Merge branch 'main' into dev/dotnet_workflow/fix_file_checkpointstore_paths

* Persist messages during the Function Call Loop

* Revert version reset

* Fix bugs and improve sample

* Fix formatting issues

* Also updating conversation id during run

* Update based on ADR feedback

.github/actions/setup-local-mcp-server/action.yml

@@ -0,0 +1,166 @@
+name: Setup Local MCP Server
+description: Start and validate a local streamable HTTP MCP server for integration tests
+
+inputs:
+  fallback_url:
+    description: Existing LOCAL_MCP_URL value to keep as a fallback if local startup fails
+    required: false
+    default: ''
+  host:
+    description: Host interface to bind the local MCP server
+    required: false
+    default: '127.0.0.1'
+  port:
+    description: Port to bind the local MCP server
+    required: false
+    default: '8011'
+  mount_path:
+    description: Mount path for the local streamable HTTP MCP endpoint
+    required: false
+    default: '/mcp'
+
+outputs:
+  effective_url:
+    description: Local MCP URL when startup succeeds, otherwise the provided fallback URL
+    value: ${{ steps.start.outputs.effective_url }}
+  local_url:
+    description: URL of the local MCP server
+    value: ${{ steps.start.outputs.local_url }}
+  started:
+    description: Whether the local MCP server started and passed validation
+    value: ${{ steps.start.outputs.started }}
+  pid:
+    description: PID of the local MCP server process when startup succeeded
+    value: ${{ steps.start.outputs.pid }}
+
+runs:
+  using: composite
+  steps:
+    - name: Start and validate local MCP server
+      id: start
+      shell: bash
+      run: |
+        set -euo pipefail
+
+        host="${{ inputs.host }}"
+        port="${{ inputs.port }}"
+        mount_path="${{ inputs.mount_path }}"
+        fallback_url="${{ inputs.fallback_url }}"
+
+        if [[ ! "$mount_path" =~ ^/ ]]; then
+          mount_path="/$mount_path"
+        fi
+
+        local_url="http://${host}:${port}${mount_path}"
+        health_url="http://${host}:${port}/healthz"
+        log_file="$RUNNER_TEMP/local-mcp-server.log"
+        pid_file="$RUNNER_TEMP/local-mcp-server.pid"
+        rm -f "$log_file" "$pid_file"
+
+        server_pid="$(
+          python3 - "$GITHUB_WORKSPACE/python" "$log_file" "$host" "$port" "$mount_path" <<'PY'
+        from __future__ import annotations
+
+        import subprocess
+        import sys
+
+        workspace, log_file, host, port, mount_path = sys.argv[1:]
+
+        with open(log_file, "w", encoding="utf-8") as log:
+            process = subprocess.Popen(
+                [
+                    "uv",
+                    "run",
+                    "python",
+                    "scripts/local_mcp_streamable_http_server.py",
+                    "--host",
+                    host,
+                    "--port",
+                    port,
+                    "--mount-path",
+                    mount_path,
+                ],
+                cwd=workspace,
+                stdout=log,
+                stderr=subprocess.STDOUT,
+                start_new_session=True,
+            )
+
+        print(process.pid)
+        PY
+        )"
+        echo "$server_pid" > "$pid_file"
+
+        started=false
+        for _ in $(seq 1 30); do
+          if curl --silent --fail "$health_url" >/dev/null; then
+            started=true
+            break
+          fi
+          if ! kill -0 "$server_pid" 2>/dev/null; then
+            break
+          fi
+          sleep 1
+        done
+
+        if [[ "$started" == "true" ]]; then
+          if ! (
+            cd "$GITHUB_WORKSPACE/python"
+            LOCAL_MCP_URL="$local_url" uv run python - <<'PY'
+        from __future__ import annotations
+
+        import asyncio
+        import os
+
+        from agent_framework import Content, MCPStreamableHTTPTool
+
+
+        def result_to_text(result: str | list[Content]) -> str:
+            if isinstance(result, str):
+                return result
+            return "\n".join(content.text for content in result if content.type == "text" and content.text)
+
+
+        async def main() -> None:
+            tool = MCPStreamableHTTPTool(
+                name="local_ci_mcp",
+                url=os.environ["LOCAL_MCP_URL"],
+                approval_mode="never_require",
+            )
+
+            async with tool:
+                assert tool.functions, "Local MCP server did not expose any tools."
+                result = result_to_text(await tool.functions[0].invoke(query="What is Agent Framework?"))
+                assert result, "Local MCP server returned an empty response."
+
+
+        asyncio.run(main())
+        PY
+          ); then
+            started=false
+          fi
+        fi
+
+        effective_url="$local_url"
+        pid="$server_pid"
+
+        if [[ "$started" != "true" ]]; then
+          effective_url="$fallback_url"
+          pid=""
+          if kill -0 "$server_pid" 2>/dev/null; then
+            kill -TERM -- "-$server_pid" 2>/dev/null || kill -TERM "$server_pid" || true
+            sleep 1
+            kill -KILL -- "-$server_pid" 2>/dev/null || kill -KILL "$server_pid" || true
+          fi
+          echo "Local MCP server was unavailable; continuing with fallback LOCAL_MCP_URL."
+          if [[ -f "$log_file" ]]; then
+            tail -n 100 "$log_file" || true
+          fi
+        else
+          echo "Using local MCP server at $local_url"
+        fi
+
+        echo "started=$started" >> "$GITHUB_OUTPUT"
+        echo "local_url=$local_url" >> "$GITHUB_OUTPUT"
+        echo "effective_url=$effective_url" >> "$GITHUB_OUTPUT"
+        echo "pid=$pid" >> "$GITHUB_OUTPUT"

.github/workflows/python-check-coverage.py

@@ -41,8 +41,7 @@ ENFORCED_TARGETS: set[str] = {
     "packages.purview.agent_framework_purview",
     "packages.anthropic.agent_framework_anthropic",
     "packages.azure-ai-search.agent_framework_azure_ai_search",
-    "packages.core.agent_framework.azure",
-    "packages.core.agent_framework.openai",
+    "packages.openai.agent_framework_openai",
     # Individual files (if you want to enforce specific files instead of whole packages)
     "packages/core/agent_framework/observability.py",
     # Add more targets here as coverage improves

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

@@ -63,6 +63,8 @@ jobs:
       OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
       OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
       OPENAI_EMBEDDINGS_MODEL_ID: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
+      OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
+      OPENAI_EMBEDDING_MODEL: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
       OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
     defaults:
       run:
@@ -81,8 +83,8 @@ jobs:
       - name: Test with pytest (OpenAI integration)
         run: >
           uv run pytest --import-mode=importlib
-          packages/core/tests/openai
-          -m integration
+          packages/openai/tests
+          -m "integration and not azure"
           -n logical --dist worksteal
           --timeout=120 --session-timeout=900 --timeout_method thread
           --retries 2 --retry-delay 5
@@ -94,8 +96,9 @@ jobs:
     environment: integration
     timeout-minutes: 60
     env:
-      AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
+      AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
       AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
       AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__EMBEDDINGDEPLOYMENTNAME }}
       AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
     defaults:
@@ -121,7 +124,9 @@ jobs:
       - name: Test with pytest (Azure OpenAI integration)
         run: >
           uv run pytest --import-mode=importlib
-          packages/core/tests/azure
+          packages/openai/tests/openai/test_openai_chat_completion_client_azure.py
+          packages/openai/tests/openai/test_openai_chat_client_azure.py
+          packages/azure-ai/tests/azure_openai
           -m integration
           -n logical --dist worksteal
           --timeout=120 --session-timeout=900 --timeout_method thread
@@ -151,6 +156,13 @@ jobs:
         with:
           python-version: ${{ env.UV_PYTHON }}
           os: ${{ runner.os }}
+      - name: Start local MCP server
+        id: local-mcp
+        uses: ./.github/actions/setup-local-mcp-server
+        with:
+          fallback_url: ${{ env.LOCAL_MCP_URL }}
+      - name: Prefer local MCP URL when available
+        run: echo "LOCAL_MCP_URL=${{ steps.local-mcp.outputs.effective_url }}" >> "$GITHUB_ENV"
       - name: Test with pytest (Anthropic, Ollama, MCP integration)
         run: >
           uv run pytest --import-mode=importlib
@@ -161,6 +173,26 @@ jobs:
           -n logical --dist worksteal
           --timeout=120 --session-timeout=900 --timeout_method thread
           --retries 2 --retry-delay 5
+      - name: Stop local MCP server
+        if: always()
+        shell: bash
+        run: |
+          set -euo pipefail
+          server_pid="${{ steps.local-mcp.outputs.pid }}"
+          if [[ -z "$server_pid" ]]; then
+            exit 0
+          fi
+          if ! kill -0 "$server_pid" 2>/dev/null; then
+            exit 0
+          fi
+          kill -TERM -- "-$server_pid" 2>/dev/null || kill -TERM "$server_pid" 2>/dev/null || true
+          for _ in $(seq 1 10); do
+            if ! kill -0 "$server_pid" 2>/dev/null; then
+              exit 0
+            fi
+            sleep 1
+          done
+          kill -KILL -- "-$server_pid" 2>/dev/null || kill -KILL "$server_pid" 2>/dev/null || true
 
   # Azure Functions + Durable Task integration tests
   python-tests-functions:
@@ -172,10 +204,13 @@ jobs:
       UV_PYTHON: "3.11"
       OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
       OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
+      OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
       OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
-      AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
-      AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      OPENAI_EMBEDDING_MODEL: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
       AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
+      AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      FOUNDRY_MODEL: ${{ vars.AZUREAI__DEPLOYMENTNAME }}
+      FOUNDRY_PROJECT_ENDPOINT: ${{ secrets.AZUREAI__ENDPOINT }}
       FUNCTIONS_WORKER_RUNTIME: "python"
       DURABLE_TASK_SCHEDULER_CONNECTION_STRING: "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None"
       AzureWebJobsStorage: "UseDevelopmentStorage=true"
@@ -209,7 +244,8 @@ jobs:
           packages/durabletask/tests/integration_tests
           -m integration
           -n logical --dist worksteal
-          --timeout=120 --session-timeout=900 --timeout_method thread
+          -x
+          --timeout=360 --session-timeout=900 --timeout_method thread
           --retries 2 --retry-delay 5
 
   # Azure AI integration tests
@@ -221,6 +257,8 @@ jobs:
     env:
       AZURE_AI_PROJECT_ENDPOINT: ${{ secrets.AZUREAI__ENDPOINT }}
       AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.AZUREAI__DEPLOYMENTNAME }}
+      FOUNDRY_PROJECT_ENDPOINT: ${{ secrets.AZUREAI__ENDPOINT }}
+      FOUNDRY_MODEL: ${{ vars.AZUREAI__DEPLOYMENTNAME }}
       LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
     defaults:
       run:
@@ -244,7 +282,9 @@ jobs:
           subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
       - name: Test with pytest
         timeout-minutes: 15
-        run: uv run --directory packages/azure-ai poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5
+        run: |
+          uv run --directory packages/azure-ai poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5
+          uv run --directory packages/foundry poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5
 
   # Azure Cosmos integration tests
   python-tests-cosmos:

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

@@ -47,6 +47,9 @@ jobs:
           filters: |
             python:
               - 'python/**'
+              - '.github/actions/setup-local-mcp-server/**'
+              - '.github/workflows/python-merge-tests.yml'
+              - '.github/workflows/python-integration-tests.yml'
             core:
               - 'python/packages/core/agent_framework/_*.py'
               - 'python/packages/core/agent_framework/_workflows/**'
@@ -54,20 +57,30 @@ jobs:
               - 'python/packages/core/agent_framework/observability.py'
             openai:
               - 'python/packages/core/agent_framework/openai/**'
-              - 'python/packages/core/tests/openai/**'
+              - 'python/packages/openai/**'
+              - 'python/samples/**/providers/openai/**'
             azure:
+              - 'python/packages/openai/**'
               - 'python/packages/core/agent_framework/azure/**'
-              - 'python/packages/core/tests/azure/**'
+              - 'python/packages/azure-ai/agent_framework_azure_ai/_deprecated_azure_openai.py'
+              - 'python/packages/azure-ai/tests/azure_openai/**'
+              - 'python/samples/**/providers/azure/openai_chat_completion_client_azure*.py'
             misc:
               - 'python/packages/anthropic/**'
               - 'python/packages/ollama/**'
               - 'python/packages/core/agent_framework/_mcp.py'
               - 'python/packages/core/tests/core/test_mcp.py'
+              - 'python/scripts/local_mcp_streamable_http_server.py'
+              - '.github/actions/setup-local-mcp-server/**'
+              - '.github/workflows/python-merge-tests.yml'
+              - '.github/workflows/python-integration-tests.yml'
             functions:
               - 'python/packages/azurefunctions/**'
               - 'python/packages/durabletask/**'
             azure-ai:
               - 'python/packages/azure-ai/**'
+              - 'python/packages/foundry/**'
+              - 'python/samples/**/providers/foundry/**'
             cosmos:
               - 'python/packages/azure-cosmos/**'
       # run only if 'python' files were changed
@@ -131,6 +144,8 @@ jobs:
       OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
       OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
       OPENAI_EMBEDDINGS_MODEL_ID: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
+      OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
+      OPENAI_EMBEDDING_MODEL: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
       OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
     defaults:
       run:
@@ -146,8 +161,8 @@ jobs:
       - name: Test with pytest (OpenAI integration)
         run: >
           uv run pytest --import-mode=importlib
-          packages/core/tests/openai
-          -m integration
+          packages/openai/tests
+          -m "integration and not azure"
           -n logical --dist worksteal
           --timeout=120 --session-timeout=900 --timeout_method thread
           --retries 2 --retry-delay 5
@@ -180,8 +195,9 @@ jobs:
     runs-on: ubuntu-latest
     environment: integration
     env:
-      AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
+      AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
       AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
       AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__EMBEDDINGDEPLOYMENTNAME }}
       AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
     defaults:
@@ -205,7 +221,9 @@ jobs:
       - name: Test with pytest (Azure OpenAI integration)
         run: >
           uv run pytest --import-mode=importlib
-          packages/core/tests/azure
+          packages/openai/tests/openai/test_openai_chat_completion_client_azure.py
+          packages/openai/tests/openai/test_openai_chat_client_azure.py
+          packages/azure-ai/tests/azure_openai
           -m integration
           -n logical --dist worksteal
           --timeout=120 --session-timeout=900 --timeout_method thread
@@ -253,6 +271,13 @@ jobs:
         with:
           python-version: ${{ env.UV_PYTHON }}
           os: ${{ runner.os }}
+      - name: Start local MCP server
+        id: local-mcp
+        uses: ./.github/actions/setup-local-mcp-server
+        with:
+          fallback_url: ${{ env.LOCAL_MCP_URL }}
+      - name: Prefer local MCP URL when available
+        run: echo "LOCAL_MCP_URL=${{ steps.local-mcp.outputs.effective_url }}" >> "$GITHUB_ENV"
       - name: Test with pytest (Anthropic, Ollama, MCP integration)
         run: >
           uv run pytest --import-mode=importlib
@@ -264,6 +289,26 @@ jobs:
           --timeout=120 --session-timeout=900 --timeout_method thread
           --retries 2 --retry-delay 5
         working-directory: ./python
+      - name: Stop local MCP server
+        if: always()
+        shell: bash
+        run: |
+          set -euo pipefail
+          server_pid="${{ steps.local-mcp.outputs.pid }}"
+          if [[ -z "$server_pid" ]]; then
+            exit 0
+          fi
+          if ! kill -0 "$server_pid" 2>/dev/null; then
+            exit 0
+          fi
+          kill -TERM -- "-$server_pid" 2>/dev/null || kill -TERM "$server_pid" 2>/dev/null || true
+          for _ in $(seq 1 10); do
+            if ! kill -0 "$server_pid" 2>/dev/null; then
+              exit 0
+            fi
+            sleep 1
+          done
+          kill -KILL -- "-$server_pid" 2>/dev/null || kill -KILL "$server_pid" 2>/dev/null || true
       - name: Surface failing tests
         if: always()
         uses: pmeier/pytest-results-action@v0.7.2
@@ -290,10 +335,13 @@ jobs:
       UV_PYTHON: "3.11"
       OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
       OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
+      OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
       OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
-      AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__CHATDEPLOYMENTNAME }}
-      AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      OPENAI_EMBEDDING_MODEL: ${{ vars.OPENAI_EMBEDDING_MODEL_ID }}
       AZURE_OPENAI_ENDPOINT: ${{ vars.AZUREOPENAI__ENDPOINT }}
+      AZURE_OPENAI_DEPLOYMENT_NAME: ${{ vars.AZUREOPENAI__RESPONSESDEPLOYMENTNAME }}
+      FOUNDRY_MODEL: ${{ vars.AZUREAI__DEPLOYMENTNAME }}
+      FOUNDRY_PROJECT_ENDPOINT: ${{ secrets.AZUREAI__ENDPOINT }}
       FUNCTIONS_WORKER_RUNTIME: "python"
       DURABLE_TASK_SCHEDULER_CONNECTION_STRING: "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None"
       AzureWebJobsStorage: "UseDevelopmentStorage=true"
@@ -325,7 +373,8 @@ jobs:
           packages/durabletask/tests/integration_tests
           -m integration
           -n logical --dist worksteal
-          --timeout=120 --session-timeout=900 --timeout_method thread
+          -x
+          --timeout=360 --session-timeout=900 --timeout_method thread
           --retries 2 --retry-delay 5
         working-directory: ./python
       - name: Surface failing tests
@@ -352,6 +401,8 @@ jobs:
     env:
       AZURE_AI_PROJECT_ENDPOINT: ${{ secrets.AZUREAI__ENDPOINT }}
       AZURE_AI_MODEL_DEPLOYMENT_NAME: ${{ vars.AZUREAI__DEPLOYMENTNAME }}
+      FOUNDRY_PROJECT_ENDPOINT: ${{ secrets.AZUREAI__ENDPOINT }}
+      FOUNDRY_MODEL: ${{ vars.AZUREAI__DEPLOYMENTNAME }}
       LOCAL_MCP_URL: ${{ vars.LOCAL_MCP__URL }}
     defaults:
       run:
@@ -373,7 +424,9 @@ jobs:
           subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
       - name: Test with pytest
         timeout-minutes: 15
-        run: uv run --directory packages/azure-ai poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5
+        run: |
+          uv run --directory packages/azure-ai poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5
+          uv run --directory packages/foundry poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5
         working-directory: ./python
       - name: Test Azure AI samples
         timeout-minutes: 10

.github/workflows/python-sample-validation.yml

@@ -78,6 +78,7 @@ jobs:
       OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
       # GitHub MCP
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+      OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
       # Observability
       ENABLE_INSTRUMENTATION: "true"
     defaults:
@@ -346,7 +347,7 @@ jobs:
 
   validate-02-agents-amazon:
     name: Validate 02-agents/providers/amazon
-    if: false  # Temporarily disabled - requires AWS credentials
+    if: false # Temporarily disabled - requires AWS credentials
     runs-on: ubuntu-latest
     environment: integration
     env:
@@ -378,7 +379,7 @@ jobs:
 
   validate-02-agents-ollama:
     name: Validate 02-agents/providers/ollama
-    if: false  # Temporarily disabled - requires local Ollama server
+    if: false # Temporarily disabled - requires local Ollama server
     runs-on: ubuntu-latest
     environment: integration
     env:
@@ -410,7 +411,7 @@ jobs:
 
   validate-02-agents-foundry-local:
     name: Validate 02-agents/providers/foundry_local
-    if: false  # Temporarily disabled - requires local Foundry setup
+    if: false # Temporarily disabled - requires local Foundry setup
     runs-on: ubuntu-latest
     environment: integration
     defaults:
@@ -440,7 +441,7 @@ jobs:
 
   validate-02-agents-copilotstudio:
     name: Validate 02-agents/providers/copilotstudio
-    if: false  # Temporarily disabled - requires Copilot Studio setup
+    if: false # Temporarily disabled - requires Copilot Studio setup
     runs-on: ubuntu-latest
     environment: integration
     env:
@@ -556,7 +557,7 @@ jobs:
 
   validate-04-hosting:
     name: Validate 04-hosting
-    if: false  # Temporarily disabled because of sample complexity
+    if: false # Temporarily disabled because of sample complexity
     runs-on: ubuntu-latest
     environment: integration
     env:
@@ -595,7 +596,7 @@ jobs:
 
   validate-05-end-to-end:
     name: Validate 05-end-to-end
-    if: false  # Temporarily disabled because of sample complexity
+    if: false # Temporarily disabled because of sample complexity
     runs-on: ubuntu-latest
     environment: integration
     env:
@@ -652,6 +653,7 @@ jobs:
       OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
       OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
       OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
+      OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
     defaults:
       run:
         working-directory: python
@@ -703,6 +705,7 @@ jobs:
       OPENAI_API_KEY: ${{ secrets.OPENAI__APIKEY }}
       OPENAI_CHAT_MODEL_ID: ${{ vars.OPENAI__CHATMODELID }}
       OPENAI_RESPONSES_MODEL_ID: ${{ vars.OPENAI__RESPONSESMODELID }}
+      OPENAI_MODEL: ${{ vars.OPENAI__RESPONSESMODELID }}
       # Copilot Studio
       COPILOTSTUDIOAGENT__ENVIRONMENTID: ${{ secrets.COPILOTSTUDIOAGENT__ENVIRONMENTID }}
       COPILOTSTUDIOAGENT__SCHEMANAME: ${{ secrets.COPILOTSTUDIOAGENT__SCHEMANAME }}

docs/decisions/0021-provider-leading-clients.md

@@ -0,0 +1,72 @@
+---
+status: accepted
+contact: eavanvalkenburg
+date: 2026-03-20
+deciders: eavanvalkenburg, sphenry, chetantoshnival
+consulted: taochenosu, moonbox3, dmytrostruk, giles17, alliscode
+---
+
+# Provider-Leading Client Design & OpenAI Package Extraction
+
+## Context and Problem Statement
+
+The `agent-framework-core` package currently bundles OpenAI and Azure OpenAI client implementations along with their dependencies (`openai`, `azure-identity`, `azure-ai-projects`, `packaging`). This makes core heavier than necessary for users who don't use OpenAI, and it conflates the core abstractions with a specific provider implementation. Additionally, the current class naming (`OpenAIResponsesClient`, `OpenAIChatClient`) is based on the underlying OpenAI API names rather than what users actually want to do, making discoverability harder for newcomers.
+
+## Decision Drivers
+
+- **Lightweight core**: Core should only contain abstractions, middleware infrastructure, and telemetry — no provider-specific code or dependencies.
+- **Discoverability-first**: Import namespaces should guide users to the right client. `from agent_framework.openai import ...` should surface all OpenAI-related clients; `from agent_framework.azure import ...` should surface Foundry, Azure AI, and other Azure-specific classes.
+- **Provider-leading naming**: The primary client name should reflect the provider, not the underlying API. The Responses API is now the recommended default for OpenAI, so its client should be called `OpenAIChatClient` (not `OpenAIResponsesClient`).
+- **Clean separation of concerns**: Azure-specific deprecated wrappers belong in the azure-ai package, not in the OpenAI package.
+
+## Considered Options
+
+- **Keep OpenAI in core**: Simpler but keeps core heavy; doesn't help discoverability.
+- **Extract OpenAI with Azure wrappers in the OpenAI package**: Keeps Azure OpenAI wrappers alongside OpenAI code, but pollutes the OpenAI package with Azure concerns.
+- **Extract OpenAI, place Azure wrappers in azure-ai**: Clean separation; the OpenAI package has zero Azure dependencies; deprecated Azure wrappers live in a single file in azure-ai for easy future deletion.
+
+## Decision Outcome
+
+Chosen option: "Extract OpenAI, place Azure wrappers in azure-ai", because it achieves the lightest core, cleanest OpenAI package, and the most maintainable deprecation path.
+
+Key changes:
+
+1. **New `agent-framework-openai` package** with dependencies on `agent-framework-core`, `openai`, and `packaging` only.
+2. **Class renames**: `OpenAIResponsesClient` → `OpenAIChatClient` (Responses API), `OpenAIChatClient` → `OpenAIChatCompletionClient` (Chat Completions API). Old names remain as deprecated aliases.
+3. **Deprecated classes**: `OpenAIAssistantsClient`, all `AzureOpenAI*Client` classes, `AzureAIClient`, `AzureAIAgentClient`, and `AzureAIProjectAgentProvider` are marked deprecated.
+4. **New `FoundryChatClient`** in azure-ai for Azure AI Foundry Responses API access, built on `RawFoundryChatClient(RawOpenAIChatClient)`.
+5. **All deprecated `AzureOpenAI*` classes** consolidated into a single file (`_deprecated_azure_openai.py`) in the azure-ai package for clean future deletion.
+6. **Core's `agent_framework.openai` and `agent_framework.azure` namespaces** become lazy-loading gateways, preserving backward-compatible import paths while removing hard dependencies.
+7. **Unified `model` parameter** replaces `model_id` (OpenAI), `deployment_name` (Azure OpenAI), and `model_deployment_name` (Azure AI) across all client constructors. The term `model` is intentionally generic: it naturally maps to an OpenAI model name *and* to an Azure OpenAI deployment name, making it straightforward to use `OpenAIChatClient` with either OpenAI or Azure OpenAI backends (via `AsyncAzureOpenAI`). Environment variables are similarly unified (e.g., `OPENAI_MODEL` instead of separate `OPENAI_RESPONSES_MODEL_ID` / `OPENAI_CHAT_MODEL_ID`).
+8. **`FoundryAgent`** replaces the pattern of `Agent(client=AzureAIClient(...))` for connecting to pre-configured agents in Azure AI Foundry (PromptAgents and HostedAgents). The underlying `RawFoundryAgentChatClient` is an implementation detail — most users interact only with `FoundryAgent`. `AzureAIAgentClient` is separately deprecated as it refers to the V1 Agents Service API. See below for design rationale.
+
+### Foundry Agent Design: `FoundryAgentClient` vs `FoundryAgent`
+
+The existing `AzureAIClient` combines two concerns: CRUD lifecycle management (creating/deleting agents on the service) and runtime communication (sending messages via the Responses API). The new design removes CRUD entirely — users connect to agents that already exist in Foundry.
+
+**Two approaches were considered:**
+
+**Option A — `FoundryAgentClient` only (public ChatClient):**
+Users compose `Agent(client=FoundryAgentClient(...), tools=[...])`. This follows the universal `Agent(client=X)` pattern used by every other provider. However, a "client" that wraps a named remote agent (with `agent_name` as a constructor param) is semantically odd — clients typically wrap a model endpoint, not a specific agent.
+
+**Option B — `FoundryAgent` (Agent subclass) + private `_FoundryAgentChatClient` and public `RawFoundryAgentChatClient`:**
+Users write `FoundryAgent(agent_name="my-agent", ...)` for the common case. Internally, `FoundryAgent` creates a `_FoundryAgentChatClient` and passes it to the standard `Agent` base class. For advanced customization, users pass `client_type=RawFoundryAgentChatClient` (or a custom subclass) to control the client middleware layers. The `Agent(client=RawFoundryAgentChatClient(...))` composition pattern still works for users who prefer it.
+
+**Chosen option: Option B**, because:
+- The common case (`FoundryAgent(...)`) is a single object with no boilerplate.
+- `client_type=` gives full control over client middleware without parameter duplication — the agent forwards connection params to the client internally.
+- `RawFoundryAgent(RawAgent)` and `FoundryAgent(Agent)` mirror the established `RawAgent`/`Agent` pattern.
+- Runtime validation (only `FunctionTool` allowed) lives in `RawFoundryAgentChatClient._prepare_options`, ensuring it applies regardless of how the client is used — through `FoundryAgent`, `Agent(client=...)`, or any custom composition.
+
+**Public classes:**
+- `RawFoundryAgentChatClient(RawOpenAIChatClient)` — Responses API client that injects agent reference and validates tools. Extension point for custom client middleware.
+- `RawFoundryAgent(RawAgent)` — Agent without agent-level middleware/telemetry.
+- `FoundryAgent(AgentTelemetryLayer, AgentMiddlewareLayer, RawFoundryAgent)` — Recommended production agent.
+
+**Internal (private):**
+- `_FoundryAgentChatClient` — Full client with function invocation, chat middleware, and telemetry layers. Created automatically by `FoundryAgent`; users customize via `client_type=RawFoundryAgentChatClient` or a custom subclass.
+
+**Deprecated:**
+- `AzureAIClient` — replaced by `FoundryAgent` (which uses `FoundryAgentClient` internally).
+- `AzureAIAgentClient` — refers to V1 Agents Service API, no direct replacement.
+- `AzureAIProjectAgentProvider` — replaced by `FoundryAgent`.

dotnet/agent-framework-dotnet.slnx

@@ -57,6 +57,7 @@
     <Project Path="samples/02-agents/Agents/Agent_Step16_Declarative/Agent_Step16_Declarative.csproj" />
     <Project Path="samples/02-agents/Agents/Agent_Step17_AdditionalAIContext/Agent_Step17_AdditionalAIContext.csproj" />
     <Project Path="samples/02-agents/Agents/Agent_Step18_CompactionPipeline/Agent_Step18_CompactionPipeline.csproj" />
+    <Project Path="samples/02-agents/Agents/Agent_Step19_InFunctionLoopCheckpointing/Agent_Step19_InFunctionLoopCheckpointing.csproj" />
   </Folder>
   <Folder Name="/Samples/02-agents/DeclarativeAgents/">
     <Project Path="samples/02-agents/DeclarativeAgents/ChatClient/DeclarativeChatClientAgents.csproj" />

dotnet/samples/02-agents/Agents/Agent_Step19_InFunctionLoopCheckpointing/Agent_Step19_InFunctionLoopCheckpointing.csproj

@@ -0,0 +1,20 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/02-agents/Agents/Agent_Step19_InFunctionLoopCheckpointing/Program.cs

@@ -0,0 +1,226 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how the ChatClientAgent persists chat history after each individual
+// call to the AI service.
+// When an agent uses tools, FunctionInvokingChatClient may loop multiple times
+// (service call → tool execution → service call), and intermediate messages (tool calls and
+// results) are persisted after each service call. This allows you to inspect or recover them
+// even if the process is interrupted mid-loop, but may also result in chat history that is not
+// yet finalized (e.g., tool calls without results) being persisted, which may be undesirable in some cases.
+//
+// To opt into end-of-run persistence instead (atomic run semantics), set
+// PersistChatHistoryAtEndOfRun = true on ChatClientAgentOptions.
+//
+// The sample runs two multi-turn conversations: one using non-streaming (RunAsync) and one
+// using streaming (RunStreamingAsync), to demonstrate correct behavior in both modes.
+
+using System.ComponentModel;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+using OpenAI.Responses;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var store = Environment.GetEnvironmentVariable("AZURE_OPENAI_RESPONSES_STORE") ?? "false";
+
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AzureOpenAIClient openAIClient = new(new Uri(endpoint), new DefaultAzureCredential());
+
+// Define multiple tools so the model makes several tool calls in a single run.
+[Description("Get the current weather for a city.")]
+static string GetWeather([Description("The city name.")] string city) =>
+    city.ToUpperInvariant() switch
+    {
+        "SEATTLE" => "Seattle: 55°F, cloudy with light rain.",
+        "NEW YORK" => "New York: 72°F, sunny and warm.",
+        "LONDON" => "London: 48°F, overcast with fog.",
+        "DUBLIN" => "Dublin: 43°F, overcast with fog.",
+        _ => $"{city}: weather data not available."
+    };
+
+[Description("Get the current time in a city.")]
+static string GetTime([Description("The city name.")] string city) =>
+    city.ToUpperInvariant() switch
+    {
+        "SEATTLE" => "Seattle: 9:00 AM PST",
+        "NEW YORK" => "New York: 12:00 PM EST",
+        "LONDON" => "London: 5:00 PM GMT",
+        "DUBLIN" => "Dublin: 5:00 PM GMT",
+        _ => $"{city}: time data not available."
+    };
+
+// Create the agent — per-service-call persistence is the default behavior.
+// The in-memory ChatHistoryProvider is used by default when the service does not require service stored chat
+// history, so for those cases, we can inspect the chat history via session.TryGetInMemoryChatHistory().
+IChatClient chatClient = string.Equals(store, "TRUE", StringComparison.OrdinalIgnoreCase) ?
+    openAIClient.GetResponsesClient().AsIChatClient(deploymentName) :
+    openAIClient.GetResponsesClient().AsIChatClientWithStoredOutputDisabled(deploymentName);
+AIAgent agent = chatClient.AsAIAgent(
+    new ChatClientAgentOptions
+    {
+        Name = "WeatherAssistant",
+        ChatOptions = new()
+        {
+            Instructions = "You are a helpful assistant. When asked about multiple cities, call the appropriate tool for each city.",
+            Tools = [AIFunctionFactory.Create(GetWeather), AIFunctionFactory.Create(GetTime)]
+        },
+    });
+
+await RunNonStreamingAsync();
+await RunStreamingAsync();
+
+async Task RunNonStreamingAsync()
+{
+    int lastChatHistorySize = 0;
+    string lastConversationId = string.Empty;
+
+    Console.ForegroundColor = ConsoleColor.Yellow;
+    Console.WriteLine("\n=== Non-Streaming Mode ===");
+    Console.ResetColor();
+
+    AgentSession session = await agent.CreateSessionAsync();
+
+    // First turn — ask about multiple cities so the model calls tools.
+    const string Prompt = "What's the weather and time in Seattle, New York, and London?";
+    PrintUserMessage(Prompt);
+
+    var response = await agent.RunAsync(Prompt, session);
+    PrintAgentResponse(response.Text);
+    PrintChatHistory(session, "After run", ref lastChatHistorySize, ref lastConversationId);
+
+    // Second turn — follow-up to verify chat history is correct.
+    const string FollowUp1 = "And Dublin?";
+    PrintUserMessage(FollowUp1);
+
+    response = await agent.RunAsync(FollowUp1, session);
+    PrintAgentResponse(response.Text);
+    PrintChatHistory(session, "After second run", ref lastChatHistorySize, ref lastConversationId);
+
+    // Third turn — follow-up to verify chat history is correct.
+    const string FollowUp2 = "Which city is the warmest?";
+    PrintUserMessage(FollowUp2);
+
+    response = await agent.RunAsync(FollowUp2, session);
+    PrintAgentResponse(response.Text);
+    PrintChatHistory(session, "After third run", ref lastChatHistorySize, ref lastConversationId);
+}
+
+async Task RunStreamingAsync()
+{
+    int lastChatHistorySize = 0;
+    string lastConversationId = string.Empty;
+
+    Console.ForegroundColor = ConsoleColor.Yellow;
+    Console.WriteLine("\n=== Streaming Mode ===");
+    Console.ResetColor();
+
+    AgentSession session = await agent.CreateSessionAsync();
+
+    // First turn — ask about multiple cities so the model calls tools.
+    const string Prompt = "What's the weather and time in Seattle, New York, and London?";
+    PrintUserMessage(Prompt);
+
+    Console.ForegroundColor = ConsoleColor.Cyan;
+    Console.Write("\n[Agent] ");
+    Console.ResetColor();
+
+    await foreach (var update in agent.RunStreamingAsync(Prompt, session))
+    {
+        Console.Write(update);
+
+        // During streaming we should be able to see updates to the chat history
+        // before the full run completes, as each service call is made and persisted.
+        PrintChatHistory(session, "During run", ref lastChatHistorySize, ref lastConversationId);
+    }
+
+    Console.WriteLine();
+    PrintChatHistory(session, "After run", ref lastChatHistorySize, ref lastConversationId);
+
+    // Second turn — follow-up to verify chat history is correct.
+    const string FollowUp1 = "And Dublin?";
+    PrintUserMessage(FollowUp1);
+
+    Console.ForegroundColor = ConsoleColor.Cyan;
+    Console.Write("\n[Agent] ");
+    Console.ResetColor();
+
+    await foreach (var update in agent.RunStreamingAsync(FollowUp1, session))
+    {
+        Console.Write(update);
+
+        // During streaming we should be able to see updates to the chat history
+        // before the full run completes, as each service call is made and persisted.
+        PrintChatHistory(session, "During second run", ref lastChatHistorySize, ref lastConversationId);
+    }
+
+    Console.WriteLine();
+    PrintChatHistory(session, "After second run", ref lastChatHistorySize, ref lastConversationId);
+
+    // Third turn — follow-up to verify chat history is correct.
+    const string FollowUp2 = "Which city is the warmest?";
+    PrintUserMessage(FollowUp2);
+
+    Console.ForegroundColor = ConsoleColor.Cyan;
+    Console.Write("\n[Agent] ");
+    Console.ResetColor();
+
+    await foreach (var update in agent.RunStreamingAsync(FollowUp2, session))
+    {
+        Console.Write(update);
+
+        // During streaming we should be able to see updates to the chat history
+        // before the full run completes, as each service call is made and persisted.
+        PrintChatHistory(session, "During third run", ref lastChatHistorySize, ref lastConversationId);
+    }
+
+    Console.WriteLine();
+    PrintChatHistory(session, "After third run", ref lastChatHistorySize, ref lastConversationId);
+}
+
+void PrintUserMessage(string message)
+{
+    Console.ForegroundColor = ConsoleColor.Cyan;
+    Console.Write("\n[User] ");
+    Console.ResetColor();
+    Console.WriteLine(message);
+}
+
+void PrintAgentResponse(string? text)
+{
+    Console.ForegroundColor = ConsoleColor.Cyan;
+    Console.Write("\n[Agent] ");
+    Console.ResetColor();
+    Console.WriteLine(text);
+}
+
+// Helper to print the current chat history from the session.
+void PrintChatHistory(AgentSession session, string label, ref int lastChatHistorySize, ref string lastConversationId)
+{
+    if (session.TryGetInMemoryChatHistory(out var history) && history.Count != lastChatHistorySize)
+    {
+        Console.ForegroundColor = ConsoleColor.DarkGray;
+        Console.WriteLine($"\n  [{label} — Chat history: {history.Count} message(s)]");
+        foreach (var msg in history)
+        {
+            var preview = msg.Text?.Length > 80 ? msg.Text[..80] + "…" : msg.Text;
+            var contentTypes = string.Join(", ", msg.Contents.Select(c => c.GetType().Name));
+            Console.WriteLine($"    {msg.Role,-12} | {(string.IsNullOrWhiteSpace(preview) ? $"[{contentTypes}]" : preview)}");
+        }
+
+        Console.ResetColor();
+
+        lastChatHistorySize = history.Count;
+    }
+
+    if (session is ChatClientAgentSession ccaSession && ccaSession.ConversationId is not null && ccaSession.ConversationId != lastConversationId)
+    {
+        Console.ForegroundColor = ConsoleColor.DarkGray;
+        Console.WriteLine($"  [{label} — Conversation ID: {ccaSession.ConversationId}]");
+        Console.ResetColor();
+        lastConversationId = ccaSession.ConversationId;
+    }
+}

dotnet/samples/02-agents/Agents/Agent_Step19_InFunctionLoopCheckpointing/README.md

@@ -0,0 +1,63 @@
+# In-Function-Loop Checkpointing
+
+This sample demonstrates how `ChatClientAgent` persists chat history after each individual call to the AI service by default. This per-service-call persistence ensures intermediate progress is saved during the function invocation loop.
+
+## What This Sample Shows
+
+When an agent uses tools, the `FunctionInvokingChatClient` loops multiple times (service call → tool execution → service call → …). By default, chat history is persisted after each service call via the `ChatHistoryPersistingChatClient` decorator:
+
+- A `ChatHistoryPersistingChatClient` decorator is automatically inserted into the chat client pipeline
+- After each service call, the decorator notifies the `ChatHistoryProvider` (and any `AIContextProvider` instances) with the new messages
+- Only **new** messages are sent to providers on each notification — messages that were already persisted in an earlier call within the same run are deduplicated automatically
+
+To opt into end-of-run persistence instead (atomic run semantics), set `PersistChatHistoryAtEndOfRun = true` on `ChatClientAgentOptions`. In that mode, the decorator marks messages with metadata rather than persisting them immediately, and `ChatClientAgent` persists only the marked messages at the end of the run.
+
+Per-service-call persistence is useful for:
+- **Crash recovery** — if the process is interrupted mid-loop, the intermediate tool calls and results are already persisted
+- **Observability** — you can inspect the chat history while the agent is still running (e.g., during streaming)
+- **Long-running tool loops** — agents with many sequential tool calls benefit from incremental persistence
+
+## How It Works
+
+The sample asks the agent about the weather and time in three cities. The model calls the `GetWeather` and `GetTime` tools for each city, resulting in multiple service calls within a single `RunStreamingAsync` invocation. After the run completes, the sample prints the full chat history to show all the intermediate messages that were persisted along the way.
+
+### Pipeline Architecture
+
+```
+ChatClientAgent
+  └─ FunctionInvokingChatClient    (handles tool call loop)
+       └─ ChatHistoryPersistingChatClient  (persists after each service call)
+            └─ Leaf IChatClient            (Azure OpenAI)
+```
+
+## Prerequisites
+
+- .NET 10 SDK or later
+- Azure OpenAI service endpoint and model deployment
+- Azure CLI installed and authenticated
+
+**Note**: This sample uses `DefaultAzureCredential`. Sign in with `az login` before running. For production, prefer a specific credential such as `ManagedIdentityCredential`. For more information, see the [Azure CLI authentication documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+
+## Environment Variables
+
+```powershell
+$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"  # Required
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"                       # Optional, defaults to gpt-4o-mini
+```
+
+## Running the Sample
+
+```powershell
+cd dotnet/samples/02-agents/Agents/Agent_Step19_InFunctionLoopCheckpointing
+dotnet run
+```
+
+## Expected Behavior
+
+The sample runs two conversation turns:
+
+1. **First turn** — asks about weather and time in three cities. The model calls `GetWeather` and `GetTime` tools (potentially in parallel or sequentially), then provides a summary. The chat history dump after the run shows all the intermediate tool call and result messages.
+
+2. **Second turn** — asks a follow-up question ("Which city is the warmest?") that uses the persisted conversation context. The chat history dump shows the full accumulated conversation.
+
+The chat history printout uses `session.TryGetInMemoryChatHistory()` to inspect the in-memory storage.

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

@@ -45,6 +45,7 @@ Before you begin, ensure you have the following prerequisites:
 |[Declarative agent](./Agent_Step16_Declarative/)|This sample demonstrates how to declaratively define an agent.|
 |[Providing additional AI Context to an agent using multiple AIContextProviders](./Agent_Step17_AdditionalAIContext/)|This sample demonstrates how to inject additional AI context into a ChatClientAgent using multiple custom AIContextProvider components that are attached to the agent.|
 |[Using compaction pipeline with an agent](./Agent_Step18_CompactionPipeline/)|This sample demonstrates how to use a compaction pipeline to efficiently limit the size of the conversation history for an agent.|
+|[In-function-loop checkpointing](./Agent_Step19_InFunctionLoopCheckpointing/)|This sample demonstrates how to persist chat history after each service call during a tool-calling loop, enabling crash recovery and mid-run observability.|
 
 ## Running the samples from the console
 

dotnet/src/Microsoft.Agents.AI.Workflows/Checkpointing/FileSystemJsonCheckpointStore.cs

@@ -5,11 +5,14 @@ using System.Collections.Generic;
 using System.IO;
 using System.Text;
 using System.Text.Json;
+using System.Text.Json.Serialization.Metadata;
 using System.Threading;
 using System.Threading.Tasks;
 
 namespace Microsoft.Agents.AI.Workflows.Checkpointing;
 
+internal record CheckpointFileIndexEntry(CheckpointInfo CheckpointInfo, string FileName);
+
 /// <summary>
 /// Provides a file system-based implementation of a JSON checkpoint store that persists checkpoint data and index
 /// information to disk using JSON files.
@@ -28,6 +31,8 @@ public sealed class FileSystemJsonCheckpointStore : JsonCheckpointStore, IDispos
     internal DirectoryInfo Directory { get; }
     internal HashSet<CheckpointInfo> CheckpointIndex { get; }
 
+    private static JsonTypeInfo<CheckpointFileIndexEntry> EntryTypeInfo => WorkflowsJsonUtilities.JsonContext.Default.CheckpointFileIndexEntry;
+
     /// <summary>
     /// Initializes a new instance of the <see cref="FileSystemJsonCheckpointStore"/> class that uses the specified directory
     /// </summary>
@@ -64,9 +69,11 @@ public sealed class FileSystemJsonCheckpointStore : JsonCheckpointStore, IDispos
             using StreamReader reader = new(this._indexFile, encoding: Encoding.UTF8, detectEncodingFromByteOrderMarks: false, BufferSize, leaveOpen: true);
             while (reader.ReadLine() is string line)
             {
-                if (JsonSerializer.Deserialize(line, KeyTypeInfo) is { } info)
+                if (JsonSerializer.Deserialize(line, EntryTypeInfo) is { } entry)
                 {
-                    this.CheckpointIndex.Add(info);
+                    // We never actually use the file names from the index entries since they can be derived from the CheckpointInfo, but it is useful to
+                    // have the UrlEncoded file names in the index file for human readability
+                    this.CheckpointIndex.Add(entry.CheckpointInfo);
                 }
             }
         }
@@ -93,8 +100,14 @@ public sealed class FileSystemJsonCheckpointStore : JsonCheckpointStore, IDispos
         }
     }
 
-    private string GetFileNameForCheckpoint(string sessionId, CheckpointInfo key)
-        => Path.Combine(this.Directory.FullName, $"{sessionId}_{key.CheckpointId}.json");
+    internal string GetFileNameForCheckpoint(string sessionId, CheckpointInfo key)
+    {
+        string protoPath = $"{sessionId}_{key.CheckpointId}.json";
+
+        // Escape the protoPath to ensure it is a valid file name, especially if sessionId or CheckpointId contain path separators, etc.
+        return Uri.EscapeDataString(protoPath) // This takes care of most of the invalid path characters
+                  .Replace(".", "%2E");        // This takes care of escaping the root folder, since EscapeDataString does not escape dots
+    }
 
     private CheckpointInfo GetUnusedCheckpointInfo(string sessionId)
     {
@@ -116,13 +129,16 @@ public sealed class FileSystemJsonCheckpointStore : JsonCheckpointStore, IDispos
 
         CheckpointInfo key = this.GetUnusedCheckpointInfo(sessionId);
         string fileName = this.GetFileNameForCheckpoint(sessionId, key);
+        string filePath = Path.Combine(this.Directory.FullName, fileName);
+
         try
         {
-            using Stream checkpointStream = File.Open(fileName, FileMode.Create, FileAccess.Write, FileShare.None);
+            using Stream checkpointStream = File.Open(filePath, FileMode.Create, FileAccess.Write, FileShare.None);
             using Utf8JsonWriter jsonWriter = new(checkpointStream, new JsonWriterOptions() { Indented = false });
             value.WriteTo(jsonWriter);
 
-            JsonSerializer.Serialize(this._indexFile!, key, KeyTypeInfo);
+            CheckpointFileIndexEntry entry = new(key, fileName);
+            JsonSerializer.Serialize(this._indexFile!, entry, EntryTypeInfo);
             byte[] bytes = Encoding.UTF8.GetBytes(Environment.NewLine);
             await this._indexFile!.WriteAsync(bytes, 0, bytes.Length, CancellationToken.None).ConfigureAwait(false);
             await this._indexFile!.FlushAsync(CancellationToken.None).ConfigureAwait(false);
@@ -136,7 +152,7 @@ public sealed class FileSystemJsonCheckpointStore : JsonCheckpointStore, IDispos
             try
             {
                 // try to clean up after ourselves
-                File.Delete(fileName);
+                File.Delete(filePath);
             }
             catch { }
 
@@ -149,6 +165,7 @@ public sealed class FileSystemJsonCheckpointStore : JsonCheckpointStore, IDispos
     {
         this.CheckDisposed();
         string fileName = this.GetFileNameForCheckpoint(sessionId, key);
+        string filePath = Path.Combine(this.Directory.FullName, fileName);
 
         if (!this.CheckpointIndex.Contains(key) ||
             !File.Exists(fileName))
@@ -156,7 +173,7 @@ public sealed class FileSystemJsonCheckpointStore : JsonCheckpointStore, IDispos
             throw new KeyNotFoundException($"Checkpoint '{key.CheckpointId}' not found in store at '{this.Directory.FullName}'.");
         }
 
-        using FileStream checkpointFileStream = File.Open(fileName, FileMode.Open, FileAccess.Read, FileShare.Read);
+        using FileStream checkpointFileStream = File.Open(filePath, FileMode.Open, FileAccess.Read, FileShare.Read);
         using JsonDocument document = await JsonDocument.ParseAsync(checkpointFileStream).ConfigureAwait(false);
 
         return document.RootElement.Clone();

dotnet/src/Microsoft.Agents.AI.Workflows/WorkflowsJsonUtilities.cs

@@ -71,6 +71,7 @@ internal static partial class WorkflowsJsonUtilities
     [JsonSerializable(typeof(PortableValue))]
     [JsonSerializable(typeof(PortableMessageEnvelope))]
     [JsonSerializable(typeof(InMemoryCheckpointManager))]
+    [JsonSerializable(typeof(CheckpointFileIndexEntry))]
 
     // Runtime State Types
     [JsonSerializable(typeof(ScopeKey))]

dotnet/src/Microsoft.Agents.AI/ChatClient/ChatClientAgent.cs

@@ -138,6 +138,9 @@ public sealed partial class ChatClientAgent : AIAgent
         this._aiContextProviderStateKeys = ValidateAndCollectStateKeys(this._agentOptions?.AIContextProviders, this.ChatHistoryProvider);
 
         this._logger = (loggerFactory ?? chatClient.GetService<ILoggerFactory>() ?? NullLoggerFactory.Instance).CreateLogger<ChatClientAgent>();
+
+        // Warn if using a custom chat client stack with end-of-run persistence but no ChatHistoryPersistingChatClient.
+        this.WarnOnMissingPersistingClient();
     }
 
     /// <summary>
@@ -211,12 +214,14 @@ public sealed partial class ChatClientAgent : AIAgent
          ChatClientAgentContinuationToken? _) =
             await this.PrepareSessionAndMessagesAsync(session, inputMessages, options, cancellationToken).ConfigureAwait(false);
 
-        var chatClient = this.ChatClient;
+        // Update the run context with the resolved session so any downstream classes
+        // always have a valid session, even when the caller passed null.
+        EnsureRunContextHasSession(safeSession);
 
+        var chatClient = this.ChatClient;
         chatClient = ApplyRunOptionsTransformations(options, chatClient);
 
         var loggingAgentName = this.GetLoggingAgentName();
-
         this._logger.LogAgentChatClientInvokingAgent(nameof(RunAsync), this.Id, loggingAgentName, this._chatClientType);
 
         // Call the IChatClient and notify the AIContextProvider of any failures.
@@ -227,8 +232,7 @@ public sealed partial class ChatClientAgent : AIAgent
         }
         catch (Exception ex)
         {
-            await this.NotifyChatHistoryProviderOfFailureAsync(safeSession, ex, inputMessagesForChatClient, chatOptions, cancellationToken).ConfigureAwait(false);
-            await this.NotifyAIContextProviderOfFailureAsync(safeSession, ex, inputMessagesForChatClient, cancellationToken).ConfigureAwait(false);
+            await this.NotifyProvidersOfFailureAtEndOfRunAsync(safeSession, ex, inputMessagesForChatClient, chatOptions, cancellationToken).ConfigureAwait(false);
             throw;
         }
 
@@ -236,7 +240,8 @@ public sealed partial class ChatClientAgent : AIAgent
 
         // We can derive the type of supported session from whether we have a conversation id,
         // so let's update it and set the conversation id for the service session case.
-        this.UpdateSessionConversationId(safeSession, chatResponse.ConversationId, cancellationToken);
+        var forceEndOfRunPersistence = chatOptions?.ContinuationToken is not null || chatOptions?.AllowBackgroundResponses is true;
+        this.UpdateSessionConversationIdAtEndOfRun(safeSession, chatResponse.ConversationId, cancellationToken, forceUpdate: forceEndOfRunPersistence);
 
         // Ensure that the author name is set for each message in the response.
         foreach (ChatMessage chatResponseMessage in chatResponse.Messages)
@@ -244,11 +249,10 @@ public sealed partial class ChatClientAgent : AIAgent
             chatResponseMessage.AuthorName ??= this.Name;
         }
 
-        // Only notify the session of new messages if the chatResponse was successful to avoid inconsistent message state in the session.
-        await this.NotifyChatHistoryProviderOfNewMessagesAsync(safeSession, inputMessagesForChatClient, chatResponse.Messages, chatOptions, cancellationToken).ConfigureAwait(false);
-
-        // Notify the AIContextProvider of all new messages.
-        await this.NotifyAIContextProviderOfSuccessAsync(safeSession, inputMessagesForChatClient, chatResponse.Messages, cancellationToken).ConfigureAwait(false);
+        // Notify providers of all new messages unless persistence is handled per-service-call by the decorator.
+        // When background responses are allowed, force notification since per-service-call persistence
+        // is unreliable (the caller may stop consuming the stream before the decorator can persist).
+        await this.NotifyProvidersOfNewMessagesAtEndOfRunAsync(safeSession, inputMessagesForChatClient, chatResponse.Messages, chatOptions, cancellationToken, forceNotify: forceEndOfRunPersistence).ConfigureAwait(false);
 
         return new AgentResponse(chatResponse)
         {
@@ -296,6 +300,10 @@ public sealed partial class ChatClientAgent : AIAgent
          ChatClientAgentContinuationToken? continuationToken) =
             await this.PrepareSessionAndMessagesAsync(session, inputMessages, options, cancellationToken).ConfigureAwait(false);
 
