative.csproj",
      "src\\Microsoft.Agents.AI.Workflows.Generators\\Microsoft.Agents.AI.Workflows.Generators.csproj",
      "src\\Microsoft.Agents.AI.Workflows\\Microsoft.Agents.AI.Workflows.csproj",
-      "src\\Microsoft.Agents.AI\\Microsoft.Agents.AI.csproj",
-      "src\\Aspire.Hosting.AgentFramework.DevUI\\Aspire.Hosting.AgentFramework.DevUI.csproj"
+      "src\\Microsoft.Agents.AI\\Microsoft.Agents.AI.csproj"
    ]
  }
 }
@@ -246,7 +246,7 @@ internal static class AgentsSamples
            ExpectedOutputDescription =
            [
                "The output should contain information about both the current time and the weather in Seattle.",
-                "The weather information should be similar to: cloudy with a high of 15°C. Exact phrasing may vary.",
+                "The weather information should reference the plugin result: cloudy with a high of 15°C.",
                "The output should not contain error messages or stack traces.",
            ],
        },
@@ -521,7 +521,7 @@ internal static class AgentsSamples
            OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
            ExpectedOutputDescription =
            [
-                "The output should contain multiple joke responses showing a multi-turn conversation.",
+                "The output should demonstrate server-side conversation sessions with non-streaming and streaming turns.",
                "The output should not contain error messages or stack traces.",
            ],
        },
@@ -14,9 +14,6 @@
 //   dotnet run -- --log results.log                     # Write sequential log to file
 //   dotnet run -- --csv results.csv                     # Write CSV summary to file
 //   dotnet run -- --md results.md                       # Write Markdown summary to file
-//   dotnet run -- --build                                # Build samples during run (default: --no-build)
-// Note: By default, this tool expects sample build outputs to already exist.
-// Pre-build the solution before running, or pass --build to avoid missing build output failures.
 //
 // Required environment variables (for AI-powered samples):
 //   AZURE_OPENAI_ENDPOINT
@@ -66,7 +63,7 @@ try
    // Run all samples
    var reporter = new ConsoleReporter();
    var verifier = new SampleVerifier(chatClient);
-    var orchestrator = new VerificationOrchestrator(verifier, reporter, dotnetRoot, TimeSpan.FromMinutes(3), logWriter, buildSamples: options.BuildSamples);
+    var orchestrator = new VerificationOrchestrator(verifier, reporter, dotnetRoot, TimeSpan.FromMinutes(3), logWriter);

    var run = await orchestrator.RunAllAsync(options.Samples, options.MaxParallelism);

@@ -20,32 +20,23 @@ internal static class SampleRunner
 {
    /// <summary>
    /// Runs <c>dotnet run --framework net10.0</c> in the given project directory.
-    /// When <paramref name="build"/> is false (the default), <c>--no-build</c> is passed
-    /// to skip building, assuming the project was pre-built.
    /// </summary>
    public static Task<SampleRunResult> RunAsync(
        string projectPath,
        TimeSpan timeout,
-        bool build = false,
        CancellationToken cancellationToken = default)
-        => RunAsync(projectPath, DotnetRunArgs(build), timeout, inputs: null, inputDelayMs: 0, cancellationToken: cancellationToken);
+        => RunAsync(projectPath, "run --framework net10.0", timeout, inputs: null, inputDelayMs: 0, cancellationToken: cancellationToken);

    /// <summary>
    /// Runs <c>dotnet run --framework net10.0</c> with stdin inputs.
-    /// When <paramref name="build"/> is false (the default), <c>--no-build</c> is passed
-    /// to skip building, assuming the project was pre-built.
    /// </summary>
    public static Task<SampleRunResult> RunAsync(
        string projectPath,
        TimeSpan timeout,
        string?[]? inputs,
        int inputDelayMs = 2000,
-        bool build = false,
        CancellationToken cancellationToken = default)
-        => RunAsync(projectPath, DotnetRunArgs(build), timeout, inputs, inputDelayMs, cancellationToken);
-
-    private static string DotnetRunArgs(bool build) =>
-        $"run {(build ? "" : "--no-build")} --framework net10.0";
+        => RunAsync(projectPath, "run --framework net10.0", timeout, inputs, inputDelayMs, cancellationToken);

    /// <summary>
    /// Runs an arbitrary <c>dotnet</c> command in the given working directory.
@@ -1,6 +1,5 @@
 // Copyright (c) Microsoft. All rights reserved.

-using System.ComponentModel;
 using System.Text.Json.Serialization;
 using Microsoft.Agents.AI;
 using Microsoft.Extensions.AI;
@@ -28,19 +27,11 @@ internal sealed class SampleVerifier
                instructions: """
                    You are a test output verifier. You will be given:
                    1. The actual stdout output of a program
-                    2. The stderr output (if any)
-                    3. A list of expectations about what the output should contain or demonstrate
+                    2. A list of expectations about what the output should contain or demonstrate

                    Your job is to determine whether the actual output satisfies each expectation.
                    Be reasonable — the output comes from an LLM so exact wording won't match, but the
                    semantic intent should be clearly satisfied.
-
-                    In your response, you MUST:
-                    - Always provide ai_reasoning with a brief overall assessment.
-                    - Always provide exactly one entry in expectation_results for each expectation,
-                      in the same order as the input list.
-                    - For each expectation_results entry, echo the expectation text in the expectation
-                      field and explain your assessment in the detail field, citing evidence from the output.
                    """,
                name: "OutputVerifier");
        }
@@ -87,7 +78,7 @@ internal sealed class SampleVerifier
            }
            else
            {
-                var aiResult = await this.VerifyWithAIAsync(run.Stdout, run.Stderr, sample.ExpectedOutputDescription);
+                var aiResult = await this.VerifyWithAIAsync(run.Stdout, sample.ExpectedOutputDescription);
                aiReasoning = aiResult.Reasoning;

                foreach (var unmet in aiResult.UnmetExpectations)
@@ -109,28 +100,16 @@ internal sealed class SampleVerifier
    }

    private async Task<(string Reasoning, List<string> UnmetExpectations)> VerifyWithAIAsync(
-        string stdout,
-        string stderr,
+        string actualOutput,
        string[] expectations)
    {
        var expectationList = string.Join("\n", expectations.Select((e, i) => $"  {i + 1}. {e}"));
-
-        var stderrSection = string.IsNullOrWhiteSpace(stderr)
-            ? ""
-            : $"""
-
-                Stderr output:
-                ---
-                {Truncate(stderr, 2000)}
-                ---
-                """;
-
        var prompt = $"""
            Actual program output:
            ---
-            {Truncate(stdout, 4000)}
+            {Truncate(actualOutput, 4000)}
            ---
-            {stderrSection}
+
            Expectations to verify:
            {expectationList}

@@ -147,9 +126,7 @@ internal sealed class SampleVerifier
                return ($"AI verification returned null result. Raw: {response.Text}", ["AI verification returned null result."]);
            }

-            var reasoning = string.IsNullOrWhiteSpace(result.AIReasoning)
-                ? "(no reasoning provided)"
-                : result.AIReasoning;
+            var reasoning = result.Reasoning ?? "(no reasoning provided)";

            // Collect unmet expectations as individual failures
            var unmet = new List<string>();
@@ -197,14 +174,12 @@ internal sealed class AIVerificationResponse
    public bool Pass { get; set; }

    /// <summary>Brief explanation of the overall assessment.</summary>
-    [JsonPropertyName("ai_reasoning")]
-    [Description("Always required. Brief explanation of the overall assessment, covering all expectations.")]
-    public string AIReasoning { get; set; } = string.Empty;
+    [JsonPropertyName("reasoning")]
+    public string? Reasoning { get; set; }

    /// <summary>Per-expectation results.</summary>
    [JsonPropertyName("expectation_results")]
-    [Description("Always required. One entry per expectation, in the same order as the input list.")]
-    public List<ExpectationResult> ExpectationResults { get; set; } = [];
+    public List<ExpectationResult>? ExpectationResults { get; set; }
 }

 /// <summary>
@@ -215,8 +190,7 @@ internal sealed class ExpectationResult
 {
    /// <summary>The expectation text that was evaluated.</summary>
    [JsonPropertyName("expectation")]
-    [Description("Echo back the expectation text being evaluated.")]
-    public string Expectation { get; set; } = string.Empty;
+    public string? Expectation { get; set; }

    /// <summary>Whether this expectation was met.</summary>
    [JsonPropertyName("met")]
@@ -224,6 +198,5 @@ internal sealed class ExpectationResult

    /// <summary>Detail about how the expectation was or was not met.</summary>
    [JsonPropertyName("detail")]
-    [Description("Explain how the expectation was or was not met, citing specific evidence from the output.")]
-    public string Detail { get; set; } = string.Empty;
+    public string? Detail { get; set; }
 }
@@ -14,22 +14,19 @@ internal sealed class VerificationOrchestrator
    private readonly LogFileWriter? _logWriter;
    private readonly string _dotnetRoot;
    private readonly TimeSpan _timeout;
-    private readonly bool _buildSamples;

    public VerificationOrchestrator(
        SampleVerifier verifier,
        ConsoleReporter reporter,
        string dotnetRoot,
        TimeSpan timeout,
-        LogFileWriter? logWriter = null,
-        bool buildSamples = false)
+        LogFileWriter? logWriter = null)
    {
        this._verifier = verifier;
        this._reporter = reporter;
        this._logWriter = logWriter;
        this._dotnetRoot = dotnetRoot;
        this._timeout = timeout;
-        this._buildSamples = buildSamples;
    }

    /// <summary>
@@ -139,8 +136,8 @@ internal sealed class VerificationOrchestrator

            var projectPath = Path.Combine(this._dotnetRoot, sample.ProjectPath);
            var run = sample.Inputs.Length > 0
-                ? await SampleRunner.RunAsync(projectPath, this._timeout, sample.Inputs, sample.InputDelayMs, build: this._buildSamples)
-                : await SampleRunner.RunAsync(projectPath, this._timeout, build: this._buildSamples);
+                ? await SampleRunner.RunAsync(projectPath, this._timeout, sample.Inputs, sample.InputDelayMs)
+                : await SampleRunner.RunAsync(projectPath, this._timeout);

            log.Add($"[{sample.Name}] Completed ({run.Elapsed.TotalSeconds:F1}s, exit={run.ExitCode})");
            this._reporter.WriteLineWithPrefix(
@@ -27,12 +27,6 @@ internal sealed class VerifyOptions
    /// </summary>
    public string? LogFilePath { get; init; }

-    /// <summary>
-    /// When true, samples are built as part of <c>dotnet run</c>.
-    /// When false (the default), <c>--no-build</c> is passed, assuming a prior build step.
-    /// </summary>
-    public bool BuildSamples { get; init; }
-
    /// <summary>
    /// The filtered list of samples to process.
    /// </summary>
@@ -61,7 +55,6 @@ internal sealed class VerifyOptions
        var logFilePath = ExtractArg(argList, "--log");
        var csvFilePath = ExtractArg(argList, "--csv");
        var markdownFilePath = ExtractArg(argList, "--md");
-        var buildSamples = ExtractFlag(argList, "--build");

        int maxParallelism = 8;
        var parallelArg = ExtractArg(argList, "--parallel");
@@ -112,7 +105,6 @@ internal sealed class VerifyOptions
            LogFilePath = logFilePath,
            CsvFilePath = csvFilePath,
            MarkdownFilePath = markdownFilePath,
-            BuildSamples = buildSamples,
            Samples = samples,
        };
    }
@@ -136,16 +128,4 @@ internal sealed class VerifyOptions
        list.RemoveRange(idx, 2);
        return value;
    }
-
-    private static bool ExtractFlag(List<string> list, string flag)
-    {
-        var idx = list.IndexOf(flag);
-        if (idx < 0)
-        {
-            return false;
-        }
-
-        list.RemoveAt(idx);
-        return true;
-    }
 }
@@ -1,4 +1,4 @@
-<?xml version="1.0" encoding="utf-8"?>
+<?xml version="1.0" encoding="utf-8"?>
 <configuration>
  <packageSources>
    <clear />
@@ -9,4 +9,4 @@
      <package pattern="*" />
    </packageSource>
  </packageSourceMapping>
-</configuration>
+</configuration>
@@ -1,22 +1,21 @@
 <Project>
  <PropertyGroup>
    <!-- Central version prefix - applies to all nuget packages. -->
-    <VersionPrefix>1.2.0</VersionPrefix>
-    <RCNumber>1</RCNumber>
-    <DateSuffix>260421</DateSuffix>
+    <VersionPrefix>1.0.0</VersionPrefix>
+    <RCNumber>6</RCNumber>
    <PackageVersion Condition="'$(IsReleaseCandidate)' == 'true'">$(VersionPrefix)-rc$(RCNumber)</PackageVersion>
-    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).$(DateSuffix).1</PackageVersion>
-    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' == ''">$(VersionPrefix)-preview.$(DateSuffix).1</PackageVersion>
+    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).260402.1</PackageVersion>
+    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' == ''">$(VersionPrefix)-preview.260402.1</PackageVersion>
    <PackageVersion Condition="'$(IsReleased)' == 'true'">$(VersionPrefix)</PackageVersion>
-    <GitTag>1.2.0</GitTag>
+    <GitTag>1.0.0</GitTag>

    <Configurations>Debug;Release;Publish</Configurations>
    <IsPackable>true</IsPackable>

    <!-- Package validation. Baseline Version should be the latest version available on NuGet. -->
-    <PackageValidationBaselineVersion>1.0.0</PackageValidationBaselineVersion>
-    <!-- Enable validation for GA packages -->
-    <EnablePackageValidation Condition="'$(IsReleased)' == 'true'">true</EnablePackageValidation>
+    <PackageValidationBaselineVersion>1.0.0-rc5</PackageValidationBaselineVersion>
+    <!-- Enable validation for RC packages and GA packages -->
+    <EnablePackageValidation Condition="'$(IsReleaseCandidate)' == 'true' OR '$(IsReleased)' == 'true'">true</EnablePackageValidation>
    <!-- Validate assembly attributes only for Publish builds -->
    <NoWarn Condition="'$(Configuration)' != 'Publish'">$(NoWarn);CP0003</NoWarn>
    <!-- Do not validate reference assemblies -->
@@ -30,8 +29,7 @@