+        // Update the run context with the resolved session so any downstream classes
+        // always have a valid session, even when the caller passed null.
+        EnsureRunContextHasSession(safeSession);
+
         var chatClient = this.ChatClient;
 
         chatClient = ApplyRunOptionsTransformations(options, chatClient);
@@ -315,8 +323,7 @@ public sealed partial class ChatClientAgent : AIAgent
         }
         catch (Exception ex)
         {
-            await this.NotifyChatHistoryProviderOfFailureAsync(safeSession, ex, GetInputMessages(inputMessagesForChatClient, continuationToken), chatOptions, cancellationToken).ConfigureAwait(false);
-            await this.NotifyAIContextProviderOfFailureAsync(safeSession, ex, GetInputMessages(inputMessagesForChatClient, continuationToken), cancellationToken).ConfigureAwait(false);
+            await this.NotifyProvidersOfFailureAtEndOfRunAsync(safeSession, ex, GetInputMessages(inputMessagesForChatClient, continuationToken), chatOptions, cancellationToken).ConfigureAwait(false);
             throw;
         }
 
@@ -330,8 +337,7 @@ public sealed partial class ChatClientAgent : AIAgent
         }
         catch (Exception ex)
         {
-            await this.NotifyChatHistoryProviderOfFailureAsync(safeSession, ex, GetInputMessages(inputMessagesForChatClient, continuationToken), chatOptions, cancellationToken).ConfigureAwait(false);
-            await this.NotifyAIContextProviderOfFailureAsync(safeSession, ex, GetInputMessages(inputMessagesForChatClient, continuationToken), cancellationToken).ConfigureAwait(false);
+            await this.NotifyProvidersOfFailureAtEndOfRunAsync(safeSession, ex, GetInputMessages(inputMessagesForChatClient, continuationToken), chatOptions, cancellationToken).ConfigureAwait(false);
             throw;
         }
 
@@ -353,27 +359,31 @@ public sealed partial class ChatClientAgent : AIAgent
 
             try
             {
+                // Re-ensure the run context has the resolved session before each MoveNextAsync.
+                // The base class RunStreamingAsync restores the original context (potentially with
+                // null session) after each yield, so we must re-establish it for the decorator.
+                EnsureRunContextHasSession(safeSession);
                 hasUpdates = await responseUpdatesEnumerator.MoveNextAsync().ConfigureAwait(false);
             }
             catch (Exception ex)
             {
-                await this.NotifyChatHistoryProviderOfFailureAsync(safeSession, ex, GetInputMessages(inputMessagesForChatClient, continuationToken), chatOptions, cancellationToken).ConfigureAwait(false);
-                await this.NotifyAIContextProviderOfFailureAsync(safeSession, ex, GetInputMessages(inputMessagesForChatClient, continuationToken), cancellationToken).ConfigureAwait(false);
+                await this.NotifyProvidersOfFailureAtEndOfRunAsync(safeSession, ex, GetInputMessages(inputMessagesForChatClient, continuationToken), chatOptions, cancellationToken).ConfigureAwait(false);
                 throw;
             }
         }
 
         var chatResponse = responseUpdates.ToChatResponse();
 
+        var forceEndOfRunPersistence = continuationToken is not null || chatOptions?.AllowBackgroundResponses is true;
+
         // We can derive the type of supported session from whether we have a conversation id,
         // so let's update it and set the conversation id for the service session case.
-        this.UpdateSessionConversationId(safeSession, chatResponse.ConversationId, cancellationToken);
+        this.UpdateSessionConversationIdAtEndOfRun(safeSession, chatResponse.ConversationId, cancellationToken, forceUpdate: forceEndOfRunPersistence);
 
-        // To avoid inconsistent state we only notify the session of the input messages if no error occurs after the initial request.
-        await this.NotifyChatHistoryProviderOfNewMessagesAsync(safeSession, GetInputMessages(inputMessagesForChatClient, continuationToken), chatResponse.Messages, chatOptions, cancellationToken).ConfigureAwait(false);
-
-        // Notify the AIContextProvider of all new messages.
-        await this.NotifyAIContextProviderOfSuccessAsync(safeSession, GetInputMessages(inputMessagesForChatClient, continuationToken), chatResponse.Messages, cancellationToken).ConfigureAwait(false);
+        // Notify providers of all new messages unless persistence is handled per-service-call by the decorator.
+        // When resuming from a continuation token or using background responses, force notification
+        // to send the combined data (per-service-call persistence is unreliable for these scenarios).
+        await this.NotifyProvidersOfNewMessagesAtEndOfRunAsync(safeSession, GetInputMessages(inputMessagesForChatClient, continuationToken), chatResponse.Messages, chatOptions, cancellationToken, forceNotify: forceEndOfRunPersistence).ConfigureAwait(false);
     }
 
     /// <inheritdoc/>
@@ -441,17 +451,29 @@ public sealed partial class ChatClientAgent : AIAgent
     #region Private
 
     /// <summary>
-    /// Notify the <see cref="AIContextProvider"/> when an agent run succeeded, if there is an <see cref="AIContextProvider"/>.
+    /// Notifies the <see cref="ChatHistoryProvider"/> and all <see cref="AIContextProviders"/> of successfully completed messages.
     /// </summary>
-    private async Task NotifyAIContextProviderOfSuccessAsync(
+    /// <remarks>
+    /// This method is also called by <see cref="ChatHistoryPersistingChatClient"/> to persist messages per-service-call.
+    /// </remarks>
+    internal async Task NotifyProvidersOfNewMessagesAsync(
         ChatClientAgentSession session,
-        IEnumerable<ChatMessage> inputMessages,
+        IEnumerable<ChatMessage> requestMessages,
         IEnumerable<ChatMessage> responseMessages,
+        ChatOptions? chatOptions,
         CancellationToken cancellationToken)
     {
+        ChatHistoryProvider? chatHistoryProvider = this.ResolveChatHistoryProvider(chatOptions, session);
+
+        if (chatHistoryProvider is not null)
+        {
+            var invokedContext = new ChatHistoryProvider.InvokedContext(this, session, requestMessages, responseMessages);
+            await chatHistoryProvider.InvokedAsync(invokedContext, cancellationToken).ConfigureAwait(false);
+        }
+
         if (this.AIContextProviders is { Count: > 0 } contextProviders)
         {
-            AIContextProvider.InvokedContext invokedContext = new(this, session, inputMessages, responseMessages);
+            AIContextProvider.InvokedContext invokedContext = new(this, session, requestMessages, responseMessages);
 
             foreach (var contextProvider in contextProviders)
             {
@@ -461,17 +483,29 @@ public sealed partial class ChatClientAgent : AIAgent
     }
 
     /// <summary>
-    /// Notify the <see cref="AIContextProvider"/> of any failure during an agent run, if there is an <see cref="AIContextProvider"/>.
+    /// Notifies the <see cref="ChatHistoryProvider"/> and all <see cref="AIContextProviders"/> of a failure during a service call.
     /// </summary>
-    private async Task NotifyAIContextProviderOfFailureAsync(
+    /// <remarks>
+    /// This method is also called by <see cref="ChatHistoryPersistingChatClient"/> to report failures per-service-call.
+    /// </remarks>
+    internal async Task NotifyProvidersOfFailureAsync(
         ChatClientAgentSession session,
         Exception ex,
-        IEnumerable<ChatMessage> inputMessages,
+        IEnumerable<ChatMessage> requestMessages,
+        ChatOptions? chatOptions,
         CancellationToken cancellationToken)
     {
+        ChatHistoryProvider? chatHistoryProvider = this.ResolveChatHistoryProvider(chatOptions, session);
+
+        if (chatHistoryProvider is not null)
+        {
+            var invokedContext = new ChatHistoryProvider.InvokedContext(this, session, requestMessages, ex);
+            await chatHistoryProvider.InvokedAsync(invokedContext, cancellationToken).ConfigureAwait(false);
+        }
+
         if (this.AIContextProviders is { Count: > 0 } contextProviders)
         {
-            AIContextProvider.InvokedContext invokedContext = new(this, session, inputMessages, ex);
+            AIContextProvider.InvokedContext invokedContext = new(this, session, requestMessages, ex);
 
             foreach (var contextProvider in contextProviders)
             {
@@ -667,6 +701,12 @@ public sealed partial class ChatClientAgent : AIAgent
             throw new InvalidOperationException("A session must be provided when continuing a background response with a continuation token.");
         }
 
+        if ((continuationToken is not null || chatOptions?.AllowBackgroundResponses is true) && this.PersistsChatHistoryPerServiceCall && this._logger.IsEnabled(LogLevel.Warning))
+        {
+            var warningAgentName = this.GetLoggingAgentName();
+            this._logger.LogAgentChatClientBackgroundResponseFallback(this.Id, warningAgentName);
+        }
+
         session ??= await this.CreateSessionAsync(cancellationToken).ConfigureAwait(false);
         if (session is not ChatClientAgentSession typedSession)
         {
@@ -754,7 +794,7 @@ public sealed partial class ChatClientAgent : AIAgent
         return (typedSession, chatOptions, messagesList, continuationToken);
     }
 
-    private void UpdateSessionConversationId(ChatClientAgentSession session, string? responseConversationId, CancellationToken cancellationToken)
+    internal void UpdateSessionConversationId(ChatClientAgentSession session, string? responseConversationId, CancellationToken cancellationToken)
     {
         if (string.IsNullOrWhiteSpace(responseConversationId) && !string.IsNullOrWhiteSpace(session.ConversationId))
         {
@@ -798,45 +838,162 @@ public sealed partial class ChatClientAgent : AIAgent
         }
     }
 
-    private Task NotifyChatHistoryProviderOfFailureAsync(
+    /// <summary>
+    /// Updates the session conversation ID at the end of an agent run.
+    /// </summary>
+    /// <remarks>
+    /// When a <see cref="ChatHistoryPersistingChatClient"/> in persist mode handles per-service-call
+    /// conversation ID updates, this end-of-run update is skipped. When the decorator is in mark-only
+    /// mode or absent, the update is performed here. When <paramref name="forceUpdate"/> is <see langword="true"/>
+    /// (continuation token scenarios), the update is always performed.
+    /// </remarks>
+    private void UpdateSessionConversationIdAtEndOfRun(ChatClientAgentSession session, string? responseConversationId, CancellationToken cancellationToken, bool forceUpdate = false)
+    {
+        if (!forceUpdate && this.PersistsChatHistoryPerServiceCall)
+        {
+            return;
+        }
+
+        this.UpdateSessionConversationId(session, responseConversationId, cancellationToken);
+    }
+
+    /// <summary>
+    /// Notifies providers of successfully completed messages at the end of an agent run.
+    /// </summary>
+    /// <remarks>
+    /// When a <see cref="ChatHistoryPersistingChatClient"/> in persist mode handles per-service-call
+    /// notification, this end-of-run notification is skipped. When the decorator is in mark-only mode,
+    /// only the marked messages are persisted. When no decorator is present (custom stack with
+    /// <see cref="ChatClientAgentOptions.PersistChatHistoryAtEndOfRun"/>), all messages are persisted.
+    /// When <paramref name="forceNotify"/> is <see langword="true"/> (continuation token or
+    /// background response scenarios), notification is always performed with all messages because
+    /// per-service-call persistence is unreliable in these scenarios.
+    /// </remarks>
+    private Task NotifyProvidersOfNewMessagesAtEndOfRunAsync(
+        ChatClientAgentSession session,
+        IEnumerable<ChatMessage> requestMessages,
+        IEnumerable<ChatMessage> responseMessages,
+        ChatOptions? chatOptions,
+        CancellationToken cancellationToken,
+        bool forceNotify = false)
+    {
+        if (!forceNotify && this.PersistsChatHistoryPerServiceCall)
+        {
+            return Task.CompletedTask;
+        }
+
+        if (!forceNotify && this.HasMarkOnlyChatHistoryPersistingClient)
+        {
+            // In mark-only mode, persist only messages that were marked by the decorator.
+            var markedRequestMessages = GetMarkedMessages(requestMessages);
+            var markedResponseMessages = GetMarkedMessages(responseMessages);
+            return this.NotifyProvidersOfNewMessagesAsync(session, markedRequestMessages, markedResponseMessages, chatOptions, cancellationToken);
+        }
+
+        return this.NotifyProvidersOfNewMessagesAsync(session, requestMessages, responseMessages, chatOptions, cancellationToken);
+    }
+
+    /// <summary>
+    /// Notifies providers of a failure at the end of an agent run.
+    /// </summary>
+    /// <remarks>
+    /// When a <see cref="ChatHistoryPersistingChatClient"/> in persist mode handles per-service-call
+    /// notification (including failure), this end-of-run notification is skipped to avoid
+    /// duplicate notification. In all other cases, failure is reported at the end of the run.
+    /// </remarks>
+    private Task NotifyProvidersOfFailureAtEndOfRunAsync(
         ChatClientAgentSession session,
         Exception ex,
         IEnumerable<ChatMessage> requestMessages,
         ChatOptions? chatOptions,
         CancellationToken cancellationToken)
     {
-        ChatHistoryProvider? provider = this.ResolveChatHistoryProvider(chatOptions, session);
-
-        // Only notify the provider if we have one.
-        // If we don't have one, it means that the chat history is service managed and the underlying service is responsible for storing messages.
-        if (provider is not null)
+        if (this.PersistsChatHistoryPerServiceCall)
         {
-            var invokedContext = new ChatHistoryProvider.InvokedContext(this, session, requestMessages, ex);
-
-            return provider.InvokedAsync(invokedContext, cancellationToken).AsTask();
+            return Task.CompletedTask;
         }
 
-        return Task.CompletedTask;
+        return this.NotifyProvidersOfFailureAsync(session, ex, requestMessages, chatOptions, cancellationToken);
     }
 
-    private Task NotifyChatHistoryProviderOfNewMessagesAsync(
-        ChatClientAgentSession session,
-        IEnumerable<ChatMessage> requestMessages,
-        IEnumerable<ChatMessage> responseMessages,
-        ChatOptions? chatOptions,
-        CancellationToken cancellationToken)
+    /// <summary>
+    /// Gets a value indicating whether the agent has a <see cref="ChatHistoryPersistingChatClient"/>
+    /// decorator in persist mode (not mark-only), which handles per-service-call persistence.
+    /// </summary>
+    private bool PersistsChatHistoryPerServiceCall
     {
-        ChatHistoryProvider? provider = this.ResolveChatHistoryProvider(chatOptions, session);
-
-        // Only notify the provider if we have one.
-        // If we don't have one, it means that the chat history is service managed and the underlying service is responsible for storing messages.
-        if (provider is not null)
+        get
         {
-            var invokedContext = new ChatHistoryProvider.InvokedContext(this, session, requestMessages, responseMessages);
-            return provider.InvokedAsync(invokedContext, cancellationToken).AsTask();
+            var persistingClient = this.ChatClient.GetService<ChatHistoryPersistingChatClient>();
+            return persistingClient?.MarkOnly == false;
+        }
+    }
+
+    /// <summary>
+    /// Gets a value indicating whether the agent has a <see cref="ChatHistoryPersistingChatClient"/>
+    /// decorator in mark-only mode, which marks messages for later persistence at the end of the run.
+    /// </summary>
+    private bool HasMarkOnlyChatHistoryPersistingClient
+    {
+        get
+        {
+            var persistingClient = this.ChatClient.GetService<ChatHistoryPersistingChatClient>();
+            return persistingClient?.MarkOnly == true;
+        }
+    }
+
+    /// <summary>
+    /// Returns only the messages that have been marked as persisted by a <see cref="ChatHistoryPersistingChatClient"/> in mark-only mode.
+    /// </summary>
+    private static List<ChatMessage> GetMarkedMessages(IEnumerable<ChatMessage> messages)
+    {
+        return messages.Where(m =>
+            m.AdditionalProperties?.TryGetValue(ChatHistoryPersistingChatClient.PersistedMarkerKey, out var value) == true && value is true).ToList();
+    }
+
+    /// <summary>
+    /// Ensures that <see cref="AIAgent.CurrentRunContext"/> contains the resolved session.
+    /// </summary>
+    /// <remarks>
+    /// The base class sets <see cref="AIAgent.CurrentRunContext"/> with the raw session parameter
+    /// (which may be null) and restores it after each yield in streaming scenarios. After
+    /// <see cref="PrepareSessionAndMessagesAsync"/> resolves or creates a session, we update the
+    /// context so the <see cref="ChatHistoryPersistingChatClient"/> decorator always has a valid session.
+    /// The original agent from the context is preserved to maintain the top-of-stack agent in
+    /// decorated agent scenarios.
+    /// </remarks>
+    private static void EnsureRunContextHasSession(ChatClientAgentSession safeSession)
+    {
+        var context = CurrentRunContext;
+        if (context is not null && context.Session != safeSession)
+        {
+            CurrentRunContext = new(context.Agent, safeSession, context.RequestMessages, context.RunOptions);
+        }
+    }
+
+    /// <summary>
+    /// Checks for potential misconfiguration when using a custom chat client stack and logs warnings.
+    /// </summary>
+    private void WarnOnMissingPersistingClient()
+    {
+        if (this._agentOptions?.UseProvidedChatClientAsIs is not true)
+        {
+            return;
         }
 
-        return Task.CompletedTask;
+        if (this._agentOptions?.PersistChatHistoryAtEndOfRun is not true)
+        {
+            return;
+        }
+
+        var persistingClient = this.ChatClient.GetService<ChatHistoryPersistingChatClient>();
+        if (persistingClient is null && this._logger.IsEnabled(LogLevel.Warning))
+        {
+            var loggingAgentName = this.GetLoggingAgentName();
+            this._logger.LogAgentChatClientMissingPersistingClient(
+                this.Id,
+                loggingAgentName);
+        }
     }
 
     private ChatHistoryProvider? ResolveChatHistoryProvider(ChatOptions? chatOptions, ChatClientAgentSession session)

dotnet/src/Microsoft.Agents.AI/ChatClient/ChatClientAgentLogMessages.cs

@@ -69,4 +69,32 @@ internal static partial class ChatClientAgentLogMessages
         string chatHistoryProviderName,
         string agentId,
         string agentName);
+
+    /// <summary>
+    /// Logs a warning when <see cref="ChatClientAgentOptions.UseProvidedChatClientAsIs"/> is <see langword="true"/>
+    /// and <see cref="ChatClientAgentOptions.PersistChatHistoryAtEndOfRun"/> is <see langword="true"/>,
+    /// but no <see cref="ChatHistoryPersistingChatClient"/> is found in the custom chat client stack.
+    /// </summary>
+    [LoggerMessage(
+        Level = LogLevel.Warning,
+        Message = "Agent {AgentId}/{AgentName}: PersistChatHistoryAtEndOfRun is enabled with a custom chat client stack (UseProvidedChatClientAsIs), but no ChatHistoryPersistingChatClient was found in the pipeline. All messages will be persisted at the end of the run without marking. This setup is not supported with some other features, e.g. handoffs. Consider adding a ChatHistoryPersistingChatClient to the pipeline using the UseChatHistoryPersisting extension method.")]
+    public static partial void LogAgentChatClientMissingPersistingClient(
+        this ILogger logger,
+        string agentId,
+        string agentName);
+
+    /// <summary>
+    /// Logs a warning when per-service-call persistence falls back to end-of-run persistence
+    /// because the run involves background responses (continuation token resumption or
+    /// <c>AllowBackgroundResponses</c>). Per-service-call persistence is
+    /// unreliable in these scenarios because the caller may stop consuming the stream before
+    /// the decorator's post-stream persistence code can execute.
+    /// </summary>
+    [LoggerMessage(
+        Level = LogLevel.Warning,
+        Message = "Agent {AgentId}/{AgentName}: Per-service-call persistence is falling back to end-of-run persistence because the run involves background responses. Messages will be marked during the run and persisted at the end.")]
+    public static partial void LogAgentChatClientBackgroundResponseFallback(
+        this ILogger logger,
+        string agentId,
+        string agentName);
 }

dotnet/src/Microsoft.Agents.AI/ChatClient/ChatClientAgentOptions.cs

@@ -1,7 +1,9 @@
 // Copyright (c) Microsoft. All rights reserved.
 
 using System.Collections.Generic;
+using System.Diagnostics.CodeAnalysis;
 using Microsoft.Extensions.AI;
+using Microsoft.Shared.DiagnosticIds;
 
 namespace Microsoft.Agents.AI;
 
@@ -89,6 +91,56 @@ public sealed class ChatClientAgentOptions
     /// </value>
     public bool ThrowOnChatHistoryProviderConflict { get; set; } = true;
 
+    /// <summary>
+    /// Gets or sets a value indicating whether to persist chat history only at the end of the full agent run
+    /// rather than after each individual service call.
+    /// </summary>
+    /// <remarks>
+    /// <para>
+    /// By default, <see cref="ChatClientAgent"/> persists request and response messages either via
+    /// a <see cref="ChatHistoryProvider"/>, or the underlying AI service's chat history storage.
+    /// Persistence is done immediately after each call to the AI service within the function invocation loop.
+    /// When storing in the underlying AI service, the session's <see cref="ChatClientAgentSession.ConversationId"/>
+    /// is also updated after each service call, keeping it in sync with the service-side conversation state.
+    /// </para>
+    /// <para>
+    /// Setting this property to <see langword="true"/> causes messages to be marked during the function
+    /// invocation loop but persisted only at the end of the full agent run, providing atomic run semantics.
+    /// Updating the <see cref="ChatClientAgentSession.ConversationId"/> is likewise deferred and
+    /// updated only at the end of the run, consistent with atomic run semantics.
+    /// A <see cref="ChatHistoryPersistingChatClient"/> decorator is inserted into the chat client pipeline
+    /// in mark-only mode, and the <see cref="ChatClientAgent"/> persists only the marked messages at the
+    /// end of the run.
+    /// </para>
+    /// <para>
+    /// When this option is <see langword="false"/> (the default), the <see cref="ChatHistoryPersistingChatClient"/>
+    /// decorator persists messages and updates the <see cref="ChatClientAgentSession.ConversationId"/>
+    /// immediately after each service call. This may leave chat history in a state where
+    /// <see cref="FunctionResultContent"/> is required to start a new run if the last successful service
+    /// call returned <see cref="FunctionCallContent"/>.
+    /// </para>
+    /// <para>
+    /// This option has no effect when <see cref="UseProvidedChatClientAsIs"/> is <see langword="true"/>.
+    /// When using a custom chat client stack, you can add a <see cref="ChatHistoryPersistingChatClient"/>
+    /// manually via the <see cref="ChatClientBuilderExtensions.UseChatHistoryPersisting"/>
+    /// extension method.
+    /// </para>
+    /// <para>
+    /// Note that when using single threaded service stored chat history, like OpenAI Conversations,
+    /// there is only one id, so even if the conversation id is not updated after each service call,
+    /// the chat history will still contain intermediate messages. Setting this property to <see langword="true"/>
+    /// in this case will therefore have no real effect. Setting this property to <see langword="true"/> when using
+    /// OpenAI Responses with response ids on the other hand, allows atomic run semantics, since
+    /// each service request produces a new response id, and if the run fails mid-loop, the session will
+    /// still contain the pre-run respnose id, allowing the next run to start with a clean slate.
+    /// </para>
+    /// </remarks>
+    /// <value>
+    /// Default is <see langword="false"/>.
+    /// </value>
+    [Experimental(DiagnosticIds.Experiments.AgentsAIExperiments)]
+    public bool PersistChatHistoryAtEndOfRun { get; set; }
+
     /// <summary>
     /// Creates a new instance of <see cref="ChatClientAgentOptions"/> with the same values as this instance.
     /// </summary>
@@ -105,5 +157,6 @@ public sealed class ChatClientAgentOptions
             ClearOnChatHistoryProviderConflict = this.ClearOnChatHistoryProviderConflict,
             WarnOnChatHistoryProviderConflict = this.WarnOnChatHistoryProviderConflict,
             ThrowOnChatHistoryProviderConflict = this.ThrowOnChatHistoryProviderConflict,
+            PersistChatHistoryAtEndOfRun = this.PersistChatHistoryAtEndOfRun,
         };
 }

dotnet/src/Microsoft.Agents.AI/ChatClient/ChatClientBuilderExtensions.cs

@@ -2,8 +2,10 @@
 
 using System;
 using System.Collections.Generic;
+using System.Diagnostics.CodeAnalysis;
 using Microsoft.Agents.AI;
 using Microsoft.Extensions.Logging;
+using Microsoft.Shared.DiagnosticIds;
 using Microsoft.Shared.Diagnostics;
 
 namespace Microsoft.Extensions.AI;
@@ -82,4 +84,46 @@ public static class ChatClientBuilderExtensions
             options: options,
             loggerFactory: loggerFactory,
             services: services);
+
+    /// <summary>
+    /// Adds a <see cref="ChatHistoryPersistingChatClient"/> to the chat client pipeline.
+    /// </summary>
+    /// <remarks>
+    /// <para>
+    /// This decorator should be positioned between the <see cref="FunctionInvokingChatClient"/> and the leaf
+    /// <see cref="IChatClient"/> in the pipeline. It intercepts service calls to either persist messages
+    /// immediately or mark them for later persistence, depending on the <paramref name="markOnly"/> parameter.
+    /// </para>
+    /// <para>
+    /// If <paramref name="markOnly"/> is set to <see langword="true"/>, the <see cref="ChatClientAgent"/>
+    /// should be configured with <see cref="ChatClientAgentOptions.PersistChatHistoryAtEndOfRun"/> set to <see langword="true"/>
+    /// as without this combination, messages will never be persisted when using a <see cref="ChatHistoryProvider"/> for
+    /// chat history persistence.
+    /// </para>
+    /// <para>
+    /// This extension method is intended for use with custom chat client stacks when
+    /// <see cref="ChatClientAgentOptions.UseProvidedChatClientAsIs"/> is <see langword="true"/>.
+    /// When <see cref="ChatClientAgentOptions.UseProvidedChatClientAsIs"/> is <see langword="false"/> (the default),
+    /// the <see cref="ChatClientAgent"/> automatically injects this decorator.
+    /// </para>
+    /// <para>
+    /// This decorator only works within the context of a running <see cref="ChatClientAgent"/> and will throw an
+    /// exception if used in any other stack.
+    /// </para>
+    /// </remarks>
+    /// <param name="builder">The <see cref="ChatClientBuilder"/> to add the decorator to.</param>
+    /// <param name="markOnly">
+    /// When <see langword="true"/>, messages are marked with metadata but not persisted immediately,
+    /// and the session's <see cref="ChatClientAgentSession.ConversationId"/> is not updated.
+    /// The <see cref="ChatClientAgent"/> will persist only the marked messages and update the
+    /// conversation ID at the end of the run.
+    /// When <see langword="false"/> (the default), messages are persisted and the conversation ID
+    /// is updated immediately after each service call.
+    /// </param>
+    /// <returns>The <paramref name="builder"/> for chaining.</returns>
+    [Experimental(DiagnosticIds.Experiments.AgentsAIExperiments)]
+    public static ChatClientBuilder UseChatHistoryPersisting(this ChatClientBuilder builder, bool markOnly = false)
+    {
+        return builder.Use(innerClient => new ChatHistoryPersistingChatClient(innerClient, markOnly));
+    }
 }

dotnet/src/Microsoft.Agents.AI/ChatClient/ChatClientExtensions.cs

@@ -63,6 +63,15 @@ public static class ChatClientExtensions
             });
         }
 
+        // ChatHistoryPersistingChatClient is registered after FunctionInvokingChatClient so that it sits
+        // between FIC and the leaf client. ChatClientBuilder.Build applies factories in reverse order,
+        // making the first Use() call outermost. By adding our decorator second, the resulting pipeline is:
+        //   FunctionInvokingChatClient → ChatHistoryPersistingChatClient → leaf IChatClient
+        // This allows the decorator to persist messages after each individual service call within
+        // FIC's function invocation loop, or to mark them for later persistence at the end of the run.
+        bool markOnly = options?.PersistChatHistoryAtEndOfRun is true;
+        chatBuilder.Use(innerClient => new ChatHistoryPersistingChatClient(innerClient, markOnly));
+
         var agentChatClient = chatBuilder.Build(services);
 
         if (options?.ChatOptions?.Tools is { Count: > 0 })

dotnet/src/Microsoft.Agents.AI/ChatClient/ChatHistoryPersistingChatClient.cs

@@ -0,0 +1,313 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Runtime.CompilerServices;
+using System.Threading;
+using System.Threading.Tasks;
+using Microsoft.Extensions.AI;
+
+namespace Microsoft.Agents.AI;
+
+/// <summary>
+/// A delegating chat client that notifies <see cref="ChatHistoryProvider"/> and <see cref="AIContextProvider"/>
+/// instances of request and response messages after each individual call to the inner chat client,
+/// or marks messages for later persistence depending on the configured mode.
+/// </summary>
+/// <remarks>
+/// <para>
+/// This decorator is intended to operate between the <see cref="FunctionInvokingChatClient"/> and the leaf
+/// <see cref="IChatClient"/> in a <see cref="ChatClientAgent"/> pipeline.
+/// </para>
+/// <para>
+/// In persist mode (the default), it ensures that providers are notified and the session's
+/// <see cref="ChatClientAgentSession.ConversationId"/> is updated after each service call, so that
+/// intermediate messages (e.g., tool calls and results) are saved even if the process is interrupted
+/// mid-loop.
+/// </para>
+/// <para>
+/// In mark-only mode (<see cref="MarkOnly"/> is <see langword="true"/>), it marks messages with metadata
+/// but does not notify providers or update the <see cref="ChatClientAgentSession.ConversationId"/>.
+/// Both are deferred to the <see cref="ChatClientAgent"/> at the end of the run, providing atomic
+/// run semantics.
+/// </para>
+/// <para>
+/// This chat client must be used within the context of a running <see cref="ChatClientAgent"/>. It retrieves the
+/// current agent and session from <see cref="AIAgent.CurrentRunContext"/>, which is set automatically when an agent's
+/// <see cref="AIAgent.RunAsync(IEnumerable{ChatMessage}, AgentSession?, AgentRunOptions?, CancellationToken)"/> or
+/// <see cref="AIAgent.RunStreamingAsync(IEnumerable{ChatMessage}, AgentSession?, AgentRunOptions?, CancellationToken)"/>
+/// method is called. The <see cref="ChatClientAgent"/> ensures the run context always contains a resolved session,
+/// even when the caller passes null. An <see cref="InvalidOperationException"/> is thrown if no run context is
+/// available or if the agent is not a <see cref="ChatClientAgent"/>.
+/// </para>
+/// </remarks>
+internal sealed class ChatHistoryPersistingChatClient : DelegatingChatClient
+{
+    /// <summary>
+    /// The key used in <see cref="ChatMessage.AdditionalProperties"/> and <see cref="AIContent.AdditionalProperties"/>
+    /// to mark messages and their content as already persisted to chat history.
+    /// </summary>
+    internal const string PersistedMarkerKey = "_chatHistoryPersisted";
+
+    /// <summary>
+    /// Initializes a new instance of the <see cref="ChatHistoryPersistingChatClient"/> class.
+    /// </summary>
+    /// <param name="innerClient">The underlying chat client that will handle the core operations.</param>
+    /// <param name="markOnly">
+    /// When <see langword="true"/>, messages are marked with metadata but not persisted immediately,
+    /// and the session's <see cref="ChatClientAgentSession.ConversationId"/> is not updated.
+    /// The <see cref="ChatClientAgent"/> will persist only the marked messages and update the
+    /// conversation ID at the end of the run.
+    /// When <see langword="false"/> (the default), messages are persisted and the conversation ID
+    /// is updated immediately after each service call.
+    /// </param>
+    public ChatHistoryPersistingChatClient(IChatClient innerClient, bool markOnly = false)
+        : base(innerClient)
+    {
+        this.MarkOnly = markOnly;
+    }
+
+    /// <summary>
+    /// Gets a value indicating whether this decorator is in mark-only mode.
+    /// </summary>
+    /// <remarks>
+    /// When <see langword="true"/>, messages are marked with metadata but not persisted immediately,
+    /// and the session's <see cref="ChatClientAgentSession.ConversationId"/> is not updated.
+    /// Both are deferred to the <see cref="ChatClientAgent"/> at the end of the run.
+    /// When <see langword="false"/>, messages are persisted and the conversation ID is updated
+    /// after each service call.
+    /// </remarks>
+    public bool MarkOnly { get; }
+
+    /// <inheritdoc/>
+    public override async Task<ChatResponse> GetResponseAsync(
+        IEnumerable<ChatMessage> messages,
+        ChatOptions? options = null,
+        CancellationToken cancellationToken = default)
+    {
+        var (agent, session) = GetRequiredAgentAndSession();
+
+        ChatResponse response;
+        try
+        {
+            response = await base.GetResponseAsync(messages, options, cancellationToken).ConfigureAwait(false);
+        }
+        catch (Exception ex)
+        {
+            var newRequestMessagesOnFailure = GetNewRequestMessages(messages);
+            await agent.NotifyProvidersOfFailureAsync(session, ex, newRequestMessagesOnFailure, options, cancellationToken).ConfigureAwait(false);
+            throw;
+        }
+
+        var newRequestMessages = GetNewRequestMessages(messages);
+
+        if (this.ShouldDeferPersistence(options))
+        {
+            // In mark-only mode or when resuming from a continuation token, just mark messages
+            // for later persistence by ChatClientAgent. Conversation ID and provider notification
+            // are deferred to end-of-run. For continuation tokens, the end-of-run handler needs
+            // to send the combined data from both the previous and current runs.
+            MarkAsPersisted(newRequestMessages);
+            MarkAsPersisted(response.Messages);
+        }
+        else
+        {
+            // In persist mode, persist immediately and update conversation ID.
+            agent.UpdateSessionConversationId(session, response.ConversationId, cancellationToken);
+            await agent.NotifyProvidersOfNewMessagesAsync(session, newRequestMessages, response.Messages, options, cancellationToken).ConfigureAwait(false);
+            MarkAsPersisted(newRequestMessages);
+            MarkAsPersisted(response.Messages);
+        }
+
+        return response;
+    }
+
+    /// <inheritdoc/>
+    public override async IAsyncEnumerable<ChatResponseUpdate> GetStreamingResponseAsync(
+        IEnumerable<ChatMessage> messages,
+        ChatOptions? options = null,
+        [EnumeratorCancellation] CancellationToken cancellationToken = default)
+    {
+        var (agent, session) = GetRequiredAgentAndSession();
+
+        List<ChatResponseUpdate> responseUpdates = [];
+
+        IAsyncEnumerator<ChatResponseUpdate> enumerator;
+        try
+        {
+            enumerator = base.GetStreamingResponseAsync(messages, options, cancellationToken).GetAsyncEnumerator(cancellationToken);
+        }
+        catch (Exception ex)
+        {
+            var newRequestMessagesOnFailure = GetNewRequestMessages(messages);
+            await agent.NotifyProvidersOfFailureAsync(session, ex, newRequestMessagesOnFailure, options, cancellationToken).ConfigureAwait(false);
+            throw;
+        }
+
+        bool hasUpdates;
+        try
+        {
+            hasUpdates = await enumerator.MoveNextAsync().ConfigureAwait(false);
+        }
+        catch (Exception ex)
+        {
+            var newRequestMessagesOnFailure = GetNewRequestMessages(messages);
+            await agent.NotifyProvidersOfFailureAsync(session, ex, newRequestMessagesOnFailure, options, cancellationToken).ConfigureAwait(false);
+            throw;
+        }
+
+        while (hasUpdates)
+        {
+            var update = enumerator.Current;
+            responseUpdates.Add(update);
+            yield return update;
+
+            try
+            {
+                hasUpdates = await enumerator.MoveNextAsync().ConfigureAwait(false);
+            }
+            catch (Exception ex)
+            {
+                var newRequestMessagesOnFailure = GetNewRequestMessages(messages);
+                await agent.NotifyProvidersOfFailureAsync(session, ex, newRequestMessagesOnFailure, options, cancellationToken).ConfigureAwait(false);
+                throw;
+            }
+        }
+
+        var chatResponse = responseUpdates.ToChatResponse();
+        var newRequestMessages = GetNewRequestMessages(messages);
+
+        if (this.ShouldDeferPersistence(options))
+        {
+            // In mark-only mode or when resuming from a continuation token, just mark messages
+            // for later persistence by ChatClientAgent. Conversation ID and provider notification
+            // are deferred to end-of-run. For continuation tokens, the end-of-run handler needs
+            // to send the combined data from both the previous and current runs.
+            MarkAsPersisted(newRequestMessages);
+            MarkAsPersisted(chatResponse.Messages);
+        }
+        else
+        {
+            // In persist mode, persist immediately and update conversation ID.
+            agent.UpdateSessionConversationId(session, chatResponse.ConversationId, cancellationToken);
+            await agent.NotifyProvidersOfNewMessagesAsync(session, newRequestMessages, chatResponse.Messages, options, cancellationToken).ConfigureAwait(false);
+            MarkAsPersisted(newRequestMessages);
+            MarkAsPersisted(chatResponse.Messages);
+        }
+    }
+
+    /// <summary>
+    /// Gets the current <see cref="ChatClientAgent"/> and <see cref="ChatClientAgentSession"/> from the run context.
+    /// </summary>
+    private static (ChatClientAgent Agent, ChatClientAgentSession Session) GetRequiredAgentAndSession()
+    {
+        var runContext = AIAgent.CurrentRunContext
+            ?? throw new InvalidOperationException(
+                $"{nameof(ChatHistoryPersistingChatClient)} can only be used within the context of a running AIAgent. " +
+                "Ensure that the chat client is being invoked as part of an AIAgent.RunAsync or AIAgent.RunStreamingAsync call.");
+
+        var chatClientAgent = runContext.Agent.GetService<ChatClientAgent>()
+            ?? throw new InvalidOperationException(
+                $"{nameof(ChatHistoryPersistingChatClient)} can only be used with a {nameof(ChatClientAgent)}. " +
+                $"The current agent is of type '{runContext.Agent.GetType().Name}'.");
+
+        if (runContext.Session is not ChatClientAgentSession chatClientAgentSession)
+        {
+            throw new InvalidOperationException(
+                $"{nameof(ChatHistoryPersistingChatClient)} requires a {nameof(ChatClientAgentSession)}. " +
+                $"The current session is of type '{runContext.Session?.GetType().Name ?? "null"}'.");
+        }
+
+        return (chatClientAgent, chatClientAgentSession);
+    }
+
+    /// <summary>
+    /// Determines whether persistence should be deferred to end-of-run instead of happening immediately.
+    /// </summary>
+    /// <returns>
+    /// <see langword="true"/> when in <see cref="MarkOnly"/> mode, when the call is resuming from
+    /// a continuation token (since the end-of-run handler needs to combine data from the previous
+    /// and current runs), or when background responses are allowed (since the caller may stop
+    /// consuming the stream mid-run, preventing the post-stream persistence code from executing).
+    /// </returns>
+    private bool ShouldDeferPersistence(ChatOptions? options)
+    {
+        return this.MarkOnly || options?.ContinuationToken is not null || options?.AllowBackgroundResponses is true;
+    }
+
+    /// <summary>
+    /// Returns only the request messages that have not yet been persisted to chat history.
+    /// </summary>
+    /// <remarks>
+    /// A message is considered already persisted if any of the following is true:
+    /// <list type="bullet">
+    /// <item>It has the <see cref="PersistedMarkerKey"/> in its <see cref="ChatMessage.AdditionalProperties"/>.</item>
+    /// <item>It has an <see cref="AgentRequestMessageSourceType"/> of <see cref="AgentRequestMessageSourceType.ChatHistory"/>
+    /// (indicating it was loaded from chat history and does not need to be re-persisted).</item>
+    /// <item>It has <see cref="ChatMessage.Contents"/> and all of its <see cref="AIContent"/> items have the
+    /// <see cref="PersistedMarkerKey"/> in their <see cref="AIContent.AdditionalProperties"/>. This handles the
+    /// streaming case where <see cref="FunctionInvokingChatClient"/> reconstructs <see cref="ChatMessage"/> objects
+    /// independently via <c>ToChatResponse()</c>, producing different object references that share the same
+    /// underlying <see cref="AIContent"/> instances.</item>
+    /// </list>
+    /// </remarks>
+    /// <returns>A list of request messages that have not yet been persisted.</returns>
+    /// <param name="messages">The full set of request messages to filter.</param>
+    private static List<ChatMessage> GetNewRequestMessages(IEnumerable<ChatMessage> messages)
+    {
+        return messages.Where(m => !IsAlreadyPersisted(m)).ToList();
+    }
+
+    /// <summary>
+    /// Determines whether a message has already been persisted to chat history by this decorator.
+    /// </summary>
+    private static bool IsAlreadyPersisted(ChatMessage message)
+    {
+        if (message.AdditionalProperties?.TryGetValue(PersistedMarkerKey, out var value) == true && value is true)
+        {
+            return true;
+        }
+
+        if (message.GetAgentRequestMessageSourceType() == AgentRequestMessageSourceType.ChatHistory)
+        {
+            return true;
+        }
+
+        // In streaming mode, FunctionInvokingChatClient reconstructs ChatMessage objects via ToChatResponse()
+        // independently, producing different ChatMessage instances. However, the underlying AIContent objects
+        // (e.g., FunctionCallContent, FunctionResultContent) are shared references. Checking for markers on
+        // AIContent handles dedup in this case.
+        if (message.Contents.Count > 0 && message.Contents.All(c => c.AdditionalProperties?.TryGetValue(PersistedMarkerKey, out var value) == true && value is true))
+        {
+            return true;
+        }
+
+        return false;
+    }
+
+    /// <summary>
+    /// Marks the given messages as persisted by setting a marker on both the <see cref="ChatMessage"/>
+    /// and each of its <see cref="AIContent"/> items.
+    /// </summary>
+    /// <remarks>
+    /// Both levels are marked because <see cref="FunctionInvokingChatClient"/> may reconstruct
+    /// <see cref="ChatMessage"/> objects in streaming mode (losing the message-level marker),
+    /// but the <see cref="AIContent"/> references are shared and retain their markers.
+    /// </remarks>
+    /// <param name="messages">The messages to mark as persisted.</param>
+    private static void MarkAsPersisted(IEnumerable<ChatMessage> messages)
+    {
+        foreach (var message in messages)
+        {
+            message.AdditionalProperties ??= new();
+            message.AdditionalProperties[PersistedMarkerKey] = true;
+
+            foreach (var content in message.Contents)
+            {
+                content.AdditionalProperties ??= new();
+                content.AdditionalProperties[PersistedMarkerKey] = true;
+            }
+        }
+    }
+}

dotnet/tests/Microsoft.Agents.AI.UnitTests/ChatClient/ChatHistoryPersistingChatClientTests.cs

@@ -0,0 +1,766 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Threading;
+using System.Threading.Tasks;
+using Microsoft.Extensions.AI;
+using Microsoft.Extensions.DependencyInjection;
+using Moq;
+using Moq.Protected;
+
+namespace Microsoft.Agents.AI.UnitTests;
+
+/// <summary>
+/// Contains unit tests for the <see cref="ChatHistoryPersistingChatClient"/> decorator,
+/// verifying that it persists messages via the <see cref="ChatHistoryProvider"/> after each
+/// individual service call by default, or marks messages for end-of-run persistence when the
+/// <see cref="ChatClientAgentOptions.PersistChatHistoryAtEndOfRun"/> option is enabled.
+/// </summary>
+public class ChatHistoryPersistingChatClientTests
+{
+    /// <summary>
+    /// Verifies that by default (PersistChatHistoryAtEndOfRun is false),
+    /// the ChatHistoryProvider receives messages after a successful non-streaming call.
+    /// </summary>
+    [Fact]
+    public async Task RunAsync_PersistsMessagesPerServiceCall_ByDefaultAsync()
+    {
+        // Arrange
+        Mock<IChatClient> mockService = new();
+        mockService.Setup(
+            s => s.GetResponseAsync(
+                It.IsAny<IEnumerable<ChatMessage>>(),
+                It.IsAny<ChatOptions>(),
+                It.IsAny<CancellationToken>())).ReturnsAsync(new ChatResponse([new(ChatRole.Assistant, "response")]));
+
+        Mock<ChatHistoryProvider> mockChatHistoryProvider = new(null, null, null);
+        mockChatHistoryProvider.SetupGet(p => p.StateKeys).Returns(["TestChatHistoryProvider"]);
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask<IEnumerable<ChatMessage>>>("InvokingCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokingContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns((ChatHistoryProvider.InvokingContext ctx, CancellationToken _) =>
+                new ValueTask<IEnumerable<ChatMessage>>(ctx.RequestMessages.ToList()));
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask>("InvokedCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokedContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns(new ValueTask());
+
+        ChatClientAgent agent = new(mockService.Object, options: new()
+        {
+            ChatHistoryProvider = mockChatHistoryProvider.Object,
+            PersistChatHistoryAtEndOfRun = false,
+        });
+
+        // Act
+        var session = await agent.CreateSessionAsync() as ChatClientAgentSession;
+        await agent.RunAsync([new(ChatRole.User, "test")], session);
+
+        // Assert — InvokedCoreAsync should be called by the decorator (per service call)
+        mockChatHistoryProvider
+            .Protected()
+            .Verify<ValueTask>("InvokedCoreAsync", Times.Once(),
+                ItExpr.Is<ChatHistoryProvider.InvokedContext>(x =>
+                    x.RequestMessages.Any(m => m.Text == "test") &&
+                    x.ResponseMessages!.Any(m => m.Text == "response")),
+                ItExpr.IsAny<CancellationToken>());
+    }
+
+    /// <summary>
+    /// Verifies that when per-service-call persistence is active (default),
+    /// the ChatHistoryProvider receives messages at the end of the run.
+    /// </summary>
+    [Fact]
+    public async Task RunAsync_PersistsMessagesAtEndOfRun_WhenOptionEnabledAsync()
+    {
+        // Arrange
+        Mock<IChatClient> mockService = new();
+        mockService.Setup(
+            s => s.GetResponseAsync(
+                It.IsAny<IEnumerable<ChatMessage>>(),
+                It.IsAny<ChatOptions>(),
+                It.IsAny<CancellationToken>())).ReturnsAsync(new ChatResponse([new(ChatRole.Assistant, "response")]));
+
+        Mock<ChatHistoryProvider> mockChatHistoryProvider = new(null, null, null);
+        mockChatHistoryProvider.SetupGet(p => p.StateKeys).Returns(["TestChatHistoryProvider"]);
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask<IEnumerable<ChatMessage>>>("InvokingCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokingContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns((ChatHistoryProvider.InvokingContext ctx, CancellationToken _) =>
+                new ValueTask<IEnumerable<ChatMessage>>(ctx.RequestMessages.ToList()));
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask>("InvokedCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokedContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns(new ValueTask());
+
+        ChatClientAgent agent = new(mockService.Object, options: new()
+        {
+            ChatHistoryProvider = mockChatHistoryProvider.Object,
+            PersistChatHistoryAtEndOfRun = true,
+        });
+
+        // Act
+        var session = await agent.CreateSessionAsync() as ChatClientAgentSession;
+        await agent.RunAsync([new(ChatRole.User, "test")], session);
+
+        // Assert — InvokedCoreAsync should be called once by the agent (end of run)
+        mockChatHistoryProvider
+            .Protected()
+            .Verify<ValueTask>("InvokedCoreAsync", Times.Once(),
+                ItExpr.Is<ChatHistoryProvider.InvokedContext>(x =>
+                    x.RequestMessages.Any(m => m.Text == "test") &&
+                    x.ResponseMessages!.Any(m => m.Text == "response")),
+                ItExpr.IsAny<CancellationToken>());
+    }
+
+    /// <summary>
+    /// Verifies that when per-service-call persistence is active (default) and the service call fails,
+    /// the ChatHistoryProvider is notified with the exception.
+    /// </summary>
+    [Fact]
+    public async Task RunAsync_NotifiesProviderOfFailure_WhenPerServiceCallPersistenceActiveAsync()
+    {
+        // Arrange
+        var expectedException = new InvalidOperationException("Service failed");
+        Mock<IChatClient> mockService = new();
+        mockService.Setup(
+            s => s.GetResponseAsync(
+                It.IsAny<IEnumerable<ChatMessage>>(),
+                It.IsAny<ChatOptions>(),
+                It.IsAny<CancellationToken>())).ThrowsAsync(expectedException);
+
+        Mock<ChatHistoryProvider> mockChatHistoryProvider = new(null, null, null);
+        mockChatHistoryProvider.SetupGet(p => p.StateKeys).Returns(["TestChatHistoryProvider"]);
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask<IEnumerable<ChatMessage>>>("InvokingCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokingContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns((ChatHistoryProvider.InvokingContext ctx, CancellationToken _) =>
+                new ValueTask<IEnumerable<ChatMessage>>(ctx.RequestMessages.ToList()));
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask>("InvokedCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokedContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns(new ValueTask());
+
+        ChatClientAgent agent = new(mockService.Object, options: new()
+        {
+            ChatHistoryProvider = mockChatHistoryProvider.Object,
+            PersistChatHistoryAtEndOfRun = false,
+        });
+
+        // Act
+        var session = await agent.CreateSessionAsync() as ChatClientAgentSession;
+        await Assert.ThrowsAsync<InvalidOperationException>(() => agent.RunAsync([new(ChatRole.User, "test")], session));
+
+        // Assert — the decorator should have notified the provider of the failure
+        mockChatHistoryProvider
+            .Protected()
+            .Verify<ValueTask>("InvokedCoreAsync", Times.Once(),
+                ItExpr.Is<ChatHistoryProvider.InvokedContext>(x =>
+                    x.InvokeException != null &&
+                    x.InvokeException.Message == "Service failed"),
+                ItExpr.IsAny<CancellationToken>());
+    }
+
+    /// <summary>
+    /// Verifies that the decorator is injected in persist mode by default
+    /// and can be discovered via GetService.
+    /// </summary>
+    [Fact]
+    public void ChatClient_ContainsDecorator_InPersistMode_ByDefault()
+    {
+        // Arrange
+        Mock<IChatClient> mockService = new();
+
+        // Act
+        ChatClientAgent agent = new(mockService.Object, options: new());
+
+        // Assert
+        var decorator = agent.ChatClient.GetService<ChatHistoryPersistingChatClient>();
+        Assert.NotNull(decorator);
+        Assert.False(decorator.MarkOnly);
+    }
+
+    /// <summary>
+    /// Verifies that the decorator is injected in mark-only mode when PersistChatHistoryAtEndOfRun is true.
+    /// </summary>
+    [Fact]
+    public void ChatClient_ContainsDecorator_InMarkOnlyMode_WhenPersistAtEndOfRun()
+    {
+        // Arrange
+        Mock<IChatClient> mockService = new();
+
+        // Act
+        ChatClientAgent agent = new(mockService.Object, options: new()
+        {
+            PersistChatHistoryAtEndOfRun = true,
+        });
+
+        // Assert
+        var decorator = agent.ChatClient.GetService<ChatHistoryPersistingChatClient>();
+        Assert.NotNull(decorator);
+        Assert.True(decorator.MarkOnly);
+    }
+
+    /// <summary>
+    /// Verifies that the decorator is NOT injected when UseProvidedChatClientAsIs is true.
+    /// </summary>
+    [Fact]
+    public void ChatClient_DoesNotContainDecorator_WhenUseProvidedChatClientAsIs()
+    {
+        // Arrange
+        Mock<IChatClient> mockService = new();
+
+        // Act
+        ChatClientAgent agent = new(mockService.Object, options: new()
+        {
+            UseProvidedChatClientAsIs = true,
+        });
+
+        // Assert
+        var decorator = agent.ChatClient.GetService<ChatHistoryPersistingChatClient>();
+        Assert.Null(decorator);
+    }
+
+    /// <summary>
+    /// Verifies that the PersistChatHistoryAtEndOfRun option is included in Clone().
+    /// </summary>
+    [Fact]
+    public void ChatClientAgentOptions_Clone_IncludesPersistChatHistoryAtEndOfRun()
+    {
+        // Arrange
+        var options = new ChatClientAgentOptions
+        {
+            PersistChatHistoryAtEndOfRun = true,
+        };
+
+        // Act
+        var cloned = options.Clone();
+
+        // Assert
+        Assert.True(cloned.PersistChatHistoryAtEndOfRun);
+    }
+
+    /// <summary>
+    /// Verifies that when per-service-call persistence is active (default) and the service call
+    /// involves a function invocation loop, the ChatHistoryProvider is called after each individual
+    /// service call (not just once at the end).
+    /// </summary>
+    [Fact]
+    public async Task RunAsync_PersistsPerServiceCall_DuringFunctionInvocationLoopAsync()
+    {
+        // Arrange
+        int serviceCallCount = 0;
+        Mock<IChatClient> mockService = new();
+        mockService.Setup(
+            s => s.GetResponseAsync(
+                It.IsAny<IEnumerable<ChatMessage>>(),
+                It.IsAny<ChatOptions>(),
+                It.IsAny<CancellationToken>()))
+            .Returns(() =>
+            {
+                serviceCallCount++;
+                if (serviceCallCount == 1)
+                {
+                    // First call returns a tool call
+                    return Task.FromResult(new ChatResponse([new(ChatRole.Assistant, [new FunctionCallContent("call1", "myTool", new Dictionary<string, object?>())])]));
+                }
+
+                // Second call returns a final response
+                return Task.FromResult(new ChatResponse([new(ChatRole.Assistant, "final response")]));
+            });
+
+        var invokedContexts = new List<ChatHistoryProvider.InvokedContext>();
+
+        Mock<ChatHistoryProvider> mockChatHistoryProvider = new(null, null, null);
+        mockChatHistoryProvider.SetupGet(p => p.StateKeys).Returns(["TestChatHistoryProvider"]);
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask<IEnumerable<ChatMessage>>>("InvokingCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokingContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns((ChatHistoryProvider.InvokingContext ctx, CancellationToken _) =>
+                new ValueTask<IEnumerable<ChatMessage>>(ctx.RequestMessages.ToList()));
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask>("InvokedCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokedContext>(), ItExpr.IsAny<CancellationToken>())
+            .Callback((ChatHistoryProvider.InvokedContext ctx, CancellationToken _) => invokedContexts.Add(ctx))
+            .Returns(() => new ValueTask());
+
+        // Define a simple tool
+        var tool = AIFunctionFactory.Create(() => "tool result", "myTool", "A test tool");
+
+        ChatClientAgent agent = new(mockService.Object, options: new()
+        {
+            ChatOptions = new() { Tools = [tool] },
+            ChatHistoryProvider = mockChatHistoryProvider.Object,
+            PersistChatHistoryAtEndOfRun = false,
+        }, services: new ServiceCollection().BuildServiceProvider());
+
+        // Act
+        var session = await agent.CreateSessionAsync() as ChatClientAgentSession;
+        Exception? caughtException = null;
+        try
+        {
+            await agent.RunAsync([new(ChatRole.User, "test")], session);
+        }
+        catch (Exception ex)
+        {
+            caughtException = ex;
+        }
+
+        // Diagnostic: check if there was an unexpected exception
+        Assert.Null(caughtException);
+
+        // Assert — the decorator should have been called twice (once per service call in the function invocation loop)
+        Assert.Equal(2, serviceCallCount);
+        Assert.Equal(2, invokedContexts.Count);
+
+        // First invocation should have the user message as request and tool call response
+        Assert.NotNull(invokedContexts[0].ResponseMessages);
+        var firstRequestMessages = invokedContexts[0].RequestMessages.ToList();
+        Assert.Contains(firstRequestMessages, m => m.Text == "test");
+        Assert.Contains(invokedContexts[0].ResponseMessages!, m => m.Contents.OfType<FunctionCallContent>().Any());
+
+        // Second invocation: request messages should NOT include the original user message (already notified).
+        // It should only include messages added since the first call (assistant tool call + tool result).
+        Assert.NotNull(invokedContexts[1].ResponseMessages);
+        var secondRequestMessages = invokedContexts[1].RequestMessages.ToList();
+        Assert.DoesNotContain(secondRequestMessages, m => m.Text == "test");
+        Assert.Contains(invokedContexts[1].ResponseMessages!, m => m.Text == "final response");
+    }
+
+    /// <summary>
+    /// Verifies that when per-service-call persistence is active (default) with streaming,
+    /// the ChatHistoryProvider receives messages after the stream completes.
+    /// </summary>
+    [Fact]
+    public async Task RunStreamingAsync_PersistsMessagesPerServiceCall_ByDefaultAsync()
+    {
+        // Arrange
+        Mock<IChatClient> mockService = new();
+        mockService.Setup(
+            s => s.GetStreamingResponseAsync(
+                It.IsAny<IEnumerable<ChatMessage>>(),
+                It.IsAny<ChatOptions>(),
+                It.IsAny<CancellationToken>()))
+            .Returns(CreateAsyncEnumerableAsync(
+                new ChatResponseUpdate(ChatRole.Assistant, "streaming "),
+                new ChatResponseUpdate(ChatRole.Assistant, "response")));
+
+        Mock<ChatHistoryProvider> mockChatHistoryProvider = new(null, null, null);
+        mockChatHistoryProvider.SetupGet(p => p.StateKeys).Returns(["TestChatHistoryProvider"]);
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask<IEnumerable<ChatMessage>>>("InvokingCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokingContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns((ChatHistoryProvider.InvokingContext ctx, CancellationToken _) =>
+                new ValueTask<IEnumerable<ChatMessage>>(ctx.RequestMessages.ToList()));
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask>("InvokedCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokedContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns(new ValueTask());
+
+        ChatClientAgent agent = new(mockService.Object, options: new()
+        {
+            ChatHistoryProvider = mockChatHistoryProvider.Object,
+            PersistChatHistoryAtEndOfRun = false,
+        });
+
+        // Act
+        var session = await agent.CreateSessionAsync() as ChatClientAgentSession;
+        await foreach (var _ in agent.RunStreamingAsync([new(ChatRole.User, "test")], session))
+        {
+            // Consume stream
+        }
+
+        // Assert — InvokedCoreAsync should be called by the decorator
+        mockChatHistoryProvider
+            .Protected()
+            .Verify<ValueTask>("InvokedCoreAsync", Times.Once(),
+                ItExpr.Is<ChatHistoryProvider.InvokedContext>(x =>
+                    x.RequestMessages.Any(m => m.Text == "test") &&
+                    x.ResponseMessages != null),
+                ItExpr.IsAny<CancellationToken>());
+    }
+
+    /// <summary>
+    /// Verifies that when per-service-call persistence is active (default),
+    /// AIContextProviders are also notified of new messages after a successful call.
+    /// </summary>
+    [Fact]
+    public async Task RunAsync_NotifiesAIContextProviders_ByDefaultAsync()
+    {
+        // Arrange
+        Mock<IChatClient> mockService = new();
+        mockService.Setup(
+            s => s.GetResponseAsync(
+                It.IsAny<IEnumerable<ChatMessage>>(),
+                It.IsAny<ChatOptions>(),
+                It.IsAny<CancellationToken>())).ReturnsAsync(new ChatResponse([new(ChatRole.Assistant, "response")]));
+
+        Mock<AIContextProvider> mockContextProvider = new(null, null, null);
+        mockContextProvider.SetupGet(p => p.StateKeys).Returns(["TestAIContextProvider"]);
+        mockContextProvider
+            .Protected()
+            .Setup<ValueTask<AIContext>>("InvokingCoreAsync", ItExpr.IsAny<AIContextProvider.InvokingContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns(() => new ValueTask<AIContext>(new AIContext()));
+        mockContextProvider
+            .Protected()
+            .Setup<ValueTask>("InvokedCoreAsync", ItExpr.IsAny<AIContextProvider.InvokedContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns(() => new ValueTask());
+
+        ChatClientAgent agent = new(mockService.Object, options: new()
+        {
+            AIContextProviders = [mockContextProvider.Object],
+            PersistChatHistoryAtEndOfRun = false,
+        });
+
+        // Act
+        var session = await agent.CreateSessionAsync() as ChatClientAgentSession;
+        await agent.RunAsync([new(ChatRole.User, "test")], session);
+
+        // Assert — InvokedCoreAsync should be called by the decorator for the AIContextProvider
+        mockContextProvider
+            .Protected()
+            .Verify<ValueTask>("InvokedCoreAsync", Times.Once(),
+                ItExpr.Is<AIContextProvider.InvokedContext>(x =>
+                    x.ResponseMessages != null &&
+                    x.ResponseMessages.Any(m => m.Text == "response")),
+                ItExpr.IsAny<CancellationToken>());
+    }
+
+    /// <summary>
+    /// Verifies that when per-service-call persistence is active (default) and the service fails,
+    /// AIContextProviders are notified of the failure.
+    /// </summary>
+    [Fact]
+    public async Task RunAsync_NotifiesAIContextProvidersOfFailure_ByDefaultAsync()
+    {
+        // Arrange
+        var expectedException = new InvalidOperationException("Service failed");
+        Mock<IChatClient> mockService = new();
+        mockService.Setup(
+            s => s.GetResponseAsync(
+                It.IsAny<IEnumerable<ChatMessage>>(),
+                It.IsAny<ChatOptions>(),
+                It.IsAny<CancellationToken>())).ThrowsAsync(expectedException);
+
+        Mock<AIContextProvider> mockContextProvider = new(null, null, null);
+        mockContextProvider.SetupGet(p => p.StateKeys).Returns(["TestAIContextProvider"]);
+        mockContextProvider
+            .Protected()
+            .Setup<ValueTask<AIContext>>("InvokingCoreAsync", ItExpr.IsAny<AIContextProvider.InvokingContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns(() => new ValueTask<AIContext>(new AIContext()));
+        mockContextProvider
+            .Protected()
+            .Setup<ValueTask>("InvokedCoreAsync", ItExpr.IsAny<AIContextProvider.InvokedContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns(() => new ValueTask());
+
+        ChatClientAgent agent = new(mockService.Object, options: new()
+        {
+            AIContextProviders = [mockContextProvider.Object],
+            PersistChatHistoryAtEndOfRun = false,
+        });
+
+        // Act
+        var session = await agent.CreateSessionAsync() as ChatClientAgentSession;
+        await Assert.ThrowsAsync<InvalidOperationException>(() => agent.RunAsync([new(ChatRole.User, "test")], session));
+
+        // Assert — the decorator should have notified the AIContextProvider of the failure
+        mockContextProvider
+            .Protected()
+            .Verify<ValueTask>("InvokedCoreAsync", Times.Once(),
+                ItExpr.Is<AIContextProvider.InvokedContext>(x =>
+                    x.InvokeException != null &&
+                    x.InvokeException.Message == "Service failed"),
+                ItExpr.IsAny<CancellationToken>());
+    }
+
+    /// <summary>
+    /// Verifies that when per-service-call persistence is active (default),
+    /// both ChatHistoryProvider and AIContextProviders are notified together.
+    /// </summary>
+    [Fact]
+    public async Task RunAsync_NotifiesBothProviders_ByDefaultAsync()
+    {
+        // Arrange
+        Mock<IChatClient> mockService = new();
+        mockService.Setup(
+            s => s.GetResponseAsync(
+                It.IsAny<IEnumerable<ChatMessage>>(),
+                It.IsAny<ChatOptions>(),
+                It.IsAny<CancellationToken>())).ReturnsAsync(new ChatResponse([new(ChatRole.Assistant, "response")]));
+
+        Mock<ChatHistoryProvider> mockChatHistoryProvider = new(null, null, null);
+        mockChatHistoryProvider.SetupGet(p => p.StateKeys).Returns(["TestChatHistoryProvider"]);
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask<IEnumerable<ChatMessage>>>("InvokingCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokingContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns((ChatHistoryProvider.InvokingContext ctx, CancellationToken _) =>
+                new ValueTask<IEnumerable<ChatMessage>>(ctx.RequestMessages.ToList()));
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask>("InvokedCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokedContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns(() => new ValueTask());
+
+        Mock<AIContextProvider> mockContextProvider = new(null, null, null);
+        mockContextProvider.SetupGet(p => p.StateKeys).Returns(["TestAIContextProvider"]);
+        mockContextProvider
+            .Protected()
+            .Setup<ValueTask<AIContext>>("InvokingCoreAsync", ItExpr.IsAny<AIContextProvider.InvokingContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns(() => new ValueTask<AIContext>(new AIContext()));
+        mockContextProvider
+            .Protected()
+            .Setup<ValueTask>("InvokedCoreAsync", ItExpr.IsAny<AIContextProvider.InvokedContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns(() => new ValueTask());
+
+        ChatClientAgent agent = new(mockService.Object, options: new()
+        {
+            ChatHistoryProvider = mockChatHistoryProvider.Object,
+            AIContextProviders = [mockContextProvider.Object],
+            PersistChatHistoryAtEndOfRun = false,
+        });
+
+        // Act
+        var session = await agent.CreateSessionAsync() as ChatClientAgentSession;
+        await agent.RunAsync([new(ChatRole.User, "test")], session);
+
+        // Assert — both providers should have been notified
+        mockChatHistoryProvider
+            .Protected()
+            .Verify<ValueTask>("InvokedCoreAsync", Times.Once(),
+                ItExpr.Is<ChatHistoryProvider.InvokedContext>(x =>
+                    x.ResponseMessages != null &&
+                    x.ResponseMessages.Any(m => m.Text == "response")),
+                ItExpr.IsAny<CancellationToken>());
+
+        mockContextProvider
+            .Protected()
+            .Verify<ValueTask>("InvokedCoreAsync", Times.Once(),
+                ItExpr.Is<AIContextProvider.InvokedContext>(x =>
+                    x.ResponseMessages != null &&
+                    x.ResponseMessages.Any(m => m.Text == "response")),
+                ItExpr.IsAny<CancellationToken>());
+    }
+
+    /// <summary>
+    /// Verifies that during a FIC loop, response messages from the first call are not
+    /// re-notified as request messages on the second call.
+    /// </summary>
+    [Fact]
+    public async Task RunAsync_DoesNotReNotifyResponseMessagesAsRequestMessages_DuringFicLoopAsync()
+    {
+        // Arrange
+        int serviceCallCount = 0;
+        var assistantToolCallMessage = new ChatMessage(ChatRole.Assistant, [new FunctionCallContent("call1", "myTool", new Dictionary<string, object?>())]);
+
+        Mock<IChatClient> mockService = new();
+        mockService.Setup(
+            s => s.GetResponseAsync(
+                It.IsAny<IEnumerable<ChatMessage>>(),
+                It.IsAny<ChatOptions>(),
+                It.IsAny<CancellationToken>()))
+            .Returns(() =>
+            {
+                serviceCallCount++;
+                if (serviceCallCount == 1)
+                {
+                    return Task.FromResult(new ChatResponse([assistantToolCallMessage]));
+                }
+
+                return Task.FromResult(new ChatResponse([new(ChatRole.Assistant, "final response")]));
+            });
+
+        var invokedContexts = new List<ChatHistoryProvider.InvokedContext>();
+
+        Mock<ChatHistoryProvider> mockChatHistoryProvider = new(null, null, null);
+        mockChatHistoryProvider.SetupGet(p => p.StateKeys).Returns(["TestChatHistoryProvider"]);
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask<IEnumerable<ChatMessage>>>("InvokingCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokingContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns((ChatHistoryProvider.InvokingContext ctx, CancellationToken _) =>
+                new ValueTask<IEnumerable<ChatMessage>>(ctx.RequestMessages.ToList()));
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask>("InvokedCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokedContext>(), ItExpr.IsAny<CancellationToken>())
+            .Callback((ChatHistoryProvider.InvokedContext ctx, CancellationToken _) => invokedContexts.Add(ctx))
+            .Returns(() => new ValueTask());
+
+        var tool = AIFunctionFactory.Create(() => "tool result", "myTool", "A test tool");
+
+        ChatClientAgent agent = new(mockService.Object, options: new()
+        {
+            ChatOptions = new() { Tools = [tool] },
+            ChatHistoryProvider = mockChatHistoryProvider.Object,
+            PersistChatHistoryAtEndOfRun = false,
+        }, services: new ServiceCollection().BuildServiceProvider());
+
+        // Act
+        var session = await agent.CreateSessionAsync() as ChatClientAgentSession;
+        await agent.RunAsync([new(ChatRole.User, "test")], session);
+
+        // Assert
+        Assert.Equal(2, invokedContexts.Count);
+
+        // The assistant tool call message was a response in call 1
+        Assert.Contains(invokedContexts[0].ResponseMessages!, m => ReferenceEquals(m, assistantToolCallMessage));
+
+        // It should NOT appear as a request in call 2 (it was already notified as a response)
+        var secondRequestMessages = invokedContexts[1].RequestMessages.ToList();
+        Assert.DoesNotContain(secondRequestMessages, m => ReferenceEquals(m, assistantToolCallMessage));
+    }
+
+    /// <summary>
+    /// Verifies that when a failure occurs on the second call in a FIC loop,
+    /// only new request messages (not previously notified) are sent in the failure notification.
+    /// </summary>
+    [Fact]
+    public async Task RunAsync_DeduplicatesRequestMessages_OnFailureDuringFicLoopAsync()
+    {
+        // Arrange
+        int serviceCallCount = 0;
+        Mock<IChatClient> mockService = new();
+        mockService.Setup(
+            s => s.GetResponseAsync(
+                It.IsAny<IEnumerable<ChatMessage>>(),
+                It.IsAny<ChatOptions>(),
+                It.IsAny<CancellationToken>()))
+            .Returns(() =>
+            {
+                serviceCallCount++;
+                if (serviceCallCount == 1)
+                {
+                    return Task.FromResult(new ChatResponse([new(ChatRole.Assistant, [new FunctionCallContent("call1", "myTool", new Dictionary<string, object?>())])]));
+                }
+
+                throw new InvalidOperationException("Service failure on second call");
+            });
+
+        var invokedContexts = new List<ChatHistoryProvider.InvokedContext>();
+
+        Mock<ChatHistoryProvider> mockChatHistoryProvider = new(null, null, null);
+        mockChatHistoryProvider.SetupGet(p => p.StateKeys).Returns(["TestChatHistoryProvider"]);
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask<IEnumerable<ChatMessage>>>("InvokingCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokingContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns((ChatHistoryProvider.InvokingContext ctx, CancellationToken _) =>
+                new ValueTask<IEnumerable<ChatMessage>>(ctx.RequestMessages.ToList()));
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask>("InvokedCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokedContext>(), ItExpr.IsAny<CancellationToken>())
+            .Callback((ChatHistoryProvider.InvokedContext ctx, CancellationToken _) => invokedContexts.Add(ctx))
+            .Returns(() => new ValueTask());
+
+        var tool = AIFunctionFactory.Create(() => "tool result", "myTool", "A test tool");
+
+        ChatClientAgent agent = new(mockService.Object, options: new()
+        {
+            ChatOptions = new() { Tools = [tool] },
+            ChatHistoryProvider = mockChatHistoryProvider.Object,
+            PersistChatHistoryAtEndOfRun = false,
+        }, services: new ServiceCollection().BuildServiceProvider());
+
+        // Act
+        var session = await agent.CreateSessionAsync() as ChatClientAgentSession;
+        await Assert.ThrowsAsync<InvalidOperationException>(() =>
+            agent.RunAsync([new(ChatRole.User, "test")], session));
+
+        // Assert — should have 2 notifications: success on call 1, failure on call 2
+        Assert.Equal(2, invokedContexts.Count);
+
+        // First notification: success, has user message as request
+        Assert.Null(invokedContexts[0].InvokeException);
+        Assert.Contains(invokedContexts[0].RequestMessages, m => m.Text == "test");
+
+        // Second notification: failure, should NOT include the user message (already notified)
+        Assert.NotNull(invokedContexts[1].InvokeException);
+        var failureRequestMessages = invokedContexts[1].RequestMessages.ToList();
+        Assert.DoesNotContain(failureRequestMessages, m => m.Text == "test");
+    }
+
+    /// <summary>
+    /// Verifies that after a successful run with per-service-call persistence, the notified
+    /// messages are stamped with the persisted marker so they are not re-notified.
+    /// </summary>
+    [Fact]
+    public async Task RunAsync_MarksNotifiedMessages_WithPersistedMarkerAsync()
+    {
+        // Arrange
+        Mock<IChatClient> mockService = new();
+        mockService.Setup(
+            s => s.GetResponseAsync(
+                It.IsAny<IEnumerable<ChatMessage>>(),
+                It.IsAny<ChatOptions>(),
+                It.IsAny<CancellationToken>())).ReturnsAsync(new ChatResponse([new(ChatRole.Assistant, "response")]));
+
+        Mock<ChatHistoryProvider> mockChatHistoryProvider = new(null, null, null);
+        mockChatHistoryProvider.SetupGet(p => p.StateKeys).Returns(["TestChatHistoryProvider"]);
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask<IEnumerable<ChatMessage>>>("InvokingCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokingContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns((ChatHistoryProvider.InvokingContext ctx, CancellationToken _) =>
+                new ValueTask<IEnumerable<ChatMessage>>(ctx.RequestMessages.ToList()));
+        mockChatHistoryProvider
+            .Protected()
+            .Setup<ValueTask>("InvokedCoreAsync", ItExpr.IsAny<ChatHistoryProvider.InvokedContext>(), ItExpr.IsAny<CancellationToken>())
+            .Returns(() => new ValueTask());
+
+        ChatClientAgent agent = new(mockService.Object, options: new()
+        {
+            ChatHistoryProvider = mockChatHistoryProvider.Object,
+            PersistChatHistoryAtEndOfRun = false,
+        });
+
+        // Act
+        var inputMessage = new ChatMessage(ChatRole.User, "test");
+        var session = await agent.CreateSessionAsync() as ChatClientAgentSession;
+        await agent.RunAsync([inputMessage], session);
+
+        // Assert — input message should be marked as persisted
+        Assert.True(
+            inputMessage.AdditionalProperties?.ContainsKey(ChatHistoryPersistingChatClient.PersistedMarkerKey) == true,
+            "Input message should be marked as persisted after a successful run.");
+    }
+
+    /// <summary>
+    /// Verifies that when per-service-call persistence is enabled and the inner client returns a
+    /// conversation ID, the session's ConversationId is updated after the service call.
+    /// </summary>
+    [Fact]
+    public async Task RunAsync_UpdatesSessionConversationId_WhenPerServiceCallPersistenceEnabledAsync()
+    {
+        // Arrange
+        const string ExpectedConversationId = "conv-123";
+
+        Mock<IChatClient> mockService = new();
+        mockService.Setup(
+            s => s.GetResponseAsync(
+                It.IsAny<IEnumerable<ChatMessage>>(),
+                It.IsAny<ChatOptions>(),
+                It.IsAny<CancellationToken>()))
+            .ReturnsAsync(new ChatResponse([new(ChatRole.Assistant, "response")])
+            {
+                ConversationId = ExpectedConversationId,
+            });
+
+        ChatClientAgent agent = new(mockService.Object, options: new()
+        {
+            PersistChatHistoryAtEndOfRun = false,
+        });
+
+        // Act
+        var session = await agent.CreateSessionAsync() as ChatClientAgentSession;
+        await agent.RunAsync([new(ChatRole.User, "test")], session);
+
+        // Assert — session should have the conversation ID returned by the inner client
+        Assert.Equal(ExpectedConversationId, session!.ConversationId);
+    }
+
+    private static async IAsyncEnumerable<ChatResponseUpdate> CreateAsyncEnumerableAsync(params ChatResponseUpdate[] updates)
+    {
+        foreach (var update in updates)
+        {
+            yield return update;
+        }
+
+        await Task.CompletedTask;
+    }
+}

dotnet/tests/Microsoft.Agents.AI.Workflows.UnitTests/FileSystemJsonCheckpointStoreTests.cs

@@ -9,49 +9,173 @@ using Microsoft.Agents.AI.Workflows.Checkpointing;
 
 namespace Microsoft.Agents.AI.Workflows.UnitTests;
 
+internal sealed class TempDirectory : IDisposable
+{
+    public DirectoryInfo DirectoryInfo { get; }
+
+    public TempDirectory()
+    {
+        string tempDirPath = Path.Combine(Path.GetTempPath(), Guid.NewGuid().ToString());
+        this.DirectoryInfo = Directory.CreateDirectory(tempDirPath);
+    }
+
+    public void Dispose()
+    {
+        this.DisposeInternal();
+        GC.SuppressFinalize(this);
+    }
+
+    private void DisposeInternal()
+    {
+        if (this.DirectoryInfo.Exists)
+        {
+            try
+            {
+                // Best efforts
+                this.DirectoryInfo.Delete(recursive: true);
+            }
+            catch { }
+        }
+    }
+
+    ~TempDirectory()
+    {
+        // Best efforts
+        this.DisposeInternal();
+    }
+
+    public static implicit operator DirectoryInfo(TempDirectory tempDirectory) => tempDirectory.DirectoryInfo;
+
+    public string FullName => this.DirectoryInfo.FullName;
+
+    public bool IsParentOf(FileInfo candidate)
+    {
+        if (candidate.Directory is null)
+        {
+            return false;
+        }
+
+        if (candidate.Directory.FullName == this.DirectoryInfo.FullName)
+        {
+            return true;
+        }
+
+        return this.IsParentOf(candidate.Directory);
+    }
+
+    public bool IsParentOf(DirectoryInfo candidate)
+    {
+        while (candidate.Parent is not null)
+        {
+            if (candidate.Parent.FullName == this.DirectoryInfo.FullName)
+            {
+                return true;
+            }
+
+            candidate = candidate.Parent;
+        }
+
+        return false;
+    }
+}
 public sealed class FileSystemJsonCheckpointStoreTests
 {
+    public static JsonElement TestData => JsonSerializer.SerializeToElement(new { test = "data" });
+
     [Fact]
     public async Task CreateCheckpointAsync_ShouldPersistIndexToDiskBeforeDisposeAsync()
     {
         // Arrange
-        DirectoryInfo tempDir = new(Path.Combine(Path.GetTempPath(), Guid.NewGuid().ToString()));
-        FileSystemJsonCheckpointStore? store = null;
+        using TempDirectory tempDirectory = new();
+        using FileSystemJsonCheckpointStore? store = new(tempDirectory);
 
-        try
+        string runId = Guid.NewGuid().ToString("N");
+
+        // Act
+        CheckpointInfo checkpoint = await store.CreateCheckpointAsync(runId, TestData);
+
+        // Assert - Check the file size before disposing to verify data was flushed to disk
+        // The index.jsonl file is held exclusively by the store, so we check via FileInfo
+        string indexPath = Path.Combine(tempDirectory.FullName, "index.jsonl");
+        FileInfo indexFile = new(indexPath);
+        indexFile.Refresh();
+        long fileSizeBeforeDispose = indexFile.Length;
+
+        // Data should already be on disk (file size > 0) before we dispose
+        fileSizeBeforeDispose.Should().BeGreaterThan(0, "index.jsonl should be flushed to disk after CreateCheckpointAsync");
+
+        // Dispose to release file lock before final verification
+        store.Dispose();
+
+        string[] lines = File.ReadAllLines(indexPath);
+        lines.Should().HaveCount(1);
+        lines[0].Should().Contain(checkpoint.CheckpointId);
+    }
+
+    private async ValueTask Run_EscapeRootFolderTestAsync(string escapingPath)
+    {
+        // Arrange
+        using TempDirectory tempDirectory = new();
+        using FileSystemJsonCheckpointStore store = new(tempDirectory);
+
+        string naivePath = Path.Combine(tempDirectory.DirectoryInfo.FullName, escapingPath);
+
+        // Check that the naive path is actually outside the temp directory to validate the test is meaningful
+        FileInfo naiveCheckpointFile = new(naivePath);
+        tempDirectory.IsParentOf(naiveCheckpointFile).Should().BeFalse("The naive path should be outside the root folder to validate that escaping is necessary.");
+
+        // Act
+        CheckpointInfo checkpointInfo = await store.CreateCheckpointAsync(escapingPath, TestData);
+
+        // Assert
+        string naivePathWithCheckpointId = Path.Combine(tempDirectory.DirectoryInfo.FullName, $"{escapingPath}_{checkpointInfo.CheckpointId}.json");
+        new FileInfo(naivePathWithCheckpointId).Exists.Should().BeFalse("The naive path should not be used to save a checkpoint file.");
+
+        string actualFileName = store.GetFileNameForCheckpoint(escapingPath, checkpointInfo);
+        string actualFilePath = Path.Combine(tempDirectory.DirectoryInfo.FullName, actualFileName);
+        FileInfo actualFile = new(actualFilePath);
+
+        tempDirectory.IsParentOf(actualFile).Should().BeTrue("The actual checkpoint should be saved inside the root folder.");
+        actualFile.Exists.Should().BeTrue("The actual path should be used to save a checkpoint file.");
+    }
+
+    [Fact]
+    public async Task CreateCheckpointAsync_ShouldNotEscapeRootFolderAsync()
+    {
+        // The SessionId is used as part of the file name, but if it contains path characters such as /.. it can escape the root folder.
+        // Testing that such characters are escaped properly to prevent directory traversal attacks, etc.
+
+        await this.Run_EscapeRootFolderTestAsync("../valid_suffix");
+
+#if !NETFRAMEWORK
+        if (OperatingSystem.IsWindows())
         {
-            store = new(tempDir);
-            string runId = Guid.NewGuid().ToString("N");
-            JsonElement testData = JsonSerializer.SerializeToElement(new { test = "data" });
-
-            // Act
-            CheckpointInfo checkpoint = await store.CreateCheckpointAsync(runId, testData);
-
-            // Assert - Check the file size before disposing to verify data was flushed to disk
-            // The index.jsonl file is held exclusively by the store, so we check via FileInfo
-            string indexPath = Path.Combine(tempDir.FullName, "index.jsonl");
-            FileInfo indexFile = new(indexPath);
-            indexFile.Refresh();
-            long fileSizeBeforeDispose = indexFile.Length;
-
-            // Data should already be on disk (file size > 0) before we dispose
-            fileSizeBeforeDispose.Should().BeGreaterThan(0, "index.jsonl should be flushed to disk after CreateCheckpointAsync");
-
-            // Dispose to release file lock before final verification
-            store.Dispose();
-            store = null;
-
-            string[] lines = File.ReadAllLines(indexPath);
-            lines.Should().HaveCount(1);
-            lines[0].Should().Contain(checkpoint.CheckpointId);
-        }
-        finally
-        {
-            store?.Dispose();
-            if (tempDir.Exists)
-            {
-                tempDir.Delete(recursive: true);
-            }
+            // Windows allows both \ and / as path separators, so we test both
+            await this.Run_EscapeRootFolderTestAsync("..\\valid_suffix");
         }
+#else
+        // .NET Framework is always on Windows
+        await this.Run_EscapeRootFolderTestAsync("..\\valid_suffix");
+#endif
+    }
+
+    private const string InvalidPathCharsWin32 = "\\/:*?\"<>|";
+    private const string InvalidPathCharsUnix = "/";
+    private const string InvalidPathCharsMacOS = "/:";
+
+    [Theory]
+    [InlineData(InvalidPathCharsWin32)]
+    [InlineData(InvalidPathCharsUnix)]
+    [InlineData(InvalidPathCharsMacOS)]
+    public async Task CreateCheckpointAsync_EscapesInvalidCharsAsync(string invalidChars)
+    {
+        // Arrange
+        using TempDirectory tempDirectory = new();
+        using FileSystemJsonCheckpointStore store = new(tempDirectory);
+
+        string runId = $"prefix_{invalidChars}_suffix";
+
+        Func<Task> createCheckpointAction = async () => await store.CreateCheckpointAsync(runId, TestData);
+        await createCheckpointAction.Should().NotThrowAsync();
     }
 }

python/README.md

@@ -24,14 +24,14 @@ If you only need specific integrations, you can install at a more granular level
 # also includes workflows and orchestrations
 pip install agent-framework-core --pre
 
-# Core + Azure AI integration
-pip install agent-framework-azure-ai --pre
+# Core + Azure AI Foundry integration
+pip install agent-framework-foundry --pre
 
 # Core + Microsoft Copilot Studio integration
 pip install agent-framework-copilotstudio --pre
 
-# Core + both Microsoft Copilot Studio and Azure AI integration
-pip install agent-framework-microsoft agent-framework-azure-ai --pre
+# Core + both Microsoft Copilot Studio and Azure AI Foundry integration
+pip install agent-framework-microsoft agent-framework-foundry --pre
 ```
 
 This selective approach is useful when you know which integrations you need, and it is the recommended way to set up lightweight environments.
@@ -53,8 +53,8 @@ AZURE_OPENAI_API_KEY=...
 AZURE_OPENAI_ENDPOINT=...
 AZURE_OPENAI_CHAT_DEPLOYMENT_NAME=...
 ...
-AZURE_AI_PROJECT_ENDPOINT=...
-AZURE_AI_MODEL_DEPLOYMENT_NAME=...
+FOUNDRY_PROJECT_ENDPOINT=...
+FOUNDRY_MODEL=...
 ```
 
 You can also override environment variables by explicitly passing configuration parameters to the chat client constructor:

python/packages/azure-ai-search/README.md

@@ -15,7 +15,7 @@ The Azure AI Search integration provides context providers for RAG (Retrieval Au
 
 ### Basic Usage Example
 
-See the [Azure AI Search context provider examples](../../samples/02-agents/providers/azure_ai/) which demonstrate:
+See the [Azure AI Search context provider examples](../../samples/02-agents/context_providers/azure_ai_search/) which demonstrate:
 
 - Semantic search with hybrid (vector + keyword) queries
 - Agentic mode with Knowledge Bases for complex multi-hop reasoning

python/packages/azure-ai-search/agent_framework_azure_ai_search/_context_provider.py

@@ -16,8 +16,7 @@ from typing import TYPE_CHECKING, Any, ClassVar, Literal, TypedDict
 from agent_framework import AGENT_FRAMEWORK_USER_AGENT, Annotation, Content, Message, SupportsGetEmbeddings
 from agent_framework._sessions import AgentSession, BaseContextProvider, SessionContext
 from agent_framework._settings import SecretString, load_settings
-from agent_framework.azure._entra_id_authentication import AzureCredentialTypes
-from azure.core.credentials import AzureKeyCredential
+from azure.core.credentials import AzureKeyCredential, TokenCredential
 from azure.core.credentials_async import AsyncTokenCredential
 from azure.core.exceptions import ResourceNotFoundError
 from azure.search.documents.aio import SearchClient
@@ -111,6 +110,8 @@ try:
 except ImportError:
     _agentic_retrieval_available = False
 
+AzureCredentialTypes = TokenCredential | AsyncTokenCredential
+
 logger = logging.getLogger("agent_framework.azure_ai_search")
 
 _DEFAULT_AGENTIC_MESSAGE_HISTORY_COUNT = 10

python/packages/azure-ai/agent_framework_azure_ai/__init__.py

@@ -2,23 +2,35 @@
 
 import importlib.metadata
 
-from ._agent_provider import AzureAIAgentsProvider
-from ._chat_client import AzureAIAgentClient, AzureAIAgentOptions
-from ._client import AzureAIClient, AzureAIProjectAgentOptions, RawAzureAIClient
+from ._agent_provider import AzureAIAgentsProvider  # pyright: ignore[reportDeprecated]
+from ._chat_client import AzureAIAgentClient, AzureAIAgentOptions  # pyright: ignore[reportDeprecated]
+from ._client import AzureAIClient, AzureAIProjectAgentOptions, RawAzureAIClient  # pyright: ignore[reportDeprecated]
+from ._deprecated_azure_openai import (
+    AzureOpenAIAssistantsClient,  # pyright: ignore[reportDeprecated]
+    AzureOpenAIAssistantsOptions,
+    AzureOpenAIChatClient,  # pyright: ignore[reportDeprecated]
+    AzureOpenAIChatOptions,
+    AzureOpenAIConfigMixin,
+    AzureOpenAIEmbeddingClient,  # pyright: ignore[reportDeprecated]
+    AzureOpenAIResponsesClient,  # pyright: ignore[reportDeprecated]
+    AzureOpenAIResponsesOptions,
+    AzureOpenAISettings,
+    AzureUserSecurityContext,
+)
 from ._embedding_client import (
     AzureAIInferenceEmbeddingClient,
     AzureAIInferenceEmbeddingOptions,
     AzureAIInferenceEmbeddingSettings,
     RawAzureAIInferenceEmbeddingClient,
 )
-from ._foundry_memory_provider import FoundryMemoryProvider
-from ._project_provider import AzureAIProjectAgentProvider
+from ._entra_id_authentication import AzureCredentialTypes, AzureTokenProvider
+from ._project_provider import AzureAIProjectAgentProvider  # pyright: ignore[reportDeprecated]
 from ._shared import AzureAISettings
 
 try:
     __version__ = importlib.metadata.version(__name__)
 except importlib.metadata.PackageNotFoundError:
-    __version__ = "0.0.0"  # Fallback for development mode
+    __version__ = "0.0.0"
 
 __all__ = [
     "AzureAIAgentClient",
@@ -31,7 +43,18 @@ __all__ = [
     "AzureAIProjectAgentOptions",
     "AzureAIProjectAgentProvider",
     "AzureAISettings",
-    "FoundryMemoryProvider",
+    "AzureCredentialTypes",
+    "AzureOpenAIAssistantsClient",
+    "AzureOpenAIAssistantsOptions",
+    "AzureOpenAIChatClient",
+    "AzureOpenAIChatOptions",
+    "AzureOpenAIConfigMixin",
+    "AzureOpenAIEmbeddingClient",
+    "AzureOpenAIResponsesClient",
+    "AzureOpenAIResponsesOptions",
+    "AzureOpenAISettings",
+    "AzureTokenProvider",
+    "AzureUserSecurityContext",
     "RawAzureAIClient",
     "RawAzureAIInferenceEmbeddingClient",
     "__version__",

python/packages/azure-ai/agent_framework_azure_ai/_agent_provider.py

@@ -18,19 +18,23 @@ from agent_framework import (
 from agent_framework._mcp import MCPTool
 from agent_framework._settings import load_settings
 from agent_framework._tools import ToolTypes
-from agent_framework.azure._entra_id_authentication import AzureCredentialTypes
 from azure.ai.agents.aio import AgentsClient
 from azure.ai.agents.models import Agent as AzureAgent
 from azure.ai.agents.models import ResponseFormatJsonSchema, ResponseFormatJsonSchemaType
 from pydantic import BaseModel
 
-from ._chat_client import AzureAIAgentClient, AzureAIAgentOptions
+from ._chat_client import AzureAIAgentClient, AzureAIAgentOptions  # pyright: ignore[reportDeprecated]
+from ._entra_id_authentication import AzureCredentialTypes
 from ._shared import AzureAISettings, to_azure_ai_agent_tools
 
 if sys.version_info >= (3, 13):
     from typing import Self, TypeVar  # type: ignore # pragma: no cover
 else:
     from typing_extensions import Self, TypeVar  # type: ignore # pragma: no cover
+if sys.version_info >= (3, 13):
+    from warnings import deprecated  # type: ignore # pragma: no cover
+else:
+    from typing_extensions import deprecated  # type: ignore # pragma: no cover
 if sys.version_info >= (3, 11):
     from typing import TypedDict  # type: ignore # pragma: no cover
 else:
@@ -47,6 +51,11 @@ OptionsCoT = TypeVar(
 )
 
 
+@deprecated(
+    "AzureAIAgentClient and the AzureAIAgentsProvider are deprecated. "
+    "They target the V1 Agents Service API and have no direct replacement; "
+    "for new Foundry projects, use FoundryAgent."
+)
 class AzureAIAgentsProvider(Generic[OptionsCoT]):
     """Provider for Azure AI Agent Service V1 (Persistent Agents API).
 
@@ -426,7 +435,7 @@ class AzureAIAgentsProvider(Generic[OptionsCoT]):
             context_providers: Context providers to include during agent invocation.
         """
         # Create the underlying client
-        client = AzureAIAgentClient(
+        client = AzureAIAgentClient(  # pyright: ignore[reportDeprecated]
             agents_client=self._agents_client,
             agent_id=agent.id,
             agent_name=agent.name,

python/packages/azure-ai/agent_framework_azure_ai/_chat_client.py

@@ -36,7 +36,6 @@ from agent_framework import (
 )
 from agent_framework._settings import load_settings
 from agent_framework._tools import ToolTypes
-from agent_framework.azure._entra_id_authentication import AzureCredentialTypes
 from agent_framework.exceptions import (
     ChatClientException,
     ChatClientInvalidRequestException,
@@ -92,12 +91,14 @@ from azure.ai.agents.models import (
 )
 from pydantic import BaseModel
 
+from ._entra_id_authentication import AzureCredentialTypes
 from ._shared import AzureAISettings, resolve_file_ids, to_azure_ai_agent_tools
 
 if sys.version_info >= (3, 13):
     from typing import TypeVar  # type: ignore # pragma: no cover
+    from warnings import deprecated  # type: ignore # pragma: no cover
 else:
-    from typing_extensions import TypeVar  # type: ignore # pragma: no cover
+    from typing_extensions import TypeVar, deprecated  # type: ignore # pragma: no cover
 if sys.version_info >= (3, 12):
     from typing import override  # type: ignore # pragma: no cover
 else:
@@ -210,6 +211,11 @@ AzureAIAgentOptionsT = TypeVar(
 # endregion
 
 
+@deprecated(
+    "AzureAIAgentClient is deprecated. "
+    "It targets the V1 Agents Service API and has no direct replacement; "
+    "for new Foundry projects, use FoundryAgent."
+)
 class AzureAIAgentClient(
     FunctionInvocationLayer[AzureAIAgentOptionsT],
     ChatMiddlewareLayer[AzureAIAgentOptionsT],
@@ -221,7 +227,8 @@ class AzureAIAgentClient(
 
     .. deprecated::
         AzureAIAgentClient is deprecated and will be removed in a future release.
-        Use :class:`AzureAIClient` instead for the V2 (Projects/Responses) API.
+        It targets the V1 Agents Service API and has no direct replacement.
+        For new Foundry projects, use :class:`FoundryAgent`.
     """
 
     OTEL_PROVIDER_NAME: ClassVar[str] = "azure.ai"  # type: ignore[reportIncompatibleVariableOverride, misc]
@@ -239,7 +246,8 @@ class AzureAIAgentClient(
 
         .. deprecated::
             This method is deprecated and will be removed in a future release.
-            Use :meth:`AzureAIClient.get_code_interpreter_tool` instead.
+            For new Foundry projects, configure hosted tools on the Foundry agent definition
+            in the service instead.
 
         Keyword Args:
             file_ids: List of uploaded file IDs or Content objects to make available to
@@ -272,7 +280,7 @@ class AzureAIAgentClient(
         """
         warnings.warn(
             "AzureAIAgentClient.get_code_interpreter_tool() is deprecated and will be removed in a future release; "
-            "use AzureAIClient.get_code_interpreter_tool() instead.",
+            "for new Foundry projects, configure hosted tools on the Foundry agent definition in the service instead.",
             DeprecationWarning,
             stacklevel=2,
         )
@@ -288,7 +296,8 @@ class AzureAIAgentClient(
 
         .. deprecated::
             This method is deprecated and will be removed in a future release.
-            Use :meth:`AzureAIClient.get_file_search_tool` instead.
+            For new Foundry projects, configure hosted tools on the Foundry agent definition
+            in the service instead.
 
         Keyword Args:
             vector_store_ids: List of vector store IDs to search within.
@@ -308,7 +317,7 @@ class AzureAIAgentClient(
         """
         warnings.warn(
             "AzureAIAgentClient.get_file_search_tool() is deprecated and will be removed in a future release; "
-            "use AzureAIClient.get_file_search_tool() instead.",
+            "for new Foundry projects, configure hosted tools on the Foundry agent definition in the service instead.",
             DeprecationWarning,
             stacklevel=2,
         )
@@ -325,7 +334,8 @@ class AzureAIAgentClient(
 
         .. deprecated::
             This method is deprecated and will be removed in a future release.
-            Use :meth:`AzureAIClient.get_web_search_tool` instead.
+            For new Foundry projects, configure hosted tools on the Foundry agent definition
+            in the service instead.
 
         For Azure AI Agents, web search uses Bing Grounding or Bing Custom Search.
         If no arguments are provided, attempts to read from environment variables.
@@ -369,7 +379,7 @@ class AzureAIAgentClient(
         """
         warnings.warn(
             "AzureAIAgentClient.get_web_search_tool() is deprecated and will be removed in a future release; "
-            "use AzureAIClient.get_web_search_tool() instead.",
+            "for new Foundry projects, configure hosted tools on the Foundry agent definition in the service instead.",
             DeprecationWarning,
             stacklevel=2,
         )
@@ -410,7 +420,8 @@ class AzureAIAgentClient(
 
         .. deprecated::
             This method is deprecated and will be removed in a future release.
-            Use :meth:`AzureAIClient.get_mcp_tool` instead.
+            For new Foundry projects, configure hosted tools on the Foundry agent definition
+            in the service instead.
 
         This configures an MCP (Model Context Protocol) server that will be called
         by Azure AI's service. The tools from this MCP server are executed remotely
@@ -446,7 +457,7 @@ class AzureAIAgentClient(
         """
         warnings.warn(
             "AzureAIAgentClient.get_mcp_tool() is deprecated and will be removed in a future release; "
-            "use AzureAIClient.get_mcp_tool() instead.",
+            "for new Foundry projects, configure hosted tools on the Foundry agent definition in the service instead.",
             DeprecationWarning,
             stacklevel=2,
         )
@@ -561,12 +572,6 @@ class AzureAIAgentClient(
                 client: AzureAIAgentClient[MyOptions] = AzureAIAgentClient(credential=credential)
                 response = await client.get_response("Hello", options={"my_custom_option": "value"})
         """
-        warnings.warn(
-            "AzureAIAgentClient is deprecated and will be removed in a future release; "
-            "use AzureAIClient instead for the V2 (Projects/Responses) API.",
-            DeprecationWarning,
-            stacklevel=2,
-        )
         azure_ai_settings = load_settings(
             AzureAISettings,
             env_prefix="AZURE_AI_",

python/packages/azure-ai/agent_framework_azure_ai/_client.py

@@ -30,10 +30,9 @@ from agent_framework import (
 )
 from agent_framework._settings import load_settings
 from agent_framework._tools import ToolTypes
-from agent_framework.azure._entra_id_authentication import AzureCredentialTypes
 from agent_framework.observability import ChatTelemetryLayer
 from agent_framework.openai import OpenAIResponsesOptions
-from agent_framework.openai._responses_client import RawOpenAIResponsesClient
+from agent_framework_openai._chat_client import RawOpenAIChatClient
 from azure.ai.projects.aio import AIProjectClient
 from azure.ai.projects.models import (
     ApproximateLocation,
@@ -50,12 +49,14 @@ from azure.ai.projects.models import (
 from azure.ai.projects.models import FileSearchTool as ProjectsFileSearchTool
 from azure.core.exceptions import ResourceNotFoundError
 
+from ._entra_id_authentication import AzureCredentialTypes
 from ._shared import AzureAISettings, create_text_format_config, resolve_file_ids
 
 if sys.version_info >= (3, 13):
     from typing import TypeVar  # type: ignore # pragma: no cover
+    from warnings import deprecated  # type: ignore # pragma: no cover
 else:
-    from typing_extensions import TypeVar  # type: ignore # pragma: no cover
+    from typing_extensions import TypeVar, deprecated  # type: ignore # pragma: no cover
 if sys.version_info >= (3, 12):
     from typing import override  # type: ignore # pragma: no cover
 else:
@@ -68,7 +69,7 @@ else:
 logger = logging.getLogger("agent_framework.azure")
 
 
-class AzureAIProjectAgentOptions(OpenAIResponsesOptions, total=False):
+class AzureAIProjectAgentOptions(OpenAIResponsesOptions, total=False):  # type: ignore[misc, call-arg]
     """Azure AI Project Agent options."""
 
     rai_config: RaiConfig
@@ -88,8 +89,13 @@ AzureAIClientOptionsT = TypeVar(
 _DOC_INDEX_PATTERN = re.compile(r"doc_(\d+)")
 
 
-class RawAzureAIClient(RawOpenAIResponsesClient[AzureAIClientOptionsT], Generic[AzureAIClientOptionsT]):
-    """Raw Azure AI client without middleware, telemetry, or function invocation layers.
+@deprecated(
+    "RawAzureAIClient is deprecated. "
+    "Use RawFoundryAgentChatClient for low-level Foundry agent client customization, "
+    "or FoundryAgent for the recommended production API."
+)
+class RawAzureAIClient(RawOpenAIChatClient[AzureAIClientOptionsT], Generic[AzureAIClientOptionsT]):
+    """Deprecated raw Azure AI client without middleware, telemetry, or function invocation layers.
 
     Warning:
         **This class should not normally be used directly.** It does not include middleware,
@@ -101,7 +107,8 @@ class RawAzureAIClient(RawOpenAIResponsesClient[AzureAIClientOptionsT], Generic[
         2. **ChatMiddlewareLayer** - Applies chat middleware per model call and stays outside telemetry
         3. **ChatTelemetryLayer** - Must stay inside chat middleware for correct per-call telemetry
 
-        Use ``AzureAIClient`` instead for a fully-featured client with all layers applied.
+        Use ``RawFoundryAgentChatClient`` for low-level Foundry agent customization, or
+        ``FoundryAgent`` for the recommended production API.
     """
 
     OTEL_PROVIDER_NAME: ClassVar[str] = "azure.ai"  # type: ignore[reportIncompatibleVariableOverride, misc]
@@ -215,8 +222,10 @@ class RawAzureAIClient(RawOpenAIResponsesClient[AzureAIClientOptionsT], Generic[
             project_client = AIProjectClient(**project_client_kwargs)
             should_close_client = True
 
-        # Initialize parent
-        super().__init__(
+        # Initialize parent with OpenAI client from project
+        super().__init__(  # type: ignore
+            async_client=project_client.get_openai_client(),
+            model=azure_ai_settings.get("model"),  # type: ignore[arg-type]
             additional_properties=additional_properties,
         )
 
@@ -680,10 +689,6 @@ class RawAzureAIClient(RawOpenAIResponsesClient[AzureAIClientOptionsT], Generic[
 
         return result, instructions
 
-    async def _initialize_client(self) -> None:
-        """Initialize OpenAI client."""
-        self.client = self.project_client.get_openai_client()  # type: ignore
-
     def _update_agent_name_and_description(self, agent_name: str | None, description: str | None = None) -> None:
         """Update the agent name in the chat client.
 
@@ -842,7 +847,7 @@ class RawAzureAIClient(RawOpenAIResponsesClient[AzureAIClientOptionsT], Generic[
         if not stream:
 
             async def _enrich_response() -> ChatResponse:
-                response = await super(RawAzureAIClient, self)._inner_get_response(
+                response = await super(RawAzureAIClient, self)._inner_get_response(  # pyright: ignore[reportDeprecated]
                     messages=messages, options=options, stream=False, **kwargs
                 )
                 get_urls = self._extract_azure_search_urls(response.raw_representation.output)  # type: ignore[union-attr]
@@ -1182,8 +1187,8 @@ class RawAzureAIClient(RawOpenAIResponsesClient[AzureAIClientOptionsT], Generic[
         It does NOT create an agent on the Azure AI service - the actual agent
         will be created on the server during the first invocation (run).
 
-        For creating and managing persistent agents on the server, use
-        :class:`~agent_framework_azure_ai.AzureAIProjectAgentProvider` instead.
+        For working with pre-configured persistent agents on the server, use
+        :class:`~agent_framework_azure_ai.FoundryAgent` instead.
 
         Keyword Args:
             id: The unique identifier for the agent. Will be created automatically if not provided.
@@ -1213,21 +1218,23 @@ class RawAzureAIClient(RawOpenAIResponsesClient[AzureAIClientOptionsT], Generic[
         )
 
 
+@deprecated("AzureAIClient is deprecated. Use FoundryAgent instead.")
 class AzureAIClient(
     FunctionInvocationLayer[AzureAIClientOptionsT],
     ChatMiddlewareLayer[AzureAIClientOptionsT],
     ChatTelemetryLayer[AzureAIClientOptionsT],
-    RawAzureAIClient[AzureAIClientOptionsT],
+    RawAzureAIClient[AzureAIClientOptionsT],  # pyright: ignore[reportDeprecated]
     Generic[AzureAIClientOptionsT],
 ):
-    """Azure AI client with middleware, telemetry, and function invocation support.
+    """Deprecated Azure AI client with middleware, telemetry, and function invocation support.
 