    <!-- Report low, moderate, high and critical advisories -->
    <NuGetAuditLevel>low</NuGetAuditLevel>
-
-
+    
    <!-- Default description and tags. Packages can override. -->
    <Authors>Microsoft</Authors>
    <Company>Microsoft</Company>
@@ -8,7 +8,7 @@ using Microsoft.Agents.AI;
 using OpenAI.Chat;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+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
@@ -11,7 +11,7 @@ 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-5.4-mini";
+var 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)
@@ -8,7 +8,7 @@ using Microsoft.Agents.AI;
 using OpenAI.Chat;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+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
@@ -16,7 +16,7 @@ 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-5.4-mini";
+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
@@ -8,7 +8,7 @@
 //
 // Environment variables:
 //   AZURE_OPENAI_ENDPOINT
-//   AZURE_OPENAI_DEPLOYMENT_NAME (defaults to "gpt-5.4-mini")
+//   AZURE_OPENAI_DEPLOYMENT_NAME (defaults to "gpt-4o-mini")
 //
 // Run with: func start
 // Then call: POST http://localhost:7071/api/agents/HostedAgent/run
@@ -23,7 +23,7 @@ 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-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // Set up an AI agent following the standard Microsoft Agent Framework pattern.
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
@@ -1,19 +0,0 @@
-<Project Sdk="Microsoft.NET.Sdk">
-
-  <PropertyGroup>
-    <OutputType>Exe</OutputType>
-    <TargetFrameworks>net10.0</TargetFrameworks>
-
-    <Nullable>enable</Nullable>
-    <ImplicitUsings>enable</ImplicitUsings>
-  </PropertyGroup>
-
-  <ItemGroup>
-    <PackageReference Include="A2A" />
-  </ItemGroup>
-
-  <ItemGroup>
-    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.A2A\Microsoft.Agents.AI.A2A.csproj" />
-  </ItemGroup>
-
-</Project>
@@ -1,36 +0,0 @@
-// Copyright (c) Microsoft. All rights reserved.
-
-// This sample demonstrates how to select the A2A protocol binding (HTTP+JSON vs JSON-RPC) when
-// creating an AIAgent from an A2A agent card using A2AClientOptions.PreferredBindings.
-
-using A2A;
-using Microsoft.Agents.AI;
-
-var a2aAgentHost = Environment.GetEnvironmentVariable("A2A_AGENT_HOST") ?? throw new InvalidOperationException("A2A_AGENT_HOST is not set.");
-
-// Initialize an A2ACardResolver to get an A2A agent card.
-A2ACardResolver agentCardResolver = new(new Uri(a2aAgentHost));
-
-// Get the agent card
-AgentCard agentCard = await agentCardResolver.GetAgentCardAsync();
-
-// Use A2AClientOptions to explicitly select the HTTP+JSON protocol binding.
-// This tells the A2A client factory to prefer the HTTP+JSON interface when the agent card
-// advertises multiple supported interfaces.
-A2AClientOptions options = new()
-{
-    PreferredBindings = [ProtocolBindingNames.HttpJson]
-};
-
-// To prefer JSON-RPC instead, use:
-// A2AClientOptions options = new()
-// {
-//     PreferredBindings = [ProtocolBindingNames.JsonRpc]
-// };
-
-// Create an instance of the AIAgent for an existing A2A agent, using the specified protocol binding.
-AIAgent agent = agentCard.AsAIAgent(options: options);
-
-// Invoke the agent and output the text result.
-AgentResponse response = await agent.RunAsync("Tell me a joke about a pirate.");
-Console.WriteLine(response);
@@ -1,27 +0,0 @@
-# A2A Agent Protocol Selection
-
-This sample demonstrates how to select the A2A protocol binding when creating an `AIAgent` from an A2A agent card.
-
-A2A agents can expose multiple interfaces with different protocol bindings (e.g., HTTP+JSON, JSON-RPC). By default, `AsAIAgent()` prefers HTTP+JSON with JSON-RPC as a fallback. This sample shows how to use `A2AClientOptions.PreferredBindings` to explicitly control which protocol binding is used.
-
-The sample:
-
- Connects to an A2A agent server specified in the `A2A_AGENT_HOST` environment variable
- Configures `A2AClientOptions` to prefer the HTTP+JSON protocol binding
- Creates an `AIAgent` from the resolved agent card using the specified binding
- Sends a message to the agent and displays the response
-
-## Prerequisites
-
-Before you begin, ensure you have the following prerequisites:
-
- .NET 10.0 SDK or later
- An A2A agent server running and accessible via HTTP
-
-**Note**: These samples need to be run against a valid A2A server. If no A2A server is available, they can be run against the echo-agent that can be spun up locally by following the guidelines at: https://github.com/a2aproject/a2a-dotnet/blob/main/samples/AgentServer/README.md
-
-Set the following environment variable:
-
-```powershell
-$env:A2A_AGENT_HOST="http://localhost:5000"  # Replace with your A2A agent server host
-```
@@ -1,23 +0,0 @@
-<Project Sdk="Microsoft.NET.Sdk">
-
-  <PropertyGroup>
-    <OutputType>Exe</OutputType>
-    <TargetFrameworks>net10.0</TargetFrameworks>
-
-    <Nullable>enable</Nullable>
-    <ImplicitUsings>enable</ImplicitUsings>
-  </PropertyGroup>
-
-  <ItemGroup>
-    <PackageReference Include="A2A" />
-    <PackageReference Include="Azure.AI.OpenAI" />
-    <PackageReference Include="Azure.Identity" />
-    <PackageReference Include="Microsoft.Extensions.Hosting" />
-  </ItemGroup>
-
-  <ItemGroup>
-    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.A2A\Microsoft.Agents.AI.A2A.csproj" />
-    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
-  </ItemGroup>
-
-</Project>
@@ -1,55 +0,0 @@
-// Copyright (c) Microsoft. All rights reserved.
-
-// This sample demonstrates how to reconnect to an A2A agent's streaming response using continuation tokens,
-// allowing recovery from stream interruptions without losing progress.
-
-using A2A;
-using Microsoft.Agents.AI;
-using Microsoft.Extensions.AI;
-
-var a2aAgentHost = Environment.GetEnvironmentVariable("A2A_AGENT_HOST") ?? throw new InvalidOperationException("A2A_AGENT_HOST is not set.");
-
-// Initialize an A2ACardResolver to get an A2A agent card.
-A2ACardResolver agentCardResolver = new(new Uri(a2aAgentHost));
-
-// Get the agent card
-AgentCard agentCard = await agentCardResolver.GetAgentCardAsync();
-
-// Create an instance of the AIAgent for an existing A2A agent specified by the agent card.
-AIAgent agent = agentCard.AsAIAgent();
-
-AgentSession session = await agent.CreateSessionAsync();
-
-ResponseContinuationToken? continuationToken = null;
-
-await foreach (var update in agent.RunStreamingAsync("Conduct a comprehensive analysis of quantum computing applications in cryptography, including recent breakthroughs, implementation challenges, and future roadmap. Please include diagrams and visual representations to illustrate complex concepts.", session))
-{
-    // Saving the continuation token to be able to reconnect to the same response stream later.
-    // Note: Continuation tokens are only returned for long-running tasks. If the underlying A2A agent
-    // returns a message instead of a task, the continuation token will not be initialized.
-    // A2A agents do not support stream resumption from a specific point in the stream,
-    // but only reconnection to obtain the same response stream from the beginning.
-    // So, A2A agents will return an initialized continuation token in the first update
-    // representing the beginning of the stream, and it will be null in all subsequent updates.
-    if (update.ContinuationToken is { } token)
-    {
-        continuationToken = token;
-    }
-
-    // Imitating stream interruption
-    break;
-}
-
-// Reconnect to the same response stream using the continuation token obtained from the previous run.
-// As a first update, the agent will return an update representing the current state of the response at the moment of calling
-// RunStreamingAsync with the same continuation token, followed by other updates until the end of the stream is reached.
-if (continuationToken is not null)
-{
-    await foreach (var update in agent.RunStreamingAsync(session, options: new() { ContinuationToken = continuationToken }))
-    {
-        if (!string.IsNullOrEmpty(update.Text))
-        {
-            Console.WriteLine(update.Text);
-        }
-    }
-}
@@ -1,29 +0,0 @@
-# A2A Agent Stream Reconnection
-
-This sample demonstrates how to reconnect to an A2A agent's streaming response using continuation tokens, allowing recovery from stream interruptions without losing progress.
-
-The sample:
-
- Connects to an A2A agent server specified in the `A2A_AGENT_HOST` environment variable
- Sends a request to the agent and begins streaming the response
- Captures a continuation token from the stream for later reconnection
- Simulates a stream interruption by breaking out of the streaming loop
- Reconnects to the same response stream using the captured continuation token
- Displays the response received after reconnection
-
-This pattern is useful when network interruptions or other failures may disrupt an ongoing streaming response, and you need to recover and continue processing.
-
-> **Note:** Continuation tokens are only available when the underlying A2A agent returns a task. If the agent returns a message instead, the continuation token will not be initialized and stream reconnection is not applicable.
-
-# Prerequisites
-
-Before you begin, ensure you have the following prerequisites:
-
- .NET 10.0 SDK or later
- An A2A agent server running and accessible via HTTP
-
-Set the following environment variable:
-
-```powershell
-$env:A2A_AGENT_HOST="http://localhost:5000"  # Replace with your A2A agent server host
-```
@@ -15,7 +15,7 @@ All samples require the following environment variables:

 ```bash
 export AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"
-export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
 ```