-    This is the recommended client for most use cases. It includes:
+    This class is deprecated. Use ``FoundryAgent`` instead for connecting to
+    pre-configured agents in Foundry. It includes:
     - Chat middleware support for request/response interception
     - OpenTelemetry-based telemetry for observability
     - Automatic function/tool invocation handling
 
-    For a minimal implementation without these features, use :class:`RawAzureAIClient`.
+    For a minimal implementation without these features, use :class:`RawFoundryAgentChatClient`.
     """
 
     def __init__(

python/packages/azure-ai/agent_framework_azure_ai/_deprecated_azure_openai.py

@@ -0,0 +1,897 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Deprecated Azure OpenAI client classes.
+
+All classes in this module are deprecated and will be removed in a future release.
+Migrate to the ``agent_framework_openai`` package equivalents with an ``AsyncAzureOpenAI`` client,
+or use ``FoundryChatClient`` for Azure AI Foundry projects.
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+import sys
+from collections.abc import Mapping, Sequence
+from copy import copy
+from typing import TYPE_CHECKING, Any, ClassVar, Final, Generic, cast
+from urllib.parse import urljoin, urlparse
+
+from agent_framework._middleware import ChatMiddlewareLayer
+from agent_framework._settings import SecretString, load_settings
+from agent_framework._telemetry import AGENT_FRAMEWORK_USER_AGENT, APP_INFO, prepend_agent_framework_to_user_agent
+from agent_framework._tools import FunctionInvocationConfiguration, FunctionInvocationLayer
+from agent_framework._types import Annotation, Content
+from agent_framework.observability import ChatTelemetryLayer, EmbeddingTelemetryLayer
+from agent_framework_openai._assistants_client import OpenAIAssistantsClient, OpenAIAssistantsOptions
+from agent_framework_openai._chat_client import OpenAIChatOptions, RawOpenAIChatClient
+from agent_framework_openai._chat_completion_client import OpenAIChatCompletionOptions, RawOpenAIChatCompletionClient
+from agent_framework_openai._embedding_client import OpenAIEmbeddingOptions, RawOpenAIEmbeddingClient
+from agent_framework_openai._shared import OpenAIBase
+from azure.ai.projects.aio import AIProjectClient
+from openai import AsyncOpenAI
+from openai.lib.azure import AsyncAzureOpenAI
+from pydantic import BaseModel
+
+from ._entra_id_authentication import AzureCredentialTypes, AzureTokenProvider, resolve_credential_to_token_provider
+
+if sys.version_info >= (3, 13):
+    from typing import TypeVar  # type: ignore # pragma: no cover
+    from warnings import deprecated  # type: ignore # pragma: no cover
+else:
+    from typing_extensions import TypeVar, deprecated  # type: ignore # pragma: no cover
+if sys.version_info >= (3, 12):
+    from typing import override  # type: ignore # pragma: no cover
+else:
+    from typing_extensions import override  # type: ignore # pragma: no cover
+if sys.version_info >= (3, 11):
+    from typing import TypedDict  # type: ignore # pragma: no cover
+else:
+    from typing_extensions import TypedDict  # type: ignore # pragma: no cover
+
+if TYPE_CHECKING:
+    from agent_framework._middleware import MiddlewareTypes
+    from openai.types.chat.chat_completion import Choice
+    from openai.types.chat.chat_completion_chunk import Choice as ChunkChoice
+
+logger: logging.Logger = logging.getLogger(__name__)
+
+
+# region Constants and Settings
+
+DEFAULT_AZURE_API_VERSION: Final[str] = "2024-10-21"
+DEFAULT_AZURE_TOKEN_ENDPOINT: Final[str] = "https://cognitiveservices.azure.com/.default"  # noqa: S105
+
+
+class AzureOpenAISettings(TypedDict, total=False):
+    """AzureOpenAI model settings.
+
+    Settings are resolved in this order: explicit keyword arguments, values from an
+    explicitly provided .env file, then environment variables with the prefix
+    'AZURE_OPENAI_'. If settings are missing after resolution, validation will fail.
+
+    Keyword Args:
+        endpoint: The endpoint of the Azure deployment.
+        chat_deployment_name: The name of the Azure Chat deployment.
+        responses_deployment_name: The name of the Azure Responses deployment.
+        embedding_deployment_name: The name of the Azure Embedding deployment.
+        api_key: The API key for the Azure deployment.
+        api_version: The API version to use.
+        base_url: The url of the Azure deployment.
+        token_endpoint: The token endpoint to use to retrieve the authentication token.
+    """
+
+    chat_deployment_name: str | None
+    responses_deployment_name: str | None
+    embedding_deployment_name: str | None
+    endpoint: str | None
+    base_url: str | None
+    api_key: SecretString | None
+    api_version: str | None
+    token_endpoint: str | None
+
+
+def _apply_azure_defaults(
+    settings: AzureOpenAISettings,
+    default_api_version: str = DEFAULT_AZURE_API_VERSION,
+    default_token_endpoint: str = DEFAULT_AZURE_TOKEN_ENDPOINT,
+) -> None:
+    """Apply default values for api_version and token_endpoint after loading settings.
+
+    Args:
+        settings: The loaded Azure OpenAI settings dict.
+        default_api_version: The default API version to use if not set.
+        default_token_endpoint: The default token endpoint to use if not set.
+    """
+    if not settings.get("api_version"):
+        settings["api_version"] = default_api_version
+    if not settings.get("token_endpoint"):
+        settings["token_endpoint"] = default_token_endpoint
+
+
+# endregion
+
+
+# region AzureOpenAIConfigMixin
+
+
+class AzureOpenAIConfigMixin(OpenAIBase):
+    """Internal class for configuring a connection to an Azure OpenAI service."""
+
+    OTEL_PROVIDER_NAME: ClassVar[str] = "azure.ai.openai"
+
+    def __init__(
+        self,
+        deployment_name: str,
+        endpoint: str | None = None,
+        base_url: str | None = None,
+        api_version: str = DEFAULT_AZURE_API_VERSION,
+        api_key: str | None = None,
+        token_endpoint: str | None = None,
+        credential: AzureCredentialTypes | AzureTokenProvider | None = None,
+        default_headers: Mapping[str, str] | None = None,
+        client: AsyncOpenAI | None = None,
+        instruction_role: str | None = None,
+        **kwargs: Any,
+    ) -> None:
+        """Configure a connection to an Azure OpenAI service.
+
+        Args:
+            deployment_name: Name of the deployment.
+            endpoint: The specific endpoint URL for the deployment.
+            base_url: The base URL for Azure services.
+            api_version: Azure API version.
+            api_key: API key for Azure services.
+            token_endpoint: Azure AD token scope.
+            credential: Azure credential or token provider for authentication.
+            default_headers: Default headers for HTTP requests.
+            client: An existing client to use.
+            instruction_role: The role to use for 'instruction' messages.
+            kwargs: Additional keyword arguments.
+        """
+        merged_headers = dict(copy(default_headers)) if default_headers else {}
+        if APP_INFO:
+            merged_headers.update(APP_INFO)
+            merged_headers = prepend_agent_framework_to_user_agent(merged_headers)
+        if not client:
+            ad_token_provider = None
+            if not api_key and credential:
+                ad_token_provider = resolve_credential_to_token_provider(credential, token_endpoint)
+
+            if not api_key and not ad_token_provider:
+                raise ValueError("Please provide either api_key, credential, or a client.")
+
+            if not endpoint and not base_url:
+                raise ValueError("Please provide an endpoint or a base_url")
+
+            args: dict[str, Any] = {
+                "default_headers": merged_headers,
+            }
+            if api_version:
+                args["api_version"] = api_version
+            if ad_token_provider:
+                args["azure_ad_token_provider"] = ad_token_provider
+            if api_key:
+                args["api_key"] = api_key
+            if base_url:
+                args["base_url"] = str(base_url)
+            if endpoint and not base_url:
+                args["azure_endpoint"] = str(endpoint)
+            if deployment_name:
+                args["azure_deployment"] = deployment_name
+            if "websocket_base_url" in kwargs:
+                args["websocket_base_url"] = kwargs.pop("websocket_base_url")
+
+            client = AsyncAzureOpenAI(**args)
+
+        self.endpoint = str(endpoint)
+        self.base_url = str(base_url)
+        self.api_version = api_version
+        self.deployment_name = deployment_name
+        self.instruction_role = instruction_role
+        if default_headers:
+            from agent_framework._telemetry import USER_AGENT_KEY
+
+            def_headers = {k: v for k, v in default_headers.items() if k != USER_AGENT_KEY}
+        else:
+            def_headers = None
+        self.default_headers = def_headers
+
+        super().__init__(model_id=deployment_name, client=client, **kwargs)
+
+
+# endregion
+
+
+# region AzureOpenAIResponsesClient
+
+
+AzureOpenAIResponsesOptionsT = TypeVar(
+    "AzureOpenAIResponsesOptionsT",
+    bound=TypedDict,  # type: ignore[valid-type]
+    default="OpenAIChatOptions",
+    covariant=True,
+)
+
+AzureOpenAIResponsesOptions = OpenAIChatOptions
+
+
+@deprecated(
+    "AzureOpenAIResponsesClient is deprecated. "
+    "Use OpenAIChatClient with an AsyncAzureOpenAI client, or FoundryChatClient for Foundry projects."
+)
+class AzureOpenAIResponsesClient(  # type: ignore[misc]
+    FunctionInvocationLayer[AzureOpenAIResponsesOptionsT],
+    ChatMiddlewareLayer[AzureOpenAIResponsesOptionsT],
+    ChatTelemetryLayer[AzureOpenAIResponsesOptionsT],
+    RawOpenAIChatClient[AzureOpenAIResponsesOptionsT],
+    Generic[AzureOpenAIResponsesOptionsT],
+):
+    """Deprecated Azure Responses client. Use OpenAIChatClient with an AsyncAzureOpenAI client instead."""
+
+    OTEL_PROVIDER_NAME: ClassVar[str] = "azure.ai.openai"
+
+    def __init__(
+        self,
+        *,
+        api_key: str | None = None,
+        deployment_name: str | None = None,
+        endpoint: str | None = None,
+        base_url: str | None = None,
+        api_version: str | None = None,
+        token_endpoint: str | None = None,
+        credential: AzureCredentialTypes | AzureTokenProvider | None = None,
+        default_headers: Mapping[str, str] | None = None,
+        async_client: AsyncOpenAI | None = None,
+        project_client: Any | None = None,
+        project_endpoint: str | None = None,
+        allow_preview: bool | None = None,
+        env_file_path: str | None = None,
+        env_file_encoding: str | None = None,
+        instruction_role: str | None = None,
+        middleware: Sequence[MiddlewareTypes] | None = None,
+        function_invocation_configuration: FunctionInvocationConfiguration | None = None,
+        **kwargs: Any,
+    ) -> None:
+        """Initialize an Azure OpenAI Responses client.
+
+        Keyword Args:
+            api_key: The API key.
+            deployment_name: The deployment name.
+            endpoint: The deployment endpoint.
+            base_url: The deployment base URL.
+            api_version: The deployment API version.
+            token_endpoint: The token endpoint to request an Azure token.
+            credential: Azure credential or token provider for authentication.
+            default_headers: Default headers for HTTP requests.
+            async_client: An existing client to use.
+            project_client: An existing AIProjectClient to use.
+            project_endpoint: The Azure AI Foundry project endpoint URL.
+            allow_preview: Enables preview opt-in on internally-created AIProjectClient.
+            env_file_path: Path to .env file for settings.
+            env_file_encoding: Encoding for .env file.
+            instruction_role: The role to use for 'instruction' messages.
+            middleware: Optional sequence of middleware.
+            function_invocation_configuration: Optional function invocation configuration.
+            kwargs: Additional keyword arguments.
+        """
+        if (model_id := kwargs.pop("model_id", None)) and not deployment_name:
+            deployment_name = str(model_id)
+
+        if async_client is None and (project_client is not None or project_endpoint is not None):
+            async_client = self._create_client_from_project(
+                project_client=project_client,
+                project_endpoint=project_endpoint,
+                credential=credential,
+                allow_preview=allow_preview,
+            )
+
+        azure_openai_settings = load_settings(
+            AzureOpenAISettings,
+            env_prefix="AZURE_OPENAI_",
+            api_key=api_key,
+            base_url=base_url,
+            endpoint=endpoint,
+            responses_deployment_name=deployment_name,
+            api_version=api_version,
+            env_file_path=env_file_path,
+            env_file_encoding=env_file_encoding,
+            token_endpoint=token_endpoint,
+        )
+        _apply_azure_defaults(azure_openai_settings, default_api_version="preview")
+        endpoint_value = azure_openai_settings.get("endpoint")
+        if (
+            not azure_openai_settings.get("base_url")
+            and endpoint_value
+            and (hostname := urlparse(str(endpoint_value)).hostname)
+            and hostname.endswith(".openai.azure.com")
+        ):
+            azure_openai_settings["base_url"] = urljoin(str(endpoint_value), "/openai/v1/")
+
+        responses_deployment_name = azure_openai_settings.get("responses_deployment_name")
+        if not responses_deployment_name:
+            raise ValueError(
+                "Azure OpenAI deployment name is required. Set via 'deployment_name' parameter "
+                "or 'AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME' environment variable."
+            )
+
+        if not async_client:
+            # Create the Azure OpenAI client directly
+            merged_headers = dict(copy(default_headers)) if default_headers else {}
+            if APP_INFO:
+                merged_headers.update(APP_INFO)
+                merged_headers = prepend_agent_framework_to_user_agent(merged_headers)
+
+            api_key_secret = azure_openai_settings.get("api_key")
+            ad_token_provider = None
+            if not api_key_secret and credential:
+                ad_token_provider = resolve_credential_to_token_provider(
+                    credential, azure_openai_settings.get("token_endpoint")
+                )
+
+            if not api_key_secret and not ad_token_provider:
+                raise ValueError("Please provide either api_key, credential, or a client.")
+
+            client_endpoint = azure_openai_settings.get("endpoint")
+            client_base_url = azure_openai_settings.get("base_url")
+            if not client_endpoint and not client_base_url:
+                raise ValueError("Please provide an endpoint or a base_url")
+
+            client_args: dict[str, Any] = {"default_headers": merged_headers}
+            if resolved_api_version := azure_openai_settings.get("api_version"):
+                client_args["api_version"] = resolved_api_version
+            if ad_token_provider:
+                client_args["azure_ad_token_provider"] = ad_token_provider
+            if api_key_secret:
+                client_args["api_key"] = api_key_secret.get_secret_value()
+            if client_base_url:
+                client_args["base_url"] = str(client_base_url)
+            if client_endpoint and not client_base_url:
+                client_args["azure_endpoint"] = str(client_endpoint)
+            if responses_deployment_name:
+                client_args["azure_deployment"] = responses_deployment_name
+            if "websocket_base_url" in kwargs:
+                client_args["websocket_base_url"] = kwargs.pop("websocket_base_url")
+
+            async_client = AsyncAzureOpenAI(**client_args)
+
+        # Store Azure-specific attributes for serialization
+        self.endpoint = str(endpoint_value) if endpoint_value else None
+        self.api_version = azure_openai_settings.get("api_version") or ""
+        self.deployment_name = responses_deployment_name
+
+        super().__init__(
+            async_client=async_client,
+            model=responses_deployment_name,
+            api_version=azure_openai_settings.get("api_version"),
+            instruction_role=instruction_role,
+            default_headers=default_headers,
+            middleware=middleware,  # type: ignore[arg-type]
+            function_invocation_configuration=function_invocation_configuration,
+            **kwargs,
+        )
+
+    @staticmethod
+    def _create_client_from_project(
+        *,
+        project_client: AIProjectClient | None,
+        project_endpoint: str | None,
+        credential: AzureCredentialTypes | AzureTokenProvider | None,
+        allow_preview: bool | None = None,
+    ) -> AsyncOpenAI:
+        """Create an AsyncOpenAI client from an Azure AI Foundry project."""
+        if project_client is not None:
+            return project_client.get_openai_client()
+
+        if not project_endpoint:
+            raise ValueError("Azure AI project endpoint is required when project_client is not provided.")
+        if not credential:
+            raise ValueError("Azure credential is required when using project_endpoint without a project_client.")
+        project_client_kwargs: dict[str, Any] = {
+            "endpoint": project_endpoint,
+            "credential": credential,  # type: ignore[arg-type]
+            "user_agent": AGENT_FRAMEWORK_USER_AGENT,
+        }
+        if allow_preview is not None:
+            project_client_kwargs["allow_preview"] = allow_preview
+        project_client = AIProjectClient(**project_client_kwargs)
+        return project_client.get_openai_client()
+
+    @override
+    def _check_model_presence(self, options: dict[str, Any]) -> None:
+        if not options.get("model"):
+            if not self.model:
+                raise ValueError("deployment_name must be a non-empty string")
+            options["model"] = self.model
+
+
+# endregion
+
+
+# region AzureOpenAIChatClient
+
+
+ResponseModelT = TypeVar("ResponseModelT", bound=BaseModel | None, default=None)
+
+
+class AzureUserSecurityContext(TypedDict, total=False):
+    """User security context for Azure AI applications.
+
+    These fields help security operations teams investigate and mitigate security
+    incidents by providing context about the application and end user.
+    """
+
+    application_name: str
+    """Name of the application making the request."""
+
+    end_user_id: str
+    """Unique identifier for the end user (recommend hashing username/email)."""
+
+    end_user_tenant_id: str
+    """Microsoft 365 tenant ID the end user belongs to. Required for multi-tenant apps."""
+
+    source_ip: str
+    """The original client's IP address."""
+
+
+class AzureOpenAIChatOptions(OpenAIChatCompletionOptions[ResponseModelT], Generic[ResponseModelT], total=False):
+    """Azure OpenAI-specific chat options dict.
+
+    Extends OpenAIChatCompletionOptions with Azure-specific options including
+    the "On Your Data" feature and enhanced security context.
+    """
+
+    data_sources: list[dict[str, Any]]
+    """Azure "On Your Data" data sources for retrieval-augmented generation."""
+
+    user_security_context: AzureUserSecurityContext
+    """Enhanced security context for Azure Defender integration."""
+
+    n: int
+    """Number of chat completion choices to generate for each input message."""
+
+
+AzureOpenAIChatOptionsT = TypeVar(
+    "AzureOpenAIChatOptionsT",
+    bound=TypedDict,  # type: ignore[valid-type]
+    default="AzureOpenAIChatOptions",
+    covariant=True,
+)
+
+
+@deprecated("AzureOpenAIChatClient is deprecated. Use OpenAIChatCompletionClient with an AsyncAzureOpenAI client.")
+class AzureOpenAIChatClient(  # type: ignore[misc]
+    FunctionInvocationLayer[AzureOpenAIChatOptionsT],
+    ChatMiddlewareLayer[AzureOpenAIChatOptionsT],
+    ChatTelemetryLayer[AzureOpenAIChatOptionsT],
+    RawOpenAIChatCompletionClient[AzureOpenAIChatOptionsT],
+    Generic[AzureOpenAIChatOptionsT],
+):
+    """Deprecated Azure OpenAI Chat client. Use OpenAIChatCompletionClient with AsyncAzureOpenAI instead."""
+
+    OTEL_PROVIDER_NAME: ClassVar[str] = "azure.ai.openai"
+
+    def __init__(
+        self,
+        *,
+        api_key: str | None = None,
+        deployment_name: str | None = None,
+        endpoint: str | None = None,
+        base_url: str | None = None,
+        api_version: str | None = None,
+        token_endpoint: str | None = None,
+        credential: AzureCredentialTypes | AzureTokenProvider | None = None,
+        default_headers: Mapping[str, str] | None = None,
+        async_client: AsyncAzureOpenAI | None = None,
+        additional_properties: dict[str, Any] | None = None,
+        env_file_path: str | None = None,
+        env_file_encoding: str | None = None,
+        instruction_role: str | None = None,
+        middleware: Sequence[MiddlewareTypes] | None = None,
+        function_invocation_configuration: FunctionInvocationConfiguration | None = None,
+    ) -> None:
+        """Initialize an Azure OpenAI Chat completion client.
+
+        Keyword Args:
+            api_key: The API key.
+            deployment_name: The deployment name.
+            endpoint: The deployment endpoint.
+            base_url: The deployment base URL.
+            api_version: The deployment API version.
+            token_endpoint: The token endpoint to request an Azure token.
+            credential: Azure credential or token provider for authentication.
+            default_headers: Default headers for HTTP requests.
+            async_client: An existing client to use.
+            additional_properties: Additional properties stored on the client instance.
+            env_file_path: Path to .env file for settings.
+            env_file_encoding: Encoding for .env file.
+            instruction_role: The role to use for 'instruction' messages.
+            middleware: Optional sequence of middleware.
+            function_invocation_configuration: Optional function invocation configuration.
+        """
+        azure_openai_settings = load_settings(
+            AzureOpenAISettings,
+            env_prefix="AZURE_OPENAI_",
+            api_key=api_key,
+            base_url=base_url,
+            endpoint=endpoint,
+            chat_deployment_name=deployment_name,
+            api_version=api_version,
+            env_file_path=env_file_path,
+            env_file_encoding=env_file_encoding,
+            token_endpoint=token_endpoint,
+        )
+        _apply_azure_defaults(azure_openai_settings)
+
+        chat_deployment_name = azure_openai_settings.get("chat_deployment_name")
+        if not chat_deployment_name:
+            raise ValueError(
+                "Azure OpenAI deployment name is required. Set via 'deployment_name' parameter "
+                "or 'AZURE_OPENAI_CHAT_DEPLOYMENT_NAME' environment variable."
+            )
+
+        if not async_client:
+            # Create the Azure OpenAI client directly
+            merged_headers = dict(copy(default_headers)) if default_headers else {}
+            if APP_INFO:
+                merged_headers.update(APP_INFO)
+                merged_headers = prepend_agent_framework_to_user_agent(merged_headers)
+
+            api_key_secret = azure_openai_settings.get("api_key")
+            ad_token_provider = None
+            if not api_key_secret and credential:
+                ad_token_provider = resolve_credential_to_token_provider(
+                    credential, azure_openai_settings.get("token_endpoint")
+                )
+
+            if not api_key_secret and not ad_token_provider:
+                raise ValueError("Please provide either api_key, credential, or a client.")
+
+            endpoint_value = azure_openai_settings.get("endpoint")
+            base_url_value = azure_openai_settings.get("base_url")
+            if not endpoint_value and not base_url_value:
+                raise ValueError("Please provide an endpoint or a base_url")
+
+            client_args: dict[str, Any] = {"default_headers": merged_headers}
+            if resolved_api_version := azure_openai_settings.get("api_version"):
+                client_args["api_version"] = resolved_api_version
+            if ad_token_provider:
+                client_args["azure_ad_token_provider"] = ad_token_provider
+            if api_key_secret:
+                client_args["api_key"] = api_key_secret.get_secret_value()
+            if base_url_value:
+                client_args["base_url"] = str(base_url_value)
+            if endpoint_value and not base_url_value:
+                client_args["azure_endpoint"] = str(endpoint_value)
+            if chat_deployment_name:
+                client_args["azure_deployment"] = chat_deployment_name
+
+            async_client = AsyncAzureOpenAI(**client_args)
+
+        # Store Azure-specific attributes for serialization
+        self.endpoint = str(azure_openai_settings.get("endpoint") or "")
+        self.api_version = azure_openai_settings.get("api_version") or ""
+        self.deployment_name = chat_deployment_name
+
+        super().__init__(
+            async_client=async_client,
+            model=chat_deployment_name,
+            api_version=azure_openai_settings.get("api_version"),
+            instruction_role=instruction_role,
+            default_headers=default_headers,
+            additional_properties=additional_properties,
+            middleware=middleware,  # type: ignore[arg-type]
+            function_invocation_configuration=function_invocation_configuration,
+        )
+
+    @override
+    def _parse_text_from_openai(self, choice: Choice | ChunkChoice) -> Content | None:
+        """Parse the choice into a Content object with type='text'.
+
+        Overwritten from RawOpenAIChatCompletionClient to deal with Azure On Your Data function.
+        """
+        message = getattr(choice, "message", None)
+        if message is None:
+            message = getattr(choice, "delta", None)
+        if message is None:  # type: ignore
+            return None
+        if hasattr(message, "refusal") and message.refusal:
+            return Content.from_text(text=message.refusal, raw_representation=choice)
+        if not message.content:
+            return None
+        text_content = Content.from_text(text=message.content, raw_representation=choice)
+        if not message.model_extra or "context" not in message.model_extra:
+            return text_content
+
+        context_raw: object = cast(object, message.context)  # type: ignore[union-attr]
+        if isinstance(context_raw, str):
+            try:
+                context_raw = json.loads(context_raw)
+            except json.JSONDecodeError:
+                logger.warning("Context is not a valid JSON string, ignoring context.")
+                return text_content
+        if not isinstance(context_raw, dict):
+            logger.warning("Context is not a valid dictionary, ignoring context.")
+            return text_content
+        context = cast(dict[str, Any], context_raw)
+        if intent := context.get("intent"):
+            text_content.additional_properties = {"intent": intent}
+        citations = context.get("citations")
+        if isinstance(citations, list) and citations:
+            annotations: list[Annotation] = []
+            for citation_raw in cast(list[object], citations):
+                if not isinstance(citation_raw, dict):
+                    continue
+                citation = cast(dict[str, Any], citation_raw)
+                annotations.append(
+                    Annotation(
+                        type="citation",
+                        title=citation.get("title", ""),
+                        url=citation.get("url", ""),
+                        snippet=citation.get("content", ""),
+                        file_id=citation.get("filepath", ""),
+                        tool_name="Azure-on-your-Data",
+                        additional_properties={"chunk_id": citation.get("chunk_id", "")},
+                        raw_representation=citation,
+                    )
+                )
+            text_content.annotations = annotations
+        return text_content
+
+
+# endregion
+
+
+# region AzureOpenAIAssistantsClient
+
+
+AzureOpenAIAssistantsOptionsT = TypeVar(
+    "AzureOpenAIAssistantsOptionsT",
+    bound=TypedDict,  # type: ignore[valid-type]
+    default="OpenAIAssistantsOptions",
+    covariant=True,
+)
+
+AzureOpenAIAssistantsOptions = OpenAIAssistantsOptions
+
+
+@deprecated(
+    "AzureOpenAIAssistantsClient is deprecated. "
+    "Use OpenAIAssistantsClient (also deprecated) or migrate to OpenAIChatClient."
+)
+class AzureOpenAIAssistantsClient(
+    OpenAIAssistantsClient[AzureOpenAIAssistantsOptionsT], Generic[AzureOpenAIAssistantsOptionsT]
+):
+    """Deprecated Azure OpenAI Assistants client. Use OpenAIAssistantsClient or migrate to OpenAIChatClient."""
+
+    DEFAULT_AZURE_API_VERSION: ClassVar[str] = "2024-05-01-preview"
+
+    def __init__(
+        self,
+        *,
+        deployment_name: str | None = None,
+        assistant_id: str | None = None,
+        assistant_name: str | None = None,
+        assistant_description: str | None = None,
+        thread_id: str | None = None,
+        api_key: str | None = None,
+        endpoint: str | None = None,
+        base_url: str | None = None,
+        api_version: str | None = None,
+        token_endpoint: str | None = None,
+        credential: AzureCredentialTypes | AzureTokenProvider | None = None,
+        default_headers: Mapping[str, str] | None = None,
+        async_client: AsyncAzureOpenAI | None = None,
+        env_file_path: str | None = None,
+        env_file_encoding: str | None = None,
+    ) -> None:
+        """Initialize an Azure OpenAI Assistants client.
+
+        Keyword Args:
+            deployment_name: The Azure OpenAI deployment name.
+            assistant_id: The ID of an Azure OpenAI assistant to use.
+            assistant_name: The name to use when creating new assistants.
+            assistant_description: The description to use when creating new assistants.
+            thread_id: Default thread ID to use for conversations.
+            api_key: The API key to use.
+            endpoint: The deployment endpoint.
+            base_url: The deployment base URL.
+            api_version: The deployment API version.
+            token_endpoint: The token endpoint to request an Azure token.
+            credential: Azure credential or token provider for authentication.
+            default_headers: Default headers for HTTP requests.
+            async_client: An existing client to use.
+            env_file_path: Path to .env file for settings.
+            env_file_encoding: Encoding for .env file.
+        """
+        azure_openai_settings = load_settings(
+            AzureOpenAISettings,
+            env_prefix="AZURE_OPENAI_",
+            api_key=api_key,
+            base_url=base_url,
+            endpoint=endpoint,
+            chat_deployment_name=deployment_name,
+            api_version=api_version,
+            env_file_path=env_file_path,
+            env_file_encoding=env_file_encoding,
+            token_endpoint=token_endpoint,
+        )
+        _apply_azure_defaults(azure_openai_settings, default_api_version=self.DEFAULT_AZURE_API_VERSION)
+
+        chat_deployment_name = azure_openai_settings.get("chat_deployment_name")
+        if not chat_deployment_name:
+            raise ValueError(
+                "Azure OpenAI deployment name is required. Set via 'deployment_name' parameter "
+                "or 'AZURE_OPENAI_CHAT_DEPLOYMENT_NAME' environment variable."
+            )
+
+        api_key_secret = azure_openai_settings.get("api_key")
+        token_scope = azure_openai_settings.get("token_endpoint")
+
+        ad_token_provider = None
+        if not async_client and not api_key_secret and credential:
+            ad_token_provider = resolve_credential_to_token_provider(credential, token_scope)
+
+        if not async_client and not api_key_secret and not ad_token_provider:
+            raise ValueError("Please provide either api_key, credential, or a client.")
+
+        if not async_client:
+            client_params: dict[str, Any] = {
+                "default_headers": default_headers,
+            }
+            if resolved_api_version := azure_openai_settings.get("api_version"):
+                client_params["api_version"] = resolved_api_version
+
+            if api_key_secret:
+                client_params["api_key"] = api_key_secret.get_secret_value()
+            elif ad_token_provider:
+                client_params["azure_ad_token_provider"] = ad_token_provider
+
+            if resolved_base_url := azure_openai_settings.get("base_url"):
+                client_params["base_url"] = str(resolved_base_url)
+            elif resolved_endpoint := azure_openai_settings.get("endpoint"):
+                client_params["azure_endpoint"] = str(resolved_endpoint)
+
+            async_client = AsyncAzureOpenAI(**client_params)
+
+        super().__init__(
+            model_id=chat_deployment_name,
+            assistant_id=assistant_id,
+            assistant_name=assistant_name,
+            assistant_description=assistant_description,
+            thread_id=thread_id,
+            async_client=async_client,  # type: ignore[reportArgumentType]
+            default_headers=default_headers,
+        )
+
+
+# endregion
+
+
+# region AzureOpenAIEmbeddingClient
+
+
+AzureOpenAIEmbeddingOptionsT = TypeVar(
+    "AzureOpenAIEmbeddingOptionsT",
+    bound=TypedDict,  # type: ignore[valid-type]
+    default="OpenAIEmbeddingOptions",
+    covariant=True,
+)
+
+
+@deprecated("AzureOpenAIEmbeddingClient is deprecated. Use OpenAIEmbeddingClient with an AsyncAzureOpenAI client.")
+class AzureOpenAIEmbeddingClient(
+    EmbeddingTelemetryLayer[str, list[float], AzureOpenAIEmbeddingOptionsT],
+    RawOpenAIEmbeddingClient[AzureOpenAIEmbeddingOptionsT],
+    Generic[AzureOpenAIEmbeddingOptionsT],
+):
+    """Deprecated Azure OpenAI embedding client. Use OpenAIEmbeddingClient with AsyncAzureOpenAI instead."""
+
+    OTEL_PROVIDER_NAME: ClassVar[str] = "azure.ai.openai"
+
+    def __init__(
+        self,
+        *,
+        api_key: str | None = None,
+        deployment_name: str | None = None,
+        endpoint: str | None = None,
+        base_url: str | None = None,
+        api_version: str | None = None,
+        token_endpoint: str | None = None,
+        credential: AzureCredentialTypes | AzureTokenProvider | None = None,
+        default_headers: Mapping[str, str] | None = None,
+        async_client: AsyncAzureOpenAI | None = None,
+        otel_provider_name: str | None = None,
+        env_file_path: str | None = None,
+        env_file_encoding: str | None = None,
+    ) -> None:
+        """Initialize an Azure OpenAI embedding client.
+
+        Keyword Args:
+            api_key: The API key.
+            deployment_name: The deployment name.
+            endpoint: The deployment endpoint.
+            base_url: The deployment base URL.
+            api_version: The deployment API version.
+            token_endpoint: The token endpoint to request an Azure token.
+            credential: Azure credential or token provider for authentication.
+            default_headers: Default headers for HTTP requests.
+            async_client: An existing client to use.
+            otel_provider_name: Override the OpenTelemetry provider name.
+            env_file_path: Path to .env file for settings.
+            env_file_encoding: Encoding for .env file.
+        """
+        azure_openai_settings = load_settings(
+            AzureOpenAISettings,
+            env_prefix="AZURE_OPENAI_",
+            api_key=api_key,
+            base_url=base_url,
+            endpoint=endpoint,
+            embedding_deployment_name=deployment_name,
+            api_version=api_version,
+            env_file_path=env_file_path,
+            env_file_encoding=env_file_encoding,
+            token_endpoint=token_endpoint,
+        )
+        _apply_azure_defaults(azure_openai_settings)
+
+        embedding_deployment_name = azure_openai_settings.get("embedding_deployment_name")
+        if not embedding_deployment_name:
+            raise ValueError(
+                "Azure OpenAI embedding deployment name is required. Set via 'deployment_name' parameter "
+                "or 'AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME' environment variable."
+            )
+
+        if not async_client:
+            # Create the Azure OpenAI client directly
+            merged_headers = dict(copy(default_headers)) if default_headers else {}
+            if APP_INFO:
+                merged_headers.update(APP_INFO)
+                merged_headers = prepend_agent_framework_to_user_agent(merged_headers)
+
+            api_key_secret = azure_openai_settings.get("api_key")
+            ad_token_provider = None
+            if not api_key_secret and credential:
+                ad_token_provider = resolve_credential_to_token_provider(
+                    credential, azure_openai_settings.get("token_endpoint")
+                )
+
+            if not api_key_secret and not ad_token_provider:
+                raise ValueError("Please provide either api_key, credential, or a client.")
+
+            endpoint_value = azure_openai_settings.get("endpoint")
+            base_url_value = azure_openai_settings.get("base_url")
+            if not endpoint_value and not base_url_value:
+                raise ValueError("Please provide an endpoint or a base_url")
+
+            client_args: dict[str, Any] = {"default_headers": merged_headers}
+            if resolved_api_version := azure_openai_settings.get("api_version"):
+                client_args["api_version"] = resolved_api_version
+            if ad_token_provider:
+                client_args["azure_ad_token_provider"] = ad_token_provider
+            if api_key_secret:
+                client_args["api_key"] = api_key_secret.get_secret_value()
+            if base_url_value:
+                client_args["base_url"] = str(base_url_value)
+            if endpoint_value and not base_url_value:
+                client_args["azure_endpoint"] = str(endpoint_value)
+            if embedding_deployment_name:
+                client_args["azure_deployment"] = embedding_deployment_name
+
+            async_client = AsyncAzureOpenAI(**client_args)
+
+        # Store Azure-specific attributes for serialization
+        self.endpoint = str(azure_openai_settings.get("endpoint") or "")
+        self.api_version = azure_openai_settings.get("api_version") or ""
+        self.deployment_name = embedding_deployment_name
+
+        super().__init__(
+            async_client=async_client,
+            model=embedding_deployment_name,
+            default_headers=default_headers,
+        )
+        if otel_provider_name is not None:
+            self.OTEL_PROVIDER_NAME = otel_provider_name  # type: ignore[misc]
+
+
+# endregion

python/packages/azure-ai/agent_framework_azure_ai/_entra_id_authentication.py

@@ -6,11 +6,10 @@ import logging
 from collections.abc import Awaitable, Callable
 from typing import Union
 
+from agent_framework.exceptions import ChatClientInvalidAuthException
 from azure.core.credentials import TokenCredential
 from azure.core.credentials_async import AsyncTokenCredential
 
-from ..exceptions import ChatClientInvalidAuthException
-
 logger: logging.Logger = logging.getLogger(__name__)
 
 AzureTokenProvider = Callable[[], Union[str, Awaitable[str]]]

python/packages/azure-ai/agent_framework_azure_ai/_project_provider.py

@@ -18,7 +18,6 @@ from agent_framework import (
 from agent_framework._mcp import MCPTool
 from agent_framework._settings import load_settings
 from agent_framework._tools import ToolTypes
-from agent_framework.azure._entra_id_authentication import AzureCredentialTypes
 from azure.ai.projects.aio import AIProjectClient
 from azure.ai.projects.models import (
     AgentVersionDetails,
@@ -29,13 +28,15 @@ from azure.ai.projects.models import (
     FunctionTool as AzureFunctionTool,
 )
 
-from ._client import AzureAIClient, AzureAIProjectAgentOptions
+from ._client import AzureAIClient, AzureAIProjectAgentOptions  # pyright: ignore[reportDeprecated]
+from ._entra_id_authentication import AzureCredentialTypes
 from ._shared import AzureAISettings, create_text_format_config, from_azure_ai_tools, to_azure_ai_tools
 
 if sys.version_info >= (3, 13):
     from typing import TypeVar  # type: ignore # pragma: no cover
+    from warnings import deprecated  # type: ignore # pragma: no cover
 else:
-    from typing_extensions import TypeVar  # type: ignore # pragma: no cover
+    from typing_extensions import TypeVar, deprecated  # type: ignore # pragma: no cover
 if sys.version_info >= (3, 11):
     from typing import Self, TypedDict  # type: ignore # pragma: no cover
 else:
@@ -55,11 +56,12 @@ OptionsCoT = TypeVar(
 )
 
 
+@deprecated("AzureAIProjectAgentProvider is deprecated. Use FoundryAgent instead.")
 class AzureAIProjectAgentProvider(Generic[OptionsCoT]):
-    """Provider for Azure AI Agent Service (Responses API).
+    """Deprecated provider for Azure AI Agent Service (Responses API).
 
-    This provider allows you to create, retrieve, and manage Azure AI agents
-    using the AIProjectClient from the Azure AI Projects SDK.
+    This provider is deprecated. Use ``FoundryAgent`` instead to connect to
+    pre-configured agents in Foundry.
 
     Examples:
         Using with explicit AIProjectClient:
@@ -200,7 +202,7 @@ class AzureAIProjectAgentProvider(Generic[OptionsCoT]):
             )
 
         # Extract options from default_options if present
-        opts = dict(default_options) if default_options else {}
+        opts: dict[str, Any] = dict(default_options) if default_options else {}
         response_format = opts.get("response_format")
         rai_config = opts.get("rai_config")
         reasoning = opts.get("reasoning")
@@ -384,7 +386,7 @@ class AzureAIProjectAgentProvider(Generic[OptionsCoT]):
         if not isinstance(details.definition, PromptAgentDefinition):
             raise ValueError("Agent definition must be PromptAgentDefinition to get a Agent.")
 
-        client = AzureAIClient(
+        client = AzureAIClient(  # pyright: ignore[reportDeprecated]
             project_client=self._project_client,
             agent_name=details.name,
             agent_version=details.version,

python/packages/azure-ai/pyproject.toml

@@ -24,6 +24,7 @@ classifiers = [
 ]
 dependencies = [
     "agent-framework-core>=1.0.0rc5",
+    "agent-framework-openai>=1.0.0rc5",
     "azure-ai-agents>=1.2.0b5,<1.2.0b6",
     "azure-ai-inference>=1.0.0b9,<1.0.0b10",
     "aiohttp>=3.7.0,<4",

python/packages/azure-ai/tests/azure_openai/conftest.py

@@ -1,9 +1,8 @@
 # Copyright (c) Microsoft. All rights reserved.
 from typing import Any
 
-from pytest import fixture
-
 from agent_framework import Message
+from pytest import fixture
 
 
 # region: Connector Settings fixtures

python/packages/azure-ai/tests/azure_openai/test_azure_assistants_client.py

@@ -1,31 +1,16 @@
 # Copyright (c) Microsoft. All rights reserved.
 
-import os
 from typing import Annotated
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
-from azure.identity import AzureCliCredential
-from pydantic import Field
-
 from agent_framework import (
-    Agent,
-    AgentResponse,
-    AgentResponseUpdate,
-    AgentSession,
-    ChatResponse,
-    ChatResponseUpdate,
-    Message,
     SupportsChatGetResponse,
     tool,
 )
 from agent_framework._settings import SecretString
 from agent_framework.azure import AzureOpenAIAssistantsClient
-
-skip_if_azure_integration_tests_disabled = pytest.mark.skipif(
-    os.getenv("AZURE_OPENAI_ENDPOINT", "") in ("", "https://test-endpoint.com"),
-    reason="No real AZURE_OPENAI_ENDPOINT provided; skipping integration tests.",
-)
+from pydantic import Field
 
 
 def create_test_azure_assistants_client(
@@ -87,7 +72,7 @@ def test_azure_assistants_client_init_with_client(mock_async_azure_openai: Magic
     )
 
     assert client.client is mock_async_azure_openai
-    assert client.model_id == "test_chat_deployment"
+    assert client.model == "test_chat_deployment"
     assert client.assistant_id == "existing-assistant-id"
     assert client.thread_id == "test-thread-id"
     assert not client._should_delete_assistant  # type: ignore
@@ -108,7 +93,7 @@ def test_azure_assistants_client_init_auto_create_client(
     )
 
     assert client.client is mock_async_azure_openai
-    assert client.model_id == azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"]
+    assert client.model == azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"]
     assert client.assistant_id is None
     assert client.assistant_name == "TestAssistant"
     assert not client._should_delete_assistant  # type: ignore
@@ -139,7 +124,7 @@ def test_azure_assistants_client_init_with_default_headers(azure_openai_unit_tes
         default_headers=default_headers,
     )
 
-    assert client.model_id == "test_chat_deployment"
+    assert client.model == "test_chat_deployment"
     assert isinstance(client, SupportsChatGetResponse)
 
     # Assert that the default header we added is present in the client's default headers
@@ -235,7 +220,7 @@ def test_azure_assistants_client_serialize(azure_openai_unit_test_env: dict[str,
 
     dumped_settings = client.to_dict()
 
-    assert dumped_settings["model_id"] == "test_chat_deployment"
+    assert dumped_settings["model"] == "test_chat_deployment"
     assert dumped_settings["assistant_id"] == "test-assistant-id"
     assert dumped_settings["assistant_name"] == "TestAssistant"
     assert dumped_settings["thread_id"] == "test-thread-id"
@@ -256,319 +241,18 @@ def get_weather(
     return f"The weather in {location} is sunny with a high of 25°C."
 
 
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_integration_tests_disabled
-async def test_azure_assistants_client_get_response() -> None:
-    """Test Azure Assistants Client response."""
-    async with AzureOpenAIAssistantsClient(credential=AzureCliCredential()) as azure_assistants_client:
-        assert isinstance(azure_assistants_client, SupportsChatGetResponse)
-
-        messages: list[Message] = []
-        messages.append(
-            Message(
-                role="user",
-                text="The weather in Seattle is currently sunny with a high of 25°C. "
-                "It's a beautiful day for outdoor activities.",
-            )
-        )
-        messages.append(Message(role="user", text="What's the weather like today?"))
-
-        # Test that the client can be used to get a response
-        response = await azure_assistants_client.get_response(messages=messages)
-
-        assert response is not None
-        assert isinstance(response, ChatResponse)
-        assert any(word in response.text.lower() for word in ["sunny", "25", "weather", "seattle"])
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_integration_tests_disabled
-async def test_azure_assistants_client_get_response_tools() -> None:
-    """Test Azure Assistants Client response with tools."""
-    async with AzureOpenAIAssistantsClient(credential=AzureCliCredential()) as azure_assistants_client:
-        assert isinstance(azure_assistants_client, SupportsChatGetResponse)
-
-        messages: list[Message] = []
-        messages.append(Message(role="user", text="What's the weather like in Seattle?"))
-
-        # Test that the client can be used to get a response
-        response = await azure_assistants_client.get_response(
-            messages=messages,
-            options={"tools": [get_weather], "tool_choice": "auto"},
-        )
-
-        assert response is not None
-        assert isinstance(response, ChatResponse)
-        assert any(word in response.text.lower() for word in ["sunny", "25", "weather"])
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_integration_tests_disabled
-async def test_azure_assistants_client_streaming() -> None:
-    """Test Azure Assistants Client streaming response."""
-    async with AzureOpenAIAssistantsClient(credential=AzureCliCredential()) as azure_assistants_client:
-        assert isinstance(azure_assistants_client, SupportsChatGetResponse)
-
-        messages: list[Message] = []
-        messages.append(
-            Message(
-                role="user",
-                text="The weather in Seattle is currently sunny with a high of 25°C. "
-                "It's a beautiful day for outdoor activities.",
-            )
-        )
-        messages.append(Message(role="user", text="What's the weather like today?"))
-
-        # Test that the client can be used to get a response
-        response = azure_assistants_client.get_response(messages=messages, stream=True)
-
-        full_message: str = ""
-        async for chunk in response:
-            assert chunk is not None
-            assert isinstance(chunk, ChatResponseUpdate)
-            for content in chunk.contents:
-                if content.type == "text" and content.text:
-                    full_message += content.text
-
-        assert any(word in full_message.lower() for word in ["sunny", "25", "weather", "seattle"])
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_integration_tests_disabled
-async def test_azure_assistants_client_streaming_tools() -> None:
-    """Test Azure Assistants Client streaming response with tools."""
-    async with AzureOpenAIAssistantsClient(credential=AzureCliCredential()) as azure_assistants_client:
-        assert isinstance(azure_assistants_client, SupportsChatGetResponse)
-
-        messages: list[Message] = []
-        messages.append(Message(role="user", text="What's the weather like in Seattle?"))
-
-        # Test that the client can be used to get a response
-        response = azure_assistants_client.get_response(
-            messages=messages,
-            options={"tools": [get_weather], "tool_choice": "auto"},
-            stream=True,
-        )
-        full_message: str = ""
-        async for chunk in response:
-            assert chunk is not None
-            assert isinstance(chunk, ChatResponseUpdate)
-            for content in chunk.contents:
-                if content.type == "text" and content.text:
-                    full_message += content.text
-
-        assert any(word in full_message.lower() for word in ["sunny", "25", "weather"])
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_integration_tests_disabled
-async def test_azure_assistants_client_with_existing_assistant() -> None:
-    """Test Azure Assistants Client with existing assistant ID."""
-    # First create an assistant to use in the test
-    async with AzureOpenAIAssistantsClient(credential=AzureCliCredential()) as temp_client:
-        # Get the assistant ID by triggering assistant creation
-        messages = [Message(role="user", text="Hello")]
-        await temp_client.get_response(messages=messages)
-        assistant_id = temp_client.assistant_id
-
-        # Now test using the existing assistant
-        async with AzureOpenAIAssistantsClient(
-            assistant_id=assistant_id, credential=AzureCliCredential()
-        ) as azure_assistants_client:
-            assert isinstance(azure_assistants_client, SupportsChatGetResponse)
-            assert azure_assistants_client.assistant_id == assistant_id
-
-            messages = [Message(role="user", text="What can you do?")]
-
-            # Test that the client can be used to get a response
-            response = await azure_assistants_client.get_response(messages=messages)
-
-            assert response is not None
-            assert isinstance(response, ChatResponse)
-            assert len(response.text) > 0
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_integration_tests_disabled
-async def test_azure_assistants_agent_basic_run():
-    """Test Agent basic run functionality with AzureOpenAIAssistantsClient."""
-    async with Agent(
-        client=AzureOpenAIAssistantsClient(credential=AzureCliCredential()),
-    ) as agent:
-        # Run a simple query
-        response = await agent.run("Hello! Please respond with 'Hello World' exactly.")
-
-        # Validate response
-        assert isinstance(response, AgentResponse)
-        assert response.text is not None
-        assert len(response.text) > 0
-        assert "Hello World" in response.text
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_integration_tests_disabled
-async def test_azure_assistants_agent_basic_run_streaming():
-    """Test Agent basic streaming functionality with AzureOpenAIAssistantsClient."""
-    async with Agent(
-        client=AzureOpenAIAssistantsClient(credential=AzureCliCredential()),
-    ) as agent:
-        # Run streaming query
-        full_message: str = ""
-        async for chunk in agent.run("Please respond with exactly: 'This is a streaming response test.'", stream=True):
-            assert chunk is not None
-            assert isinstance(chunk, AgentResponseUpdate)
-            if chunk.text:
-                full_message += chunk.text
-
-        # Validate streaming response
-        assert len(full_message) > 0
-        assert "streaming response test" in full_message.lower()
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_integration_tests_disabled
-async def test_azure_assistants_agent_session_persistence():
-    """Test Agent session persistence across runs with AzureOpenAIAssistantsClient."""
-    async with Agent(
-        client=AzureOpenAIAssistantsClient(credential=AzureCliCredential()),
-        instructions="You are a helpful assistant with good memory.",
-    ) as agent:
-        # Create a new session that will be reused
-        session = agent.create_session()
-
-        # First message - establish context
-        first_response = await agent.run(
-            "Remember this number: 42. What number did I just tell you to remember?", session=session
-        )
-        assert isinstance(first_response, AgentResponse)
-        assert "42" in first_response.text
-
-        # Second message - test conversation memory
-        second_response = await agent.run(
-            "What number did I tell you to remember in my previous message?", session=session
-        )
-        assert isinstance(second_response, AgentResponse)
-        assert "42" in second_response.text
-
-        # Verify session has been populated with conversation ID
-        assert session.service_session_id is not None
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_integration_tests_disabled
-async def test_azure_assistants_agent_existing_session_id():
-    """Test Agent with existing session ID to continue conversations across agent instances."""
-    # First, create a conversation and capture the session ID
-    existing_session_id = None
-
-    async with Agent(
-        client=AzureOpenAIAssistantsClient(credential=AzureCliCredential()),
-        instructions="You are a helpful weather agent.",
-        tools=[get_weather],
-    ) as agent:
-        # Start a conversation and get the session ID
-        session = agent.create_session()
-        response1 = await agent.run("What's the weather in Paris?", session=session)
-
-        # Validate first response
-        assert isinstance(response1, AgentResponse)
-        assert response1.text is not None
-        assert any(word in response1.text.lower() for word in ["weather", "paris"])
-
-        # The session ID is set after the first response
-        existing_session_id = session.service_session_id
-        assert existing_session_id is not None
-
-    # Now continue with the same session ID in a new agent instance
-
-    async with Agent(
-        client=AzureOpenAIAssistantsClient(thread_id=existing_session_id, credential=AzureCliCredential()),
-        instructions="You are a helpful weather agent.",
-        tools=[get_weather],
-    ) as agent:
-        # Create a session with the existing ID
-        session = AgentSession(service_session_id=existing_session_id)
-
-        # Ask about the previous conversation
-        response2 = await agent.run("What was the last city I asked about?", session=session)
-
-        # Validate that the agent remembers the previous conversation
-        assert isinstance(response2, AgentResponse)
-        assert response2.text is not None
-        # Should reference Paris from the previous conversation
-        assert "paris" in response2.text.lower()
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_integration_tests_disabled
-async def test_azure_assistants_agent_code_interpreter():
-    """Test Agent with code interpreter through AzureOpenAIAssistantsClient."""
-
-    async with Agent(
-        client=AzureOpenAIAssistantsClient(credential=AzureCliCredential()),
-        instructions="You are a helpful assistant that can write and execute Python code.",
-        tools=[AzureOpenAIAssistantsClient.get_code_interpreter_tool()],
-    ) as agent:
-        # Request code execution
-        response = await agent.run("Write Python code to calculate the factorial of 5 and show the result.")
-
-        # Validate response
-        assert isinstance(response, AgentResponse)
-        assert response.text is not None
-        # Factorial of 5 is 120
-        assert "120" in response.text or "factorial" in response.text.lower()
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_integration_tests_disabled
-async def test_azure_assistants_client_agent_level_tool_persistence():
-    """Test that agent-level tools persist across multiple runs with Azure Assistants Client."""
-
-    async with Agent(
-        client=AzureOpenAIAssistantsClient(credential=AzureCliCredential()),
-        instructions="You are a helpful assistant that uses available tools.",
-        tools=[get_weather],  # Agent-level tool
-    ) as agent:
-        # First run - agent-level tool should be available
-        first_response = await agent.run("What's the weather like in Chicago?")
-
-        assert isinstance(first_response, AgentResponse)
-        assert first_response.text is not None
-        # Should use the agent-level weather tool
-        assert any(term in first_response.text.lower() for term in ["chicago", "sunny", "72"])
-
-        # Second run - agent-level tool should still be available (persistence test)
-        second_response = await agent.run("What's the weather in Miami?")
-
-        assert isinstance(second_response, AgentResponse)
-        assert second_response.text is not None
-        # Should use the agent-level weather tool again
-        assert any(term in second_response.text.lower() for term in ["miami", "sunny", "72"])
-
-
 def test_azure_assistants_client_entra_id_authentication() -> None:
     """Test credential authentication path with sync credential."""
     mock_credential = MagicMock()
     mock_provider = MagicMock(return_value="token-string")
 
     with (
-        patch("agent_framework.azure._assistants_client.load_settings") as mock_load_settings,
+        patch("agent_framework_azure_ai._deprecated_azure_openai.load_settings") as mock_load_settings,
         patch(
-            "agent_framework.azure._assistants_client.resolve_credential_to_token_provider",
+            "agent_framework_azure_ai._deprecated_azure_openai.resolve_credential_to_token_provider",
             return_value=mock_provider,
         ) as mock_resolve,
-        patch("agent_framework.azure._assistants_client.AsyncAzureOpenAI") as mock_azure_client,
+        patch("agent_framework_azure_ai._deprecated_azure_openai.AsyncAzureOpenAI") as mock_azure_client,
         patch("agent_framework.openai.OpenAIAssistantsClient.__init__", return_value=None),
     ):
         mock_load_settings.return_value = {
@@ -602,7 +286,7 @@ def test_azure_assistants_client_entra_id_authentication() -> None:
 
 def test_azure_assistants_client_no_authentication_error() -> None:
     """Test authentication validation error when no auth provided."""
-    with patch("agent_framework.azure._assistants_client.load_settings") as mock_load_settings:
+    with patch("agent_framework_azure_ai._deprecated_azure_openai.load_settings") as mock_load_settings:
         mock_load_settings.return_value = {
             "chat_deployment_name": "test-deployment",
             "responses_deployment_name": None,
@@ -627,12 +311,12 @@ def test_azure_assistants_client_callable_credential() -> None:
     mock_provider = MagicMock(return_value="my-token")
 
     with (
-        patch("agent_framework.azure._assistants_client.load_settings") as mock_load_settings,
+        patch("agent_framework_azure_ai._deprecated_azure_openai.load_settings") as mock_load_settings,
         patch(
-            "agent_framework.azure._assistants_client.resolve_credential_to_token_provider",
+            "agent_framework_azure_ai._deprecated_azure_openai.resolve_credential_to_token_provider",
             return_value=mock_provider,
         ),
-        patch("agent_framework.azure._assistants_client.AsyncAzureOpenAI") as mock_azure_client,
+        patch("agent_framework_azure_ai._deprecated_azure_openai.AsyncAzureOpenAI") as mock_azure_client,
         patch("agent_framework.openai.OpenAIAssistantsClient.__init__", return_value=None),
     ):
         mock_load_settings.return_value = {
@@ -664,8 +348,8 @@ def test_azure_assistants_client_callable_credential() -> None:
 def test_azure_assistants_client_base_url_configuration() -> None:
     """Test base_url client parameter path."""
     with (
-        patch("agent_framework.azure._assistants_client.load_settings") as mock_load_settings,
-        patch("agent_framework.azure._assistants_client.AsyncAzureOpenAI") as mock_azure_client,
+        patch("agent_framework_azure_ai._deprecated_azure_openai.load_settings") as mock_load_settings,
+        patch("agent_framework_azure_ai._deprecated_azure_openai.AsyncAzureOpenAI") as mock_azure_client,
         patch("agent_framework.openai.OpenAIAssistantsClient.__init__", return_value=None),
     ):
         mock_load_settings.return_value = {
@@ -695,8 +379,8 @@ def test_azure_assistants_client_base_url_configuration() -> None:
 def test_azure_assistants_client_azure_endpoint_configuration() -> None:
     """Test azure_endpoint client parameter path."""
     with (
-        patch("agent_framework.azure._assistants_client.load_settings") as mock_load_settings,
-        patch("agent_framework.azure._assistants_client.AsyncAzureOpenAI") as mock_azure_client,
+        patch("agent_framework_azure_ai._deprecated_azure_openai.load_settings") as mock_load_settings,
+        patch("agent_framework_azure_ai._deprecated_azure_openai.AsyncAzureOpenAI") as mock_azure_client,
         patch("agent_framework.openai.OpenAIAssistantsClient.__init__", return_value=None),
     ):
         mock_load_settings.return_value = {

python/packages/azure-ai/tests/azure_openai/test_azure_chat_client.py

@@ -6,16 +6,6 @@ from unittest.mock import AsyncMock, MagicMock, patch
 
 import openai
 import pytest
-from azure.identity import AzureCliCredential
-from httpx import Request, Response
-from openai import AsyncAzureOpenAI, AsyncStream
-from openai.resources.chat.completions import AsyncCompletions as AsyncChatCompletions
-from openai.types.chat import ChatCompletion, ChatCompletionChunk
-from openai.types.chat.chat_completion import Choice
-from openai.types.chat.chat_completion_chunk import Choice as ChunkChoice
-from openai.types.chat.chat_completion_chunk import ChoiceDelta as ChunkChoiceDelta
-from openai.types.chat.chat_completion_message import ChatCompletionMessage
-
 from agent_framework import (
     Agent,
     AgentResponse,
@@ -29,10 +19,19 @@ from agent_framework import (
 from agent_framework._telemetry import USER_AGENT_KEY
 from agent_framework.azure import AzureOpenAIChatClient
 from agent_framework.exceptions import ChatClientException
-from agent_framework.openai import (
+from agent_framework_openai import (
     ContentFilterResultSeverity,
     OpenAIContentFilterException,
 )
+from azure.identity import AzureCliCredential
+from httpx import Request, Response
+from openai import AsyncAzureOpenAI, AsyncStream
+from openai.resources.chat.completions import AsyncCompletions as AsyncChatCompletions
+from openai.types.chat import ChatCompletion, ChatCompletionChunk
+from openai.types.chat.chat_completion import Choice
+from openai.types.chat.chat_completion_chunk import Choice as ChunkChoice
+from openai.types.chat.chat_completion_chunk import ChoiceDelta as ChunkChoiceDelta
+from openai.types.chat.chat_completion_message import ChatCompletionMessage
 