 For the client samples, you can optionally set:
@@ -97,7 +97,7 @@ Console.WriteLine("""
    """);

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT environment variable is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // Log application startup
 appLogger.LogInformation("OpenTelemetry Aspire Demo application started");
@@ -34,7 +34,7 @@ graph TD
 Set the following environment variables:
 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
 ```

 **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.
@@ -9,7 +9,7 @@ using Azure.Identity;
 using Microsoft.Agents.AI;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 const string JokerName = "Joker";
 const string JokerInstructions = "You are good at telling jokes.";
@@ -22,5 +22,5 @@ Set the following environment variables:

 ```powershell
 $env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Microsoft Foundry resource endpoint
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
+$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
 ```
@@ -9,7 +9,7 @@ using Microsoft.Agents.AI;
 using Microsoft.Agents.AI.Foundry;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 const string JokerName = "JokerAgent";

@@ -22,5 +22,5 @@ Set the following environment variables:

 ```powershell
 $env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Microsoft Foundry resource endpoint
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
+$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
 ```
@@ -8,7 +8,7 @@ using Microsoft.Agents.AI;
 using OpenAI.Chat;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+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
@@ -12,5 +12,5 @@ Set the following environment variables:

 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
 ```
@@ -9,7 +9,7 @@ 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-5.4-mini";
+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
@@ -12,5 +12,5 @@ Set the following environment variables:

 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
 ```
@@ -8,7 +8,7 @@ using OpenAI;
 using OpenAI.Chat;

 var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";
+var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";

 AIAgent agent = new OpenAIClient(
    apiKey)
@@ -9,5 +9,5 @@ Set the following environment variables:

 ```powershell
 $env:OPENAI_API_KEY="*****" # Replace with your OpenAI api key
-$env:OPENAI_CHAT_MODEL_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
+$env:OPENAI_CHAT_MODEL_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
 ```
@@ -7,7 +7,7 @@ using OpenAI;
 using OpenAI.Responses;

 var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";
+var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";

 AIAgent agent = new OpenAIClient(
    apiKey)
@@ -9,5 +9,5 @@ Set the following environment variables:

 ```powershell
 $env:OPENAI_API_KEY="*****" # Replace with your OpenAI api key
-$env:OPENAI_CHAT_MODEL_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
+$env:OPENAI_CHAT_MODEL_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
 ```
@@ -16,7 +16,7 @@ using OpenAI.Responses;

 // --- Configuration ---
 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-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // --- Skills Provider ---
 // Discovers skills from the 'skills' directory containing SKILL.md files.
@@ -30,7 +30,7 @@ Converts between common units (miles↔km, pounds↔kg) using a multiplication f

 ```bash
 export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
-export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
 ```

 ### Run
@@ -16,7 +16,7 @@ using OpenAI.Responses;

 // --- Configuration ---
 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-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // --- Build the code-defined skill ---
 var unitConverterSkill = new AgentInlineSkill(
@@ -31,7 +31,7 @@ Converts between common units using multiplication factors. Defined entirely in

 ```bash
 export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
-export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
 ```

 ### Run
@@ -6,7 +6,7 @@

    <Nullable>enable</Nullable>
    <ImplicitUsings>enable</ImplicitUsings>
-    <NoWarn>$(NoWarn);MAAI001;IDE0051</NoWarn>
+    <NoWarn>$(NoWarn);MAAI001</NoWarn>
  </PropertyGroup>

  <ItemGroup>
@@ -1,9 +1,8 @@
 // Copyright (c) Microsoft. All rights reserved.

-// This sample demonstrates how to define Agent Skills as C# classes using AgentClassSkill
-// with attributes for automatic script and resource discovery.
+// This sample demonstrates how to define Agent Skills as C# classes using AgentClassSkill.
+// Class-based skills bundle all components into a single class implementation.

-using System.ComponentModel;
 using System.Text.Json;
 using Azure.AI.OpenAI;
 using Azure.Identity;
@@ -12,7 +11,7 @@ using OpenAI.Responses;

 // --- Configuration ---
 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-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // --- Class-Based Skill ---
 // Instantiate the skill class.
@@ -45,16 +44,17 @@ AgentResponse response = await agent.RunAsync(
 Console.WriteLine($"Agent: {response.Text}");

 /// <summary>
-/// A unit-converter skill defined as a C# class using attributes for discovery.
+/// A unit-converter skill defined as a C# class.
 /// </summary>
 /// <remarks>
-/// Properties annotated with <see cref="AgentSkillResourceAttribute"/> are automatically
-/// discovered as skill resources, and methods annotated with <see cref="AgentSkillScriptAttribute"/>
-/// are automatically discovered as skill scripts. Alternatively,
-/// <see cref="AgentSkill.Resources"/> and <see cref="AgentSkill.Scripts"/> can be overridden.
+/// Class-based skills bundle all components (name, description, body, resources, scripts)
+/// into a single class.
 /// </remarks>
-internal sealed class UnitConverterSkill : AgentClassSkill<UnitConverterSkill>
+internal sealed class UnitConverterSkill : AgentClassSkill
 {
+    private IReadOnlyList<AgentSkillResource>? _resources;
+    private IReadOnlyList<AgentSkillScript>? _scripts;
+
    /// <inheritdoc/>
    public override AgentSkillFrontmatter Frontmatter { get; } = new(
        "unit-converter",
@@ -69,40 +69,31 @@ internal sealed class UnitConverterSkill : AgentClassSkill<UnitConverterSkill>
        3. Present the result clearly with both units.
        """;

-    /// <summary>
-    /// Gets the <see cref="JsonSerializerOptions"/> used to marshal parameters and return values
-    /// for scripts and resources.
-    /// </summary>
-    /// <remarks>
-    /// This override is not necessary for this sample, but can be used to provide custom
-    /// serialization options, for example a source-generated <c>JsonTypeInfoResolver</c>
-    /// for Native AOT compatibility.
-    /// </remarks>
-    protected override JsonSerializerOptions? SerializerOptions => null;
+    /// <inheritdoc/>
+    public override IReadOnlyList<AgentSkillResource>? Resources => this._resources ??=
+    [
+        CreateResource(
+            "conversion-table",
+            """
+            # Conversion Tables

-    /// <summary>
-    /// A conversion table resource providing multiplication factors.
-    /// </summary>
-    [AgentSkillResource("conversion-table")]
-    [Description("Lookup table of multiplication factors for common unit conversions.")]
-    public string ConversionTable => """
-        # Conversion Tables
+            Formula: **result = value × factor**

-        Formula: **result = value × factor**
+            | From        | To          | Factor   |
+            |-------------|-------------|----------|
+            | miles       | kilometers  | 1.60934  |
+            | kilometers  | miles       | 0.621371 |
+            | pounds      | kilograms   | 0.453592 |
+            | kilograms   | pounds      | 2.20462  |
+            """),
+    ];

-        | From        | To          | Factor   |
-        |-------------|-------------|----------|
-        | miles       | kilometers  | 1.60934  |
-        | kilometers  | miles       | 0.621371 |
-        | pounds      | kilograms   | 0.453592 |
-        | kilograms   | pounds      | 2.20462  |
-        """;
+    /// <inheritdoc/>
+    public override IReadOnlyList<AgentSkillScript>? Scripts => this._scripts ??=
+    [
+        CreateScript("convert", ConvertUnits),
+    ];

-    /// <summary>
-    /// Converts a value by the given factor.
-    /// </summary>
-    [AgentSkillScript("convert")]
-    [Description("Multiplies a value by a conversion factor and returns the result as JSON.")]
    private static string ConvertUnits(double value, double factor)
    {
        double result = Math.Round(value * factor, 4);
@@ -1,16 +1,12 @@
 # Class-Based Agent Skills Sample

-This sample demonstrates how to define **Agent Skills as C# classes** using `AgentClassSkill`
-with **attributes** for automatic script and resource discovery.
+This sample demonstrates how to define **Agent Skills as C# classes** using `AgentClassSkill`.

 ## What it demonstrates

 - Creating skills as classes that extend `AgentClassSkill`
- Using `[AgentSkillResource]` on properties to define resources
- Using `[AgentSkillScript]` on methods to define scripts
- Automatic discovery (no need to override `Resources`/`Scripts`)
+- Bundling name, description, body, resources, and scripts into a single class
 - Using the `AgentSkillsProvider` constructor with class-based skills
- Overriding `SerializerOptions` for Native AOT compatibility

 ## Skills Included

@@ -32,7 +28,7 @@ A `UnitConverterSkill` class that converts between common units. Defined in `Pro