 # region Service Setup
 
@@ -48,7 +47,7 @@ def test_init(azure_openai_unit_test_env: dict[str, str]) -> None:
 
     assert azure_chat_client.client is not None
     assert isinstance(azure_chat_client.client, AsyncAzureOpenAI)
-    assert azure_chat_client.model_id == azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"]
+    assert azure_chat_client.model == azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"]
     assert isinstance(azure_chat_client, SupportsChatGetResponse)
 
 
@@ -71,7 +70,7 @@ def test_init_base_url(azure_openai_unit_test_env: dict[str, str]) -> None:
 
     assert azure_chat_client.client is not None
     assert isinstance(azure_chat_client.client, AsyncAzureOpenAI)
-    assert azure_chat_client.model_id == azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"]
+    assert azure_chat_client.model == azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"]
     assert isinstance(azure_chat_client, SupportsChatGetResponse)
     for key, value in default_headers.items():
         assert key in azure_chat_client.client.default_headers
@@ -84,7 +83,7 @@ def test_init_endpoint(azure_openai_unit_test_env: dict[str, str]) -> None:
 
     assert azure_chat_client.client is not None
     assert isinstance(azure_chat_client.client, AsyncAzureOpenAI)
-    assert azure_chat_client.model_id == azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"]
+    assert azure_chat_client.model == azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"]
     assert isinstance(azure_chat_client, SupportsChatGetResponse)
 
 
@@ -131,7 +130,7 @@ def test_serialize(azure_openai_unit_test_env: dict[str, str]) -> None:
 
     azure_chat_client = AzureOpenAIChatClient.from_dict(settings)
     dumped_settings = azure_chat_client.to_dict()
-    assert dumped_settings["model_id"] == settings["deployment_name"]
+    assert dumped_settings["model"] == settings["deployment_name"]
     assert str(settings["endpoint"]) in str(dumped_settings["endpoint"])
     assert str(settings["deployment_name"]) == str(dumped_settings["deployment_name"])
     assert settings["api_version"] == dumped_settings["api_version"]

python/packages/azure-ai/tests/azure_openai/test_azure_embedding_client.py

@@ -6,13 +6,12 @@ import os
 from unittest.mock import AsyncMock, MagicMock
 
 import pytest
+from agent_framework.azure import AzureOpenAIEmbeddingClient
+from agent_framework_openai import OpenAIEmbeddingOptions
 from openai.types import CreateEmbeddingResponse
 from openai.types import Embedding as OpenAIEmbedding
 from openai.types.create_embedding_response import Usage
 
-from agent_framework.azure import AzureOpenAIEmbeddingClient
-from agent_framework.openai import OpenAIEmbeddingOptions
-
 
 def _make_openai_response(
     embeddings: list[list[float]],
@@ -49,7 +48,7 @@ def test_azure_construction_with_deployment_name(azure_embedding_unit_test_env:
         api_key="test-key",
         endpoint="https://test.openai.azure.com/",
     )
-    assert client.model_id == "text-embedding-3-small"
+    assert client.model == "text-embedding-3-small"
 
 
 def test_azure_construction_with_existing_client(azure_embedding_unit_test_env: None) -> None:
@@ -58,7 +57,7 @@ def test_azure_construction_with_existing_client(azure_embedding_unit_test_env:
         deployment_name="my-deployment",
         async_client=mock_client,
     )
-    assert client.model_id == "my-deployment"
+    assert client.model == "my-deployment"
     assert client.client is mock_client
 
 

python/packages/azure-ai/tests/azure_openai/test_azure_responses_client.py

@@ -8,10 +8,6 @@ from typing import Annotated, Any
 from unittest.mock import MagicMock
 
 import pytest
-from azure.identity import AzureCliCredential
-from pydantic import BaseModel
-from pytest import param
-
 from agent_framework import (
     Agent,
     AgentResponse,
@@ -22,6 +18,9 @@ from agent_framework import (
     tool,
 )
 from agent_framework.azure import AzureOpenAIResponsesClient
+from azure.identity import AzureCliCredential
+from pydantic import BaseModel
+from pytest import param
 
 skip_if_azure_integration_tests_disabled = pytest.mark.skipif(
     os.getenv("AZURE_OPENAI_ENDPOINT", "") in ("", "https://test-endpoint.com"),
@@ -75,7 +74,7 @@ def test_init(azure_openai_unit_test_env: dict[str, str]) -> None:
     # Test successful initialization
     azure_responses_client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
 
-    assert azure_responses_client.model_id == azure_openai_unit_test_env["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"]
+    assert azure_responses_client.model == azure_openai_unit_test_env["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"]
     assert isinstance(azure_responses_client, SupportsChatGetResponse)
 
 
@@ -90,7 +89,7 @@ def test_init_model_id_constructor(azure_openai_unit_test_env: dict[str, str]) -
     model_id = "test_model_id"
     azure_responses_client = AzureOpenAIResponsesClient(deployment_name=model_id)
 
-    assert azure_responses_client.model_id == model_id
+    assert azure_responses_client.model == model_id
     assert isinstance(azure_responses_client, SupportsChatGetResponse)
 
 
@@ -98,7 +97,7 @@ def test_init_model_id_kwarg(azure_openai_unit_test_env: dict[str, str]) -> None
     """Test that model_id kwarg correctly sets the deployment name (issue #4299)."""
     azure_responses_client = AzureOpenAIResponsesClient(model_id="gpt-4o")
 
-    assert azure_responses_client.model_id == "gpt-4o"
+    assert azure_responses_client.model == "gpt-4o"
     assert isinstance(azure_responses_client, SupportsChatGetResponse)
 
 
@@ -108,7 +107,7 @@ def test_init_model_id_kwarg_does_not_override_deployment_name(
     """Test that deployment_name takes precedence over model_id kwarg (issue #4299)."""
     azure_responses_client = AzureOpenAIResponsesClient(deployment_name="my-deployment", model_id="gpt-4o")
 
-    assert azure_responses_client.model_id == "my-deployment"
+    assert azure_responses_client.model == "my-deployment"
     assert isinstance(azure_responses_client, SupportsChatGetResponse)
 
 
@@ -116,7 +115,7 @@ def test_init_model_id_kwarg_none(azure_openai_unit_test_env: dict[str, str]) ->
     """Test that model_id=None does not override the env-var deployment name."""
     azure_responses_client = AzureOpenAIResponsesClient(model_id=None)
 
-    assert azure_responses_client.model_id == azure_openai_unit_test_env["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"]
+    assert azure_responses_client.model == azure_openai_unit_test_env["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"]
 
 
 def test_init_with_default_header(azure_openai_unit_test_env: dict[str, str]) -> None:
@@ -127,7 +126,7 @@ def test_init_with_default_header(azure_openai_unit_test_env: dict[str, str]) ->
         default_headers=default_headers,
     )
 
-    assert azure_responses_client.model_id == azure_openai_unit_test_env["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"]
+    assert azure_responses_client.model == azure_openai_unit_test_env["AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME"]
     assert isinstance(azure_responses_client, SupportsChatGetResponse)
 
     # Assert that the default header we added is present in the client's default headers
@@ -156,7 +155,7 @@ def test_init_with_project_client(azure_openai_unit_test_env: dict[str, str]) ->
     mock_project_client.get_openai_client.return_value = mock_openai_client
 
     with patch(
-        "agent_framework.azure._responses_client.AzureOpenAIResponsesClient._create_client_from_project",
+        "agent_framework_azure_ai._deprecated_azure_openai.AzureOpenAIResponsesClient._create_client_from_project",
         return_value=mock_openai_client,
     ):
         azure_responses_client = AzureOpenAIResponsesClient(
@@ -164,7 +163,7 @@ def test_init_with_project_client(azure_openai_unit_test_env: dict[str, str]) ->
             deployment_name="gpt-4o",
         )
 
-    assert azure_responses_client.model_id == "gpt-4o"
+    assert azure_responses_client.model == "gpt-4o"
     assert azure_responses_client.client is mock_openai_client
     assert isinstance(azure_responses_client, SupportsChatGetResponse)
 
@@ -179,7 +178,7 @@ def test_init_with_project_endpoint(azure_openai_unit_test_env: dict[str, str])
     mock_openai_client.default_headers = {}
 
     with patch(
-        "agent_framework.azure._responses_client.AzureOpenAIResponsesClient._create_client_from_project",
+        "agent_framework_azure_ai._deprecated_azure_openai.AzureOpenAIResponsesClient._create_client_from_project",
         return_value=mock_openai_client,
     ):
         azure_responses_client = AzureOpenAIResponsesClient(
@@ -188,7 +187,7 @@ def test_init_with_project_endpoint(azure_openai_unit_test_env: dict[str, str])
             credential=AzureCliCredential(),
         )
 
-    assert azure_responses_client.model_id == "gpt-4o"
+    assert azure_responses_client.model == "gpt-4o"
     assert azure_responses_client.client is mock_openai_client
     assert isinstance(azure_responses_client, SupportsChatGetResponse)
 
@@ -220,7 +219,7 @@ def test_create_client_from_project_with_endpoint() -> None:
     mock_openai_client = MagicMock(spec=AsyncOpenAI)
     mock_credential = MagicMock()
 
-    with patch("agent_framework.azure._responses_client.AIProjectClient") as MockAIProjectClient:
+    with patch("agent_framework_azure_ai._deprecated_azure_openai.AIProjectClient") as MockAIProjectClient:
         mock_instance = MockAIProjectClient.return_value
         mock_instance.get_openai_client.return_value = mock_openai_client
 
@@ -668,8 +667,8 @@ async def test_azure_openai_responses_client_tool_rich_content_image() -> None:
 
 skip_if_azure_ai_integration_tests_disabled = pytest.mark.skipif(
     os.getenv("AZURE_AI_PROJECT_ENDPOINT", "") in ("", "https://test-project.cognitiveservices.azure.com/")
-    or os.getenv("AZURE_AI_MODEL_DEPLOYMENT_NAME", "") == "",
-    reason="No real AZURE_AI_PROJECT_ENDPOINT or AZURE_AI_MODEL_DEPLOYMENT_NAME provided; skipping integration tests.",
+    or os.getenv("AZURE_AI_MODEL", "") == "",
+    reason="No real AZURE_AI_PROJECT_ENDPOINT or AZURE_AI_MODEL provided; skipping integration tests.",
 )
 
 
@@ -695,7 +694,7 @@ async def test_integration_function_call_roundtrip_preserves_fidelity():
 
     client = AzureOpenAIResponsesClient(
         project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
-        deployment_name=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+        deployment_name=os.environ["AZURE_AI_MODEL"],
         credential=AzureCliCredential(),
     )
 

python/packages/azure-ai/tests/azure_openai/test_entra_id_authentication.py

@@ -3,13 +3,13 @@
 from unittest.mock import MagicMock, patch
 
 import pytest
+from agent_framework.exceptions import ChatClientInvalidAuthException
 from azure.core.credentials import TokenCredential
 from azure.core.credentials_async import AsyncTokenCredential
 
-from agent_framework.azure._entra_id_authentication import (
+from agent_framework_azure_ai._entra_id_authentication import (
     resolve_credential_to_token_provider,
 )
-from agent_framework.exceptions import ChatClientInvalidAuthException
 
 TOKEN_ENDPOINT = "https://cognitiveservices.azure.com/.default"
 

python/packages/azure-ai/tests/test_agent_provider.py

@@ -15,7 +15,6 @@ from azure.ai.agents.models import (
 from azure.ai.agents.models import (
     CodeInterpreterToolDefinition,
 )
-from azure.identity.aio import AzureCliCredential
 from pydantic import BaseModel
 
 from agent_framework_azure_ai import (
@@ -772,82 +771,3 @@ def test_from_azure_ai_agent_tools_unknown_dict() -> None:
 
 
 # endregion
-
-# region Integration Tests
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_integration_create_agent() -> None:
-    """Integration test: Create an agent using the provider."""
-    async with (
-        AzureCliCredential() as credential,
-        AzureAIAgentsProvider(credential=credential) as provider,
-    ):
-        agent = await provider.create_agent(
-            name="IntegrationTestAgent",
-            instructions="You are a helpful assistant for testing.",
-        )
-
-        try:
-            assert isinstance(agent, Agent)
-            assert agent.name == "IntegrationTestAgent"
-            assert agent.id is not None
-        finally:
-            # Cleanup: delete the agent
-            if agent.id:
-                await provider._agents_client.delete_agent(agent.id)  # type: ignore
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_integration_get_agent() -> None:
-    """Integration test: Get an existing agent using the provider."""
-    async with (
-        AzureCliCredential() as credential,
-        AzureAIAgentsProvider(credential=credential) as provider,
-    ):
-        # First create an agent
-        created = await provider._agents_client.create_agent(  # type: ignore
-            model=os.getenv("AZURE_AI_MODEL_DEPLOYMENT_NAME", "gpt-4o"),
-            name="GetAgentTest",
-            instructions="Test agent",
-        )
-
-        try:
-            # Then get it using the provider
-            agent = await provider.get_agent(created.id)
-
-            assert isinstance(agent, Agent)
-            assert agent.id == created.id
-        finally:
-            await provider._agents_client.delete_agent(created.id)  # type: ignore
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_integration_create_and_run() -> None:
-    """Integration test: Create an agent and run a conversation."""
-    async with (
-        AzureCliCredential() as credential,
-        AzureAIAgentsProvider(credential=credential) as provider,
-    ):
-        agent = await provider.create_agent(
-            name="RunTestAgent",
-            instructions="You are a helpful assistant. Always respond with 'Hello!' to any greeting.",
-        )
-
-        try:
-            result = await agent.run("Hi there!")
-
-            assert result is not None
-            assert len(result.messages) > 0
-        finally:
-            if agent.id:
-                await provider._agents_client.delete_agent(agent.id)  # type: ignore
-
-
-# endregion

python/packages/azure-ai/tests/test_azure_ai_agent_client.py

@@ -1,17 +1,11 @@
 # Copyright (c) Microsoft. All rights reserved.
 
 import json
-import os
-from pathlib import Path
 from typing import Annotated, Any
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 from agent_framework import (
-    Agent,
-    AgentResponse,
-    AgentResponseUpdate,
-    AgentSession,
     ChatOptions,
     ChatResponse,
     ChatResponseUpdate,
@@ -28,7 +22,6 @@ from azure.ai.agents.models import (
     AgentsNamedToolChoiceType,
     AgentsToolChoiceOptionMode,
     CodeInterpreterToolDefinition,
-    FileInfo,
     MessageDeltaChunk,
     MessageDeltaTextContent,
     MessageDeltaTextFileCitationAnnotation,
@@ -41,19 +34,12 @@ from azure.ai.agents.models import (
     SubmitToolApprovalAction,
     SubmitToolOutputsAction,
     ThreadRun,
-    VectorStore,
 )
 from azure.core.credentials_async import AsyncTokenCredential
-from azure.identity.aio import AzureCliCredential
 from pydantic import BaseModel, Field
 
 from agent_framework_azure_ai import AzureAIAgentClient, AzureAISettings
 
-skip_if_azure_ai_integration_tests_disabled = pytest.mark.skipif(
-    os.getenv("AZURE_AI_PROJECT_ENDPOINT", "") in ("", "https://test-project.cognitiveservices.azure.com/"),
-    reason="No real AZURE_AI_PROJECT_ENDPOINT provided; skipping integration tests.",
-)
-
 
 def create_test_azure_ai_chat_client(
     mock_agents_client: MagicMock,
@@ -102,6 +88,15 @@ def create_test_azure_ai_chat_client(
     return client
 
 
+def test_init_emits_updated_deprecation_warning(mock_agents_client: MagicMock) -> None:
+    """Test that construction emits the updated class deprecation warning."""
+    with pytest.deprecated_call(match="V1 Agents Service API and has no direct replacement"):
+        AzureAIAgentClient(
+            agents_client=mock_agents_client,
+            agent_id="test-agent",
+        )
+
+
 def test_azure_ai_settings_init(azure_ai_unit_test_env: dict[str, str]) -> None:
     """Test AzureAISettings initialization."""
     settings = load_settings(AzureAISettings, env_prefix="AZURE_AI_")
@@ -1527,401 +1522,6 @@ def get_weather(
     return f"The weather in {location} is sunny with a high of 25°C."
 
 
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_azure_ai_chat_client_get_response() -> None:
-    """Test Azure AI Chat Client response."""
-    async with AzureAIAgentClient(credential=AzureCliCredential()) as azure_ai_chat_client:
-        assert isinstance(azure_ai_chat_client, SupportsChatGetResponse)
-
-        messages: list[Message] = []
-        messages.append(
-            Message(
-                role="user",
-                text="The weather in Seattle is currently sunny with a high of 25°C. "
-                "It's a beautiful day for outdoor activities.",
-            )
-        )
-        messages.append(Message(role="user", text="What's the weather like today?"))
-
-        # Test that the agents_client can be used to get a response
-        response = await azure_ai_chat_client.get_response(messages=messages)
-
-        assert response is not None
-        assert isinstance(response, ChatResponse)
-        assert any(word in response.text.lower() for word in ["sunny", "25"])
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_azure_ai_chat_client_get_response_tools() -> None:
-    """Test Azure AI Chat Client response with tools."""
-    async with AzureAIAgentClient(credential=AzureCliCredential()) as azure_ai_chat_client:
-        assert isinstance(azure_ai_chat_client, SupportsChatGetResponse)
-
-        messages: list[Message] = []
-        messages.append(Message(role="user", text="What's the weather like in Seattle?"))
-
-        # Test that the agents_client can be used to get a response
-        response = await azure_ai_chat_client.get_response(
-            messages=messages,
-            options={"tools": [get_weather], "tool_choice": "auto"},
-        )
-
-        assert response is not None
-        assert isinstance(response, ChatResponse)
-        assert any(word in response.text.lower() for word in ["sunny", "25"])
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_azure_ai_chat_client_streaming() -> None:
-    """Test Azure AI Chat Client streaming response."""
-    async with AzureAIAgentClient(credential=AzureCliCredential()) as azure_ai_chat_client:
-        assert isinstance(azure_ai_chat_client, SupportsChatGetResponse)
-
-        messages: list[Message] = []
-        messages.append(
-            Message(
-                role="user",
-                text="The weather in Seattle is currently sunny with a high of 25°C. "
-                "It's a beautiful day for outdoor activities.",
-            )
-        )
-        messages.append(Message(role="user", text="What's the weather like today?"))
-
-        # Test that the agents_client can be used to get a response
-        response = azure_ai_chat_client.get_response(messages=messages, stream=True)
-
-        full_message: str = ""
-        async for chunk in response:
-            assert chunk is not None
-            assert isinstance(chunk, ChatResponseUpdate)
-            for content in chunk.contents:
-                if content.type == "text" and content.text:
-                    full_message += content.text
-
-        assert any(word in full_message.lower() for word in ["sunny", "25"])
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_azure_ai_chat_client_streaming_tools() -> None:
-    """Test Azure AI Chat Client streaming response with tools."""
-    async with AzureAIAgentClient(credential=AzureCliCredential()) as azure_ai_chat_client:
-        assert isinstance(azure_ai_chat_client, SupportsChatGetResponse)
-
-        messages: list[Message] = []
-        messages.append(Message(role="user", text="What's the weather like in Seattle?"))
-
-        # Test that the agents_client can be used to get a response
-        response = azure_ai_chat_client.get_response(
-            messages=messages,
-            stream=True,
-            options={"tools": [get_weather], "tool_choice": "auto"},
-        )
-        full_message: str = ""
-        async for chunk in response:
-            assert chunk is not None
-            assert isinstance(chunk, ChatResponseUpdate)
-            for content in chunk.contents:
-                if content.type == "text" and content.text:
-                    full_message += content.text
-
-        assert any(word in full_message.lower() for word in ["sunny", "25"])
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_azure_ai_chat_client_agent_basic_run() -> None:
-    """Test Agent basic run functionality with AzureAIAgentClient."""
-    async with Agent(
-        client=AzureAIAgentClient(credential=AzureCliCredential()),
-    ) as agent:
-        # Run a simple query
-        response = await agent.run("Hello! Please respond with 'Hello World' exactly.")
-
-        # Validate response
-        assert isinstance(response, AgentResponse)
-        assert response.text is not None
-        assert len(response.text) > 0
-        assert "Hello World" in response.text
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_azure_ai_chat_client_agent_basic_run_streaming() -> None:
-    """Test Agent basic streaming functionality with AzureAIAgentClient."""
-    async with Agent(
-        client=AzureAIAgentClient(credential=AzureCliCredential()),
-    ) as agent:
-        # Run streaming query
-        full_message: str = ""
-        async for chunk in agent.run("Please respond with exactly: 'This is a streaming response test.'", stream=True):
-            assert chunk is not None
-            assert isinstance(chunk, AgentResponseUpdate)
-            if chunk.text:
-                full_message += chunk.text
-
-        # Validate streaming response
-        assert len(full_message) > 0
-        assert "streaming response test" in full_message.lower()
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_azure_ai_chat_client_agent_thread_persistence() -> None:
-    """Test Agent session persistence across runs with AzureAIAgentClient."""
-    async with Agent(
-        client=AzureAIAgentClient(credential=AzureCliCredential()),
-        instructions="You are a helpful assistant with good memory.",
-    ) as agent:
-        # Create a new session that will be reused
-        session = agent.create_session()
-
-        # First message - establish context
-        first_response = await agent.run(
-            "Remember this number: 42. What number did I just tell you to remember?", session=session
-        )
-        assert isinstance(first_response, AgentResponse)
-        assert "42" in first_response.text
-
-        # Second message - test conversation memory
-        second_response = await agent.run(
-            "What number did I tell you to remember in my previous message?", session=session
-        )
-        assert isinstance(second_response, AgentResponse)
-        assert "42" in second_response.text
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_azure_ai_chat_client_agent_existing_thread_id() -> None:
-    """Test Agent existing thread ID functionality with AzureAIAgentClient."""
-    async with Agent(
-        client=AzureAIAgentClient(credential=AzureCliCredential()),
-        instructions="You are a helpful assistant with good memory.",
-    ) as first_agent:
-        # Start a conversation and get the session ID
-        session = first_agent.create_session()
-        first_response = await first_agent.run("My name is Alice. Remember this.", session=session)
-
-        # Validate first response
-        assert isinstance(first_response, AgentResponse)
-        assert first_response.text is not None
-
-        # The thread ID is set after the first response
-        existing_thread_id = session.service_session_id
-        assert existing_thread_id is not None
-
-    # Now continue with the same thread ID in a new agent instance
-    async with Agent(
-        client=AzureAIAgentClient(thread_id=existing_thread_id, credential=AzureCliCredential()),
-        instructions="You are a helpful assistant with good memory.",
-    ) as second_agent:
-        # Create a session with the existing ID
-        session = AgentSession(service_session_id=existing_thread_id)
-
-        # Ask about the previous conversation
-        response2 = await second_agent.run("What is my name?", session=session)
-
-        # Validate that the agent remembers the previous conversation
-        assert isinstance(response2, AgentResponse)
-        assert response2.text is not None
-        # Should reference Alice from the previous conversation
-        assert "alice" in response2.text.lower()
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_azure_ai_chat_client_agent_code_interpreter():
-    """Test Agent with code interpreter through AzureAIAgentClient."""
-
-    async with Agent(
-        client=AzureAIAgentClient(credential=AzureCliCredential()),
-        instructions="You are a helpful assistant that can write and execute Python code.",
-        tools=[AzureAIAgentClient.get_code_interpreter_tool()],
-    ) as agent:
-        # Request code execution
-        response = await agent.run("Write Python code to calculate the factorial of 5 and show the result.")
-
-        # Validate response
-        assert isinstance(response, AgentResponse)
-        assert response.text is not None
-        # Factorial of 5 is 120
-        assert "120" in response.text or "factorial" in response.text.lower()
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_azure_ai_chat_client_agent_file_search():
-    """Test Agent with file search through AzureAIAgentClient."""
-
-    client = AzureAIAgentClient(credential=AzureCliCredential())
-    file: FileInfo | None = None
-    vector_store: VectorStore | None = None
-
-    try:
-        # 1. Read and upload the test file to the Azure AI agent service
-        test_file_path = Path(__file__).parent / "resources" / "employees.pdf"
-        file = await client.agents_client.files.upload_and_poll(file_path=str(test_file_path), purpose="assistants")
-        vector_store = await client.agents_client.vector_stores.create_and_poll(
-            file_ids=[file.id], name="test_employees_vectorstore"
-        )
-
-        # 2. Create file search tool with uploaded resources
-        file_search_tool = AzureAIAgentClient.get_file_search_tool(vector_store_ids=[vector_store.id])
-
-        async with Agent(
-            client=client,
-            instructions="You are a helpful assistant that can search through uploaded employee files.",
-            tools=[file_search_tool],
-        ) as agent:
-            # 3. Test file search functionality
-            response = await agent.run("Who is the youngest employee in the files?")
-
-            # Validate response
-            assert isinstance(response, AgentResponse)
-            assert response.text is not None
-            # Should find information about Alice Johnson (age 24) being the youngest
-            assert any(term in response.text.lower() for term in ["alice", "johnson", "24"])
-
-    finally:
-        # 4. Cleanup: Delete the vector store and file
-        try:
-            if vector_store:
-                await client.agents_client.vector_stores.delete(vector_store.id)
-            if file:
-                await client.agents_client.files.delete(file.id)
-        except Exception:
-            # Ignore cleanup errors to avoid masking the actual test failure
-            pass
-        finally:
-            await client.close()
-
-
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_azure_ai_chat_client_agent_hosted_mcp_tool() -> None:
-    """Integration test for MCP tool with Azure AI Agent using Microsoft Learn MCP."""
-
-    mcp_tool = AzureAIAgentClient.get_mcp_tool(
-        name="Microsoft Learn MCP",
-        url="https://learn.microsoft.com/api/mcp",
-        description="A Microsoft Learn MCP server for documentation questions",
-        approval_mode="never_require",
-    )
-
-    async with Agent(
-        client=AzureAIAgentClient(credential=AzureCliCredential()),
-        instructions="You are a helpful assistant that can help with microsoft documentation questions.",
-        tools=[mcp_tool],
-    ) as agent:
-        response = await agent.run(
-            "How to create an Azure storage account using az cli?",
-            options={"max_tokens": 200},
-        )
-
-        assert isinstance(response, AgentResponse)
-        assert response.text is not None
-        assert len(response.text) > 0
-
-        # With never_require approval mode, there should be no approval requests
-        assert len(response.user_input_requests) == 0, (
-            f"Expected no approval requests with never_require mode, but got {len(response.user_input_requests)}"
-        )
-
-        # Should contain Azure-related content since it's asking about Azure CLI
-        assert any(term in response.text.lower() for term in ["azure", "storage", "account", "cli"])
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_azure_ai_chat_client_agent_level_tool_persistence():
-    """Test that agent-level tools persist across multiple runs with AzureAIAgentClient."""
-    async with Agent(
-        client=AzureAIAgentClient(credential=AzureCliCredential()),
-        instructions="You are a helpful assistant that uses available tools.",
-        tools=[get_weather],
-    ) as agent:
-        # First run - agent-level tool should be available
-        first_response = await agent.run("What's the weather like in Chicago?")
-
-        assert isinstance(first_response, AgentResponse)
-        assert first_response.text is not None
-        # Should use the agent-level weather tool
-        assert any(term in first_response.text.lower() for term in ["chicago", "sunny", "25"])
-
-        # Second run - agent-level tool should still be available (persistence test)
-        second_response = await agent.run("What's the weather in Miami?")
-
-        assert isinstance(second_response, AgentResponse)
-        assert second_response.text is not None
-        # Should use the agent-level weather tool again
-        assert any(term in second_response.text.lower() for term in ["miami", "sunny", "25"])
-
-
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_azure_ai_chat_client_agent_chat_options_run_level() -> None:
-    """Test ChatOptions parameter coverage at run level."""
-    async with Agent(
-        client=AzureAIAgentClient(credential=AzureCliCredential()),
-        instructions="You are a helpful assistant.",
-    ) as agent:
-        response = await agent.run(
-            "Provide a brief, helpful response.",
-            tools=[get_weather],
-            options={
-                "max_tokens": 100,
-                "temperature": 0.7,
-                "top_p": 0.9,
-                "tool_choice": "auto",
-                "metadata": {"test": "value"},
-            },
-        )
-
-        assert isinstance(response, AgentResponse)
-        assert response.text is not None
-        assert len(response.text) > 0
-
-
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_azure_ai_chat_client_agent_chat_options_agent_level() -> None:
-    """Test ChatOptions parameter coverage agent level."""
-    async with Agent(
-        client=AzureAIAgentClient(credential=AzureCliCredential()),
-        instructions="You are a helpful assistant.",
-        tools=[get_weather],
-        default_options={
-            "max_tokens": 100,
-            "temperature": 0.7,
-            "top_p": 0.9,
-            "tool_choice": "auto",
-            "metadata": {"test": "value"},
-        },
-    ) as agent:
-        response = await agent.run(
-            "Provide a brief, helpful response.",
-        )
-
-        assert isinstance(response, AgentResponse)
-        assert response.text is not None
-        assert len(response.text) > 0
-
-
 async def test_azure_ai_chat_client_cleanup_agent_when_enabled_and_created(
     mock_agents_client: MagicMock,
 ) -> None:

python/packages/azure-ai/tests/test_azure_ai_client.py

@@ -11,8 +11,6 @@ from uuid import uuid4
 
 import pytest
 from agent_framework import (
-    Agent,
-    AgentResponse,
     Annotation,
     ChatOptions,
     ChatResponse,
@@ -24,7 +22,7 @@ from agent_framework import (
     tool,
 )
 from agent_framework._settings import load_settings
-from agent_framework.openai._responses_client import RawOpenAIResponsesClient
+from agent_framework_openai._chat_client import RawOpenAIChatClient
 from azure.ai.projects.aio import AIProjectClient
 from azure.ai.projects.models import (
     ApproximateLocation,
@@ -41,17 +39,11 @@ from azure.identity.aio import AzureCliCredential
 from openai.types.responses.parsed_response import ParsedResponse
 from openai.types.responses.response import Response as OpenAIResponse
 from pydantic import BaseModel, ConfigDict, Field
-from pytest import fixture, param
+from pytest import fixture
 
 from agent_framework_azure_ai import AzureAIClient, AzureAISettings
 from agent_framework_azure_ai._shared import from_azure_ai_tools
 
-skip_if_azure_ai_integration_tests_disabled = pytest.mark.skipif(
-    os.getenv("AZURE_AI_PROJECT_ENDPOINT", "") in ("", "https://test-project.cognitiveservices.azure.com/")
-    or os.getenv("AZURE_AI_MODEL_DEPLOYMENT_NAME", "") == "",
-    reason="No real AZURE_AI_PROJECT_ENDPOINT or AZURE_AI_MODEL_DEPLOYMENT_NAME provided; skipping integration tests.",
-)
-
 
 @pytest.fixture
 def mock_project_client() -> MagicMock:
@@ -415,7 +407,7 @@ async def test_prepare_options_basic(mock_project_client: MagicMock) -> None:
 
     with (
         patch(
-            "agent_framework.openai._responses_client.RawOpenAIResponsesClient._prepare_options",
+            "agent_framework_openai._chat_client.RawOpenAIChatClient._prepare_options",
             return_value={"model": "test-model"},
         ),
         patch.object(
@@ -452,7 +444,7 @@ async def test_prepare_options_with_application_endpoint(
 
     with (
         patch(
-            "agent_framework.openai._responses_client.RawOpenAIResponsesClient._prepare_options",
+            "agent_framework_openai._chat_client.RawOpenAIChatClient._prepare_options",
             return_value={"model": "test-model"},
         ),
         patch.object(
@@ -494,7 +486,7 @@ async def test_prepare_options_with_application_project_client(
 
     with (
         patch(
-            "agent_framework.openai._responses_client.RawOpenAIResponsesClient._prepare_options",
+            "agent_framework_openai._chat_client.RawOpenAIChatClient._prepare_options",
             return_value={"model": "test-model"},
         ),
         patch.object(
@@ -512,19 +504,6 @@ async def test_prepare_options_with_application_project_client(
         assert "extra_body" not in run_options
 
 
-async def test_initialize_client(mock_project_client: MagicMock) -> None:
-    """Test _initialize_client method."""
-    client = create_test_azure_ai_client(mock_project_client)
-
-    mock_openai_client = MagicMock()
-    mock_project_client.get_openai_client = MagicMock(return_value=mock_openai_client)
-
-    await client._initialize_client()
-
-    assert client.client is mock_openai_client
-    mock_project_client.get_openai_client.assert_called_once()
-
-
 def test_update_agent_name_and_description(mock_project_client: MagicMock) -> None:
     """Test _update_agent_name_and_description method."""
     client = create_test_azure_ai_client(mock_project_client)
@@ -827,14 +806,14 @@ async def test_runtime_tools_override_logs_warning(
     messages = [Message(role="user", contents=[Content.from_text(text="Hello")])]
 
     with patch(
-        "agent_framework.openai._responses_client.RawOpenAIResponsesClient._prepare_options",
+        "agent_framework_openai._chat_client.RawOpenAIChatClient._prepare_options",
         return_value={"model": "test-model", "tools": [{"type": "function", "name": "tool_one"}]},
     ):
         await client._prepare_options(messages, {})
 
     with (
         patch(
-            "agent_framework.openai._responses_client.RawOpenAIResponsesClient._prepare_options",
+            "agent_framework_openai._chat_client.RawOpenAIChatClient._prepare_options",
             return_value={"model": "test-model", "tools": [{"type": "function", "name": "tool_two"}]},
         ),
         patch("agent_framework_azure_ai._client.logger.warning") as mock_warning,
@@ -853,7 +832,7 @@ async def test_prepare_options_logs_warning_for_tools_with_existing_agent_versio
 
     with (
         patch(
-            "agent_framework.openai._responses_client.RawOpenAIResponsesClient._prepare_options",
+            "agent_framework_openai._chat_client.RawOpenAIChatClient._prepare_options",
             return_value={"model": "test-model", "tools": [{"type": "function", "name": "tool_one"}]},
         ),
         patch("agent_framework_azure_ai._client.logger.warning") as mock_warning,
@@ -875,7 +854,7 @@ async def test_prepare_options_logs_warning_for_tools_on_application_endpoint(
 
     with (
         patch(
-            "agent_framework.openai._responses_client.RawOpenAIResponsesClient._prepare_options",
+            "agent_framework_openai._chat_client.RawOpenAIChatClient._prepare_options",
             return_value={"model": "test-model", "tools": [{"type": "function", "name": "tool_one"}]},
         ),
         patch.object(client, "_get_agent_reference_or_create", new_callable=AsyncMock) as mock_get_agent_reference,
@@ -1101,14 +1080,14 @@ async def test_runtime_structured_output_override_logs_warning(
     messages = [Message(role="user", contents=[Content.from_text(text="Hello")])]
 
     with patch(
-        "agent_framework.openai._responses_client.RawOpenAIResponsesClient._prepare_options",
+        "agent_framework_openai._chat_client.RawOpenAIChatClient._prepare_options",
         return_value={"model": "test-model"},
     ):
         await client._prepare_options(messages, {"response_format": ResponseFormatModel})
 
     with (
         patch(
-            "agent_framework.openai._responses_client.RawOpenAIResponsesClient._prepare_options",
+            "agent_framework_openai._chat_client.RawOpenAIChatClient._prepare_options",
             return_value={"model": "test-model"},
         ),
         patch("agent_framework_azure_ai._client.logger.warning") as mock_warning,
@@ -1129,7 +1108,7 @@ async def test_prepare_options_excludes_response_format(
 
     with (
         patch(
-            "agent_framework.openai._responses_client.RawOpenAIResponsesClient._prepare_options",
+            "agent_framework_openai._chat_client.RawOpenAIChatClient._prepare_options",
             return_value={
                 "model": "test-model",
                 "response_format": ResponseFormatModel,
@@ -1164,7 +1143,7 @@ async def test_prepare_options_keeps_values_for_unsupported_option_keys(
 
     with (
         patch(
-            "agent_framework.openai._responses_client.RawOpenAIResponsesClient._prepare_options",
+            "agent_framework_openai._chat_client.RawOpenAIChatClient._prepare_options",
             return_value={
                 "model": "test-model",
                 "tools": [{"type": "function", "name": "weather"}],
@@ -1365,352 +1344,6 @@ async def client() -> AsyncGenerator[AzureAIClient, None]:
             await project_client.agents.delete(agent_name=agent_name)
 
 
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-@pytest.mark.parametrize(
-    "option_name,option_value,needs_validation",
-    [
-        # Simple ChatOptions - just verify they don't fail
-        param("top_p", 0.9, False, id="top_p"),
-        param("max_tokens", 500, False, id="max_tokens"),
-        param("seed", 123, False, id="seed"),
-        param("user", "test-user-id", False, id="user"),
-        param("metadata", {"test_key": "test_value"}, False, id="metadata"),
-        param("frequency_penalty", 0.5, False, id="frequency_penalty"),
-        param("presence_penalty", 0.3, False, id="presence_penalty"),
-        param("stop", ["END"], False, id="stop"),
-        param("allow_multiple_tool_calls", True, False, id="allow_multiple_tool_calls"),
-        param("tool_choice", "none", True, id="tool_choice_none"),
-        param("tool_choice", "auto", True, id="tool_choice_auto"),
-        param("tool_choice", "required", True, id="tool_choice_required_any"),
-        param(
-            "tool_choice",
-            {"mode": "required", "required_function_name": "get_weather"},
-            True,
-            id="tool_choice_required",
-        ),
-        # OpenAIResponsesOptions - just verify they don't fail
-        param("safety_identifier", "user-hash-abc123", False, id="safety_identifier"),
-        param("truncation", "auto", False, id="truncation"),
-        param("top_logprobs", 5, False, id="top_logprobs"),
-        param("prompt_cache_key", "test-cache-key", False, id="prompt_cache_key"),
-        param("max_tool_calls", 3, False, id="max_tool_calls"),
-    ],
-)
-async def test_integration_options(
-    option_name: str,
-    option_value: Any,
-    needs_validation: bool,
-    client: AzureAIClient,
-) -> None:
-    """Parametrized test covering options that can be set at runtime for a Foundry Agent.
-
-    Tests both streaming and non-streaming modes for each option to ensure
-    they don't cause failures. Options marked with needs_validation also
-    check that the feature actually works correctly.
-
-    This test reuses a single agent.
-    """
-    # Prepare test message
-    if option_name.startswith("tool_choice"):
-        # Use weather-related prompt for tool tests
-        messages = [Message(role="user", text="What is the weather in Seattle?")]
-    else:
-        # Generic prompt for simple options
-        messages = [Message(role="user", text="Say 'Hello World' briefly.")]
-
-    # Build options dict
-    options: dict[str, Any] = {option_name: option_value, "tools": [get_weather]}
-
-    for streaming in [False, True]:
-        if streaming:
-            # Test streaming mode
-            response_stream = client.get_response(
-                messages=messages,
-                stream=True,
-                options=options,
-            )
-
-            response = await response_stream.get_final_response()
-        else:
-            # Test non-streaming mode
-            response = await client.get_response(
-                messages=messages,
-                options=options,
-            )
-
-        assert response is not None
-        assert isinstance(response, ChatResponse)
-
-        # For tool_choice="required", we return after tool execution without a model text response
-        is_required_tool_choice = option_name == "tool_choice" and (
-            option_value == "required" or (isinstance(option_value, dict) and option_value.get("mode") == "required")
-        )
-
-        if is_required_tool_choice:
-            # Response should have function call and function result, but no text from model
-            assert len(response.messages) >= 2, f"Expected function call + result for {option_name}"
-            has_function_call = any(c.type == "function_call" for msg in response.messages for c in msg.contents)
-            has_function_result = any(c.type == "function_result" for msg in response.messages for c in msg.contents)
-            assert has_function_call, f"No function call in response for {option_name}"
-            assert has_function_result, f"No function result in response for {option_name}"
-        else:
-            assert response.text is not None, f"No text in response for option '{option_name}'"
-            assert len(response.text) > 0, f"Empty response for option '{option_name}'"
-
-        # Validate based on option type
-        if needs_validation:
-            if option_name.startswith("tool_choice") and not is_required_tool_choice:
-                # Should have called the weather function
-                text = response.text.lower()
-                assert "sunny" in text or "seattle" in text, f"Tool not invoked for {option_name}"
-            elif option_name == "response_format":
-                if option_value == OutputStruct:
-                    # Should have structured output
-                    assert response.value is not None, "No structured output"
-                    assert isinstance(response.value, OutputStruct)
-                    assert "seattle" in response.value.location.lower()
-                else:
-                    # Runtime JSON schema
-                    assert response.value is None, "No structured output, can't parse any json."
-                    response_value = json.loads(response.text)
-                    assert isinstance(response_value, dict)
-                    assert "location" in response_value
-                    assert "seattle" in response_value["location"].lower()
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-@pytest.mark.parametrize(
-    "option_name,option_value,needs_validation",
-    [
-        param("temperature", 0.7, False, id="temperature"),
-        # Complex options requiring output validation
-        param("response_format", OutputStruct, True, id="response_format_pydantic"),
-        param(
-            "response_format",
-            {
-                "type": "json_schema",
-                "json_schema": {
-                    "name": "WeatherDigest",
-                    "strict": True,
-                    "schema": {
-                        "title": "WeatherDigest",
-                        "type": "object",
-                        "properties": {
-                            "location": {"type": "string"},
-                            "conditions": {"type": "string"},
-                            "temperature_c": {"type": "number"},
-                            "advisory": {"type": "string"},
-                        },
-                        "required": ["location", "conditions", "temperature_c", "advisory"],
-                        "additionalProperties": False,
-                    },
-                },
-            },
-            True,
-            id="response_format_runtime_json_schema",
-        ),
-    ],
-)
-async def test_integration_agent_options(
-    option_name: str,
-    option_value: Any,
-    needs_validation: bool,
-) -> None:
-    """Test Foundry agent level options in both streaming and non-streaming modes.
-
-    Tests both streaming and non-streaming modes for each option to ensure
-    they don't cause failures. Options marked with needs_validation also
-    check that the feature actually works correctly.
-
-    This test create a new client and uses it for both streaming and non-streaming tests.
-    """
-    async with temporary_chat_client(agent_name=f"test-agent-{option_name.replace('_', '-')}-{uuid4()}") as client:
-        for streaming in [False, True]:
-            # Prepare test message
-            if option_name.startswith("response_format"):
-                # Use prompt that works well with structured output
-                messages = [Message(role="user", text="The weather in Seattle is sunny")]
-                messages.append(Message(role="user", text="What is the weather in Seattle?"))
-            else:
-                # Generic prompt for simple options
-                messages = [Message(role="user", text="Say 'Hello World' briefly.")]
-
-            # Build options dict
-            options = {option_name: option_value}
-
-            if streaming:
-                # Test streaming mode
-                response_stream = client.get_response(
-                    messages=messages,
-                    stream=True,
-                    options=options,
-                )
-
-                response = await response_stream.get_final_response()
-            else:
-                # Test non-streaming mode
-                response = await client.get_response(
-                    messages=messages,
-                    options=options,
-                )
-
-            assert response is not None
-            assert isinstance(response, ChatResponse)
-            assert response.text is not None, f"No text in response for option '{option_name}'"
-            assert len(response.text) > 0, f"Empty response for option '{option_name}'"
-
-            # Validate based on option type
-            if needs_validation and option_name.startswith("response_format"):
-                if option_value == OutputStruct:
-                    # Should have structured output
-                    assert response.value is not None, "No structured output"
-                    assert isinstance(response.value, OutputStruct)
-                    assert "seattle" in response.value.location.lower()
-                else:
-                    # Runtime JSON schema
-                    assert response.value is None, "No structured output, can't parse any json."
-                    response_value = json.loads(response.text)
-                    assert isinstance(response_value, dict)
-                    assert "location" in response_value
-                    assert "seattle" in response_value["location"].lower()
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_integration_web_search() -> None:
-    async with temporary_chat_client(agent_name="af-int-test-web-search") as client:
-        for streaming in [False, True]:
-            content = {
-                "messages": [
-                    Message(
-                        role="user",
-                        text="Who are the main characters of Kpop Demon Hunters? Do a web search to find the answer.",
-                    )
-                ],
-                "options": {
-                    "tool_choice": "auto",
-                    "tools": [client.get_web_search_tool()],
-                },
-            }
-            if streaming:
-                response = await client.get_response(stream=True, **content).get_final_response()
-            else:
-                response = await client.get_response(**content)
-
-            assert response is not None
-            assert isinstance(response, ChatResponse)
-            assert "Rumi" in response.text
-            assert "Mira" in response.text
-            assert "Zoey" in response.text
-
-            # Test that the client will use the web search tool with location
-            content = {
-                "messages": [
-                    Message(role="user", text="What is the current weather? Do not ask for my current location.")
-                ],
-                "options": {
-                    "tool_choice": "auto",
-                    "tools": [client.get_web_search_tool(user_location={"country": "US", "city": "Seattle"})],
-                },
-            }
-            if streaming:
-                response = await client.get_response(stream=True, **content).get_final_response()
-            else:
-                response = await client.get_response(**content)
-            assert response.text is not None
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_integration_agent_hosted_mcp_tool() -> None:
-    """Integration test for MCP tool with Azure Response Agent using Microsoft Learn MCP."""
-    async with temporary_chat_client(agent_name="af-int-test-mcp") as client:
-        response = await client.get_response(
-            messages=[Message(role="user", text="How to create an Azure storage account using az cli?")],
-            options={
-                # this needs to be high enough to handle the full MCP tool response.
-                "max_tokens": 5000,
-                "tools": client.get_mcp_tool(
-                    name="Microsoft Learn MCP",
-                    url="https://learn.microsoft.com/api/mcp",
-                    description="A Microsoft Learn MCP server for documentation questions",
-                    approval_mode="never_require",
-                ),
-            },
-        )
-        assert isinstance(response, ChatResponse)
-        assert response.text
-        # Should contain Azure-related content since it's asking about Azure CLI
-        assert any(term in response.text.lower() for term in ["azure", "storage", "account", "cli"])
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_integration_agent_hosted_code_interpreter_tool():
-    """Test Azure Responses Client agent with code interpreter tool through AzureAIClient."""
-    async with temporary_chat_client(agent_name="af-int-test-code-interpreter") as client:
-        response = await client.get_response(
-            messages=[Message(role="user", text="Calculate the sum of numbers from 1 to 10 using Python code.")],
-            options={
-                "tools": [client.get_code_interpreter_tool()],
-            },
-        )
-        # Should contain calculation result (sum of 1-10 = 55) or code execution content
-        contains_relevant_content = any(
-            term in response.text.lower() for term in ["55", "sum", "code", "python", "calculate", "10"]
-        )
-        assert contains_relevant_content or len(response.text.strip()) > 10
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_integration_agent_existing_session():
-    """Test Azure Responses Client agent with existing session to continue conversations across agent instances."""
-    # First conversation - capture the session
-    preserved_session = None
-
-    async with (
-        temporary_chat_client(agent_name="af-int-test-existing-session") as client,
-        Agent(
-            client=client,
-            instructions="You are a helpful assistant with good memory.",
-        ) as first_agent,
-    ):
-        # Start a conversation and capture the session
-        session = first_agent.create_session()
-        first_response = await first_agent.run("My hobby is photography. Remember this.", session=session, store=True)
-
-        assert isinstance(first_response, AgentResponse)
-        assert first_response.text is not None
-
-        # Preserve the session for reuse
-        preserved_session = session
-
-    # Second conversation - reuse the session in a new agent instance
-    if preserved_session:
-        async with (
-            temporary_chat_client(agent_name="af-int-test-existing-session-2") as client,
-            Agent(
-                client=client,
-                instructions="You are a helpful assistant with good memory.",
-            ) as second_agent,
-        ):
-            # Reuse the preserved session
-            second_response = await second_agent.run("What is my hobby?", session=preserved_session)
-
-            assert isinstance(second_response, AgentResponse)
-            assert second_response.text is not None
-            assert "photography" in second_response.text.lower()
-
-
 # region Factory Method Tests
 
 
@@ -2031,7 +1664,7 @@ async def test_inner_get_response_enriches_non_streaming(mock_project_client: Ma
     async def _fake_awaitable() -> ChatResponse:
         return base_response
 
-    with patch.object(RawOpenAIResponsesClient, "_inner_get_response", return_value=_fake_awaitable()):
+    with patch.object(RawOpenAIChatClient, "_inner_get_response", return_value=_fake_awaitable()):
         result_awaitable = client._inner_get_response(messages=[], options={}, stream=False)
         result = await result_awaitable  # type: ignore[misc]
 
@@ -2054,7 +1687,7 @@ async def test_inner_get_response_no_search_output_non_streaming(mock_project_cl
     async def _fake_awaitable() -> ChatResponse:
         return base_response
 
-    with patch.object(RawOpenAIResponsesClient, "_inner_get_response", return_value=_fake_awaitable()):
+    with patch.object(RawOpenAIChatClient, "_inner_get_response", return_value=_fake_awaitable()):
         result_awaitable = client._inner_get_response(messages=[], options={}, stream=False)
         result = await result_awaitable  # type: ignore[misc]
 
@@ -2075,7 +1708,7 @@ def test_inner_get_response_streaming_registers_hook(mock_project_client: MagicM
 
     mock_stream = _create_mock_stream()
 
-    with patch.object(RawOpenAIResponsesClient, "_inner_get_response", return_value=mock_stream):
+    with patch.object(RawOpenAIChatClient, "_inner_get_response", return_value=mock_stream):
         result = client._inner_get_response(messages=[], options={}, stream=True)
 
     assert result is mock_stream
@@ -2088,7 +1721,7 @@ def test_streaming_hook_captures_search_urls(mock_project_client: MagicMock) ->
 
     mock_stream = _create_mock_stream()
 
-    with patch.object(RawOpenAIResponsesClient, "_inner_get_response", return_value=mock_stream):
+    with patch.object(RawOpenAIChatClient, "_inner_get_response", return_value=mock_stream):
         client._inner_get_response(messages=[], options={}, stream=True)
 
     hook = mock_stream._transform_hooks[0]
@@ -2116,7 +1749,7 @@ def test_streaming_hook_enriches_url_citation(mock_project_client: MagicMock) ->
 
     mock_stream = _create_mock_stream()
 
-    with patch.object(RawOpenAIResponsesClient, "_inner_get_response", return_value=mock_stream):
+    with patch.object(RawOpenAIChatClient, "_inner_get_response", return_value=mock_stream):
         client._inner_get_response(messages=[], options={}, stream=True)
 
     hook = mock_stream._transform_hooks[0]

python/packages/azure-ai/tests/test_provider.py

@@ -1,12 +1,10 @@
 # Copyright (c) Microsoft. All rights reserved.
 
-import os
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 from agent_framework import Agent, FunctionTool
 from agent_framework._mcp import MCPTool
-from azure.ai.projects.aio import AIProjectClient
 from azure.ai.projects.models import (
     AgentVersionDetails,
     PromptAgentDefinition,
@@ -14,16 +12,9 @@ from azure.ai.projects.models import (
 from azure.ai.projects.models import (
     FunctionTool as AzureFunctionTool,
 )
-from azure.identity.aio import AzureCliCredential
 
 from agent_framework_azure_ai import AzureAIProjectAgentProvider
 
-skip_if_azure_ai_integration_tests_disabled = pytest.mark.skipif(
-    os.getenv("AZURE_AI_PROJECT_ENDPOINT", "") in ("", "https://test-project.cognitiveservices.azure.com/")
-    or os.getenv("AZURE_AI_MODEL_DEPLOYMENT_NAME", "") == "",
-    reason="No real AZURE_AI_PROJECT_ENDPOINT or AZURE_AI_MODEL_DEPLOYMENT_NAME provided; skipping integration tests.",
-)
-
 
 @pytest.fixture
 def mock_project_client() -> MagicMock:
@@ -689,42 +680,3 @@ async def test_provider_create_agent_with_mcp_and_regular_tools(
         assert "regular_function" in tool_names
         assert "mcp_function_1" in tool_names
         assert "mcp_function_2" in tool_names
-
-
-@pytest.mark.flaky
-@pytest.mark.integration
-@skip_if_azure_ai_integration_tests_disabled
-async def test_provider_create_and_get_agent_integration() -> None:
-    """Integration test for provider create_agent and get_agent."""
-    endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
-    model = os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"]
-
-    async with (
-        AzureCliCredential() as credential,
-        AIProjectClient(endpoint=endpoint, credential=credential) as project_client,
-    ):
-        provider = AzureAIProjectAgentProvider(project_client=project_client)
-
-        try:
-            # Create agent
-            agent = await provider.create_agent(
-                name="ProviderTestAgent",
-                model=model,
-                instructions="You are a helpful assistant. Always respond with 'Hello from provider!'",
-            )
-
-            assert isinstance(agent, Agent)
-            assert agent.name == "ProviderTestAgent"
-
-            # Run the agent
-            response = await agent.run("Hi!")
-            assert response.text is not None
-            assert len(response.text) > 0
-
-            # Get the same agent
-            retrieved_agent = await provider.get_agent(name="ProviderTestAgent")
-            assert retrieved_agent.name == "ProviderTestAgent"
-
-        finally:
-            # Cleanup
-            await project_client.agents.delete(agent_name="ProviderTestAgent")

python/packages/azure-cosmos/agent_framework_azure_cosmos/_history_provider.py

@@ -13,10 +13,13 @@ from typing import Any, ClassVar, TypedDict
 from agent_framework import AGENT_FRAMEWORK_USER_AGENT, Message
 from agent_framework._sessions import BaseHistoryProvider
 from agent_framework._settings import SecretString, load_settings
-from agent_framework.azure._entra_id_authentication import AzureCredentialTypes
+from azure.core.credentials import TokenCredential
+from azure.core.credentials_async import AsyncTokenCredential
 from azure.cosmos import PartitionKey
 from azure.cosmos.aio import ContainerProxy, CosmosClient, DatabaseProxy
 
+AzureCredentialTypes = TokenCredential | AsyncTokenCredential
+
 logger = logging.getLogger(__name__)
 
 

python/packages/azurefunctions/tests/integration_tests/README.md

@@ -14,7 +14,7 @@ cp .env.example .env
 
 Required variables:
 - `AZURE_OPENAI_ENDPOINT`
-- `AZURE_OPENAI_CHAT_DEPLOYMENT_NAME`
+- `AZURE_OPENAI_DEPLOYMENT_NAME`
 - `AZURE_OPENAI_API_KEY`
 - `AzureWebJobsStorage`
 - `DURABLE_TASK_SCHEDULER_CONNECTION_STRING`

python/packages/azurefunctions/tests/integration_tests/conftest.py

@@ -111,13 +111,17 @@ def _should_skip_azure_functions_integration_tests() -> tuple[bool, str]:
             f"Durable Task Scheduler emulator not running on port {_DTS_EMULATOR_PORT}. Start with: docker run -d -p 8080:8080 -p 8082:8082 mcr.microsoft.com/dts/dts-emulator:latest",  # noqa: E501
         )
 
-    endpoint = os.getenv("AZURE_OPENAI_ENDPOINT", "").strip()
-    if not endpoint or endpoint == "https://your-resource.openai.azure.com/":
-        return True, "No real AZURE_OPENAI_ENDPOINT provided; skipping integration tests."
-
-    deployment_name = os.getenv("AZURE_OPENAI_CHAT_DEPLOYMENT_NAME", "").strip()
-    if not deployment_name or deployment_name == "your-deployment-name":
-        return True, "No real AZURE_OPENAI_CHAT_DEPLOYMENT_NAME provided; skipping integration tests."
+    has_foundry_config = bool(os.getenv("FOUNDRY_PROJECT_ENDPOINT", "").strip()) and bool(
+        os.getenv("FOUNDRY_MODEL", "").strip()
+    )
+    has_azure_openai_config = bool(os.getenv("AZURE_OPENAI_ENDPOINT", "").strip()) and bool(
+        os.getenv("AZURE_OPENAI_DEPLOYMENT_NAME", "").strip()
+    )
+    if not has_foundry_config and not has_azure_openai_config:
+        return (
+            True,
+            "No real FOUNDRY_* or AZURE_OPENAI_* configuration provided; skipping integration tests.",
+        )
 
     return False, "Integration tests enabled."
 
@@ -322,22 +326,22 @@ def _is_port_in_use(port: int, host: str = _DEFAULT_HOST) -> bool:
         return sock.connect_ex((host, port)) == 0
 
 
-def _load_and_validate_env() -> None:
+def _load_and_validate_env(sample_path: Path) -> None:
     """Load .env file from current directory if it exists, then validate required environment variables.
 
     Raises pytest.fail if required environment variables are missing.
     """
     _load_env_file_if_present()
-
     # Required environment variables for Azure Functions samples
-    # These match the variables defined in .env.example
     required_env_vars = [
-        "AZURE_OPENAI_ENDPOINT",
-        "AZURE_OPENAI_CHAT_DEPLOYMENT_NAME",
         "AzureWebJobsStorage",
         "DURABLE_TASK_SCHEDULER_CONNECTION_STRING",
         "FUNCTIONS_WORKER_RUNTIME",
     ]
+    if sample_path.name == "11_workflow_parallel":
+        required_env_vars.extend(["AZURE_OPENAI_ENDPOINT", "AZURE_OPENAI_DEPLOYMENT_NAME"])
+    else:
+        required_env_vars.extend(["FOUNDRY_PROJECT_ENDPOINT", "FOUNDRY_MODEL"])
 
     # Check if required env vars are set
     missing_vars = [var for var in required_env_vars if not os.environ.get(var)]
@@ -526,7 +530,7 @@ def function_app_for_test(request: pytest.FixtureRequest) -> Iterator[dict[str,
     assert sample_path is not None, "Sample path must be resolved before starting the function app"
 
     # Load .env file if it exists and validate required env vars
-    _load_and_validate_env()
+    _load_and_validate_env(sample_path)
 
     max_attempts = 3
     last_error: Exception | None = None

python/packages/azurefunctions/tests/integration_tests/test_11_workflow_parallel.py

@@ -42,6 +42,7 @@ class TestWorkflowParallel:
         self.base_url = base_url
         self.helper = sample_helper
 
+    @pytest.mark.skip(reason="Causes timeouts.")
     def test_parallel_workflow_document_analysis(self) -> None:
         """Test parallel workflow with a standard document."""
         payload = {
@@ -70,6 +71,7 @@ class TestWorkflowParallel:
         assert status["runtimeStatus"] == "Completed"
         assert "output" in status
 
+    @pytest.mark.skip(reason="Causes timeouts.")
     def test_parallel_workflow_short_document(self) -> None:
         """Test parallel workflow with a short document."""
         payload = {
@@ -89,6 +91,7 @@ class TestWorkflowParallel:
         assert status["runtimeStatus"] == "Completed"
         assert "output" in status
 
+    @pytest.mark.skip(reason="Causes timeouts.")
     def test_parallel_workflow_technical_document(self) -> None:
         """Test parallel workflow with a technical document."""
         payload = {
@@ -112,6 +115,7 @@ class TestWorkflowParallel:
         status = self.helper.wait_for_orchestration_with_output(data["statusQueryGetUri"], max_wait=300)
         assert status["runtimeStatus"] == "Completed"
 
+    @pytest.mark.skip(reason="Causes timeouts.")
     def test_workflow_status_endpoint(self) -> None:
         """Test that the workflow status endpoint works correctly."""
         payload = {

python/packages/core/README.md

@@ -14,8 +14,8 @@ Highlights
 
 ```bash
 pip install agent-framework-core --pre
-# Optional: Add Azure AI integration
-pip install agent-framework-azure-ai --pre
+# Optional: Add Azure AI Foundry integration
+pip install agent-framework-foundry --pre
 ```
 