 ```bash
 export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
-export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
 ```

 ### Run
@@ -6,7 +6,7 @@

    <Nullable>enable</Nullable>
    <ImplicitUsings>enable</ImplicitUsings>
-    <NoWarn>$(NoWarn);MAAI001;IDE0051</NoWarn>
+    <NoWarn>$(NoWarn);MAAI001</NoWarn>
  </PropertyGroup>

  <ItemGroup>
@@ -8,12 +8,11 @@
 // Three different skill sources are registered here:
 // 1. File-based: unit-converter (miles↔km, pounds↔kg) from SKILL.md on disk
 // 2. Code-defined: volume-converter (gallons↔liters) using AgentInlineSkill
-// 3. Class-based: temperature-converter (°F↔°C↔K) using AgentClassSkill with attributes
+// 3. Class-based: temperature-converter (°F↔°C↔K) using AgentClassSkill
 //
 // For simpler, single-source scenarios, see the earlier steps in this sample series
 // (e.g., Step01 for file-based, Step02 for code-defined, Step03 for class-based).

-using System.ComponentModel;
 using System.Text.Json;
 using Azure.AI.OpenAI;
 using Azure.Identity;
@@ -23,7 +22,7 @@ using OpenAI.Responses;
 // --- Configuration ---
 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-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // --- 1. Code-Defined Skill: volume-converter ---
 var volumeConverterSkill = new AgentInlineSkill(
@@ -90,15 +89,13 @@ AgentResponse response = await agent.RunAsync(
 Console.WriteLine($"Agent: {response.Text}");

 /// <summary>
-/// A temperature-converter skill defined as a C# class using attributes for discovery.
+/// A temperature-converter skill defined as a C# class.
 /// </summary>
-/// <remarks>
-/// Properties annotated with <see cref="AgentSkillResourceAttribute"/> are automatically
-/// discovered as skill resources, and methods annotated with <see cref="AgentSkillScriptAttribute"/>
-/// are automatically discovered as skill scripts.
-/// </remarks>
-internal sealed class TemperatureConverterSkill : AgentClassSkill<TemperatureConverterSkill>
+internal sealed class TemperatureConverterSkill : AgentClassSkill
 {
+    private IReadOnlyList<AgentSkillResource>? _resources;
+    private IReadOnlyList<AgentSkillScript>? _scripts;
+
    /// <inheritdoc/>
    public override AgentSkillFrontmatter Frontmatter { get; } = new(
        "temperature-converter",
@@ -113,27 +110,29 @@ internal sealed class TemperatureConverterSkill : AgentClassSkill<TemperatureCon
        3. Present the result clearly with both temperature scales.
        """;

-    /// <summary>
-    /// A reference table of temperature conversion formulas.
-    /// </summary>
-    [AgentSkillResource("temperature-conversion-formulas")]
-    [Description("Formulas for converting between Fahrenheit, Celsius, and Kelvin.")]
-    public string ConversionFormulas => """
-        # Temperature Conversion Formulas
+    /// <inheritdoc/>
+    public override IReadOnlyList<AgentSkillResource>? Resources => this._resources ??=
+    [
+        CreateResource(
+            "temperature-conversion-formulas",
+            """
+            # Temperature Conversion Formulas

-        | From        | To          | Formula                   |
-        |-------------|-------------|---------------------------|
-        | Fahrenheit  | Celsius     | °C = (°F − 32) × 5/9     |
-        | Celsius     | Fahrenheit  | °F = (°C × 9/5) + 32     |
-        | Celsius     | Kelvin      | K = °C + 273.15           |
-        | Kelvin      | Celsius     | °C = K − 273.15           |
-        """;
+            | From        | To          | Formula                   |
+            |-------------|-------------|---------------------------|
+            | Fahrenheit  | Celsius     | °C = (°F − 32) × 5/9     |
+            | Celsius     | Fahrenheit  | °F = (°C × 9/5) + 32     |
+            | Celsius     | Kelvin      | K = °C + 273.15           |
+            | Kelvin      | Celsius     | °C = K − 273.15           |
+            """),
+    ];
+
+    /// <inheritdoc/>
+    public override IReadOnlyList<AgentSkillScript>? Scripts => this._scripts ??=
+    [
+        CreateScript("convert-temperature", ConvertTemperature),
+    ];

-    /// <summary>
-    /// Converts a temperature value between scales.
-    /// </summary>
-    [AgentSkillScript("convert-temperature")]
-    [Description("Converts a temperature value from one scale to another.")]
    private static string ConvertTemperature(double value, string from, string to)
    {
        double result = (from.ToUpperInvariant(), to.ToUpperInvariant()) switch
@@ -45,7 +45,7 @@ Defined as `TemperatureConverterSkill` class in `Program.cs`. Converts °F↔°C

 ```bash
 export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
-export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
 ```

 ### Run
@@ -6,7 +6,7 @@

    <Nullable>enable</Nullable>
    <ImplicitUsings>enable</ImplicitUsings>
-    <NoWarn>$(NoWarn);MAAI001;CA1812;IDE0051</NoWarn>
+    <NoWarn>$(NoWarn);MAAI001;CA1812</NoWarn>
  </PropertyGroup>

  <ItemGroup>
@@ -13,7 +13,6 @@
 // showing that DI works identically regardless of how the skill is defined.
 // When prompted with a question spanning both domains, the agent uses both skills.

-using System.ComponentModel;
 using System.Text.Json;
 using Azure.AI.OpenAI;
 using Azure.Identity;
@@ -23,7 +22,7 @@ using OpenAI.Responses;

 // --- Configuration ---
 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-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // --- DI Container ---
 // Register application services that skill resources and scripts can resolve at execution time.
@@ -63,8 +62,8 @@ var distanceSkill = new AgentInlineSkill(
 // Approach 2: Class-Based Skill with DI (AgentClassSkill)
 // =====================================================================
 // Handles weight conversions (pounds ↔ kilograms).
-// Resources and scripts are discovered via reflection using attributes.
-// Methods with an IServiceProvider parameter receive DI automatically.
+// Resources and scripts are encapsulated in a class. Factory methods
+// CreateResource and CreateScript accept delegates with IServiceProvider.
 //
 // Alternatively, class-based skills can accept dependencies through their
 // constructor. Register the skill class itself in the ServiceCollection and
@@ -114,13 +113,14 @@ Console.WriteLine($"Agent: {response.Text}");
 /// </summary>
 /// <remarks>
 /// This skill resolves <see cref="ConversionService"/> from the DI container
-/// in both its resource and script methods. Methods with an <see cref="IServiceProvider"/>
-/// parameter are automatically injected by the framework. Properties and methods annotated
-/// with <see cref="AgentSkillResourceAttribute"/> and <see cref="AgentSkillScriptAttribute"/>
-/// are automatically discovered via reflection.
+/// in both its resource and script functions. This enables clean separation of
+/// concerns and testability while retaining the class-based skill pattern.
 /// </remarks>
-internal sealed class WeightConverterSkill : AgentClassSkill<WeightConverterSkill>
+internal sealed class WeightConverterSkill : AgentClassSkill
 {
+    private IReadOnlyList<AgentSkillResource>? _resources;
+    private IReadOnlyList<AgentSkillScript>? _scripts;
+
    /// <inheritdoc/>
    public override AgentSkillFrontmatter Frontmatter { get; } = new(
        "weight-converter",
@@ -135,27 +135,25 @@ internal sealed class WeightConverterSkill : AgentClassSkill<WeightConverterSkil
        3. Present the result clearly with both units.
        """;

-    /// <summary>
-    /// Returns the weight conversion table from the DI-registered <see cref="ConversionService"/>.
-    /// </summary>
-    [AgentSkillResource("weight-table")]
-    [Description("Lookup table of multiplication factors for weight conversions.")]
-    private static string GetWeightTable(IServiceProvider serviceProvider)
-    {
-        var service = serviceProvider.GetRequiredService<ConversionService>();
-        return service.GetWeightTable();
-    }
+    /// <inheritdoc/>
+    public override IReadOnlyList<AgentSkillResource>? Resources => this._resources ??=
+    [
+        CreateResource("weight-table", (IServiceProvider serviceProvider) =>
+        {
+            var service = serviceProvider.GetRequiredService<ConversionService>();
+            return service.GetWeightTable();
+        }),
+    ];

-    /// <summary>
-    /// Converts a value by the given factor using the DI-registered <see cref="ConversionService"/>.
-    /// </summary>
-    [AgentSkillScript("convert")]
-    [Description("Multiplies a value by a conversion factor and returns the result as JSON.")]
-    private static string Convert(double value, double factor, IServiceProvider serviceProvider)
-    {
-        var service = serviceProvider.GetRequiredService<ConversionService>();
-        return service.Convert(value, factor);
-    }
+    /// <inheritdoc/>
+    public override IReadOnlyList<AgentSkillScript>? Scripts => this._scripts ??=
+    [
+        CreateScript("convert", (double value, double factor, IServiceProvider serviceProvider) =>
+        {
+            var service = serviceProvider.GetRequiredService<ConversionService>();
+            return service.Convert(value, factor);
+        }),
+    ];
 }

 // ---------------------------------------------------------------------------
@@ -45,7 +45,7 @@ Set the following environment variables:
 | Variable | Description |
 |---|---|
 | `AZURE_OPENAI_ENDPOINT` | Your Azure OpenAI endpoint URL |
-| `AZURE_OPENAI_DEPLOYMENT_NAME` | Model deployment name (defaults to `gpt-5.4-mini`) |
+| `AZURE_OPENAI_DEPLOYMENT_NAME` | Model deployment name (defaults to `gpt-4o-mini`) |

 ## Running the Sample

@@ -12,7 +12,7 @@ using Microsoft.SemanticKernel.Connectors.InMemory;
 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-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
 var embeddingDeploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-3-large";

 // Create a vector store to store the chat messages in.
@@ -14,7 +14,7 @@ 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-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 var mem0ServiceUri = Environment.GetEnvironmentVariable("MEM0_ENDPOINT") ?? throw new InvalidOperationException("MEM0_ENDPOINT is not set.");
 var mem0ApiKey = Environment.GetEnvironmentVariable("MEM0_API_KEY") ?? throw new InvalidOperationException("MEM0_API_KEY is not set.");
@@ -15,7 +15,7 @@ using Microsoft.Agents.AI.Foundry;

 string foundryEndpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
 string memoryStoreName = Environment.GetEnvironmentVariable("AZURE_AI_MEMORY_STORE_ID") ?? "memory-store-sample";
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
 string embeddingModelName = Environment.GetEnvironmentVariable("AZURE_AI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-ada-002";

 // Create an AIProjectClient for Foundry with Azure Identity authentication.
@@ -14,7 +14,7 @@ This sample demonstrates how to create and run an agent that uses Microsoft Foun
 ## Prerequisites

 1. Azure subscription with Microsoft Foundry project
-2. Azure OpenAI resource with a chat model deployment (e.g., gpt-5.4-mini) and an embedding model deployment (e.g., text-embedding-ada-002)
+2. Azure OpenAI resource with a chat model deployment (e.g., gpt-4o-mini) and an embedding model deployment (e.g., text-embedding-ada-002)
 3. .NET 10.0 SDK
 4. Azure CLI logged in (`az login`)

@@ -26,7 +26,7 @@ export AZURE_AI_PROJECT_ENDPOINT="https://your-account.services.ai.azure.com/api
 export AZURE_AI_MEMORY_STORE_ID="my_memory_store"

 # Model deployment names (models deployed in your Foundry project)
-export AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
+export AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini"
 export AZURE_AI_EMBEDDING_DEPLOYMENT_NAME="text-embedding-ada-002"
 ```

@@ -15,7 +15,7 @@ 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-5.4-mini";
+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.
@@ -13,7 +13,7 @@ This sample demonstrates how to create a custom `ChatHistoryProvider` that keeps

 - [.NET 10 SDK](https://dotnet.microsoft.com/download/dotnet/10.0)
 - An Azure OpenAI resource with:
-  - A chat deployment (e.g., `gpt-5.4-mini`)
+  - A chat deployment (e.g., `gpt-4o-mini`)
  - An embedding deployment (e.g., `text-embedding-3-large`)

 ## Configuration
@@ -23,7 +23,7 @@ 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-5.4-mini` |
+| `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
@@ -7,7 +7,7 @@ using Microsoft.Agents.AI;
 using OpenAI.Responses;

 var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";
+var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";

 AIAgent agent =
    new ResponsesClient(new ApiKeyCredential(apiKey))
@@ -7,7 +7,7 @@ using Microsoft.Extensions.AI;
 using OpenAI;

 var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";
+var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5";

 var client = new OpenAIClient(apiKey)
        .GetResponsesClient()
@@ -7,7 +7,7 @@ using OpenAI.Chat;
 using OpenAIChatClientSample;

 string apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-string model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";
+string model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";