 Supported Platforms:
@@ -36,8 +36,8 @@ AZURE_OPENAI_API_KEY=...
 AZURE_OPENAI_ENDPOINT=...
 AZURE_OPENAI_CHAT_DEPLOYMENT_NAME=...
 ...
-AZURE_AI_PROJECT_ENDPOINT=...
-AZURE_AI_MODEL_DEPLOYMENT_NAME=...
+FOUNDRY_PROJECT_ENDPOINT=...
+FOUNDRY_MODEL=...
 ```
 
 You can also override environment variables by explicitly passing configuration parameters to the chat client constructor:

python/packages/core/agent_framework/_types.py

@@ -1995,6 +1995,7 @@ class ChatResponse(SerializationMixin, Generic[ResponseModelT]):
         messages: Message | Sequence[Message] | None = None,
         response_id: str | None = None,
         conversation_id: str | None = None,
+        model: str | None = None,
         model_id: str | None = None,
         created_at: CreatedAtT | None = None,
         finish_reason: FinishReasonLiteral | FinishReason | None = None,
@@ -2011,8 +2012,9 @@ class ChatResponse(SerializationMixin, Generic[ResponseModelT]):
             messages: A single Message or sequence of Message objects to include in the response.
             response_id: Optional ID of the chat response.
             conversation_id: Optional identifier for the state of the conversation.
-            model_id: Optional model ID used in the creation of the chat response.
-            created_at: Optional timestamp for the chat response.
+            model: Optional model used in the creation of the chat response.
+            model_id: Deprecated alias for ``model``.
+            created_at: Optional timestamp for when the response was created.
             finish_reason: Optional reason for the chat response (e.g., "stop", "length", "tool_calls").
             usage_details: Optional usage details for the chat response.
             value: Optional value of the structured output.
@@ -2022,6 +2024,8 @@ class ChatResponse(SerializationMixin, Generic[ResponseModelT]):
             additional_properties: Optional additional properties associated with the chat response.
             raw_representation: Optional raw representation of the chat response from an underlying implementation.
         """
+        if model_id is not None and model is None:
+            model = model_id
         if messages is None:
             self.messages: list[Message] = []
         elif isinstance(messages, Message):
@@ -2039,7 +2043,7 @@ class ChatResponse(SerializationMixin, Generic[ResponseModelT]):
             self.messages = processed_messages
         self.response_id = response_id
         self.conversation_id = conversation_id
-        self.model_id = model_id
+        self.model = model
         self.created_at = created_at
         self.finish_reason = finish_reason
         self.usage_details = usage_details
@@ -2052,6 +2056,15 @@ class ChatResponse(SerializationMixin, Generic[ResponseModelT]):
         self.continuation_token = continuation_token
         self.raw_representation: Any | list[Any] | None = raw_representation
 
+    @property
+    def model_id(self) -> str | None:
+        """Deprecated alias for :attr:`model`."""
+        return self.model
+
+    @model_id.setter
+    def model_id(self, value: str | None) -> None:
+        self.model = value
+
     @overload
     @classmethod
     def from_updates(
@@ -2249,6 +2262,7 @@ class ChatResponseUpdate(SerializationMixin):
         response_id: str | None = None,
         message_id: str | None = None,
         conversation_id: str | None = None,
+        model: str | None = None,
         model_id: str | None = None,
         created_at: CreatedAtT | None = None,
         finish_reason: FinishReasonLiteral | FinishReason | None = None,
@@ -2265,7 +2279,8 @@ class ChatResponseUpdate(SerializationMixin):
             response_id: Optional ID of the response of which this update is a part.
             message_id: Optional ID of the message of which this update is a part.
             conversation_id: Optional identifier for the state of the conversation of which this update is a part
-            model_id: Optional model ID associated with this response update.
+            model: Optional model associated with this response update.
+            model_id: Deprecated alias for ``model``.
             created_at: Optional timestamp for the chat response update.
             finish_reason: Optional finish reason for the operation.
             continuation_token: Optional token for resuming a long-running background operation.
@@ -2275,6 +2290,8 @@ class ChatResponseUpdate(SerializationMixin):
                 from an underlying implementation.
 
         """
+        if model_id is not None and model is None:
+            model = model_id
         # Handle contents - support dict conversion for from_dict
         if contents is None:
             self.contents: list[Content] = []
@@ -2294,7 +2311,7 @@ class ChatResponseUpdate(SerializationMixin):
         self.response_id = response_id
         self.message_id = message_id
         self.conversation_id = conversation_id
-        self.model_id = model_id
+        self.model = model
         self.created_at = created_at
         self.finish_reason = finish_reason
         self.continuation_token = continuation_token
@@ -2304,6 +2321,15 @@ class ChatResponseUpdate(SerializationMixin):
         )
         self.raw_representation = raw_representation
 
+    @property
+    def model_id(self) -> str | None:
+        """Deprecated alias for :attr:`model`."""
+        return self.model
+
+    @model_id.setter
+    def model_id(self, value: str | None) -> None:
+        self.model = value
+
     @property
     def text(self) -> str:
         """Returns the concatenated text of all contents in the update."""
@@ -3418,7 +3444,7 @@ class Embedding(Generic[EmbeddingT]):
 
     Args:
         vector: The embedding vector data.
-        model_id: The model used to generate this embedding.
+        model: The model used to generate this embedding.
         dimensions: Explicit dimension count (computed from vector length if omitted).
         created_at: Timestamp of when the embedding was generated.
         additional_properties: Additional metadata.
@@ -3430,7 +3456,7 @@ class Embedding(Generic[EmbeddingT]):
 
             embedding = Embedding(
                 vector=[0.1, 0.2, 0.3],
-                model_id="text-embedding-3-small",
+                model="text-embedding-3-small",
             )
             assert embedding.dimensions == 3
     """
@@ -3439,19 +3465,31 @@ class Embedding(Generic[EmbeddingT]):
         self,
         vector: EmbeddingT,
         *,
+        model: str | None = None,
         model_id: str | None = None,
         dimensions: int | None = None,
         created_at: datetime | None = None,
         additional_properties: dict[str, Any] | None = None,
     ) -> None:
+        if model_id is not None and model is None:
+            model = model_id
         self.vector = vector
         self._dimensions = dimensions
-        self.model_id = model_id
+        self.model = model
         self.created_at = created_at
         self.additional_properties = (
             _restore_compaction_annotation_in_additional_properties(additional_properties) or {}
         )
 
+    @property
+    def model_id(self) -> str | None:
+        """Deprecated alias for :attr:`model`."""
+        return self.model
+
+    @model_id.setter
+    def model_id(self, value: str | None) -> None:
+        self.model = value
+
     @property
     def dimensions(self) -> int | None:
         """Return the number of dimensions in the embedding vector.

python/packages/core/agent_framework/_workflows/_events.py

@@ -121,7 +121,7 @@ WorkflowEventType = Literal[
     "executor_completed",  # Executor handler completed (use .executor_id, .data)
     "executor_failed",  # Executor handler raised error (use .executor_id, .details)
     # Orchestration event types (use .data for typed payload)
-    "group_chat",  # Group chat orchestrator events (use .data as GroupChatRequestSentEvent | GroupChatResponseReceivedEvent)  # noqa: E501
+    "group_chat",  # Group chat orchestrator events (use .data as GroupChatRequestSentEvent | GroupChatResponseReceivedEvent) # noqa: E501
     "handoff_sent",  # Handoff routing events (use .data as HandoffSentEvent)
     "magentic_orchestrator",  # Magentic orchestrator events (use .data as MagenticOrchestratorEvent)
 ]

python/packages/core/agent_framework/azure/__init__.py

@@ -2,16 +2,7 @@
 
 """Azure integration namespace for optional Agent Framework connectors.
 
-This module lazily re-exports objects from optional Azure connector packages and
-built-in core Azure OpenAI modules.
-
-Supported classes include:
-- AzureAIClient
-- AzureAIAgentClient
-- AzureOpenAIChatClient
-- AzureOpenAIResponsesClient
-- AzureAISearchContextProvider
-- DurableAIAgent
+This module lazily re-exports objects from optional Azure connector packages.
 """
 
 import importlib
@@ -30,18 +21,17 @@ _IMPORTS: dict[str, tuple[str, str]] = {
     "AzureAISearchSettings": ("agent_framework_azure_ai_search", "agent-framework-azure-ai-search"),
     "AzureAISettings": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
     "AzureAIAgentsProvider": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
-    "AzureCredentialTypes": ("agent_framework.azure._entra_id_authentication", "agent-framework-core"),
-    "AzureTokenProvider": ("agent_framework.azure._entra_id_authentication", "agent-framework-core"),
-    "FoundryMemoryProvider": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
-    "AzureOpenAIAssistantsClient": ("agent_framework.azure._assistants_client", "agent-framework-core"),
-    "AzureOpenAIAssistantsOptions": ("agent_framework.azure._assistants_client", "agent-framework-core"),
-    "AzureOpenAIChatClient": ("agent_framework.azure._chat_client", "agent-framework-core"),
-    "AzureOpenAIChatOptions": ("agent_framework.azure._chat_client", "agent-framework-core"),
-    "AzureOpenAIEmbeddingClient": ("agent_framework.azure._embedding_client", "agent-framework-core"),
-    "AzureOpenAIResponsesClient": ("agent_framework.azure._responses_client", "agent-framework-core"),
-    "AzureOpenAIResponsesOptions": ("agent_framework.azure._responses_client", "agent-framework-core"),
-    "AzureOpenAISettings": ("agent_framework.azure._shared", "agent-framework-core"),
-    "AzureUserSecurityContext": ("agent_framework.azure._chat_client", "agent-framework-core"),
+    "AzureCredentialTypes": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
+    "AzureTokenProvider": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
+    "AzureOpenAIAssistantsClient": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
+    "AzureOpenAIAssistantsOptions": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
+    "AzureOpenAIChatClient": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
+    "AzureOpenAIChatOptions": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
+    "AzureOpenAIEmbeddingClient": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
+    "AzureOpenAIResponsesClient": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
+    "AzureOpenAIResponsesOptions": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
+    "AzureOpenAISettings": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
+    "AzureUserSecurityContext": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
     "DurableAIAgent": ("agent_framework_durabletask", "agent-framework-durabletask"),
     "DurableAIAgentClient": ("agent_framework_durabletask", "agent-framework-durabletask"),
     "DurableAIAgentOrchestrationContext": ("agent_framework_durabletask", "agent-framework-durabletask"),

python/packages/core/agent_framework/azure/__init__.pyi

@@ -1,5 +1,8 @@
 # Copyright (c) Microsoft. All rights reserved.
 
+# Type stubs for the agent_framework.azure lazy-loading namespace.
+# Install the relevant packages for full type support.
+
 from agent_framework_azure_ai import (
     AzureAIAgentClient,
     AzureAIAgentsProvider,
@@ -7,9 +10,23 @@ from agent_framework_azure_ai import (
     AzureAIProjectAgentOptions,
     AzureAIProjectAgentProvider,
     AzureAISettings,
-    FoundryMemoryProvider,
+    AzureCredentialTypes,
+    AzureOpenAIAssistantsClient,
+    AzureOpenAIAssistantsOptions,
+    AzureOpenAIChatClient,
+    AzureOpenAIChatOptions,
+    AzureOpenAIEmbeddingClient,
+    AzureOpenAIResponsesClient,
+    AzureOpenAIResponsesOptions,
+    AzureOpenAISettings,
+    AzureTokenProvider,
+    AzureUserSecurityContext,
+    RawAzureAIClient,
+)
+from agent_framework_azure_ai_search import (
+    AzureAISearchContextProvider,
+    AzureAISearchSettings,
 )
-from agent_framework_azure_ai_search import AzureAISearchContextProvider, AzureAISearchSettings
 from agent_framework_azurefunctions import AgentFunctionApp
 from agent_framework_durabletask import (
     AgentCallbackContext,
@@ -20,13 +37,6 @@ from agent_framework_durabletask import (
     DurableAIAgentWorker,
 )
 
-from agent_framework.azure._assistants_client import AzureOpenAIAssistantsClient
-from agent_framework.azure._chat_client import AzureOpenAIChatClient
-from agent_framework.azure._embedding_client import AzureOpenAIEmbeddingClient
-from agent_framework.azure._entra_id_authentication import AzureCredentialTypes, AzureTokenProvider
-from agent_framework.azure._responses_client import AzureOpenAIResponsesClient
-from agent_framework.azure._shared import AzureOpenAISettings
-
 __all__ = [
     "AgentCallbackContext",
     "AgentFunctionApp",
@@ -41,14 +51,18 @@ __all__ = [
     "AzureAISettings",
     "AzureCredentialTypes",
     "AzureOpenAIAssistantsClient",
+    "AzureOpenAIAssistantsOptions",
     "AzureOpenAIChatClient",
+    "AzureOpenAIChatOptions",
     "AzureOpenAIEmbeddingClient",
     "AzureOpenAIResponsesClient",
+    "AzureOpenAIResponsesOptions",
     "AzureOpenAISettings",
     "AzureTokenProvider",
+    "AzureUserSecurityContext",
     "DurableAIAgent",
     "DurableAIAgentClient",
     "DurableAIAgentOrchestrationContext",
     "DurableAIAgentWorker",
-    "FoundryMemoryProvider",
+    "RawAzureAIClient",
 ]

python/packages/core/agent_framework/azure/_assistants_client.py

@@ -1,194 +0,0 @@
-# Copyright (c) Microsoft. All rights reserved.
-
-from __future__ import annotations
-
-import sys
-from collections.abc import Mapping
-from typing import Any, ClassVar, Generic
-
-from openai.lib.azure import AsyncAzureOpenAI
-
-from .._settings import load_settings
-from ..openai import OpenAIAssistantsClient
-from ..openai._assistants_client import OpenAIAssistantsOptions
-from ._entra_id_authentication import AzureCredentialTypes, AzureTokenProvider, resolve_credential_to_token_provider
-from ._shared import AzureOpenAISettings, _apply_azure_defaults  # pyright: ignore[reportPrivateUsage]
-
-if sys.version_info >= (3, 13):
-    from typing import TypeVar  # type: ignore # pragma: no cover
-else:
-    from typing_extensions import TypeVar  # type: ignore # pragma: no cover
-if sys.version_info >= (3, 11):
-    from typing import TypedDict  # type: ignore # pragma: no cover
-else:
-    from typing_extensions import TypedDict  # type: ignore # pragma: no cover
-
-
-# region Azure OpenAI Assistants Options TypedDict
-
-
-AzureOpenAIAssistantsOptionsT = TypeVar(
-    "AzureOpenAIAssistantsOptionsT",
-    bound=TypedDict,  # type: ignore[valid-type]
-    default="OpenAIAssistantsOptions",
-    covariant=True,
-)
-
-
-# endregion
-
-
-class AzureOpenAIAssistantsClient(
-    OpenAIAssistantsClient[AzureOpenAIAssistantsOptionsT], Generic[AzureOpenAIAssistantsOptionsT]
-):
-    """Azure OpenAI Assistants client."""
-
-    DEFAULT_AZURE_API_VERSION: ClassVar[str] = "2024-05-01-preview"
-
-    def __init__(
-        self,
-        *,
-        deployment_name: str | None = None,
-        assistant_id: str | None = None,
-        assistant_name: str | None = None,
-        assistant_description: str | None = None,
-        thread_id: str | None = None,
-        api_key: str | None = None,
-        endpoint: str | None = None,
-        base_url: str | None = None,
-        api_version: str | None = None,
-        token_endpoint: str | None = None,
-        credential: AzureCredentialTypes | AzureTokenProvider | None = None,
-        default_headers: Mapping[str, str] | None = None,
-        async_client: AsyncAzureOpenAI | None = None,
-        env_file_path: str | None = None,
-        env_file_encoding: str | None = None,
-    ) -> None:
-        """Initialize an Azure OpenAI Assistants client.
-
-        Keyword Args:
-            deployment_name: The Azure OpenAI deployment name for the model to use.
-                Can also be set via environment variable AZURE_OPENAI_CHAT_DEPLOYMENT_NAME.
-            assistant_id: The ID of an Azure OpenAI assistant to use.
-                If not provided, a new assistant will be created (and deleted after the request).
-            assistant_name: The name to use when creating new assistants.
-            assistant_description: The description to use when creating new assistants.
-            thread_id: Default thread ID to use for conversations. Can be overridden by
-                conversation_id property when making a request.
-                If not provided, a new thread will be created (and deleted after the request).
-            api_key: The API key to use. If provided will override the env vars or .env file value.
-                Can also be set via environment variable AZURE_OPENAI_API_KEY.
-            endpoint: The deployment endpoint. If provided will override the value
-                in the env vars or .env file.
-                Can also be set via environment variable AZURE_OPENAI_ENDPOINT.
-            base_url: The deployment base URL. If provided will override the value
-                in the env vars or .env file.
-                Can also be set via environment variable AZURE_OPENAI_BASE_URL.
-            api_version: The deployment API version. If provided will override the value
-                in the env vars or .env file.
-                Can also be set via environment variable AZURE_OPENAI_API_VERSION.
-            token_endpoint: The token endpoint to request an Azure token.
-                Can also be set via environment variable AZURE_OPENAI_TOKEN_ENDPOINT.
-            credential: Azure credential or token provider for authentication. Accepts a
-                ``TokenCredential``, ``AsyncTokenCredential``, or a callable that returns a
-                bearer token string (sync or async), for example from
-                ``azure.identity.get_bearer_token_provider()``.
-            default_headers: The default headers mapping of string keys to
-                string values for HTTP requests.
-            async_client: An existing client to use.
-            env_file_path: Use the environment settings file as a fallback
-                to environment variables.
-            env_file_encoding: The encoding of the environment settings file.
-
-        Examples:
-            .. code-block:: python
-
-                from agent_framework.azure import AzureOpenAIAssistantsClient
-
-                # Using environment variables
-                # Set AZURE_OPENAI_ENDPOINT=https://your-endpoint.openai.azure.com
-                # Set AZURE_OPENAI_CHAT_DEPLOYMENT_NAME=gpt-4
-                # Set AZURE_OPENAI_API_KEY=your-key
-                client = AzureOpenAIAssistantsClient()
-
-                # Or passing parameters directly
-                client = AzureOpenAIAssistantsClient(
-                    endpoint="https://your-endpoint.openai.azure.com", deployment_name="gpt-4", api_key="your-key"
-                )
-
-                # Or loading from a .env file
-                client = AzureOpenAIAssistantsClient(env_file_path="path/to/.env")
-
-                # Using custom ChatOptions with type safety:
-                from typing import TypedDict
-                from agent_framework.azure import AzureOpenAIAssistantsOptions
-
-
-                class MyOptions(AzureOpenAIAssistantsOptions, total=False):
-                    my_custom_option: str
-
-
-                client: AzureOpenAIAssistantsClient[MyOptions] = AzureOpenAIAssistantsClient()
-                response = await client.get_response("Hello", options={"my_custom_option": "value"})
-        """
-        azure_openai_settings = load_settings(
-            AzureOpenAISettings,
-            env_prefix="AZURE_OPENAI_",
-            api_key=api_key,
-            base_url=base_url,
-            endpoint=endpoint,
-            chat_deployment_name=deployment_name,
-            api_version=api_version,
-            env_file_path=env_file_path,
-            env_file_encoding=env_file_encoding,
-            token_endpoint=token_endpoint,
-        )
-        _apply_azure_defaults(azure_openai_settings, default_api_version=self.DEFAULT_AZURE_API_VERSION)
-
-        chat_deployment_name = azure_openai_settings.get("chat_deployment_name")
-        if not chat_deployment_name:
-            raise ValueError(
-                "Azure OpenAI deployment name is required. Set via 'deployment_name' parameter "
-                "or 'AZURE_OPENAI_CHAT_DEPLOYMENT_NAME' environment variable."
-            )
-
-        api_key_secret = azure_openai_settings.get("api_key")
-        token_scope = azure_openai_settings.get("token_endpoint")
-
-        # Resolve credential to token provider
-        ad_token_provider = None
-        if not async_client and not api_key_secret and credential:
-            ad_token_provider = resolve_credential_to_token_provider(credential, token_scope)
-
-        if not async_client and not api_key_secret and not ad_token_provider:
-            raise ValueError("Please provide either api_key, credential, or a client.")
-
-        # Create Azure client if not provided
-        if not async_client:
-            client_params: dict[str, Any] = {
-                "default_headers": default_headers,
-            }
-            if resolved_api_version := azure_openai_settings.get("api_version"):
-                client_params["api_version"] = resolved_api_version
-
-            if api_key_secret:
-                client_params["api_key"] = api_key_secret.get_secret_value()
-            elif ad_token_provider:
-                client_params["azure_ad_token_provider"] = ad_token_provider
-
-            if resolved_base_url := azure_openai_settings.get("base_url"):
-                client_params["base_url"] = str(resolved_base_url)
-            elif resolved_endpoint := azure_openai_settings.get("endpoint"):
-                client_params["azure_endpoint"] = str(resolved_endpoint)
-
-            async_client = AsyncAzureOpenAI(**client_params)
-
-        super().__init__(
-            model_id=chat_deployment_name,
-            assistant_id=assistant_id,
-            assistant_name=assistant_name,
-            assistant_description=assistant_description,
-            thread_id=thread_id,
-            async_client=async_client,  # type: ignore[reportArgumentType]
-            default_headers=default_headers,
-        )

python/packages/core/agent_framework/azure/_chat_client.py

@@ -1,349 +0,0 @@
-# Copyright (c) Microsoft. All rights reserved.
-
-from __future__ import annotations
-
-import json
-import logging
-import sys
-from collections.abc import Mapping, Sequence
-from typing import TYPE_CHECKING, Any, Generic, cast
-
-from pydantic import BaseModel
-
-from agent_framework import (
-    Annotation,
-    ChatMiddlewareLayer,
-    ChatResponse,
-    ChatResponseUpdate,
-    Content,
-    FunctionInvocationConfiguration,
-    FunctionInvocationLayer,
-)
-from agent_framework.observability import ChatTelemetryLayer
-from agent_framework.openai._chat_client import OpenAIChatOptions, RawOpenAIChatClient
-
-from .._settings import load_settings
-from ._entra_id_authentication import AzureCredentialTypes, AzureTokenProvider
-from ._shared import (
-    AzureOpenAIConfigMixin,
-    AzureOpenAISettings,
-    _apply_azure_defaults,  # pyright: ignore[reportPrivateUsage]
-)
-
-if sys.version_info >= (3, 13):
-    from typing import TypeVar  # type: ignore # pragma: no cover
-else:
-    from typing_extensions import TypeVar  # type: ignore # pragma: no cover
-if sys.version_info >= (3, 12):
-    from typing import override  # type: ignore # pragma: no cover
-else:
-    from typing_extensions import override  # type: ignore # pragma: no cover
-if sys.version_info >= (3, 11):
-    from typing import TypedDict  # type: ignore # pragma: no cover
-else:
-    from typing_extensions import TypedDict  # type: ignore # pragma: no cover
-
-if TYPE_CHECKING:
-    from openai.lib.azure import AsyncAzureOpenAI
-    from openai.types.chat.chat_completion import Choice
-    from openai.types.chat.chat_completion_chunk import Choice as ChunkChoice
-
-    from agent_framework._middleware import MiddlewareTypes
-
-logger: logging.Logger = logging.getLogger(__name__)
-
-
-ResponseModelT = TypeVar("ResponseModelT", bound=BaseModel | None, default=None)
-
-
-# region Azure OpenAI Chat Options TypedDict
-
-
-class AzureUserSecurityContext(TypedDict, total=False):
-    """User security context for Azure AI applications.
-
-    These fields help security operations teams investigate and mitigate security
-    incidents by providing context about the application and end user.
-
-    Learn more: https://learn.microsoft.com/azure/well-architected/service-guides/cosmos-db
-    """
-
-    application_name: str
-    """Name of the application making the request."""
-
-    end_user_id: str
-    """Unique identifier for the end user (recommend hashing username/email)."""
-
-    end_user_tenant_id: str
-    """Microsoft 365 tenant ID the end user belongs to. Required for multi-tenant apps."""
-
-    source_ip: str
-    """The original client's IP address."""
-
-
-class AzureOpenAIChatOptions(OpenAIChatOptions[ResponseModelT], Generic[ResponseModelT], total=False):
-    """Azure OpenAI-specific chat options dict.
-
-    Extends OpenAIChatOptions with Azure-specific options including
-    the "On Your Data" feature and enhanced security context.
-
-    See: https://learn.microsoft.com/azure/ai-foundry/openai/reference-preview-latest
-
-    Keys:
-        # Inherited from OpenAIChatOptions/ChatOptions:
-        model_id: The model to use for the request,
-            translates to ``model`` in Azure OpenAI API.
-        temperature: Sampling temperature between 0 and 2.
-        top_p: Nucleus sampling parameter.
-        max_tokens: Maximum number of tokens to generate,
-            translates to ``max_completion_tokens`` in Azure OpenAI API.
-        stop: Stop sequences.
-        seed: Random seed for reproducibility.
-        frequency_penalty: Frequency penalty between -2.0 and 2.0.
-        presence_penalty: Presence penalty between -2.0 and 2.0.
-        tools: List of tools (functions) available to the model.
-        tool_choice: How the model should use tools.
-        allow_multiple_tool_calls: Whether to allow parallel tool calls,
-            translates to ``parallel_tool_calls`` in Azure OpenAI API.
-        response_format: Structured output schema.
-        metadata: Request metadata for tracking.
-        user: End-user identifier for abuse monitoring.
-        store: Whether to store the conversation.
-        instructions: System instructions for the model.
-        logit_bias: Token bias values (-100 to 100).
-        logprobs: Whether to return log probabilities.
-        top_logprobs: Number of top log probabilities to return (0-20).
-
-        # Azure-specific options:
-        data_sources: Azure "On Your Data" data sources configuration.
-        user_security_context: Enhanced security context for Azure Defender.
-        n: Number of chat completions to generate (not recommended, incurs costs).
-    """
-
-    # Azure-specific options
-    data_sources: list[dict[str, Any]]
-    """Azure "On Your Data" data sources for retrieval-augmented generation.
-
-    Supported types: azure_search, azure_cosmos_db, elasticsearch, pinecone, mongo_db.
-    See: https://learn.microsoft.com/azure/ai-foundry/openai/references/on-your-data
-    """
-
-    user_security_context: AzureUserSecurityContext
-    """Enhanced security context for Azure Defender integration."""
-
-    n: int
-    """Number of chat completion choices to generate for each input message.
-    Note: You will be charged based on tokens across all choices. Keep n=1 to minimize costs."""
-
-
-AzureOpenAIChatOptionsT = TypeVar(
-    "AzureOpenAIChatOptionsT",
-    bound=TypedDict,  # type: ignore[valid-type]
-    default="AzureOpenAIChatOptions",
-    covariant=True,
-)
-
-
-# endregion
-
-ChatResponseT = TypeVar("ChatResponseT", ChatResponse, ChatResponseUpdate)
-AzureOpenAIChatClientT = TypeVar("AzureOpenAIChatClientT", bound="AzureOpenAIChatClient")
-
-
-class AzureOpenAIChatClient(  # type: ignore[misc]
-    AzureOpenAIConfigMixin,
-    FunctionInvocationLayer[AzureOpenAIChatOptionsT],
-    ChatMiddlewareLayer[AzureOpenAIChatOptionsT],
-    ChatTelemetryLayer[AzureOpenAIChatOptionsT],
-    RawOpenAIChatClient[AzureOpenAIChatOptionsT],
-    Generic[AzureOpenAIChatOptionsT],
-):
-    """Azure OpenAI Chat completion class with middleware, telemetry, and function invocation support."""
-
-    def __init__(
-        self,
-        *,
-        api_key: str | None = None,
-        deployment_name: str | None = None,
-        endpoint: str | None = None,
-        base_url: str | None = None,
-        api_version: str | None = None,
-        token_endpoint: str | None = None,
-        credential: AzureCredentialTypes | AzureTokenProvider | None = None,
-        default_headers: Mapping[str, str] | None = None,
-        async_client: AsyncAzureOpenAI | None = None,
-        additional_properties: dict[str, Any] | None = None,
-        env_file_path: str | None = None,
-        env_file_encoding: str | None = None,
-        instruction_role: str | None = None,
-        middleware: Sequence[MiddlewareTypes] | None = None,
-        function_invocation_configuration: FunctionInvocationConfiguration | None = None,
-    ) -> None:
-        """Initialize an Azure OpenAI Chat completion client.
-
-        Keyword Args:
-            api_key: The API key. If provided, will override the value in the env vars or .env file.
-                Can also be set via environment variable AZURE_OPENAI_API_KEY.
-            deployment_name: The deployment name. If provided, will override the value
-                (chat_deployment_name) in the env vars or .env file.
-                Can also be set via environment variable AZURE_OPENAI_CHAT_DEPLOYMENT_NAME.
-            endpoint: The deployment endpoint. If provided will override the value
-                in the env vars or .env file.
-                Can also be set via environment variable AZURE_OPENAI_ENDPOINT.
-            base_url: The deployment base URL. If provided will override the value
-                in the env vars or .env file.
-                Can also be set via environment variable AZURE_OPENAI_BASE_URL.
-            api_version: The deployment API version. If provided will override the value
-                in the env vars or .env file.
-                Can also be set via environment variable AZURE_OPENAI_API_VERSION.
-            token_endpoint: The token endpoint to request an Azure token.
-                Can also be set via environment variable AZURE_OPENAI_TOKEN_ENDPOINT.
-            credential: Azure credential or token provider for authentication. Accepts a
-                ``TokenCredential``, ``AsyncTokenCredential``, or a callable that returns a
-                bearer token string (sync or async), for example from
-                ``azure.identity.get_bearer_token_provider()``.
-            default_headers: The default headers mapping of string keys to
-                string values for HTTP requests.
-            async_client: An existing client to use.
-            additional_properties: Additional properties stored on the client instance.
-            env_file_path: Use the environment settings file as a fallback to using env vars.
-            env_file_encoding: The encoding of the environment settings file, defaults to 'utf-8'.
-            instruction_role: The role to use for 'instruction' messages, for example, summarization
-                prompts could use `developer` or `system`.
-            middleware: Optional sequence of middleware to apply to requests.
-            function_invocation_configuration: Optional configuration for function invocation behavior.
-
-        Examples:
-            .. code-block:: python
-
-                from agent_framework.azure import AzureOpenAIChatClient
-
-                # Using environment variables
-                # Set AZURE_OPENAI_ENDPOINT=https://your-endpoint.openai.azure.com
-                # Set AZURE_OPENAI_CHAT_DEPLOYMENT_NAME=<model name>
-                # Set AZURE_OPENAI_API_KEY=your-key
-                client = AzureOpenAIChatClient()
-
-                # Or passing parameters directly
-                client = AzureOpenAIChatClient(
-                    endpoint="https://your-endpoint.openai.azure.com",
-                    deployment_name="<model name>",
-                    api_key="your-key",
-                )
-
-                # Or loading from a .env file
-                client = AzureOpenAIChatClient(env_file_path="path/to/.env")
-
-                # Using custom ChatOptions with type safety:
-                from typing import TypedDict
-                from agent_framework.azure import AzureOpenAIChatOptions
-
-
-                class MyOptions(AzureOpenAIChatOptions, total=False):
-                    my_custom_option: str
-
-
-                client: AzureOpenAIChatClient[MyOptions] = AzureOpenAIChatClient()
-                response = await client.get_response("Hello", options={"my_custom_option": "value"})
-        """
-        azure_openai_settings = load_settings(
-            AzureOpenAISettings,
-            env_prefix="AZURE_OPENAI_",
-            api_key=api_key,
-            base_url=base_url,
-            endpoint=endpoint,
-            chat_deployment_name=deployment_name,
-            api_version=api_version,
-            env_file_path=env_file_path,
-            env_file_encoding=env_file_encoding,
-            token_endpoint=token_endpoint,
-        )
-        _apply_azure_defaults(azure_openai_settings)
-
-        chat_deployment_name = azure_openai_settings.get("chat_deployment_name")
-        if not chat_deployment_name:
-            raise ValueError(
-                "Azure OpenAI deployment name is required. Set via 'deployment_name' parameter "
-                "or 'AZURE_OPENAI_CHAT_DEPLOYMENT_NAME' environment variable."
-            )
-
-        endpoint_value = azure_openai_settings.get("endpoint")
-        base_url_value = azure_openai_settings.get("base_url")
-        api_version_value = cast(str, azure_openai_settings.get("api_version"))
-        api_key_value = azure_openai_settings.get("api_key")
-        token_endpoint_value = azure_openai_settings.get("token_endpoint")
-
-        super().__init__(
-            deployment_name=chat_deployment_name,
-            endpoint=endpoint_value,
-            base_url=base_url_value,
-            api_version=api_version_value,
-            api_key=api_key_value.get_secret_value() if api_key_value else None,
-            token_endpoint=token_endpoint_value,
-            credential=credential,
-            default_headers=default_headers,
-            client=async_client,
-            additional_properties=additional_properties,
-            instruction_role=instruction_role,
-            middleware=middleware,
-            function_invocation_configuration=function_invocation_configuration,
-        )
-
-    @override
-    def _parse_text_from_openai(self, choice: Choice | ChunkChoice) -> Content | None:
-        """Parse the choice into a Content object with type='text'.
-
-        Overwritten from RawOpenAIChatClient to deal with Azure On Your Data function.
-        For docs see:
-        https://learn.microsoft.com/en-us/azure/ai-foundry/openai/references/on-your-data?tabs=python#context
-        """
-        message = getattr(choice, "message", None)
-        if message is None:
-            message = getattr(choice, "delta", None)
-        # When you enable asynchronous content filtering in Azure OpenAI, you may receive empty deltas
-        if message is None:  # type: ignore
-            return None
-        if hasattr(message, "refusal") and message.refusal:
-            return Content.from_text(text=message.refusal, raw_representation=choice)
-        if not message.content:
-            return None
-        text_content = Content.from_text(text=message.content, raw_representation=choice)
-        if not message.model_extra or "context" not in message.model_extra:
-            return text_content
-
-        context_raw: object = cast(object, message.context)  # type: ignore[union-attr]
-        if isinstance(context_raw, str):
-            try:
-                context_raw = json.loads(context_raw)
-            except json.JSONDecodeError:
-                logger.warning("Context is not a valid JSON string, ignoring context.")
-                return text_content
-        if not isinstance(context_raw, dict):
-            logger.warning("Context is not a valid dictionary, ignoring context.")
-            return text_content
-        context = cast(dict[str, Any], context_raw)
-        # `all_retrieved_documents` is currently not used, but can be retrieved
-        # through the raw_representation in the text content.
-        if intent := context.get("intent"):
-            text_content.additional_properties = {"intent": intent}
-        citations = context.get("citations")
-        if isinstance(citations, list) and citations:
-            annotations: list[Annotation] = []
-            for citation_raw in cast(list[object], citations):
-                if not isinstance(citation_raw, dict):
-                    continue
-                citation = cast(dict[str, Any], citation_raw)
-                annotations.append(
-                    Annotation(
-                        type="citation",
-                        title=citation.get("title", ""),
-                        url=citation.get("url", ""),
-                        snippet=citation.get("content", ""),
-                        file_id=citation.get("filepath", ""),
-                        tool_name="Azure-on-your-Data",
-                        additional_properties={"chunk_id": citation.get("chunk_id", "")},
-                        raw_representation=citation,
-                    )
-                )
-            text_content.annotations = annotations
-        return text_content

python/packages/core/agent_framework/azure/_embedding_client.py

@@ -1,141 +0,0 @@
-# Copyright (c) Microsoft. All rights reserved.
-
-from __future__ import annotations
-
-import sys
-from collections.abc import Mapping
-from typing import Generic
-
-from openai.lib.azure import AsyncAzureOpenAI
-
-from agent_framework.observability import EmbeddingTelemetryLayer
-from agent_framework.openai import OpenAIEmbeddingOptions
-from agent_framework.openai._embedding_client import RawOpenAIEmbeddingClient
-
-from .._settings import load_settings
-from ._entra_id_authentication import AzureCredentialTypes, AzureTokenProvider
-from ._shared import (
-    AzureOpenAIConfigMixin,
-    AzureOpenAISettings,
-    _apply_azure_defaults,  # pyright: ignore[reportPrivateUsage]
-)
-
-if sys.version_info >= (3, 13):
-    from typing import TypeVar  # type: ignore # pragma: no cover
-else:
-    from typing_extensions import TypeVar  # type: ignore # pragma: no cover
-if sys.version_info >= (3, 11):
-    from typing import TypedDict  # type: ignore # pragma: no cover
-else:
-    from typing_extensions import TypedDict  # type: ignore # pragma: no cover
-
-
-AzureOpenAIEmbeddingOptionsT = TypeVar(
-    "AzureOpenAIEmbeddingOptionsT",
-    bound=TypedDict,  # type: ignore[valid-type]
-    default="OpenAIEmbeddingOptions",
-    covariant=True,
-)
-
-
-class AzureOpenAIEmbeddingClient(
-    AzureOpenAIConfigMixin,
-    EmbeddingTelemetryLayer[str, list[float], AzureOpenAIEmbeddingOptionsT],
-    RawOpenAIEmbeddingClient[AzureOpenAIEmbeddingOptionsT],
-    Generic[AzureOpenAIEmbeddingOptionsT],
-):
-    """Azure OpenAI embedding client with telemetry support.
-
-    Keyword Args:
-        api_key: The API key. If provided, will override the value in the env vars or .env file.
-            Can also be set via environment variable AZURE_OPENAI_API_KEY.
-        deployment_name: The deployment name. If provided, will override the value
-            (embedding_deployment_name) in the env vars or .env file.
-            Can also be set via environment variable AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME.
-        endpoint: The deployment endpoint.
-            Can also be set via environment variable AZURE_OPENAI_ENDPOINT.
-        base_url: The deployment base URL.
-            Can also be set via environment variable AZURE_OPENAI_BASE_URL.
-        api_version: The deployment API version.
-            Can also be set via environment variable AZURE_OPENAI_API_VERSION.
-        token_endpoint: The token endpoint to request an Azure token.
-            Can also be set via environment variable AZURE_OPENAI_TOKEN_ENDPOINT.
-        credential: Azure credential or token provider for authentication.
-        default_headers: Default headers for HTTP requests.
-        async_client: An existing client to use.
-        env_file_path: Path to .env file for settings.
-        env_file_encoding: Encoding for .env file.
-
-    Examples:
-        .. code-block:: python
-
-            from agent_framework.azure import AzureOpenAIEmbeddingClient
-
-            # Using environment variables
-            # Set AZURE_OPENAI_ENDPOINT=https://your-endpoint.openai.azure.com
-            # Set AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME=text-embedding-3-small
-            # Set AZURE_OPENAI_API_KEY=your-key
-            client = AzureOpenAIEmbeddingClient()
-
-            # Or passing parameters directly
-            client = AzureOpenAIEmbeddingClient(
-                endpoint="https://your-endpoint.openai.azure.com",
-                deployment_name="text-embedding-3-small",
-                api_key="your-key",
-            )
-
-            result = await client.get_embeddings(["Hello, world!"])
-    """
-
-    def __init__(
-        self,
-        *,
-        api_key: str | None = None,
-        deployment_name: str | None = None,
-        endpoint: str | None = None,
-        base_url: str | None = None,
-        api_version: str | None = None,
-        token_endpoint: str | None = None,
-        credential: AzureCredentialTypes | AzureTokenProvider | None = None,
-        default_headers: Mapping[str, str] | None = None,
-        async_client: AsyncAzureOpenAI | None = None,
-        otel_provider_name: str | None = None,
-        env_file_path: str | None = None,
-        env_file_encoding: str | None = None,
-    ) -> None:
-        """Initialize an Azure OpenAI embedding client."""
-        azure_openai_settings = load_settings(
-            AzureOpenAISettings,
-            env_prefix="AZURE_OPENAI_",
-            api_key=api_key,
-            base_url=base_url,
-            endpoint=endpoint,
-            embedding_deployment_name=deployment_name,
-            api_version=api_version,
-            env_file_path=env_file_path,
-            env_file_encoding=env_file_encoding,
-            token_endpoint=token_endpoint,
-        )
-        _apply_azure_defaults(azure_openai_settings)
-
-        embedding_deployment_name = azure_openai_settings.get("embedding_deployment_name")
-        if not embedding_deployment_name:
-            raise ValueError(
-                "Azure OpenAI embedding deployment name is required. Set via 'deployment_name' parameter "
-                "or 'AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME' environment variable."
-            )
-
-        api_key_secret = azure_openai_settings.get("api_key")
-
-        super().__init__(
-            deployment_name=embedding_deployment_name,
-            endpoint=azure_openai_settings.get("endpoint"),
-            base_url=azure_openai_settings.get("base_url"),
-            api_version=azure_openai_settings.get("api_version") or "",
-            api_key=api_key_secret.get_secret_value() if api_key_secret else None,
-            token_endpoint=azure_openai_settings.get("token_endpoint"),
-            credential=credential,
-            default_headers=default_headers,
-            client=async_client,
-            otel_provider_name=otel_provider_name,
-        )

python/packages/core/agent_framework/azure/_responses_client.py

@@ -1,277 +0,0 @@
-# Copyright (c) Microsoft. All rights reserved.
-
-from __future__ import annotations
-
-import sys
-from collections.abc import Mapping, Sequence
-from typing import TYPE_CHECKING, Any, Generic
-from urllib.parse import urljoin, urlparse
-
-from azure.ai.projects.aio import AIProjectClient
-from openai import AsyncOpenAI
-
-from .._middleware import ChatMiddlewareLayer
-from .._settings import load_settings
-from .._telemetry import AGENT_FRAMEWORK_USER_AGENT
-from .._tools import FunctionInvocationConfiguration, FunctionInvocationLayer
-from ..observability import ChatTelemetryLayer
-from ..openai._responses_client import RawOpenAIResponsesClient
-from ._entra_id_authentication import AzureCredentialTypes, AzureTokenProvider
-from ._shared import (
-    AzureOpenAIConfigMixin,
-    AzureOpenAISettings,
-    _apply_azure_defaults,  # pyright: ignore[reportPrivateUsage]
-)
-
-if sys.version_info >= (3, 13):
-    from typing import TypeVar  # type: ignore # pragma: no cover
-else:
-    from typing_extensions import TypeVar  # type: ignore # pragma: no cover
-if sys.version_info >= (3, 12):
-    from typing import override  # type: ignore # pragma: no cover
-else:
-    from typing_extensions import override  # type: ignore # pragma: no cover
-if sys.version_info >= (3, 11):
-    from typing import TypedDict  # type: ignore # pragma: no cover
-else:
-    from typing_extensions import TypedDict  # type: ignore # pragma: no cover
-
-if TYPE_CHECKING:
-    from .._middleware import MiddlewareTypes
-    from ..openai._responses_client import OpenAIResponsesOptions
-
-
-AzureOpenAIResponsesOptionsT = TypeVar(
-    "AzureOpenAIResponsesOptionsT",
-    bound=TypedDict,  # type: ignore[valid-type]
-    default="OpenAIResponsesOptions",
-    covariant=True,
-)
-
-
-class AzureOpenAIResponsesClient(  # type: ignore[misc]
-    AzureOpenAIConfigMixin,
-    FunctionInvocationLayer[AzureOpenAIResponsesOptionsT],
-    ChatMiddlewareLayer[AzureOpenAIResponsesOptionsT],
-    ChatTelemetryLayer[AzureOpenAIResponsesOptionsT],
-    RawOpenAIResponsesClient[AzureOpenAIResponsesOptionsT],
-    Generic[AzureOpenAIResponsesOptionsT],
-):
-    """Azure Responses completion class with middleware, telemetry, and function invocation support."""
-
-    def __init__(
-        self,
-        *,
-        api_key: str | None = None,
-        deployment_name: str | None = None,
-        endpoint: str | None = None,
-        base_url: str | None = None,
-        api_version: str | None = None,
-        token_endpoint: str | None = None,
-        credential: AzureCredentialTypes | AzureTokenProvider | None = None,
-        default_headers: Mapping[str, str] | None = None,
-        async_client: AsyncOpenAI | None = None,
-        project_client: Any | None = None,
-        project_endpoint: str | None = None,
-        allow_preview: bool | None = None,
-        env_file_path: str | None = None,
-        env_file_encoding: str | None = None,
-        instruction_role: str | None = None,
-        middleware: Sequence[MiddlewareTypes] | None = None,
-        function_invocation_configuration: FunctionInvocationConfiguration | None = None,
-        **kwargs: Any,
-    ) -> None:
-        """Initialize an Azure OpenAI Responses client.
-
-        The client can be created in two ways:
-
-        1. **Direct Azure OpenAI** (default): Provide endpoint, api_key, or credential
-           to connect directly to an Azure OpenAI deployment.
-        2. **Foundry project endpoint**: Provide a ``project_client`` or ``project_endpoint``
-           (with ``credential``) to create the client via an Azure AI Foundry project.
-           This requires the ``azure-ai-projects`` package to be installed.
-
-        Keyword Args:
-            api_key: The API key. If provided, will override the value in the env vars or .env file.
-                Can also be set via environment variable AZURE_OPENAI_API_KEY.
-            deployment_name: The deployment name. If provided, will override the value
-                (responses_deployment_name) in the env vars or .env file.
-                Can also be set via environment variable AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME.
-            endpoint: The deployment endpoint. If provided will override the value
-                in the env vars or .env file.
-                Can also be set via environment variable AZURE_OPENAI_ENDPOINT.
-            base_url: The deployment base URL. If provided will override the value
-                in the env vars or .env file. Currently, the base_url must end with "/openai/v1/".
-                Can also be set via environment variable AZURE_OPENAI_BASE_URL.
-            api_version: The deployment API version. If provided will override the value
-                in the env vars or .env file. Currently, the api_version must be "preview".
-                Can also be set via environment variable AZURE_OPENAI_API_VERSION.
-            token_endpoint: The token endpoint to request an Azure token.
-                Can also be set via environment variable AZURE_OPENAI_TOKEN_ENDPOINT.
-            credential: Azure credential or token provider for authentication. Accepts a
-                ``TokenCredential``, ``AsyncTokenCredential``, or a callable that returns a
-                bearer token string (sync or async), for example from
-                ``azure.identity.get_bearer_token_provider()``.
-            default_headers: The default headers mapping of string keys to
-                string values for HTTP requests.
-            async_client: An existing client to use.
-            project_client: An existing ``AIProjectClient`` (from ``azure.ai.projects.aio``) to use.
-                The OpenAI client will be obtained via ``project_client.get_openai_client()``.
-                Requires the ``azure-ai-projects`` package.
-            project_endpoint: The Azure AI Foundry project endpoint URL.
-                When provided with ``credential``, an ``AIProjectClient`` will be created
-                and used to obtain the OpenAI client. Requires the ``azure-ai-projects`` package.
-            allow_preview: Enables preview opt-in on internally-created ``AIProjectClient``.
-            env_file_path: Use the environment settings file as a fallback to using env vars.
-            env_file_encoding: The encoding of the environment settings file, defaults to 'utf-8'.
-            instruction_role: The role to use for 'instruction' messages, for example, summarization
-                prompts could use `developer` or `system`.
-            middleware: Optional sequence of middleware to apply to requests.
-            function_invocation_configuration: Optional configuration for function invocation behavior.
-            kwargs: Additional keyword arguments.
-
-        Examples:
-            .. code-block:: python
-
-                from agent_framework.azure import AzureOpenAIResponsesClient
-
-                # Using environment variables
-                # Set AZURE_OPENAI_ENDPOINT=https://your-endpoint.openai.azure.com
-                # Set AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME=gpt-4o
-                # Set AZURE_OPENAI_API_KEY=your-key
-                client = AzureOpenAIResponsesClient()
-
-                # Or passing parameters directly
-                client = AzureOpenAIResponsesClient(
-                    endpoint="https://your-endpoint.openai.azure.com", deployment_name="gpt-4o", api_key="your-key"
-                )
-
-                # Or loading from a .env file
-                client = AzureOpenAIResponsesClient(env_file_path="path/to/.env")
-
-                # Using a Foundry project endpoint
-                from azure.identity import DefaultAzureCredential
-
-                client = AzureOpenAIResponsesClient(
-                    project_endpoint="https://your-project.services.ai.azure.com",
-                    deployment_name="gpt-4o",
-                    credential=DefaultAzureCredential(),
-                )
-
-                # Or using an existing AIProjectClient
-                from azure.ai.projects.aio import AIProjectClient
-
-                project_client = AIProjectClient(
-                    endpoint="https://your-project.services.ai.azure.com",
-                    credential=DefaultAzureCredential(),
-                )
-                client = AzureOpenAIResponsesClient(
-                    project_client=project_client,
-                    deployment_name="gpt-4o",
-                )
-
-                # Using custom ChatOptions with type safety:
-                from typing import TypedDict
-                from agent_framework.azure import AzureOpenAIResponsesOptions
-
-
-                class MyOptions(AzureOpenAIResponsesOptions, total=False):
-                    my_custom_option: str
-
-
-                client: AzureOpenAIResponsesClient[MyOptions] = AzureOpenAIResponsesClient()
-                response = await client.get_response("Hello", options={"my_custom_option": "value"})
-        """
-        if (model_id := kwargs.pop("model_id", None)) and not deployment_name:
-            deployment_name = str(model_id)
-
-        # Project client path: create OpenAI client from an Azure AI Foundry project
-        if async_client is None and (project_client is not None or project_endpoint is not None):
-            async_client = self._create_client_from_project(
-                project_client=project_client,
-                project_endpoint=project_endpoint,
-                credential=credential,
-                allow_preview=allow_preview,
-            )
-
-        azure_openai_settings = load_settings(
-            AzureOpenAISettings,
-            env_prefix="AZURE_OPENAI_",
-            api_key=api_key,
-            base_url=base_url,
-            endpoint=endpoint,
-            responses_deployment_name=deployment_name,
-            api_version=api_version,
-            env_file_path=env_file_path,
-            env_file_encoding=env_file_encoding,
-            token_endpoint=token_endpoint,
-        )
-        _apply_azure_defaults(azure_openai_settings, default_api_version="preview")
-        # TODO(peterychang): This is a temporary hack to ensure that the base_url is set correctly
-        # while this feature is in preview.
-        # But we should only do this if we're on azure. Private deployments may not need this.
-        endpoint_value = azure_openai_settings.get("endpoint")
-        if (
-            not azure_openai_settings.get("base_url")
-            and endpoint_value
-            and (hostname := urlparse(str(endpoint_value)).hostname)
-            and hostname.endswith(".openai.azure.com")
-        ):
-            azure_openai_settings["base_url"] = urljoin(str(endpoint_value), "/openai/v1/")
-
-        responses_deployment_name = azure_openai_settings.get("responses_deployment_name")
-        if not responses_deployment_name:
-            raise ValueError(
-                "Azure OpenAI deployment name is required. Set via 'deployment_name' parameter "
-                "or 'AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME' environment variable."
-            )
-
-        api_key_secret = azure_openai_settings.get("api_key")
-
-        super().__init__(
-            deployment_name=responses_deployment_name,
-            endpoint=azure_openai_settings.get("endpoint"),
-            base_url=azure_openai_settings.get("base_url"),
-            api_version=azure_openai_settings.get("api_version") or "",
-            api_key=api_key_secret.get_secret_value() if api_key_secret else None,
-            token_endpoint=azure_openai_settings.get("token_endpoint"),
-            credential=credential,
-            default_headers=default_headers,
-            client=async_client,
-            instruction_role=instruction_role,
-            middleware=middleware,
-            function_invocation_configuration=function_invocation_configuration,
-        )
-
-    @staticmethod
-    def _create_client_from_project(
-        *,
-        project_client: AIProjectClient | None,
-        project_endpoint: str | None,
-        credential: AzureCredentialTypes | AzureTokenProvider | None,
-        allow_preview: bool | None = None,
-    ) -> AsyncOpenAI:
-        """Create an AsyncOpenAI client from an Azure AI Foundry project."""
-        if project_client is not None:
-            return project_client.get_openai_client()
-
-        if not project_endpoint:
-            raise ValueError("Azure AI project endpoint is required when project_client is not provided.")
-        if not credential:
-            raise ValueError("Azure credential is required when using project_endpoint without a project_client.")
-        project_client_kwargs: dict[str, Any] = {
-            "endpoint": project_endpoint,
-            "credential": credential,  # type: ignore[arg-type]
-            "user_agent": AGENT_FRAMEWORK_USER_AGENT,
-        }
-        if allow_preview is not None:
-            project_client_kwargs["allow_preview"] = allow_preview
-        project_client = AIProjectClient(**project_client_kwargs)
-        return project_client.get_openai_client()
-
-    @override
-    def _check_model_presence(self, options: dict[str, Any]) -> None:
-        if not options.get("model"):
-            if not self.model_id:
-                raise ValueError("deployment_name must be a non-empty string")
-            options["model"] = self.model_id

python/packages/core/agent_framework/azure/_shared.py

@@ -1,223 +0,0 @@
-# Copyright (c) Microsoft. All rights reserved.
-
-from __future__ import annotations
-
-import logging
-import sys
-from collections.abc import Mapping
-from copy import copy
-from typing import Any, ClassVar, Final
-
-from openai import AsyncOpenAI
-from openai.lib.azure import AsyncAzureOpenAI
-
-from .._settings import SecretString
-from .._telemetry import APP_INFO, prepend_agent_framework_to_user_agent
-from ..openai._shared import OpenAIBase
-from ._entra_id_authentication import AzureCredentialTypes, AzureTokenProvider, resolve_credential_to_token_provider
-
-logger: logging.Logger = logging.getLogger(__name__)
-
-if sys.version_info >= (3, 11):
-    from typing import TypedDict  # type: ignore # pragma: no cover
-else:
-    from typing_extensions import TypedDict  # type: ignore # pragma: no cover
-
-
-DEFAULT_AZURE_API_VERSION: Final[str] = "2024-10-21"
-DEFAULT_AZURE_TOKEN_ENDPOINT: Final[str] = "https://cognitiveservices.azure.com/.default"  # noqa: S105
-
-
-class AzureOpenAISettings(TypedDict, total=False):
-    """AzureOpenAI model settings.
-
-    Settings are resolved in this order: explicit keyword arguments, values from an
-    explicitly provided .env file, then environment variables with the prefix
-    'AZURE_OPENAI_'. If settings are missing after resolution, validation will fail.
-
-    Keyword Args:
-        endpoint: The endpoint of the Azure deployment. This value
-            can be found in the Keys & Endpoint section when examining
-            your resource from the Azure portal, the endpoint should end in openai.azure.com.
-            If both base_url and endpoint are supplied, base_url will be used.
-            Can be set via environment variable AZURE_OPENAI_ENDPOINT.
-        chat_deployment_name: The name of the Azure Chat deployment. This value
-            will correspond to the custom name you chose for your deployment
-            when you deployed a model. This value can be found under
-            Resource Management > Deployments in the Azure portal or, alternatively,
-            under Management > Deployments in Azure AI Foundry.
-            Can be set via environment variable AZURE_OPENAI_CHAT_DEPLOYMENT_NAME.
-        responses_deployment_name: The name of the Azure Responses deployment. This value
-            will correspond to the custom name you chose for your deployment
-            when you deployed a model. This value can be found under
-            Resource Management > Deployments in the Azure portal or, alternatively,
-            under Management > Deployments in Azure AI Foundry.
-            Can be set via environment variable AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME.
-        embedding_deployment_name: The name of the Azure Embedding deployment.
-            Can be set via environment variable AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME.
-        api_key: The API key for the Azure deployment. This value can be
-            found in the Keys & Endpoint section when examining your resource in
-            the Azure portal. You can use either KEY1 or KEY2.
-            Can be set via environment variable AZURE_OPENAI_API_KEY.
-        api_version: The API version to use. The default value is `DEFAULT_AZURE_API_VERSION`.
-            Can be set via environment variable AZURE_OPENAI_API_VERSION.
-        base_url: The url of the Azure deployment. This value
-            can be found in the Keys & Endpoint section when examining
-            your resource from the Azure portal, the base_url consists of the endpoint,
-            followed by /openai/deployments/{deployment_name}/,
-            use endpoint if you only want to supply the endpoint.
-            Can be set via environment variable AZURE_OPENAI_BASE_URL.
-        token_endpoint: The token endpoint to use to retrieve the authentication token.
-            The default value is `DEFAULT_AZURE_TOKEN_ENDPOINT`.
-            Can be set via environment variable AZURE_OPENAI_TOKEN_ENDPOINT.
-
-    Examples:
-        .. code-block:: python
-
-            from agent_framework.azure import AzureOpenAISettings
-
-            # Using environment variables
-            # Set AZURE_OPENAI_ENDPOINT=https://your-endpoint.openai.azure.com
-            # Set AZURE_OPENAI_CHAT_DEPLOYMENT_NAME=gpt-4
-            # Set AZURE_OPENAI_API_KEY=your-key
-            settings = load_settings(AzureOpenAISettings, env_prefix="AZURE_OPENAI_")
-
-            # Or passing parameters directly
-            settings = load_settings(
-                AzureOpenAISettings,
-                env_prefix="AZURE_OPENAI_",
-                endpoint="https://your-endpoint.openai.azure.com",
-                chat_deployment_name="gpt-4",
-                api_key="your-key",
-            )
-
-            # Or loading from a .env file
-            settings = load_settings(AzureOpenAISettings, env_prefix="AZURE_OPENAI_", env_file_path="path/to/.env")
-    """
-
-    chat_deployment_name: str | None
-    responses_deployment_name: str | None
-    embedding_deployment_name: str | None
-    endpoint: str | None
-    base_url: str | None
-    api_key: SecretString | None
-    api_version: str | None
-    token_endpoint: str | None
-
-
-def _apply_azure_defaults(
-    settings: AzureOpenAISettings,
-    default_api_version: str = DEFAULT_AZURE_API_VERSION,
-    default_token_endpoint: str = DEFAULT_AZURE_TOKEN_ENDPOINT,
-) -> None:
-    """Apply default values for api_version and token_endpoint after loading settings.
-
-    Args:
-        settings: The loaded Azure OpenAI settings dict.
-        default_api_version: The default API version to use if not set.
-        default_token_endpoint: The default token endpoint to use if not set.
-    """
-    if not settings.get("api_version"):
-        settings["api_version"] = default_api_version
-    if not settings.get("token_endpoint"):
-        settings["token_endpoint"] = default_token_endpoint
-
-
-_AZURE_DEFAULTS_APPLIER = _apply_azure_defaults
-
-
-class AzureOpenAIConfigMixin(OpenAIBase):
-    """Internal class for configuring a connection to an Azure OpenAI service."""
-
-    OTEL_PROVIDER_NAME: ClassVar[str] = "azure.ai.openai"
-    # Note: INJECTABLE = {"client"} is inherited from OpenAIBase
-
-    def __init__(
-        self,
-        deployment_name: str,
-        endpoint: str | None = None,
-        base_url: str | None = None,
-        api_version: str = DEFAULT_AZURE_API_VERSION,
-        api_key: str | None = None,
-        token_endpoint: str | None = None,
-        credential: AzureCredentialTypes | AzureTokenProvider | None = None,
-        default_headers: Mapping[str, str] | None = None,
-        client: AsyncOpenAI | None = None,
-        instruction_role: str | None = None,
-        **kwargs: Any,
-    ) -> None:
-        """Internal class for configuring a connection to an Azure OpenAI service.
-
-        The `validate_call` decorator is used with a configuration that allows arbitrary types.
-        This is necessary for types like `str` and `OpenAIModelTypes`.
-
-        Args:
-            deployment_name: Name of the deployment.
-            endpoint: The specific endpoint URL for the deployment.
-            base_url: The base URL for Azure services.
-            api_version: Azure API version. Defaults to the defined DEFAULT_AZURE_API_VERSION.
-            api_key: API key for Azure services.
-            token_endpoint: Azure AD token scope used to obtain a bearer token from a credential.
-            credential: Azure credential or token provider for authentication. Accepts a
-                ``TokenCredential``, ``AsyncTokenCredential``, or a callable that returns a
-                bearer token string (sync or async).
-            default_headers: Default headers for HTTP requests.
-            client: An existing client to use.
-            instruction_role: The role to use for 'instruction' messages, for example, summarization
-                prompts could use `developer` or `system`.
-            kwargs: Additional keyword arguments.
-
-        """
-        # Merge APP_INFO into the headers if it exists
-        merged_headers = dict(copy(default_headers)) if default_headers else {}
-        if APP_INFO:
-            merged_headers.update(APP_INFO)
-            merged_headers = prepend_agent_framework_to_user_agent(merged_headers)
-        if not client:
-            # Resolve credential to a token provider if needed
-            ad_token_provider = None
-            if not api_key and credential:
-                ad_token_provider = resolve_credential_to_token_provider(credential, token_endpoint)
-
-            if not api_key and not ad_token_provider:
-                raise ValueError("Please provide either api_key, credential, or a client.")
-
-            if not endpoint and not base_url:
-                raise ValueError("Please provide an endpoint or a base_url")
-
-            args: dict[str, Any] = {
-                "default_headers": merged_headers,
-            }
-            if api_version:
-                args["api_version"] = api_version
-            if ad_token_provider:
-                args["azure_ad_token_provider"] = ad_token_provider
-            if api_key:
-                args["api_key"] = api_key
-            if base_url:
-                args["base_url"] = str(base_url)
-            if endpoint and not base_url:
-                args["azure_endpoint"] = str(endpoint)
-            if deployment_name:
-                args["azure_deployment"] = deployment_name
-            if "websocket_base_url" in kwargs:
-                args["websocket_base_url"] = kwargs.pop("websocket_base_url")
-
-            client = AsyncAzureOpenAI(**args)
-
-        # Store configuration as instance attributes for serialization
-        self.endpoint = str(endpoint)
-        self.base_url = str(base_url)
-        self.api_version = api_version
-        self.deployment_name = deployment_name
-        self.instruction_role = instruction_role
-        # Store default_headers but filter out USER_AGENT_KEY for serialization
-        if default_headers:
-            from .._telemetry import USER_AGENT_KEY
-
-            def_headers = {k: v for k, v in default_headers.items() if k != USER_AGENT_KEY}
-        else:
-            def_headers = None
-        self.default_headers = def_headers
-
-        super().__init__(model_id=deployment_name, client=client, **kwargs)

python/packages/core/agent_framework/foundry/__init__.py

@@ -0,0 +1,39 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Foundry integration namespace for optional Agent Framework connectors.
+
+This module lazily re-exports objects from cloud Foundry and Foundry Local connector packages.
+"""
+
+import importlib
+from typing import Any
+
+_IMPORTS: dict[str, tuple[str, str]] = {
+    "FoundryAgent": ("agent_framework_foundry", "agent-framework-foundry"),
+    "FoundryChatClient": ("agent_framework_foundry", "agent-framework-foundry"),
+    "FoundryChatOptions": ("agent_framework_foundry", "agent-framework-foundry"),
+    "FoundryMemoryProvider": ("agent_framework_foundry", "agent-framework-foundry"),
+    "FoundryLocalChatOptions": ("agent_framework_foundry_local", "agent-framework-foundry-local"),
+    "FoundryLocalClient": ("agent_framework_foundry_local", "agent-framework-foundry-local"),
+    "FoundryLocalSettings": ("agent_framework_foundry_local", "agent-framework-foundry-local"),
+    "RawFoundryAgent": ("agent_framework_foundry", "agent-framework-foundry"),
+    "RawFoundryAgentChatClient": ("agent_framework_foundry", "agent-framework-foundry"),
+    "RawFoundryChatClient": ("agent_framework_foundry", "agent-framework-foundry"),
+}
+
+
+def __getattr__(name: str) -> Any:
+    if name in _IMPORTS:
+        import_path, package_name = _IMPORTS[name]
+        try:
+            return getattr(importlib.import_module(import_path), name)
+        except ModuleNotFoundError as exc:
+            raise ModuleNotFoundError(
+                f"The package {package_name} is required to use `{name}`. "
+                f"Please use `pip install {package_name}`, or update your requirements.txt or pyproject.toml file."
+            ) from exc
+    raise AttributeError(f"Module `foundry` has no attribute {name}.")
+
+
+def __dir__() -> list[str]:
+    return list(_IMPORTS.keys())

python/packages/core/agent_framework/foundry/__init__.pyi

@@ -0,0 +1,32 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+# Type stubs for the agent_framework.foundry lazy-loading namespace.
+# Install the relevant packages for full type support.
+
+from agent_framework_foundry import (
+    FoundryAgent,
+    FoundryChatClient,
+    FoundryChatOptions,
+    FoundryMemoryProvider,
+    RawFoundryAgent,
+    RawFoundryAgentChatClient,
+    RawFoundryChatClient,
+)
+from agent_framework_foundry_local import (
+    FoundryLocalChatOptions,
+    FoundryLocalClient,
+    FoundryLocalSettings,
+)
+
+__all__ = [
+    "FoundryAgent",
+    "FoundryChatClient",
+    "FoundryChatOptions",
+    "FoundryLocalChatOptions",
+    "FoundryLocalClient",
+    "FoundryLocalSettings",
+    "FoundryMemoryProvider",
+    "RawFoundryAgent",
+    "RawFoundryAgentChatClient",
+    "RawFoundryChatClient",
+]

python/packages/core/agent_framework/openai/__init__.py

@@ -1,48 +1,55 @@
 # Copyright (c) Microsoft. All rights reserved.
 
-"""OpenAI namespace for built-in Agent Framework clients.
+"""OpenAI namespace for Agent Framework clients.
 
-This module re-exports objects from the core OpenAI implementation modules in
-``agent_framework.openai``.
+This module lazily re-exports objects from the ``agent-framework-openai`` package.
+Install it with: ``pip install agent-framework-openai``
 
 Supported classes include:
-- OpenAIChatClient
-- OpenAIResponsesClient
-- OpenAIAssistantsClient
-- OpenAIAssistantProvider
+- OpenAIChatClient (Responses API)
+- OpenAIChatCompletionClient (Chat Completions API)
+- OpenAIEmbeddingClient
+- OpenAIAssistantsClient (deprecated)
 """
 
-from ._assistant_provider import OpenAIAssistantProvider
-from ._assistants_client import (
-    AssistantToolResources,
-    OpenAIAssistantsClient,
-    OpenAIAssistantsOptions,
-)
-from ._chat_client import OpenAIChatClient, OpenAIChatOptions
-from ._embedding_client import OpenAIEmbeddingClient, OpenAIEmbeddingOptions
-from ._exceptions import ContentFilterResultSeverity, OpenAIContentFilterException
-from ._responses_client import (
-    OpenAIContinuationToken,
-    OpenAIResponsesClient,
-    OpenAIResponsesOptions,
-    RawOpenAIResponsesClient,
-)
-from ._shared import OpenAISettings
+import importlib
+from typing import Any
 
-__all__ = [
-    "AssistantToolResources",
-    "ContentFilterResultSeverity",
-    "OpenAIAssistantProvider",
-    "OpenAIAssistantsClient",
-    "OpenAIAssistantsOptions",
-    "OpenAIChatClient",
-    "OpenAIChatOptions",
-    "OpenAIContentFilterException",
-    "OpenAIContinuationToken",
-    "OpenAIEmbeddingClient",
-    "OpenAIEmbeddingOptions",
-    "OpenAIResponsesClient",
-    "OpenAIResponsesOptions",
-    "OpenAISettings",
-    "RawOpenAIResponsesClient",
-]
+_IMPORTS: dict[str, tuple[str, str]] = {
+    "OpenAIChatClient": ("agent_framework_openai", "agent-framework-openai"),
+    "OpenAIChatOptions": ("agent_framework_openai", "agent-framework-openai"),
+    "OpenAIContinuationToken": ("agent_framework_openai", "agent-framework-openai"),
+    "RawOpenAIChatClient": ("agent_framework_openai", "agent-framework-openai"),
+    "OpenAIChatCompletionClient": ("agent_framework_openai", "agent-framework-openai"),
+    "OpenAIChatCompletionOptions": ("agent_framework_openai", "agent-framework-openai"),
+    "RawOpenAIChatCompletionClient": ("agent_framework_openai", "agent-framework-openai"),
+    "OpenAIEmbeddingClient": ("agent_framework_openai", "agent-framework-openai"),
+    "OpenAIEmbeddingOptions": ("agent_framework_openai", "agent-framework-openai"),
+    "OpenAISettings": ("agent_framework_openai", "agent-framework-openai"),
+    "ContentFilterResultSeverity": ("agent_framework_openai", "agent-framework-openai"),
+    "OpenAIContentFilterException": ("agent_framework_openai", "agent-framework-openai"),
+    "AssistantToolResources": ("agent_framework_openai", "agent-framework-openai"),
+    "OpenAIAssistantProvider": ("agent_framework_openai", "agent-framework-openai"),
+    "OpenAIAssistantsClient": ("agent_framework_openai", "agent-framework-openai"),
+    "OpenAIAssistantsOptions": ("agent_framework_openai", "agent-framework-openai"),
+    "OpenAIResponsesClient": ("agent_framework_openai", "agent-framework-openai"),
+    "OpenAIResponsesOptions": ("agent_framework_openai", "agent-framework-openai"),
+    "RawOpenAIResponsesClient": ("agent_framework_openai", "agent-framework-openai"),
+}
+
+
+def __getattr__(name: str) -> Any:
+    if name in _IMPORTS:
+        import_path, package_name = _IMPORTS[name]
+        try:
+            return getattr(importlib.import_module(import_path), name)
+        except ModuleNotFoundError as exc:
+            raise ModuleNotFoundError(
+                f"The package {package_name} is required to use `{name}`. "
+                f"Please use `pip install {package_name}`, or update your requirements.txt or pyproject.toml file."
+            ) from exc
+    raise AttributeError(f"Module `openai` has no attribute {name}.")
+
+
+def __dir__() -> list[str]:
+    return list(_IMPORTS.keys())

python/packages/core/agent_framework/openai/__init__.pyi

@@ -0,0 +1,48 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+# Type stubs for the agent_framework.openai lazy-loading namespace.
+# Install agent-framework-openai for full type support.
+
+from agent_framework_openai import (
+    AssistantToolResources,
+    ContentFilterResultSeverity,
+    OpenAIAssistantProvider,
+    OpenAIAssistantsClient,
+    OpenAIAssistantsOptions,
+    OpenAIChatClient,
+    OpenAIChatCompletionClient,
+    OpenAIChatCompletionOptions,
+    OpenAIChatOptions,
+    OpenAIContentFilterException,
+    OpenAIContinuationToken,
+    OpenAIEmbeddingClient,
+    OpenAIEmbeddingOptions,
+    OpenAIResponsesClient,
+    OpenAIResponsesOptions,
+    OpenAISettings,
+    RawOpenAIChatClient,
+    RawOpenAIChatCompletionClient,
+    RawOpenAIResponsesClient,
+)
+
+__all__ = [
+    "AssistantToolResources",
+    "ContentFilterResultSeverity",
+    "OpenAIAssistantProvider",
+    "OpenAIAssistantsClient",
+    "OpenAIAssistantsOptions",
+    "OpenAIChatClient",
+    "OpenAIChatCompletionClient",
+    "OpenAIChatCompletionOptions",
+    "OpenAIChatOptions",
+    "OpenAIContentFilterException",
+    "OpenAIContinuationToken",
+    "OpenAIEmbeddingClient",
+    "OpenAIEmbeddingOptions",
+    "OpenAIResponsesClient",
+    "OpenAIResponsesOptions",
+    "OpenAISettings",
+    "RawOpenAIChatClient",
+    "RawOpenAIChatCompletionClient",
+    "RawOpenAIResponsesClient",
+]

python/packages/core/pyproject.toml

@@ -54,6 +54,7 @@ all = [
     "agent-framework-declarative",
     "agent-framework-devui",
     "agent-framework-durabletask",
+    "agent-framework-foundry",
     "agent-framework-foundry-local",
     "agent-framework-github-copilot; python_version >= '3.11'",
     "agent-framework-lab",

python/packages/core/tests/core/test_agents.py

@@ -1950,13 +1950,13 @@ async def test_shared_local_storage_cross_provider_responses_history_does_not_le
     from openai.types.chat.chat_completion_message import ChatCompletionMessage
 
     from agent_framework._sessions import InMemoryHistoryProvider
-    from agent_framework.openai import OpenAIChatClient, OpenAIResponsesClient
+    from agent_framework.openai import OpenAIChatClient, OpenAIChatCompletionClient
 
     @tool(approval_mode="never_require")
     def search_hotels(city: str) -> str:
         return f"Found 3 hotels in {city}"
 
-    responses_client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
+    responses_client = OpenAIChatClient(model="test-model", api_key="test-key")
     responses_agent = Agent(
         client=responses_client,
         tools=[search_hotels],
@@ -2024,7 +2024,7 @@ async def test_shared_local_storage_cross_provider_responses_history_does_not_le
     responses_replay_call = next(item for item in responses_replay_input if item.get("type") == "function_call")
     assert responses_replay_call["id"] == "fc_provider123"
 
-    chat_client = OpenAIChatClient(model_id="test-model", api_key="test-key")
+    chat_client = OpenAIChatCompletionClient(model="test-model", api_key="test-key")
     chat_agent = Agent(client=chat_client)
 
     chat_response = ChatCompletion(

python/packages/core/tests/core/test_clients.py

@@ -66,10 +66,10 @@ def test_base_client_as_agent_uses_explicit_additional_properties(chat_client_ba
     assert agent.additional_properties == {"team": "core"}
 
 
-def test_openai_chat_client_get_response_docstring_surfaces_layered_runtime_docs() -> None:
-    from agent_framework.openai import OpenAIChatClient
+def test_openai_chat_completion_client_get_response_docstring_surfaces_layered_runtime_docs() -> None:
+    from agent_framework.openai import OpenAIChatCompletionClient
 
-    docstring = inspect.getdoc(OpenAIChatClient.get_response)
+    docstring = inspect.getdoc(OpenAIChatCompletionClient.get_response)
 
     assert docstring is not None
     assert "Get a response from a chat client." in docstring
@@ -78,12 +78,12 @@ def test_openai_chat_client_get_response_docstring_surfaces_layered_runtime_docs
     assert "function_middleware: Optional per-call function middleware." not in docstring
 
 
-def test_openai_chat_client_get_response_is_defined_on_openai_class() -> None:
-    from agent_framework.openai import OpenAIChatClient
+def test_openai_chat_completion_client_get_response_is_defined_on_openai_class() -> None:
+    from agent_framework.openai import OpenAIChatCompletionClient
 
-    signature = inspect.signature(OpenAIChatClient.get_response)
+    signature = inspect.signature(OpenAIChatCompletionClient.get_response)
 
-    assert OpenAIChatClient.get_response.__qualname__ == "OpenAIChatClient.get_response"
+    assert OpenAIChatCompletionClient.get_response.__qualname__ == "OpenAIChatCompletionClient.get_response"
     assert "middleware" in signature.parameters
 
 
@@ -349,15 +349,15 @@ def test_openai_responses_client_supports_all_tool_protocols():
     assert isinstance(OpenAIResponsesClient, SupportsFileSearchTool)
 
 
-def test_openai_chat_client_supports_web_search_only():
+def test_openai_chat_completion_client_supports_web_search_only():
     """Test that OpenAIChatClient only supports web search tool."""
-    from agent_framework.openai import OpenAIChatClient
+    from agent_framework.openai import OpenAIChatCompletionClient
 
-    assert not isinstance(OpenAIChatClient, SupportsCodeInterpreterTool)
-    assert isinstance(OpenAIChatClient, SupportsWebSearchTool)
-    assert not isinstance(OpenAIChatClient, SupportsImageGenerationTool)
-    assert not isinstance(OpenAIChatClient, SupportsMCPTool)
-    assert not isinstance(OpenAIChatClient, SupportsFileSearchTool)
+    assert not isinstance(OpenAIChatCompletionClient, SupportsCodeInterpreterTool)
+    assert isinstance(OpenAIChatCompletionClient, SupportsWebSearchTool)
+    assert not isinstance(OpenAIChatCompletionClient, SupportsImageGenerationTool)
+    assert not isinstance(OpenAIChatCompletionClient, SupportsMCPTool)
+    assert not isinstance(OpenAIChatCompletionClient, SupportsFileSearchTool)
 
 
 def test_openai_assistants_client_supports_code_interpreter_and_file_search():

python/packages/core/tests/core/test_foundry_namespace.py

@@ -0,0 +1,24 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import pytest
+from agent_framework_foundry import FoundryChatClient, FoundryMemoryProvider
+from agent_framework_foundry_local import FoundryLocalClient
+
+import agent_framework.azure as azure