 // Create a ChatClient directly from OpenAIClient
 ChatClient chatClient = new OpenAIClient(apiKey).GetChatClient(model);
@@ -13,7 +13,7 @@ This sample demonstrates how to create an AI agent directly from an `OpenAI.Chat
 1. Set the required environment variables:
   ```bash
   set OPENAI_API_KEY=your_api_key_here
-   set OPENAI_CHAT_MODEL_NAME=gpt-5.4-mini
+   set OPENAI_CHAT_MODEL_NAME=gpt-4o-mini
   ```

 2. Run the sample:
@@ -7,7 +7,7 @@ using OpenAI.Responses;
 using OpenAIResponseClientSample;

 var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";
+var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";

 // Create a ResponsesClient directly from OpenAIClient
 ResponsesClient responseClient = new OpenAIClient(apiKey).GetResponsesClient();
@@ -13,7 +13,7 @@ This sample demonstrates how to create an AI agent directly from an `OpenAI.Resp
 1. Set the required environment variables:
   ```bash
   set OPENAI_API_KEY=your_api_key_here
-   set OPENAI_CHAT_MODEL_NAME=gpt-5.4-mini
+   set OPENAI_CHAT_MODEL_NAME=gpt-4o-mini
   ```

 2. Run the sample:
@@ -15,7 +15,7 @@ using OpenAI.Chat;
 using OpenAI.Conversations;

 string apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-string model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";
+string model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";

 // Create a ConversationClient directly from OpenAIClient
 OpenAIClient openAIClient = new(apiKey);
@@ -69,7 +69,7 @@ foreach (ClientResult result in getConversationItemsResults.GetRawPages())
 1. Set the required environment variables:
   ```powershell
   $env:OPENAI_API_KEY = "your_api_key_here"
-   $env:OPENAI_CHAT_MODEL_NAME = "gpt-5.4-mini"
+   $env:OPENAI_CHAT_MODEL_NAME = "gpt-4o-mini"
   ```

 2. Run the sample:
@@ -1,15 +0,0 @@
-<Project Sdk="Microsoft.NET.Sdk">
-
-  <PropertyGroup>
-    <OutputType>Exe</OutputType>
-    <TargetFrameworks>net10.0</TargetFrameworks>
-
-    <Nullable>enable</Nullable>
-    <ImplicitUsings>enable</ImplicitUsings>
-  </PropertyGroup>
-
-  <ItemGroup>
-    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
-  </ItemGroup>
-
-</Project>
@@ -1,89 +0,0 @@
-// Copyright (c) Microsoft. All rights reserved.
-
-// This sample shows how to download files generated by Code Interpreter using the Containers API.
-// Code Interpreter generates files inside containers (cfile_ / cntr_ IDs) which cannot be
-// downloaded via the standard Files API. Use ContainerClient instead.
-
-#pragma warning disable OPENAI001
-
-using System.ClientModel;
-using Microsoft.Agents.AI;
-using Microsoft.Extensions.AI;
-using OpenAI;
-using OpenAI.Containers;
-using OpenAI.Responses;
-
-string apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-string model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";
-
-var openAIClient = new OpenAIClient(new ApiKeyCredential(apiKey));
-
-// Create an agent with Code Interpreter tool enabled
-AIAgent agent = openAIClient
-    .GetResponsesClient()
-    .AsAIAgent(
-        model: model,
-        instructions: "You are a helpful assistant that can generate files using code.",
-        name: "CodeInterpreterAgent",
-        tools: [new HostedCodeInterpreterTool()]);
-
-// Ask the agent to generate a file
-AgentResponse response = await agent.RunAsync(
-    "Create a CSV file with the multiplication times tables from 1 to 12. Include headers.");
-
-// Display the text response
-foreach (TextContent textContent in response.Messages.SelectMany(x => x.Contents).OfType<TextContent>())
-{
-    Console.WriteLine(textContent.Text);
-}
-
-// Extract container file citations from response annotations and download
-ContainerClient containerClient = openAIClient.GetContainerClient();
-
-HashSet<string> downloadedFiles = [];
-bool foundContainerFiles = false;
-
-foreach (AIContent content in response.Messages.SelectMany(x => x.Contents))
-{
-    if (content.Annotations is null)
-    {
-        continue;
-    }
-
-    foreach (AIAnnotation annotation in content.Annotations)
-    {
-        // Container files from Code Interpreter have ContainerFileCitationMessageAnnotation as raw representation
-        if (annotation is CitationAnnotation citation
-            && citation.RawRepresentation is ContainerFileCitationMessageAnnotation containerCitation)
-        {
-            foundContainerFiles = true;
-
-            // Deduplicate by container+file ID in case the same file is cited multiple times
-            string key = $"{containerCitation.ContainerId}/{containerCitation.FileId}";
-            if (!downloadedFiles.Add(key))
-            {
-                continue;
-            }
-
-            Console.WriteLine($"\nDownloading container file: {containerCitation.Filename}");
-            Console.WriteLine($"  Container ID: {containerCitation.ContainerId}");
-            Console.WriteLine($"  File ID:      {containerCitation.FileId}");
-
-            BinaryData fileData = await containerClient.DownloadContainerFileAsync(
-                containerCitation.ContainerId,
-                containerCitation.FileId);
-
-            // Sanitize filename to prevent path traversal
-            string safeFilename = Path.GetFileName(containerCitation.Filename);
-            string outputPath = Path.Combine(Directory.GetCurrentDirectory(), safeFilename);
-            await File.WriteAllBytesAsync(outputPath, fileData.ToArray());
-            Console.WriteLine($"  Saved to:     {outputPath}");
-        }
-    }
-}
-
-if (!foundContainerFiles)
-{
-    Console.WriteLine("\nNo container file citations found in the response.");
-    Console.WriteLine("The model may not have generated a downloadable file for this prompt.");
-}
@@ -1,51 +0,0 @@
-# Code Interpreter File Download (OpenAI)
-
-This sample demonstrates how to download files generated by Code Interpreter when using the OpenAI Responses API.
-
-## What this sample demonstrates
-
- Creating an agent with Code Interpreter tool using `ResponsesClient.AsAIAgent()`
- Generating files through Code Interpreter (e.g., CSV, Excel, images)
- Extracting container file citations from agent response annotations
- Downloading container files using the `ContainerClient` API
-
-## Container files vs regular files
-
-When Code Interpreter generates a file, the file is stored inside a **container** with a `cntr_` prefixed ID. The file itself gets a `cfile_` prefixed ID.
-
-These container files **cannot** be downloaded using the standard Files API (`GetOpenAIFileClient`), which returns 404 for `cfile_` IDs. Instead, you must use the **Containers API** (`GetContainerClient`) to download them:
-
-```csharp
-// ❌ This does NOT work for container files
-var filesClient = openAIClient.GetOpenAIFileClient();
-await filesClient.DownloadFileAsync("cfile_...");  // Returns 404
-
-// ✅ Use ContainerClient instead
-var containerClient = openAIClient.GetContainerClient();
-await containerClient.DownloadContainerFileAsync("cntr_...", "cfile_...");
-```
-
-The container ID and file ID are available from the `ContainerFileCitationMessageAnnotation` annotation in the response, accessible via `CitationAnnotation.RawRepresentation`.
-
-## Prerequisites
-
- .NET 10 SDK or later
- OpenAI API key with access to a model that supports Code Interpreter
-
-Set the following environment variables:
-
-```powershell
-$env:OPENAI_API_KEY="sk-..."
-$env:OPENAI_CHAT_MODEL_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
-```
-
-## Run the sample
-
-```powershell
-dotnet run
-```
-
-## See also
-
- [Code Interpreter File Download with Foundry](../../../02-agents/AgentsWithFoundry/Agent_Step24_CodeInterpreterFileDownload/) — same scenario using Microsoft Foundry
- [Code Interpreter](../../../02-agents/AgentsWithFoundry/Agent_Step14_CodeInterpreter/) — Code Interpreter without file download
@@ -14,5 +14,4 @@ Agent Framework provides additional support to allow OpenAI developers to use th
 |[Using Reasoning Capabilities](./Agent_OpenAI_Step02_Reasoning/)|This sample demonstrates how to create an AI agent with reasoning capabilities using OpenAI's reasoning models and response types.|
 |[Creating an Agent from a ChatClient](./Agent_OpenAI_Step03_CreateFromChatClient/)|This sample demonstrates how to create an AI agent directly from an OpenAI.Chat.ChatClient instance using OpenAIChatClientAgent.|
 |[Creating an Agent from an OpenAIResponseClient](./Agent_OpenAI_Step04_CreateFromOpenAIResponseClient/)|This sample demonstrates how to create an AI agent directly from an OpenAI.Responses.OpenAIResponseClient instance using OpenAIResponseClientAgent.|
-|[Managing Conversation State](./Agent_OpenAI_Step05_Conversation/)|This sample demonstrates how to maintain conversation state across multiple turns using the AgentSession for context continuity.|
-|[Code Interpreter File Download](./Agent_OpenAI_Step06_CodeInterpreterFileDownload/)|This sample demonstrates how to download files generated by Code Interpreter using the Containers API (`cfile_`/`cntr_` IDs).|
+|[Managing Conversation State](./Agent_OpenAI_Step05_Conversation/)|This sample demonstrates how to maintain conversation state across multiple turns using the AgentSession for context continuity.|
@@ -15,7 +15,7 @@ using Microsoft.SemanticKernel.Connectors.InMemory;
 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-5.4-mini";
+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.
@@ -14,7 +14,7 @@ using OpenAI.Chat;
 using Qdrant.Client;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
 var embeddingDeploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-3-large";
 var afOverviewUrl = "https://raw.githubusercontent.com/MicrosoftDocs/semantic-kernel-docs/refs/heads/main/agent-framework/overview/index.md";
 var afMigrationUrl = "https://raw.githubusercontent.com/MicrosoftDocs/semantic-kernel-docs/refs/heads/main/agent-framework/migration-guide/from-semantic-kernel/index.md";
@@ -23,7 +23,7 @@ Set the following environment variables:

 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
 $env:AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME="text-embedding-3-large"  # Optional, defaults to text-embedding-3-large
 ```

@@ -13,7 +13,7 @@ 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-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 TextSearchProviderOptions textSearchOptions = new()
 {
@@ -14,7 +14,7 @@ using OpenAI.Responses;
 using OpenAI.VectorStores;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // Create an AI Project client and get an OpenAI client that works with the foundry service.
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
@@ -8,7 +8,7 @@ using Neo4j.AgentFramework.GraphRAG;
 using Neo4j.Driver;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
 var neo4jUri = Environment.GetEnvironmentVariable("NEO4J_URI") ?? throw new InvalidOperationException("NEO4J_URI is not set.");
 var neo4jUsername = Environment.GetEnvironmentVariable("NEO4J_USERNAME") ?? "neo4j";
 var neo4jPassword = Environment.GetEnvironmentVariable("NEO4J_PASSWORD") ?? throw new InvalidOperationException("NEO4J_PASSWORD is not set.");
@@ -15,7 +15,7 @@ The sample uses a Neo4j fulltext index for retrieval and a Cypher `RetrievalQuer

 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
 $env:NEO4J_URI="neo4j+s://your-instance.databases.neo4j.io"
 $env:NEO4J_USERNAME="neo4j"
 $env:NEO4J_PASSWORD="your-password"
@@ -14,7 +14,7 @@ using OpenAI.Chat;
 using ChatMessage = Microsoft.Extensions.AI.ChatMessage;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // Create a sample function tool that the agent can use.
 [Description("Get the weather for a given location.")]
@@ -14,7 +14,7 @@ using SampleApp;
 using ChatMessage = Microsoft.Extensions.AI.ChatMessage;

 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-5.4-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // Create chat client to be used by chat client agents.
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
@@ -28,7 +28,7 @@ Set the following environment variables:

 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
 ```

 ## Run the sample
@@ -11,7 +11,7 @@ using Microsoft.Agents.AI;
 using OpenAI.Chat;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // Create the agent
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
@@ -18,7 +18,7 @@ using SampleApp;
 using ChatMessage = Microsoft.Extensions.AI.ChatMessage;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // Create a vector store to store the chat messages in.
 // Replace this with a vector store implementation of your choice if you want to persist the chat history to disk.
@@ -11,7 +11,7 @@ using OpenTelemetry;
 using OpenTelemetry.Trace;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
 var applicationInsightsConnectionString = Environment.GetEnvironmentVariable("APPLICATIONINSIGHTS_CONNECTION_STRING");

 // Create TracerProvider with console exporter
@@ -12,7 +12,7 @@ using Microsoft.Extensions.DependencyInjection;
 using Microsoft.Extensions.Hosting;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // Create a host builder that we will register services with and then run.
 HostApplicationBuilder builder = Host.CreateApplicationBuilder(args);
@@ -11,7 +11,7 @@ using Microsoft.Extensions.Hosting;
 using ModelContextProtocol.Server;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_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
@@ -22,7 +22,7 @@ To use the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector)
 1. Open a web browser and navigate to the URL displayed in the terminal. If not opened automatically, this will open the MCP Inspector interface.
 1. In the MCP Inspector interface, add the following environment variables to allow your MCP server to access Microsoft Foundry Project to create and run the agent:
    - AZURE_AI_PROJECT_ENDPOINT = https://your-resource.openai.azure.com/ # Replace with your Microsoft Foundry Project endpoint
-    - AZURE_AI_MODEL_DEPLOYMENT_NAME = gpt-5.4-mini # Replace with your model deployment name
+    - AZURE_AI_MODEL_DEPLOYMENT_NAME = gpt-4o-mini # Replace with your model deployment name
 1. Find and click the `Connect` button in the MCP Inspector interface to connect to the MCP server.
 1. As soon as the connection is established, open the `Tools` tab in the MCP Inspector interface and select the `Joker` tool from the list.
 1. Specify your prompt as a value for the `query` argument, for example: `Tell me a joke about a pirate` and click the `Run Tool` button to run the tool.
@@ -9,7 +9,7 @@ using OpenAI.Chat;
 using ChatMessage = Microsoft.Extensions.AI.ChatMessage;

 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+var deploymentName = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o";

 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Jacob AlberandGitHub	9f549b0b6f	Merge branch 'main' into dev/dotnet_workflow/fix_multimodel_sample	2026-04-03 13:11:32 -04:00
Jacob AlberandGitHub	e8dcf44048	Merge branch 'main' into dev/dotnet_workflow/fix_multimodel_sample	2026-04-03 12:23:36 -04:00
Jacob AlberandGitHub	d84b593054	Merge branch 'main' into dev/dotnet_workflow/fix_multimodel_sample	2026-04-03 11:19:28 -04:00
Jacob Alber	4d9f0eb24d	fix: 04_MultiModelService sample - Change Bedrock to Google GenAI provider - Fix use of OpenAI ("gpt-4o-mini" requires Responses API to use HostedWebSearchTool) - Clean up output	2026-04-03 08:27:30 -04:00