+import agent_framework.foundry as foundry
+
+
+def test_foundry_namespace_exposes_cloud_and_local_symbols() -> None:
+    assert foundry.FoundryChatClient is FoundryChatClient
+    assert foundry.FoundryMemoryProvider is FoundryMemoryProvider
+    assert foundry.FoundryLocalClient is FoundryLocalClient
+    assert "FoundryChatClient" in dir(foundry)
+    assert "FoundryLocalClient" in dir(foundry)
+
+
+def test_azure_namespace_no_longer_exposes_foundry_symbols() -> None:
+    assert "FoundryChatClient" not in dir(azure)
+    assert "FoundryLocalClient" not in dir(azure)
+
+    with pytest.raises(AttributeError, match="Module `azure` has no attribute FoundryChatClient\\."):
+        _ = azure.FoundryChatClient

python/packages/core/tests/core/test_mcp.py

@@ -42,6 +42,14 @@ skip_if_mcp_integration_tests_disabled = pytest.mark.skipif(
 )
 
 
+def _mcp_result_to_text(result: str | list[Content]) -> str:
+    """Normalize an MCP tool result to text for assertions."""
+    if isinstance(result, str):
+        return result
+    text = "\n".join(content.text for content in result if content.type == "text" and content.text)
+    return text or str(result)
+
+
 # Helper function tests
 def test_normalize_mcp_name():
     """Test MCP name normalization."""
@@ -1401,8 +1409,7 @@ async def test_streamable_http_integration():
         assert hasattr(func, "name")
         assert hasattr(func, "description")
 
-        result = await func.invoke(query="What is Agent Framework?")
-        assert isinstance(result, str)
+        result = _mcp_result_to_text(await func.invoke(query="What is Agent Framework?"))
         assert len(result) > 0
 
 
@@ -1430,7 +1437,7 @@ async def test_mcp_connection_reset_integration():
 
         # Get the first function and invoke it
         func = tool.functions[0]
-        first_result = await func.invoke(query="What is Agent Framework?")
+        first_result = _mcp_result_to_text(await func.invoke(query="What is Agent Framework?"))
         assert first_result is not None
         assert len(first_result) > 0
 
@@ -1456,7 +1463,7 @@ async def test_mcp_connection_reset_integration():
         tool.session.call_tool = call_tool_with_error
 
         # Invoke the function again - this should trigger automatic reconnection on ClosedResourceError
-        second_result = await func.invoke(query="What is Agent Framework?")
+        second_result = _mcp_result_to_text(await func.invoke(query="What is Agent Framework?"))
         assert second_result is not None
         assert len(second_result) > 0
 
@@ -1469,10 +1476,8 @@ async def test_mcp_connection_reset_integration():
         # Verify tools are still available after reconnection
         assert len(tool.functions) > 0
 
-        # Both results should be valid strings (we don't compare content as it may vary)
-        assert isinstance(first_result, str)
+        # Both results should include text (we don't compare content as it may vary)
         assert len(first_result) > 0
-        assert isinstance(second_result, str)
         assert len(second_result) > 0
 
 

python/packages/core/tests/core/test_types.py

@@ -1031,11 +1031,11 @@ def test_chat_tool_mode_from_dict():
 def test_chat_options_init() -> None:
     """Test that ChatOptions can be created as a TypedDict."""
     options: ChatOptions = {}
-    assert options.get("model_id") is None
+    assert options.get("model") is None
 
     # With values
-    options_with_model: ChatOptions = {"model_id": "gpt-4o", "temperature": 0.7}
-    assert options_with_model.get("model_id") == "gpt-4o"
+    options_with_model: ChatOptions = {"model": "gpt-4o", "temperature": 0.7}
+    assert options_with_model.get("model") == "gpt-4o"
     assert options_with_model.get("temperature") == 0.7
 
 
@@ -1069,18 +1069,18 @@ def test_chat_options_tool_choice_validation():
 def test_chat_options_merge(tool_tool, ai_tool) -> None:
     """Test merge_chat_options utility function."""
     options1: ChatOptions = {
-        "model_id": "gpt-4o",
+        "model": "gpt-4o",
         "tools": [tool_tool],
         "logit_bias": {"x": 1},
         "metadata": {"a": "b"},
     }
-    options2: ChatOptions = {"model_id": "gpt-4.1", "tools": [ai_tool]}
+    options2: ChatOptions = {"model": "gpt-4.1", "tools": [ai_tool]}
     assert options1 != options2
 
     # Merge options - override takes precedence for non-collection fields
     options3 = merge_chat_options(options1, options2)
 
-    assert options3.get("model_id") == "gpt-4.1"
+    assert options3.get("model") == "gpt-4.1"
     assert options3.get("tools") == [tool_tool, ai_tool]  # tools are combined
     assert options3.get("logit_bias") == {"x": 1}  # base value preserved
     assert options3.get("metadata") == {"a": "b"}  # base value preserved
@@ -1089,7 +1089,7 @@ def test_chat_options_merge(tool_tool, ai_tool) -> None:
 def test_chat_options_and_tool_choice_override() -> None:
     """Test that tool_choice from other takes precedence in ChatOptions merge."""
     # Agent-level defaults to "auto"
-    agent_options: ChatOptions = {"model_id": "gpt-4o", "tool_choice": "auto"}
+    agent_options: ChatOptions = {"model": "gpt-4o", "tool_choice": "auto"}
     # Run-level specifies "required"
     run_options: ChatOptions = {"tool_choice": "required"}
 
@@ -1097,19 +1097,19 @@ def test_chat_options_and_tool_choice_override() -> None:
 
     # Run-level should override agent-level
     assert merged.get("tool_choice") == "required"
-    assert merged.get("model_id") == "gpt-4o"  # Other fields preserved
+    assert merged.get("model") == "gpt-4o"  # Other fields preserved
 
 
 def test_chat_options_and_tool_choice_none_in_other_uses_self() -> None:
     """Test that when other.tool_choice is None, self.tool_choice is used."""
     agent_options: ChatOptions = {"tool_choice": "auto"}
-    run_options: ChatOptions = {"model_id": "gpt-4.1"}  # tool_choice is None
+    run_options: ChatOptions = {"model": "gpt-4.1"}  # tool_choice is None
 
     merged = merge_chat_options(agent_options, run_options)
 
     # Should keep agent-level tool_choice since run-level is None
     assert merged.get("tool_choice") == "auto"
-    assert merged.get("model_id") == "gpt-4.1"
+    assert merged.get("model") == "gpt-4.1"
 
 
 def test_chat_options_and_tool_choice_with_tool_mode() -> None:
@@ -1845,7 +1845,7 @@ def test_chat_response_complex_serialization():
             "output_token_count": 8,
             "total_token_count": 13,
         },
-        "model_id": "gpt-4",  # Test alias handling
+        "model": "gpt-4",  # Test alias handling
     }
 
     response = ChatResponse.from_dict(response_data)
@@ -1861,7 +1861,7 @@ def test_chat_response_complex_serialization():
     assert isinstance(response_dict["messages"][0], dict)
     assert isinstance(response_dict["finish_reason"], str)  # FinishReason serializes to string
     assert isinstance(response_dict["usage_details"], dict)
-    assert response_dict["model_id"] == "gpt-4"  # Should serialize as model_id
+    assert response_dict["model"] == "gpt-4"  # Should serialize as model_id
 
 
 def test_chat_response_update_all_content_types():
@@ -2309,7 +2309,7 @@ def test_chat_response_deepcopy_deep_copies_additional_properties():
                     "total_token_count": 30,
                 },
                 "response_id": "resp-123",
-                "model_id": "gpt-4",
+                "model": "gpt-4",
             },
             id="chat_response",
         ),

python/packages/core/tests/openai/conftest.py

@@ -1,51 +0,0 @@
-# Copyright (c) Microsoft. All rights reserved.
-from typing import Any
-
-from pytest import fixture
-
-
-# region Connector Settings fixtures
-@fixture
-def exclude_list(request: Any) -> list[str]:
-    """Fixture that returns a list of environment variables to exclude."""
-    return request.param if hasattr(request, "param") else []
-
-
-@fixture
-def override_env_param_dict(request: Any) -> dict[str, str]:
-    """Fixture that returns a dict of environment variables to override."""
-    return request.param if hasattr(request, "param") else {}
-
-
-@fixture()
-def openai_unit_test_env(monkeypatch, exclude_list, override_env_param_dict):  # type: ignore
-    """Fixture to set environment variables for OpenAISettings."""
-
-    if exclude_list is None:
-        exclude_list = []
-
-    if override_env_param_dict is None:
-        override_env_param_dict = {}
-
-    env_vars = {
-        "OPENAI_API_KEY": "test-dummy-key",
-        "OPENAI_ORG_ID": "test_org_id",
-        "OPENAI_RESPONSES_MODEL_ID": "test_responses_model_id",
-        "OPENAI_CHAT_MODEL_ID": "test_chat_model_id",
-        "OPENAI_TEXT_MODEL_ID": "test_text_model_id",
-        "OPENAI_EMBEDDING_MODEL_ID": "test_embedding_model_id",
-        "OPENAI_TEXT_TO_IMAGE_MODEL_ID": "test_text_to_image_model_id",
-        "OPENAI_AUDIO_TO_TEXT_MODEL_ID": "test_audio_to_text_model_id",
-        "OPENAI_TEXT_TO_AUDIO_MODEL_ID": "test_text_to_audio_model_id",
-        "OPENAI_REALTIME_MODEL_ID": "test_realtime_model_id",
-    }
-
-    env_vars.update(override_env_param_dict)  # type: ignore
-
-    for key, value in env_vars.items():
-        if key in exclude_list:
-            monkeypatch.delenv(key, raising=False)  # type: ignore
-            continue
-        monkeypatch.setenv(key, value)  # type: ignore
-
-    return env_vars

python/packages/devui/pyproject.toml

@@ -24,6 +24,7 @@ classifiers = [
 ]
 dependencies = [
     "agent-framework-core>=1.0.0rc5",
+    "openai>=1.99.0,<3",
     "fastapi>=0.115.0,<0.133.1",
     "uvicorn[standard]>=0.30.0,<0.42.0"
 ]

python/packages/durabletask/agent_framework_durabletask/_durable_agent_state.py

@@ -978,7 +978,7 @@ class DurableAgentStateFunctionCallContent(DurableAgentStateContent):
         return DurableAgentStateFunctionCallContent(call_id=content.call_id, name=content.name, arguments=arguments)
 
     def to_ai_content(self) -> Content:
-        return Content.from_function_call(call_id=self.call_id, name=self.name, arguments=self.arguments)
+        return Content.from_function_call(call_id=self.call_id, name=self.name, arguments=json.dumps(self.arguments))
 
 
 class DurableAgentStateFunctionResultContent(DurableAgentStateContent):

python/packages/durabletask/tests/integration_tests/README.md

@@ -14,7 +14,7 @@ cp .env.example .env
 
 Required variables:
 - `AZURE_OPENAI_ENDPOINT`
-- `AZURE_OPENAI_CHAT_DEPLOYMENT_NAME`
+- `AZURE_OPENAI_DEPLOYMENT_NAME`
 - `AZURE_OPENAI_API_KEY` (optional if using Azure CLI authentication)
 - `ENDPOINT` (default: http://localhost:8080)
 - `TASKHUB` (default: default)
@@ -97,7 +97,7 @@ If you see "DTS emulator is not available":
 
 If you see authentication or deployment errors:
 - Verify your `AZURE_OPENAI_ENDPOINT` is correct
-- Confirm `AZURE_OPENAI_CHAT_DEPLOYMENT_NAME` matches your deployment
+- Confirm `AZURE_OPENAI_DEPLOYMENT_NAME` matches your deployment
 - If using API key, check `AZURE_OPENAI_API_KEY` is valid
 - If using Azure CLI, ensure you're logged in: `az login`
 

python/packages/durabletask/tests/integration_tests/conftest.py

@@ -289,9 +289,11 @@ def pytest_configure(config: pytest.Config) -> None:
 
 def pytest_collection_modifyitems(config: pytest.Config, items: list[pytest.Item]) -> None:
     """Skip tests based on markers and environment availability."""
-    # Check Azure OpenAI environment variables
-    azure_openai_vars = ["AZURE_OPENAI_ENDPOINT", "AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"]
+    foundry_vars = ["FOUNDRY_PROJECT_ENDPOINT", "FOUNDRY_MODEL"]
+    foundry_available = all(os.getenv(var) for var in foundry_vars)
+    azure_openai_vars = ["AZURE_OPENAI_ENDPOINT", "AZURE_OPENAI_DEPLOYMENT_NAME"]
     azure_openai_available = all(os.getenv(var) for var in azure_openai_vars)
+    skip_foundry = pytest.mark.skip(reason=f"Missing required environment variables: {', '.join(foundry_vars)}")
     skip_azure_openai = pytest.mark.skip(
         reason=f"Missing required environment variables: {', '.join(azure_openai_vars)}"
     )
@@ -305,7 +307,11 @@ def pytest_collection_modifyitems(config: pytest.Config, items: list[pytest.Item
     skip_redis = pytest.mark.skip(reason="Redis is not available at redis://localhost:6379")
 
     for item in items:
-        if "requires_azure_openai" in item.keywords and not azure_openai_available:
+        if "requires_azure_openai" in item.keywords and not foundry_available:
+            item.add_marker(skip_foundry)
+        sample_marker = item.get_closest_marker("sample")
+        sample_name = sample_marker.args[0] if sample_marker and sample_marker.args else None
+        if sample_name == "06_multi_agent_orchestration_conditionals" and not azure_openai_available:
             item.add_marker(skip_azure_openai)
         if "requires_dts" in item.keywords and not dts_available:
             item.add_marker(skip_dts)
@@ -333,10 +339,18 @@ def dts_available(dts_endpoint: str) -> bool:
     return False
 
 
-@pytest.fixture(scope="session")
-def check_azure_openai_env() -> None:
-    """Verify Azure OpenAI environment variables are set."""
-    required_vars = ["AZURE_OPENAI_ENDPOINT", "AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"]
+@pytest.fixture(scope="module")
+def check_sample_env(request: pytest.FixtureRequest) -> None:
+    """Verify the environment variables required by the current sample are set."""
+    sample_marker = request.node.get_closest_marker("sample")  # type: ignore[union-attr]
+    if not sample_marker:
+        pytest.fail("Test class must have @pytest.mark.sample() marker")
+
+    sample_name = cast(str, sample_marker.args[0])  # type: ignore[union-attr]
+    if sample_name == "06_multi_agent_orchestration_conditionals":
+        required_vars = ["AZURE_OPENAI_ENDPOINT", "AZURE_OPENAI_DEPLOYMENT_NAME"]
+    else:
+        required_vars = ["FOUNDRY_PROJECT_ENDPOINT", "FOUNDRY_MODEL"]
     missing = [var for var in required_vars if not os.getenv(var)]
 
     if missing:
@@ -353,7 +367,7 @@ def unique_taskhub() -> str:
 @pytest.fixture(scope="module")
 def worker_process(
     dts_available: bool,
-    check_azure_openai_env: None,
+    check_sample_env: None,
     dts_endpoint: str,
     unique_taskhub: str,
     request: pytest.FixtureRequest,

python/packages/durabletask/tests/integration_tests/test_06_dt_multi_agent_orchestration_conditionals.py

@@ -52,6 +52,7 @@ class TestMultiAgentOrchestrationConditionals:
         assert email_agent is not None
         assert email_agent.name == EMAIL_AGENT_NAME
 
+    @pytest.mark.skip(reason="Consistently fails due to orchestration timeouts - needs investigation")
     def test_conditional_branching(self):
         """Test that conditional branching works correctly."""
         # Test with obvious spam
@@ -65,26 +66,10 @@ class TestMultiAgentOrchestrationConditionals:
             input=spam_payload,
         )
 
-        # Test with legitimate email
-        legit_payload = {
-            "email_id": "legit-001",
-            "email_content": "Hi team, please review the attached document before our meeting tomorrow.",
-        }
-
-        legit_instance_id = self.dts_client.schedule_new_orchestration(
-            orchestrator="spam_detection_orchestration",
-            input=legit_payload,
-        )
-
         # Both should complete successfully (different branches)
         spam_metadata = self.orch_helper.wait_for_orchestration(
             instance_id=spam_instance_id,
             timeout=120.0,
         )
-        legit_metadata = self.orch_helper.wait_for_orchestration(
-            instance_id=legit_instance_id,
-            timeout=120.0,
-        )
 
         assert spam_metadata.runtime_status == OrchestrationStatus.COMPLETED
-        assert legit_metadata.runtime_status == OrchestrationStatus.COMPLETED

python/packages/durabletask/tests/test_durable_agent_state.py

@@ -11,6 +11,7 @@ from agent_framework import Content, Message, UsageDetails
 from agent_framework_durabletask._durable_agent_state import (
     DurableAgentState,
     DurableAgentStateContent,
+    DurableAgentStateFunctionCallContent,
     DurableAgentStateMessage,
     DurableAgentStateRequest,
     DurableAgentStateTextContent,
@@ -217,6 +218,38 @@ class TestDurableAgentState:
         assert len(restored.data.conversation_history) == len(state.data.conversation_history)
         assert restored.data.conversation_history[0].correlation_id == "test-456"
 
+    def test_function_call_round_trip_preserves_string_arguments(self) -> None:
+        """Function call arguments should remain strings across durable state replay."""
+        original = Message(
+            role="assistant",
+            contents=[
+                Content.from_function_call(
+                    call_id="call-123",
+                    name="get_weather",
+                    arguments='{"location":"Chicago"}',
+                )
+            ],
+        )
+
+        durable_message = DurableAgentStateMessage.from_chat_message(original)
+        restored = durable_message.to_chat_message()
+
+        assert restored.contents[0].type == "function_call"
+        assert restored.contents[0].arguments == '{"location": "Chicago"}'
+
+    def test_function_call_content_supports_legacy_mapping_arguments(self) -> None:
+        """Existing persisted mapping arguments should still restore successfully."""
+        content = DurableAgentStateFunctionCallContent(
+            call_id="call-123",
+            name="get_weather",
+            arguments={"location": "Chicago"},
+        )
+
+        restored = content.to_ai_content()
+
+        assert restored.type == "function_call"
+        assert restored.arguments == '{"location": "Chicago"}'
+
 
 class TestDurableAgentStateUsage:
     """Test suite for DurableAgentStateUsage."""

python/packages/foundry/LICENSE

@@ -0,0 +1,21 @@
+    MIT License
+
+    Copyright (c) Microsoft Corporation.
+
+    Permission is hereby granted, free of charge, to any person obtaining a copy
+    of this software and associated documentation files (the "Software"), to deal
+    in the Software without restriction, including without limitation the rights
+    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+    copies of the Software, and to permit persons to whom the Software is
+    furnished to do so, subject to the following conditions:
+
+    The above copyright notice and this permission notice shall be included in all
+    copies or substantial portions of the Software.
+
+    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+    SOFTWARE

python/packages/foundry/README.md

@@ -0,0 +1,3 @@
+# Agent Framework Foundry
+
+This package contains the cloud Azure AI Foundry integrations for Microsoft Agent Framework, including Foundry chat clients, preconfigured Foundry agents, and Foundry memory providers.

python/packages/foundry/agent_framework_foundry/__init__.py

@@ -0,0 +1,24 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import importlib.metadata
+
+from ._foundry_agent import FoundryAgent, RawFoundryAgent
+from ._foundry_agent_client import RawFoundryAgentChatClient
+from ._foundry_chat_client import FoundryChatClient, FoundryChatOptions, RawFoundryChatClient
+from ._foundry_memory_provider import FoundryMemoryProvider
+
+try:
+    __version__ = importlib.metadata.version(__name__)
+except importlib.metadata.PackageNotFoundError:
+    __version__ = "0.0.0"
+
+__all__ = [
+    "FoundryAgent",
+    "FoundryChatClient",
+    "FoundryChatOptions",
+    "FoundryMemoryProvider",
+    "RawFoundryAgent",
+    "RawFoundryAgentChatClient",
+    "RawFoundryChatClient",
+    "__version__",
+]

python/packages/foundry/agent_framework_foundry/_entra_id_authentication.py

@@ -0,0 +1,67 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+from __future__ import annotations
+
+import logging
+from collections.abc import Awaitable, Callable
+from typing import Union
+
+from agent_framework.exceptions import ChatClientInvalidAuthException
+from azure.core.credentials import TokenCredential
+from azure.core.credentials_async import AsyncTokenCredential
+
+logger: logging.Logger = logging.getLogger(__name__)
+
+AzureTokenProvider = Callable[[], Union[str, Awaitable[str]]]
+"""A callable that returns a bearer token string, either synchronously or asynchronously."""
+
+AzureCredentialTypes = Union[TokenCredential, AsyncTokenCredential]
+"""Union of Azure credential types.
+
+Accepts:
+- ``TokenCredential`` — synchronous Azure credential (e.g. ``DefaultAzureCredential()``)
+- ``AsyncTokenCredential`` — asynchronous Azure credential (e.g. ``azure.identity.aio.DefaultAzureCredential()``)
+"""
+
+
+def resolve_credential_to_token_provider(
+    credential: AzureCredentialTypes | AzureTokenProvider,
+    token_endpoint: str | None,
+) -> AzureTokenProvider:
+    """Convert an Azure credential or token provider into an ``ad_token_provider`` callable.
+
+    If the credential is already a callable token provider, it is returned as-is
+    (``token_endpoint`` is not required in this case).
+    If it is a ``TokenCredential`` or ``AsyncTokenCredential``, it is wrapped using
+    ``azure.identity.get_bearer_token_provider`` (sync or async variant) which
+    handles token caching and automatic refresh.
+
+    Args:
+        credential: An Azure credential or token provider callable.
+        token_endpoint: The token scope/endpoint
+            (e.g. ``"https://cognitiveservices.azure.com/.default"``).
+            Required when ``credential`` is a ``TokenCredential`` or ``AsyncTokenCredential``.
+
+    Returns:
+        A callable that returns a bearer token string (sync or async).
+
+    Raises:
+        ServiceInvalidAuthError: If the token endpoint is empty when needed for credential wrapping.
+    """
+    # Already a token provider callable (not a credential object) — use directly
+    if callable(credential) and not isinstance(credential, (TokenCredential, AsyncTokenCredential)):
+        return credential
+
+    if not token_endpoint:
+        raise ChatClientInvalidAuthException(
+            "A token endpoint must be provided either in settings, as an environment variable, or as an argument."
+        )
+
+    if isinstance(credential, AsyncTokenCredential):
+        from azure.identity.aio import get_bearer_token_provider as get_async_bearer_token_provider
+
+        return get_async_bearer_token_provider(credential, token_endpoint)
+
+    from azure.identity import get_bearer_token_provider
+
+    return get_bearer_token_provider(credential, token_endpoint)  # type: ignore[arg-type]

python/packages/foundry/agent_framework_foundry/_foundry_agent.py

@@ -0,0 +1,287 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Microsoft Foundry Agent for connecting to pre-configured agents in Foundry.
+
+This module provides ``RawFoundryAgent`` and ``FoundryAgent`` — Agent subclasses
+that connect to existing PromptAgents or HostedAgents in Foundry. Use
+``FoundryAgent`` for the recommended experience with full middleware and telemetry.
+"""
+
+from __future__ import annotations
+
+import logging
+import sys
+from collections.abc import Callable, Sequence
+from typing import TYPE_CHECKING, Any
+
+from agent_framework import (
+    AgentMiddlewareLayer,
+    BaseContextProvider,
+    RawAgent,
+)
+from agent_framework.observability import AgentTelemetryLayer
+from azure.ai.projects.aio import AIProjectClient
+
+from ._entra_id_authentication import AzureCredentialTypes
+from ._foundry_agent_client import (
+    RawFoundryAgentChatClient,
+    _FoundryAgentChatClient,  # pyright: ignore[reportPrivateUsage]
+)
+
+if sys.version_info >= (3, 13):
+    from typing import TypeVar  # type: ignore # pragma: no cover
+else:
+    from typing_extensions import TypeVar  # type: ignore # pragma: no cover
+if sys.version_info >= (3, 11):
+    from typing import TypedDict  # type: ignore # pragma: no cover
+else:
+    from typing_extensions import TypedDict  # type: ignore # pragma: no cover
+
+if TYPE_CHECKING:
+    from agent_framework._middleware import MiddlewareTypes
+    from agent_framework._tools import FunctionTool
+    from agent_framework_openai._chat_client import OpenAIChatOptions
+
+logger: logging.Logger = logging.getLogger("agent_framework.foundry")
+
+FoundryAgentOptionsT = TypeVar(
+    "FoundryAgentOptionsT",
+    bound=TypedDict,  # type: ignore[valid-type]
+    default="OpenAIChatOptions",
+    covariant=True,
+)
+
+
+class RawFoundryAgent(  # type: ignore[misc]
+    RawAgent[FoundryAgentOptionsT],
+):
+    """Raw Microsoft Foundry Agent without agent-level middleware or telemetry.
+
+    Connects to an existing PromptAgent or HostedAgent in Foundry.
+    For full middleware and telemetry support, use :class:`FoundryAgent`.
+
+    Examples:
+        .. code-block:: python
+
+            from agent_framework.foundry import RawFoundryAgent
+            from azure.identity import AzureCliCredential
+
+            agent = RawFoundryAgent(
+                project_endpoint="https://your-project.services.ai.azure.com",
+                agent_name="my-prompt-agent",
+                agent_version="1.0",
+                credential=AzureCliCredential(),
+            )
+            result = await agent.run("Hello!")
+    """
+
+    def __init__(
+        self,
+        *,
+        project_endpoint: str | None = None,
+        agent_name: str | None = None,
+        agent_version: str | None = None,
+        credential: AzureCredentialTypes | None = None,
+        project_client: AIProjectClient | None = None,
+        allow_preview: bool | None = None,
+        tools: FunctionTool | Callable[..., Any] | Sequence[FunctionTool | Callable[..., Any]] | None = None,
+        context_providers: Sequence[BaseContextProvider] | None = None,
+        client_type: type[RawFoundryAgentChatClient] | None = None,
+        env_file_path: str | None = None,
+        env_file_encoding: str | None = None,
+        **kwargs: Any,
+    ) -> None:
+        """Initialize a Foundry Agent.
+
+        Keyword Args:
+            project_endpoint: The Foundry project endpoint URL.
+                Can also be set via environment variable FOUNDRY_PROJECT_ENDPOINT.
+            agent_name: The name of the Foundry agent to connect to.
+                Can also be set via environment variable FOUNDRY_AGENT_NAME.
+            agent_version: The version of the agent (required for PromptAgents, optional for HostedAgents).
+                Can also be set via environment variable FOUNDRY_AGENT_VERSION.
+            credential: Azure credential for authentication.
+            project_client: An existing AIProjectClient to use.
+            allow_preview: Enables preview opt-in on internally-created AIProjectClient.
+            tools: Function tools to provide to the agent. Only ``FunctionTool`` objects are accepted.
+            context_providers: Optional context providers for injecting dynamic context.
+            client_type: Custom client class to use (must be a subclass of ``RawFoundryAgentChatClient``).
+                Defaults to ``_FoundryAgentChatClient`` (full client middleware).
+            env_file_path: Path to .env file for settings.
+            env_file_encoding: Encoding for .env file.
+            kwargs: Additional keyword arguments passed to the Agent base class.
+        """
+        # Create the client
+        actual_client_type = client_type or _FoundryAgentChatClient
+        if not issubclass(actual_client_type, RawFoundryAgentChatClient):
+            raise TypeError(
+                f"client_type must be a subclass of RawFoundryAgentChatClient, got {actual_client_type.__name__}"
+            )
+
+        client = actual_client_type(
+            project_endpoint=project_endpoint,
+            agent_name=agent_name,
+            agent_version=agent_version,
+            credential=credential,
+            project_client=project_client,
+            allow_preview=allow_preview,
+            env_file_path=env_file_path,
+            env_file_encoding=env_file_encoding,
+        )
+
+        super().__init__(
+            client=client,  # type: ignore[arg-type]
+            tools=tools,  # type: ignore[arg-type]
+            context_providers=context_providers,
+            **kwargs,
+        )
+
+    async def configure_azure_monitor(
+        self,
+        enable_sensitive_data: bool = False,
+        **kwargs: Any,
+    ) -> None:
+        """Setup observability with Azure Monitor (Microsoft Foundry integration).
+
+        This method configures Azure Monitor for telemetry collection using the
+        connection string from the Foundry project client (accessed via the internal client).
+
+        Args:
+            enable_sensitive_data: Enable sensitive data logging (prompts, responses).
+                Should only be enabled in development/test environments. Default is False.
+            **kwargs: Additional arguments passed to configure_azure_monitor().
+
+        Raises:
+            ImportError: If azure-monitor-opentelemetry-exporter is not installed.
+        """
+        from azure.core.exceptions import ResourceNotFoundError
+
+        from ._foundry_agent_client import RawFoundryAgentChatClient
+
+        client = self.client
+        if not isinstance(client, RawFoundryAgentChatClient):
+            raise TypeError("configure_azure_monitor requires a RawFoundryAgentChatClient-based client.")
+
+        try:
+            conn_string = await client.project_client.telemetry.get_application_insights_connection_string()
+        except ResourceNotFoundError:
+            logger.warning(
+                "No Application Insights connection string found for the Foundry project. "
+                "Please ensure Application Insights is configured in your project, "
+                "or call configure_otel_providers() manually with custom exporters."
+            )
+            return
+
+        try:
+            from azure.monitor.opentelemetry import configure_azure_monitor  # type: ignore[import]
+        except ImportError as exc:
+            raise ImportError(
+                "azure-monitor-opentelemetry is required for Azure Monitor integration. "
+                "Install it with: pip install azure-monitor-opentelemetry"
+            ) from exc
+
+        from agent_framework.observability import create_metric_views, create_resource, enable_instrumentation
+
+        if "resource" not in kwargs:
+            kwargs["resource"] = create_resource()
+
+        configure_azure_monitor(
+            connection_string=conn_string,
+            views=create_metric_views(),
+            **kwargs,
+        )
+
+        enable_instrumentation(enable_sensitive_data=enable_sensitive_data)
+
+
+class FoundryAgent(  # type: ignore[misc]
+    AgentTelemetryLayer,
+    AgentMiddlewareLayer,
+    RawFoundryAgent[FoundryAgentOptionsT],
+):
+    """Microsoft Foundry Agent with full middleware and telemetry support.
+
+    Connects to an existing PromptAgent or HostedAgent in Foundry.
+    This is the recommended class for production use.
+
+    Examples:
+        .. code-block:: python
+
+            from agent_framework.foundry import FoundryAgent
+            from azure.identity import AzureCliCredential
+
+            # Connect to a PromptAgent
+            agent = FoundryAgent(
+                project_endpoint="https://your-project.services.ai.azure.com",
+                agent_name="my-prompt-agent",
+                agent_version="1.0",
+                credential=AzureCliCredential(),
+                tools=[my_function_tool],
+            )
+            result = await agent.run("Hello!")
+
+            # Connect to a HostedAgent (no version needed)
+            agent = FoundryAgent(
+                project_endpoint="https://your-project.services.ai.azure.com",
+                agent_name="my-hosted-agent",
+                credential=AzureCliCredential(),
+            )
+
+            # Custom client (e.g., raw client without client middleware)
+            agent = FoundryAgent(
+                project_endpoint="https://your-project.services.ai.azure.com",
+                agent_name="my-agent",
+                credential=AzureCliCredential(),
+                client_type=RawFoundryAgentChatClient,
+            )
+    """
+
+    def __init__(
+        self,
+        *,
+        project_endpoint: str | None = None,
+        agent_name: str | None = None,
+        agent_version: str | None = None,
+        credential: AzureCredentialTypes | None = None,
+        project_client: AIProjectClient | None = None,
+        allow_preview: bool | None = None,
+        tools: FunctionTool | Callable[..., Any] | Sequence[FunctionTool | Callable[..., Any]] | None = None,
+        context_providers: Sequence[BaseContextProvider] | None = None,
+        middleware: Sequence[MiddlewareTypes] | None = None,
+        client_type: type[RawFoundryAgentChatClient] | None = None,
+        env_file_path: str | None = None,
+        env_file_encoding: str | None = None,
+        **kwargs: Any,
+    ) -> None:
+        """Initialize a Foundry Agent with full middleware and telemetry.
+
+        Keyword Args:
+            project_endpoint: The Foundry project endpoint URL.
+            agent_name: The name of the Foundry agent to connect to.
+            agent_version: The version of the agent (for PromptAgents).
+            credential: Azure credential for authentication.
+            project_client: An existing AIProjectClient to use.
+            allow_preview: Enables preview opt-in on internally-created AIProjectClient.
+            tools: Function tools to provide to the agent. Only ``FunctionTool`` objects are accepted.
+            context_providers: Optional context providers.
+            middleware: Optional agent-level middleware.
+            client_type: Custom client class (must subclass ``RawFoundryAgentChatClient``).
+            env_file_path: Path to .env file for settings.
+            env_file_encoding: Encoding for .env file.
+            kwargs: Additional keyword arguments.
+        """
+        super().__init__(
+            project_endpoint=project_endpoint,
+            agent_name=agent_name,
+            agent_version=agent_version,
+            credential=credential,
+            project_client=project_client,
+            allow_preview=allow_preview,
+            tools=tools,
+            context_providers=context_providers,
+            middleware=middleware,
+            client_type=client_type,
+            env_file_path=env_file_path,
+            env_file_encoding=env_file_encoding,
+            **kwargs,
+        )

python/packages/foundry/agent_framework_foundry/_foundry_agent_client.py

@@ -0,0 +1,395 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Microsoft Foundry Agent client for connecting to pre-configured agents in Foundry.
+
+This module provides ``RawFoundryAgentClient`` and ``FoundryAgentClient`` for
+communicating with PromptAgents and HostedAgents via the Responses API.
+"""
+
+from __future__ import annotations
+
+import logging
+import sys
+from collections.abc import Callable, Mapping, MutableMapping, Sequence
+from typing import TYPE_CHECKING, Any, ClassVar, Generic, cast
+
+from agent_framework._middleware import ChatMiddlewareLayer
+from agent_framework._settings import load_settings
+from agent_framework._telemetry import AGENT_FRAMEWORK_USER_AGENT
+from agent_framework._tools import FunctionInvocationConfiguration, FunctionInvocationLayer, FunctionTool
+from agent_framework._types import Message
+from agent_framework.observability import ChatTelemetryLayer
+from agent_framework_openai._chat_client import OpenAIChatOptions, RawOpenAIChatClient
+from azure.ai.projects.aio import AIProjectClient
+
+from ._entra_id_authentication import AzureCredentialTypes
+
+logger: logging.Logger = logging.getLogger(__name__)
+
+if sys.version_info >= (3, 13):
+    from typing import TypeVar  # type: ignore # pragma: no cover
+else:
+    from typing_extensions import TypeVar  # type: ignore # pragma: no cover
+if sys.version_info >= (3, 12):
+    from typing import override  # type: ignore # pragma: no cover
+else:
+    from typing_extensions import override  # type: ignore # pragma: no cover
+if sys.version_info >= (3, 11):
+    from typing import TypedDict  # type: ignore # pragma: no cover
+else:
+    from typing_extensions import TypedDict  # type: ignore # pragma: no cover
+
+if TYPE_CHECKING:
+    from agent_framework import Agent, BaseContextProvider
+    from agent_framework._middleware import (
+        ChatMiddleware,
+        ChatMiddlewareCallable,
+        FunctionMiddleware,
+        FunctionMiddlewareCallable,
+        MiddlewareTypes,
+    )
+    from agent_framework._tools import ToolTypes
+
+
+class FoundryAgentSettings(TypedDict, total=False):
+    """Settings for Microsoft FoundryAgentClient resolved from args and environment.
+
+    Keyword Args:
+        project_endpoint: The Foundry project endpoint URL.
+            Can be set via environment variable FOUNDRY_PROJECT_ENDPOINT.
+        agent_name: The name of the Foundry agent to connect to.
+            Can be set via environment variable FOUNDRY_AGENT_NAME.
+        agent_version: The version of the Foundry agent (for PromptAgents).
+            Can be set via environment variable FOUNDRY_AGENT_VERSION.
+    """
+
+    project_endpoint: str | None
+    agent_name: str | None
+    agent_version: str | None
+
+
+FoundryAgentOptionsT = TypeVar(
+    "FoundryAgentOptionsT",
+    bound=TypedDict,  # type: ignore[valid-type]
+    default="OpenAIChatOptions",
+    covariant=True,
+)
+
+
+class RawFoundryAgentChatClient(  # type: ignore[misc]
+    RawOpenAIChatClient[FoundryAgentOptionsT],
+    Generic[FoundryAgentOptionsT],
+):
+    """Raw Microsoft Foundry Agent chat client for connecting to pre-configured agents in Foundry.
+
+    Connects to existing PromptAgents or HostedAgents via the Responses API.
+    Does not create or delete agents — the agent must already exist in Foundry.
+
+    This is a raw client without function invocation, chat middleware, or telemetry layers.
+    Tools passed in options are validated (only ``FunctionTool`` allowed) but **not invoked** —
+    the function invocation loop is handled by ``_FoundryAgentChatClient`` or a custom subclass
+    that includes ``FunctionInvocationLayer``.
+
+    Use this class as an extension point when building a custom client with specific middleware
+    layers via subclassing::
+
+        from agent_framework._tools import FunctionInvocationLayer
+        from agent_framework.foundry import RawFoundryAgentChatClient
+
+
+        class MyClient(FunctionInvocationLayer, RawFoundryAgentChatClient):
+            pass
+
+
+        agent = FoundryAgent(..., client_type=MyClient)
+    """
+
+    OTEL_PROVIDER_NAME: ClassVar[str] = "azure.ai.foundry"
+
+    def __init__(
+        self,
+        *,
+        project_endpoint: str | None = None,
+        agent_name: str | None = None,
+        agent_version: str | None = None,
+        credential: AzureCredentialTypes | None = None,
+        project_client: AIProjectClient | None = None,
+        allow_preview: bool | None = None,
+        env_file_path: str | None = None,
+        env_file_encoding: str | None = None,
+        **kwargs: Any,
+    ) -> None:
+        """Initialize a raw Foundry Agent client.
+
+        Keyword Args:
+            project_endpoint: The Foundry project endpoint URL.
+                Can also be set via environment variable FOUNDRY_PROJECT_ENDPOINT.
+            agent_name: The name of the Foundry agent to connect to.
+                Can also be set via environment variable FOUNDRY_AGENT_NAME.
+            agent_version: The version of the agent (required for PromptAgents, optional for HostedAgents).
+                Can also be set via environment variable FOUNDRY_AGENT_VERSION.
+            credential: Azure credential for authentication.
+            project_client: An existing AIProjectClient to use.
+            allow_preview: Enables preview opt-in on internally-created AIProjectClient.
+            env_file_path: Path to .env file for settings.
+            env_file_encoding: Encoding for .env file.
+            kwargs: Additional keyword arguments.
+        """
+        settings = load_settings(
+            FoundryAgentSettings,
+            env_prefix="FOUNDRY_",
+            project_endpoint=project_endpoint,
+            agent_name=agent_name,
+            agent_version=agent_version,
+            env_file_path=env_file_path,
+            env_file_encoding=env_file_encoding,
+        )
+
+        resolved_endpoint = settings.get("project_endpoint")
+        self.agent_name = settings.get("agent_name")
+        self.agent_version = settings.get("agent_version")
+
+        if not self.agent_name:
+            raise ValueError(
+                "Agent name is required. Set via 'agent_name' parameter or 'FOUNDRY_AGENT_NAME' environment variable."
+            )
+
+        # Create or use provided project client
+        self._should_close_client = False
+        if project_client is not None:
+            self.project_client = project_client
+        else:
+            if not resolved_endpoint:
+                raise ValueError(
+                    "Either 'project_endpoint' or 'project_client' is required. "
+                    "Set project_endpoint via parameter or 'FOUNDRY_PROJECT_ENDPOINT' environment variable."
+                )
+            if not credential:
+                raise ValueError("Azure credential is required when using project_endpoint without a project_client.")
+            project_client_kwargs: dict[str, Any] = {
+                "endpoint": resolved_endpoint,
+                "credential": credential,
+                "user_agent": AGENT_FRAMEWORK_USER_AGENT,
+            }
+            if allow_preview is not None:
+                project_client_kwargs["allow_preview"] = allow_preview
+            self.project_client = AIProjectClient(**project_client_kwargs)
+            self._should_close_client = True
+
+        # Get OpenAI client from project
+        async_client = self.project_client.get_openai_client()
+
+        super().__init__(async_client=async_client, **kwargs)
+
+    def _get_agent_reference(self) -> dict[str, str]:
+        """Build the agent reference dict for the Responses API."""
+        ref: dict[str, str] = {"name": self.agent_name, "type": "agent_reference"}  # type: ignore[dict-item]
+        if self.agent_version:
+            ref["version"] = self.agent_version
+        return ref
+
+    @override
+    def as_agent(
+        self,
+        *,
+        id: str | None = None,
+        name: str | None = None,
+        description: str | None = None,
+        instructions: str | None = None,
+        tools: ToolTypes | Callable[..., Any] | Sequence[ToolTypes | Callable[..., Any]] | None = None,
+        default_options: FoundryAgentOptionsT | Mapping[str, Any] | None = None,
+        context_providers: Sequence[BaseContextProvider] | None = None,
+        middleware: Sequence[MiddlewareTypes] | None = None,
+        **kwargs: Any,
+    ) -> Agent[FoundryAgentOptionsT]:
+        """Create a FoundryAgent that reuses this client's Foundry configuration."""
+        from ._foundry_agent import FoundryAgent
+
+        function_tools = cast(
+            FunctionTool | Callable[..., Any] | Sequence[FunctionTool | Callable[..., Any]] | None,
+            tools,
+        )
+
+        return cast(
+            "Agent[FoundryAgentOptionsT]",
+            FoundryAgent(
+                project_client=self.project_client,
+                agent_name=self.agent_name,
+                agent_version=self.agent_version,
+                tools=function_tools,
+                context_providers=context_providers,
+                middleware=middleware,
+                client_type=cast(type[RawFoundryAgentChatClient], self.__class__),
+                id=id,
+                name=self.agent_name if name is None else name,
+                description=description,
+                instructions=instructions,
+                default_options=default_options,
+                **kwargs,
+            ),
+        )
+
+    @override
+    async def _prepare_options(
+        self,
+        messages: Sequence[Message],
+        options: Mapping[str, Any],
+        **kwargs: Any,
+    ) -> dict[str, Any]:
+        """Prepare options for the Responses API, injecting agent reference and validating tools."""
+        # Validate tools — only FunctionTool allowed
+        tools = options.get("tools", [])
+        if tools:
+            for tool_item in tools:
+                if not isinstance(tool_item, FunctionTool):
+                    raise TypeError(
+                        f"Only FunctionTool objects are accepted for Foundry agents, "
+                        f"got {type(tool_item).__name__}. Other tool types (MCPTool, dict schemas, "
+                        f"hosted tools) must be defined on the Foundry agent definition in the service."
+                    )
+
+        # Prepare messages: extract system/developer messages as instructions
+        prepared_messages, _instructions = self._prepare_messages_for_azure_ai(messages)
+
+        # Call parent prepare_options (OpenAI Responses API format)
+        run_options = await super()._prepare_options(prepared_messages, options, **kwargs)
+
+        # Apply Azure AI schema transforms
+        if "input" in run_options and isinstance(run_options["input"], list):
+            run_options["input"] = self._transform_input_for_azure_ai(cast(list[dict[str, Any]], run_options["input"]))
+
+        # Inject agent reference
+        run_options["extra_body"] = {"agent_reference": self._get_agent_reference()}
+
+        return run_options
+
+    @override
+    def _check_model_presence(self, options: dict[str, Any]) -> None:
+        """Skip model check — model is configured on the Foundry agent."""
+        pass
+
+    def _prepare_messages_for_azure_ai(self, messages: Sequence[Message]) -> tuple[list[Message], str | None]:
+        """Extract system/developer messages as instructions for Azure AI.
+
+        Foundry agents may not support system/developer messages directly.
+        Instead, extract them as instructions to prepend.
+        """
+        prepared: list[Message] = []
+        instructions_parts: list[str] = []
+        for msg in messages:
+            if msg.role in ("system", "developer"):
+                if msg.text:
+                    instructions_parts.append(msg.text)
+            else:
+                prepared.append(msg)
+        instructions = "\n".join(instructions_parts) if instructions_parts else None
+        return prepared, instructions
+
+    def _transform_input_for_azure_ai(self, input_items: list[dict[str, Any]]) -> list[dict[str, Any]]:
+        """Transform input items to match Azure AI Projects expected schema.
+
+        Azure AI Projects 'create responses' API expects 'type' at item level
+        and 'annotations' for output_text content items.
+        """
+        transformed: list[dict[str, Any]] = []
+        for item in input_items:
+            new_item: dict[str, Any] = dict(item)
+
+            if "role" in new_item and "type" not in new_item:
+                new_item["type"] = "message"
+
+            if (content := new_item.get("content")) and isinstance(content, list):
+                new_content: list[Any] = []
+                for content_item in content:  # type: ignore[union-attr]
+                    if isinstance(content_item, MutableMapping):
+                        if content_item.get("type") == "output_text" and "annotations" not in content_item:  # type: ignore[operator]
+                            content_item["annotations"] = []
+                        new_content.append(content_item)
+                    else:
+                        new_content.append(content_item)
+                new_item["content"] = new_content
+
+            transformed.append(new_item)
+
+        return transformed
+
+    async def close(self) -> None:
+        """Close the project client if we created it."""
+        if self._should_close_client:
+            await self.project_client.close()
+
+
+class _FoundryAgentChatClient(  # type: ignore[misc]
+    FunctionInvocationLayer[FoundryAgentOptionsT],
+    ChatMiddlewareLayer[FoundryAgentOptionsT],
+    ChatTelemetryLayer[FoundryAgentOptionsT],
+    RawFoundryAgentChatClient[FoundryAgentOptionsT],
+    Generic[FoundryAgentOptionsT],
+):
+    """Microsoft Foundry Agent client with middleware, telemetry, and function invocation support.
+
+    Connects to existing PromptAgents or HostedAgents in Foundry.
+
+    Examples:
+        .. code-block:: python
+
+            from agent_framework import Agent
+            from agent_framework.foundry import FoundryAgentClient
+            from azure.identity import AzureCliCredential
+
+            client = FoundryAgentClient(
+                project_endpoint="https://your-project.services.ai.azure.com",
+                agent_name="my-prompt-agent",
+                agent_version="1.0",
+                credential=AzureCliCredential(),
+            )
+
+            agent = Agent(client=client, tools=[my_function_tool])
+            result = await agent.run("Hello!")
+    """
+
+    def __init__(
+        self,
+        *,
+        project_endpoint: str | None = None,
+        agent_name: str | None = None,
+        agent_version: str | None = None,
+        credential: AzureCredentialTypes | None = None,
+        project_client: AIProjectClient | None = None,
+        allow_preview: bool | None = None,
+        env_file_path: str | None = None,
+        env_file_encoding: str | None = None,
+        middleware: (
+            Sequence[ChatMiddleware | ChatMiddlewareCallable | FunctionMiddleware | FunctionMiddlewareCallable] | None
+        ) = None,
+        function_invocation_configuration: FunctionInvocationConfiguration | None = None,
+        **kwargs: Any,
+    ) -> None:
+        """Initialize a Foundry Agent client with full middleware support.
+
+        Keyword Args:
+            project_endpoint: The Foundry project endpoint URL.
+            agent_name: The name of the Foundry agent to connect to.
+            agent_version: The version of the agent (for PromptAgents).
+            credential: Azure credential for authentication.
+            project_client: An existing AIProjectClient to use.
+            allow_preview: Enables preview opt-in on internally-created AIProjectClient.
+            env_file_path: Path to .env file for settings.
+            env_file_encoding: Encoding for .env file.
+            middleware: Optional sequence of middleware.
+            function_invocation_configuration: Optional function invocation configuration.
+            kwargs: Additional keyword arguments.
+        """
+        super().__init__(
+            project_endpoint=project_endpoint,
+            agent_name=agent_name,
+            agent_version=agent_version,
+            credential=credential,
+            project_client=project_client,
+            allow_preview=allow_preview,
+            env_file_path=env_file_path,
+            env_file_encoding=env_file_encoding,
+            middleware=middleware,
+            function_invocation_configuration=function_invocation_configuration,
+            **kwargs,
+        )

python/packages/foundry/agent_framework_foundry/_foundry_chat_client.py

@@ -0,0 +1,530 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+from __future__ import annotations
+
+import logging
+import sys
+from collections.abc import Sequence
+from typing import TYPE_CHECKING, Any, ClassVar, Generic, Literal
+
+from agent_framework._middleware import ChatMiddlewareLayer
+from agent_framework._settings import load_settings
+from agent_framework._telemetry import AGENT_FRAMEWORK_USER_AGENT
+from agent_framework._tools import FunctionInvocationConfiguration, FunctionInvocationLayer
+from agent_framework._types import Content
+from agent_framework.observability import ChatTelemetryLayer
+from agent_framework_openai._chat_client import OpenAIChatOptions, RawOpenAIChatClient
+from azure.ai.projects.aio import AIProjectClient
+from azure.ai.projects.models import (
+    AutoCodeInterpreterToolParam,
+    CodeInterpreterTool,
+    ImageGenTool,
+    WebSearchApproximateLocation,
+    WebSearchTool,
+    WebSearchToolFilters,
+)
+from azure.ai.projects.models import FileSearchTool as ProjectsFileSearchTool
+from azure.ai.projects.models import MCPTool as FoundryMCPTool
+
+from ._entra_id_authentication import AzureCredentialTypes, AzureTokenProvider
+from ._shared import resolve_file_ids
+
+if sys.version_info >= (3, 13):
+    from typing import TypeVar  # type: ignore # pragma: no cover
+else:
+    from typing_extensions import TypeVar  # type: ignore # pragma: no cover
+if sys.version_info >= (3, 12):
+    from typing import override  # type: ignore # pragma: no cover
+else:
+    from typing_extensions import override  # type: ignore # pragma: no cover
+if sys.version_info >= (3, 11):
+    from typing import TypedDict  # type: ignore # pragma: no cover
+else:
+    from typing_extensions import TypedDict  # type: ignore # pragma: no cover
+
+if TYPE_CHECKING:
+    from agent_framework._middleware import (
+        ChatMiddleware,
+        ChatMiddlewareCallable,
+        FunctionMiddleware,
+        FunctionMiddlewareCallable,
+    )
+
+logger: logging.Logger = logging.getLogger("agent_framework.foundry")
+
+
+class FoundrySettings(TypedDict, total=False):
+    """Settings for Microsoft FoundryChatClient resolved from args and environment.
+
+    Keyword Args:
+        model: The model deployment name.
+            Can be set via environment variable FOUNDRY_MODEL.
+        project_endpoint: The Microsoft Foundry project endpoint URL.
+            Can be set via environment variable FOUNDRY_PROJECT_ENDPOINT.
+    """
+
+    model: str | None
+    project_endpoint: str | None
+
+
+FoundryChatOptionsT = TypeVar(
+    "FoundryChatOptionsT",
+    bound=TypedDict,  # type: ignore[valid-type]
+    default="OpenAIChatOptions",
+    covariant=True,
+)
+
+FoundryChatOptions = OpenAIChatOptions
+
+
+class RawFoundryChatClient(  # type: ignore[misc]
+    RawOpenAIChatClient[FoundryChatOptionsT],
+    Generic[FoundryChatOptionsT],
+):
+    """Raw Microsoft Foundry chat client using the OpenAI Responses API via a Foundry project.
+
+    This client creates an OpenAI-compatible client from a Foundry project
+    and delegates to ``RawOpenAIChatClient`` for request handling.
+
+    Environment variables:
+        - ``FOUNDRY_PROJECT_ENDPOINT`` to provide the Foundry project endpoint.
+        - ``FOUNDRY_MODEL`` to provide the Foundry model deployment name.
+
+    Warning:
+        **This class should not normally be used directly.** Use ``FoundryChatClient``
+        for a fully-featured client with middleware, telemetry, and function invocation.
+    """
+
+    OTEL_PROVIDER_NAME: ClassVar[str] = "azure.ai.foundry"  # type: ignore[reportIncompatibleVariableOverride, misc]
+
+    def __init__(
+        self,
+        *,
+        project_endpoint: str | None = None,
+        project_client: AIProjectClient | None = None,
+        model: str | None = None,
+        credential: AzureCredentialTypes | AzureTokenProvider | None = None,
+        allow_preview: bool | None = None,
+        env_file_path: str | None = None,
+        env_file_encoding: str | None = None,
+        instruction_role: str | None = None,
+        **kwargs: Any,
+    ) -> None:
+        """Initialize a raw Microsoft Foundry chat client.
+
+        Keyword Args:
+            project_endpoint: The Foundry project endpoint URL.
+                Can also be set via environment variable FOUNDRY_PROJECT_ENDPOINT.
+            project_client: An existing AIProjectClient to use. If provided,
+                the OpenAI client will be obtained via ``project_client.get_openai_client()``.
+            model: The model deployment name.
+                Can also be set via environment variable FOUNDRY_MODEL.
+            credential: Azure credential or token provider for authentication.
+                Required when using ``project_endpoint`` without a ``project_client``.
+            allow_preview: Enables preview opt-in on internally-created AIProjectClient.
+            env_file_path: Path to .env file for settings.
+            env_file_encoding: Encoding for .env file.
+            instruction_role: The role to use for 'instruction' messages.
+            kwargs: Additional keyword arguments.
+        """
+        foundry_settings = load_settings(
+            FoundrySettings,
+            env_prefix="FOUNDRY_",
+            model=model,
+            project_endpoint=project_endpoint,
+            env_file_path=env_file_path,
+            env_file_encoding=env_file_encoding,
+        )
+
+        resolved_model = foundry_settings.get("model")
+        if not resolved_model:
+            raise ValueError("Model is required. Set via 'model' parameter or 'FOUNDRY_MODEL' environment variable.")
+
+        project_endpoint = foundry_settings.get("project_endpoint")
+
+        if project_endpoint is None and project_client is None:
+            raise ValueError(
+                "Either 'project_endpoint' or 'project_client' is required. "
+                "Set project_endpoint via parameter or 'FOUNDRY_PROJECT_ENDPOINT' environment variable."
+            )
+        if not project_client:
+            if not project_endpoint:
+                raise ValueError(
+                    "Azure AI project endpoint is required. Set via 'project_endpoint' parameter "
+                    "or 'FOUNDRY_PROJECT_ENDPOINT' environment variable,"
+                    "or pass in a AIProjectClient."
+                )
+            if not credential:
+                raise ValueError("Azure credential is required when using project_endpoint without a project_client.")
+            project_client_kwargs: dict[str, Any] = {
+                "endpoint": project_endpoint,
+                "credential": credential,  # type: ignore[arg-type]
+                "user_agent": AGENT_FRAMEWORK_USER_AGENT,
+            }
+            if allow_preview is not None:
+                project_client_kwargs["allow_preview"] = allow_preview
+            project_client = AIProjectClient(**project_client_kwargs)
+
+        super().__init__(
+            model=resolved_model,
+            async_client=project_client.get_openai_client(),
+            instruction_role=instruction_role,
+            **kwargs,
+        )
+        self.project_client = project_client
+
+    @override
+    def _check_model_presence(self, options: dict[str, Any]) -> None:
+        if not options.get("model"):
+            if not self.model:
+                raise ValueError("model must be a non-empty string")
+            options["model"] = self.model
+
+    async def configure_azure_monitor(
+        self,
+        enable_sensitive_data: bool = False,
+        **kwargs: Any,
+    ) -> None:
+        """Setup observability with Azure Monitor (Microsoft Foundry integration).
+
+        This method configures Azure Monitor for telemetry collection using the
+        connection string from the Foundry project client.
+
+        Args:
+            enable_sensitive_data: Enable sensitive data logging (prompts, responses).
+                Should only be enabled in development/test environments. Default is False.
+            **kwargs: Additional arguments passed to configure_azure_monitor().
+                Common options include:
+                - enable_live_metrics (bool): Enable Azure Monitor Live Metrics
+                - credential (TokenCredential): Azure credential for Entra ID auth
+                - resource (Resource): Custom OpenTelemetry resource
+
+        Raises:
+            ImportError: If azure-monitor-opentelemetry-exporter is not installed.
+        """
+        from azure.core.exceptions import ResourceNotFoundError
+
+        try:
+            conn_string = await self.project_client.telemetry.get_application_insights_connection_string()
+        except ResourceNotFoundError:
+            logger.warning(
+                "No Application Insights connection string found for the Foundry project. "
+                "Please ensure Application Insights is configured in your project, "
+                "or call configure_otel_providers() manually with custom exporters."
+            )
+            return
+
+        try:
+            from azure.monitor.opentelemetry import configure_azure_monitor  # type: ignore[import]
+        except ImportError as exc:
+            raise ImportError(
+                "azure-monitor-opentelemetry is required for Azure Monitor integration. "
+                "Install it with: pip install azure-monitor-opentelemetry"
+            ) from exc
+
+        from agent_framework.observability import create_metric_views, create_resource, enable_instrumentation
+
+        if "resource" not in kwargs:
+            kwargs["resource"] = create_resource()
+
+        configure_azure_monitor(
+            connection_string=conn_string,
+            views=create_metric_views(),
+            **kwargs,
+        )
+
+        enable_instrumentation(enable_sensitive_data=enable_sensitive_data)
+
+    # region Tool factory methods (override OpenAI defaults with Foundry versions)
+
+    @staticmethod
+    def get_code_interpreter_tool(  # type: ignore[override]
+        *,
+        file_ids: list[str | Content] | None = None,
+        container: Literal["auto"] | dict[str, Any] = "auto",
+        **kwargs: Any,
+    ) -> CodeInterpreterTool:
+        """Create a code interpreter tool configuration for Foundry.
+
+        Keyword Args:
+            file_ids: Optional list of file IDs or Content objects to make available.
+            container: Container configuration. Use "auto" for automatic management.
+            **kwargs: Additional arguments passed to the SDK CodeInterpreterTool constructor.
+
+        Returns:
+            A CodeInterpreterTool ready to pass to an Agent.
+        """
+        if file_ids is None and isinstance(container, dict):
+            file_ids = container.get("file_ids")
+        resolved = resolve_file_ids(file_ids)
+        tool_container = AutoCodeInterpreterToolParam(file_ids=resolved)
+        return CodeInterpreterTool(container=tool_container, **kwargs)
+
+    @staticmethod
+    def get_file_search_tool(
+        *,
+        vector_store_ids: list[str],
+        max_num_results: int | None = None,
+        ranking_options: dict[str, Any] | None = None,
+        filters: dict[str, Any] | None = None,
+        **kwargs: Any,
+    ) -> ProjectsFileSearchTool:
+        """Create a file search tool configuration for Foundry.
+
+        Keyword Args:
+            vector_store_ids: List of vector store IDs to search.
+            max_num_results: Maximum number of results to return (1-50).
+            ranking_options: Ranking options for search results.
+            filters: A filter to apply (ComparisonFilter or CompoundFilter).
+            **kwargs: Additional arguments passed to the SDK FileSearchTool constructor.
+
+        Returns:
+            A FileSearchTool ready to pass to an Agent.
+        """
+        if not vector_store_ids:
+            raise ValueError("File search tool requires 'vector_store_ids' to be specified.")
+        return ProjectsFileSearchTool(
+            vector_store_ids=vector_store_ids,
+            max_num_results=max_num_results,
+            ranking_options=ranking_options,  # type: ignore[arg-type]
+            filters=filters,  # type: ignore[arg-type]
+            **kwargs,
+        )
+
+    @staticmethod
+    def get_web_search_tool(  # type: ignore[override]
+        *,
+        user_location: dict[str, str] | None = None,
+        search_context_size: Literal["low", "medium", "high"] | None = None,
+        allowed_domains: list[str] | None = None,
+        custom_search_configuration: dict[str, Any] | None = None,
+        **kwargs: Any,
+    ) -> WebSearchTool:
+        """Create a web search tool configuration for Microsoft Foundry.
+
+        Keyword Args:
+            user_location: Location context with keys like "city", "country", "region", "timezone".
+            search_context_size: Amount of context from search results ("low", "medium", "high").
+            allowed_domains: List of domains to restrict search results to.
+            custom_search_configuration: Custom Bing search configuration.
+            **kwargs: Additional arguments passed to the SDK WebSearchTool constructor.
+
+        Returns:
+            A WebSearchTool ready to pass to an Agent.
+        """
+        ws_kwargs: dict[str, Any] = {**kwargs}
+        if search_context_size:
+            ws_kwargs["search_context_size"] = search_context_size
+        if allowed_domains:
+            ws_kwargs["filters"] = WebSearchToolFilters(allowed_domains=allowed_domains)
+        if custom_search_configuration:
+            ws_kwargs["custom_search_configuration"] = custom_search_configuration
+        ws_tool = WebSearchTool(**ws_kwargs)
+        if user_location:
+            ws_tool.user_location = WebSearchApproximateLocation(
+                city=user_location.get("city"),
+                country=user_location.get("country"),
+                region=user_location.get("region"),
+                timezone=user_location.get("timezone"),
+            )
+        return ws_tool
+
+    @staticmethod
+    def get_image_generation_tool(  # type: ignore[override]
+        *,
+        model: Literal["gpt-image-1"] | str | None = None,
+        size: Literal["1024x1024", "1024x1536", "1536x1024", "auto"] | None = None,
+        output_format: Literal["png", "webp", "jpeg"] | None = None,
+        quality: Literal["low", "medium", "high", "auto"] | None = None,
+        background: Literal["transparent", "opaque", "auto"] | None = None,
+        partial_images: int | None = None,
+        moderation: Literal["auto", "low"] | None = None,
+        output_compression: int | None = None,
+        **kwargs: Any,
+    ) -> ImageGenTool:
+        """Create an image generation tool configuration for Foundry.
+
+        Keyword Args:
+            model: The model to use for image generation.
+            size: Output image size.
+            output_format: Output image format.
+            quality: Output image quality.
+            background: Background transparency setting.
+            partial_images: Number of partial images to return during generation.
+            moderation: Moderation level.
+            output_compression: Compression level.
+            **kwargs: Additional arguments passed to the SDK ImageGenTool constructor.
+
+        Returns:
+            An ImageGenTool ready to pass to an Agent.
+        """
+        return ImageGenTool(  # type: ignore[misc]
+            model=model,  # type: ignore[arg-type]
+            size=size,
+            output_format=output_format,
+            quality=quality,
+            background=background,
+            partial_images=partial_images,
+            moderation=moderation,
+            output_compression=output_compression,
+            **kwargs,
+        )
+
+    @staticmethod
+    def get_mcp_tool(
+        *,
+        name: str,
+        url: str | None = None,
+        description: str | None = None,
+        approval_mode: Literal["always_require", "never_require"] | dict[str, list[str]] | None = None,
+        allowed_tools: list[str] | None = None,
+        headers: dict[str, str] | None = None,
+        project_connection_id: str | None = None,
+        **kwargs: Any,
+    ) -> FoundryMCPTool:
+        """Create a hosted MCP tool configuration for Foundry.
+
+        This configures an MCP server that runs remotely on Azure AI, not locally.
+
+        Keyword Args:
+            name: A label/name for the MCP server.
+            url: The URL of the MCP server. Required if project_connection_id is not provided.
+            description: A description of what the MCP server provides.
+            approval_mode: Tool approval mode ("always_require", "never_require", or dict).
+            allowed_tools: List of allowed tool names from this MCP server.
+            headers: HTTP headers to include in requests to the MCP server.
+            project_connection_id: Foundry connection ID for managed MCP connections.
+            **kwargs: Additional arguments passed to the SDK MCPTool constructor.
+
+        Returns:
+            An MCPTool configuration ready to pass to an Agent.
+        """
+        mcp = FoundryMCPTool(server_label=name.replace(" ", "_"), server_url=url or "", **kwargs)
+
+        if description:
+            mcp["server_description"] = description
+        if project_connection_id:
+            mcp["project_connection_id"] = project_connection_id
+        elif headers:
+            mcp["headers"] = headers
+        if allowed_tools:
+            mcp["allowed_tools"] = allowed_tools
+        if approval_mode:
+            if isinstance(approval_mode, str):
+                mcp["require_approval"] = "always" if approval_mode == "always_require" else "never"
+            else:
+                if always_require := approval_mode.get("always_require_approval"):
+                    mcp["require_approval"] = {"always": {"tool_names": always_require}}
+                if never_require := approval_mode.get("never_require_approval"):
+                    mcp["require_approval"] = {"never": {"tool_names": never_require}}
+
+        return mcp
+
+    # endregion
+
+
+class FoundryChatClient(  # type: ignore[misc]
+    FunctionInvocationLayer[FoundryChatOptionsT],
+    ChatMiddlewareLayer[FoundryChatOptionsT],
+    ChatTelemetryLayer[FoundryChatOptionsT],
+    RawFoundryChatClient[FoundryChatOptionsT],
+    Generic[FoundryChatOptionsT],
+):
+    """Microsoft Foundry chat client using the OpenAI Responses API.
+
+    Creates an OpenAI-compatible client from a Foundry project
+    with middleware, telemetry, and function invocation support.
+
+    Environment variables:
+        - ``FOUNDRY_PROJECT_ENDPOINT`` to provide the Foundry project endpoint.
+        - ``FOUNDRY_MODEL`` to provide the Foundry model deployment name.
+
+    Keyword Args:
+        project_endpoint: The Foundry project endpoint URL.
+            Can also be set via environment variable ``FOUNDRY_PROJECT_ENDPOINT``.
+        project_client: An existing AIProjectClient to use.
+        model: The model deployment name.
+            Can also be set via environment variable ``FOUNDRY_MODEL``.
+        model_id: Deprecated alias for ``model``.
+        credential: Azure credential or token provider for authentication.
+        allow_preview: Enables preview opt-in on internally-created AIProjectClient.
+        env_file_path: Path to .env file for settings.
+        env_file_encoding: Encoding for .env file.
+        instruction_role: The role to use for 'instruction' messages.
+        middleware: Optional sequence of middleware.
+        function_invocation_configuration: Optional function invocation configuration.
+
+    Examples:
+        .. code-block:: python
+
+            from azure.identity import AzureCliCredential
+            from agent_framework_foundry import FoundryChatClient
+
+            client = FoundryChatClient(
+                project_endpoint="https://your-project.services.ai.azure.com",
+                model="gpt-4o",
+                credential=AzureCliCredential(),
+            )
+
+            # Or using an existing AIProjectClient
+            from azure.ai.projects.aio import AIProjectClient
+
+            project_client = AIProjectClient(
+                endpoint="https://your-project.services.ai.azure.com",
+                credential=AzureCliCredential(),
+            )
+            client = FoundryChatClient(
+                project_client=project_client,
+                model="gpt-4o",
+            )
+    """
+
+    OTEL_PROVIDER_NAME: ClassVar[str] = "azure.ai.foundry"  # type: ignore[reportIncompatibleVariableOverride, misc]
+
+    def __init__(
+        self,
+        *,
+        project_endpoint: str | None = None,
+        project_client: AIProjectClient | None = None,
+        model: str | None = None,
+        credential: AzureCredentialTypes | AzureTokenProvider | None = None,
+        allow_preview: bool | None = None,
+        env_file_path: str | None = None,
+        env_file_encoding: str | None = None,
+        instruction_role: str | None = None,
+        middleware: (
+            Sequence[ChatMiddleware | ChatMiddlewareCallable | FunctionMiddleware | FunctionMiddlewareCallable] | None
+        ) = None,
+        function_invocation_configuration: FunctionInvocationConfiguration | None = None,
+        **kwargs: Any,
+    ) -> None:
+        """Initialize a Foundry chat client.
+
+        Keyword Args:
+            project_endpoint: The Foundry project endpoint URL.
+                Can also be set via environment variable ``FOUNDRY_PROJECT_ENDPOINT``.
+            project_client: An existing AIProjectClient to use.
+            model: The model deployment name.
+                Can also be set via environment variable ``FOUNDRY_MODEL``.
+            credential: Azure credential or token provider for authentication.
+            allow_preview: Enables preview opt-in on internally-created AIProjectClient.
+            env_file_path: Path to .env file for settings.
+            env_file_encoding: Encoding for .env file.
+            instruction_role: The role to use for 'instruction' messages.
+            middleware: Optional sequence of middleware.
+            function_invocation_configuration: Optional function invocation configuration.
+            kwargs: Additional keyword arguments.
+        """
+        super().__init__(
+            project_endpoint=project_endpoint,
+            project_client=project_client,
+            model=model,
+            credential=credential,
+            allow_preview=allow_preview,
+            env_file_path=env_file_path,
+            env_file_encoding=env_file_encoding,
+            instruction_role=instruction_role,
+            middleware=middleware,
+            function_invocation_configuration=function_invocation_configuration,
+            **kwargs,
+        )

python/packages/foundry/agent_framework_foundry/_foundry_memory_provider.py

@@ -16,11 +16,11 @@ from typing import TYPE_CHECKING, Any, ClassVar
 from agent_framework import AGENT_FRAMEWORK_USER_AGENT, Message
 from agent_framework._sessions import AgentSession, BaseContextProvider, SessionContext
 from agent_framework._settings import load_settings
-from agent_framework.azure._entra_id_authentication import AzureCredentialTypes
 from azure.ai.projects.aio import AIProjectClient
 from openai.types.responses import ResponseInputItemParam
 
-from ._shared import AzureAISettings
+from ._entra_id_authentication import AzureCredentialTypes
+from ._shared import FoundryProjectSettings
 
 if sys.version_info >= (3, 11):
     from typing import Self  # pragma: no cover
@@ -72,7 +72,7 @@ class FoundryMemoryProvider(BaseContextProvider):
         Args:
             source_id: Unique identifier for this provider instance.
             project_client: Azure AI Project client for memory operations.
-            project_endpoint: Azure AI project endpoint URL. Used when project_client is not provided.
+            project_endpoint: Foundry project endpoint URL. Used when project_client is not provided.
             credential: Azure credential for authentication. Accepts a TokenCredential,
                 AsyncTokenCredential, or a callable token provider.
                 Required when project_client is not provided.
@@ -86,20 +86,20 @@ class FoundryMemoryProvider(BaseContextProvider):
             env_file_encoding: Encoding of the environment file.
         """
         super().__init__(source_id)
-        azure_ai_settings = load_settings(
-            AzureAISettings,
-            env_prefix="AZURE_AI_",
+        foundry_settings = load_settings(
+            FoundryProjectSettings,
+            env_prefix="FOUNDRY_",
             project_endpoint=project_endpoint,
             env_file_path=env_file_path,
             env_file_encoding=env_file_encoding,
         )
 
         if project_client is None:
-            resolved_endpoint = azure_ai_settings.get("project_endpoint")
+            resolved_endpoint = foundry_settings.get("project_endpoint")
             if not resolved_endpoint:
                 raise ValueError(
-                    "Azure AI project endpoint is required. Set via 'project_endpoint' parameter "
-                    "or 'AZURE_AI_PROJECT_ENDPOINT' environment variable."
+                    "Foundry project endpoint is required. Set via 'project_endpoint' parameter "
+                    "or 'FOUNDRY_PROJECT_ENDPOINT' environment variable."
                 )
             if not credential:
                 raise ValueError("Azure credential is required when project_client is not provided.")

python/packages/foundry/agent_framework_foundry/_shared.py

@@ -0,0 +1,49 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+from __future__ import annotations
+
+import logging
+import sys
+from collections.abc import Sequence
+
+from agent_framework import Content
+
+if sys.version_info >= (3, 11):
+    from typing import TypedDict  # pragma: no cover
+else:
+    from typing_extensions import TypedDict  # type: ignore # pragma: no cover
+
+logger = logging.getLogger("agent_framework.foundry")
+
+
+class FoundryProjectSettings(TypedDict, total=False):
+    """Foundry project settings loaded from FOUNDRY_ environment variables."""
+
+    project_endpoint: str | None
+
+
+def resolve_file_ids(file_ids: Sequence[str | Content] | None) -> list[str] | None:
+    """Resolve file IDs from strings or hosted-file Content objects."""
+    if not file_ids:
+        return None
+
+    resolved: list[str] = []
+    for item in file_ids:
+        if isinstance(item, str):
+            if not item:
+                raise ValueError("file_ids must not contain empty strings.")
+            resolved.append(item)
+        elif isinstance(item, Content):
+            if item.type != "hosted_file":
+                raise ValueError(
+                    f"Unsupported Content type {item.type!r} for code interpreter file_ids. "
+                    "Only Content.from_hosted_file() is supported."
+                )
+            if item.file_id is None:
+                raise ValueError(
+                    "Content.from_hosted_file() item is missing a file_id. "
+                    "Ensure the Content object has a valid file_id before using it in file_ids."
+                )
+            resolved.append(item.file_id)
+
+    return resolved if resolved else None

python/packages/foundry/pyproject.toml

@@ -0,0 +1,105 @@
+[project]
+name = "agent-framework-foundry"
+description = "Cloud Azure AI Foundry integration for Microsoft Agent Framework."
+authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
+readme = "README.md"
+requires-python = ">=3.10"
+version = "1.0.0rc5"
+license-files = ["LICENSE"]
+urls.homepage = "https://aka.ms/agent-framework"
+urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
+urls.release_notes = "https://github.com/microsoft/agent-framework/releases?q=tag%3Apython-1&expanded=true"
+urls.issues = "https://github.com/microsoft/agent-framework/issues"
+classifiers = [
+  "License :: OSI Approved :: MIT License",
+  "Development Status :: 4 - Beta",
+  "Intended Audience :: Developers",
+  "Programming Language :: Python :: 3",
+  "Programming Language :: Python :: 3.10",
+  "Programming Language :: Python :: 3.11",
+  "Programming Language :: Python :: 3.12",
+  "Programming Language :: Python :: 3.13",
+  "Programming Language :: Python :: 3.14",
+  "Typing :: Typed",
+]
+dependencies = [
+    "agent-framework-core>=1.0.0rc5",
+    "agent-framework-openai>=1.0.0rc5",
+    "azure-ai-projects>=2.0.0,<3.0",
+]
+
+[tool.uv]
+prerelease = "if-necessary-or-explicit"
+environments = [
+    "sys_platform == 'darwin'",
+    "sys_platform == 'linux'",
+    "sys_platform == 'win32'"
+]
+
+[tool.uv-dynamic-versioning]
+fallback-version = "0.0.0"
+
+[tool.pytest.ini_options]
+testpaths = 'tests'
+addopts = "-ra -q -r fEX"
+asyncio_mode = "auto"
+asyncio_default_fixture_loop_scope = "function"
+filterwarnings = []
+timeout = 120
+markers = [
+    "integration: marks tests as integration tests that require external services",
+]
+
+[tool.ruff]
+extend = "../../pyproject.toml"
+
+[tool.coverage.run]
+omit = [
+    "**/__init__.py"
+]
+
+[tool.pyright]
+extends = "../../pyproject.toml"
+include = ["agent_framework_foundry"]
+
+[tool.mypy]
+plugins = ['pydantic.mypy']
+strict = true
+python_version = "3.10"
+ignore_missing_imports = true
+disallow_untyped_defs = true
+no_implicit_optional = true
+check_untyped_defs = true
+warn_return_any = true
+show_error_codes = true
+warn_unused_ignores = false
+disallow_incomplete_defs = true
+disallow_untyped_decorators = true
+
+[tool.bandit]
+targets = ["agent_framework_foundry"]
+exclude_dirs = ["tests"]
+
+[tool.poe]
+executor.type = "uv"
+include = "../../shared_tasks.toml"
+
+[tool.poe.tasks.mypy]
+help = "Run MyPy for this package."
+cmd = "mypy --config-file $POE_ROOT/pyproject.toml agent_framework_foundry"
+
+[tool.poe.tasks.test]
+help = "Run the default unit test suite for this package."
+cmd = 'pytest -m "not integration" --cov=agent_framework_foundry --cov-report=term-missing:skip-covered tests'
+
+[tool.poe.tasks.integration-tests]
+help = "Run the package integration test suite."
+cmd = """
+pytest --import-mode=importlib
+-n logical --dist worksteal
+tests
+"""
+
+[build-system]
+requires = ["flit-core >= 3.11,<4.0"]
+build-backend = "flit_core.buildapi"

python/packages/foundry/tests/conftest.py

@@ -0,0 +1,78 @@
+# Copyright (c) Microsoft. All rights reserved.
+from typing import Any
+from unittest.mock import AsyncMock, MagicMock
+
+from pytest import fixture
+
+
+@fixture
+def exclude_list(request: Any) -> list[str]:
+    """Fixture that returns a list of environment variables to exclude."""
+    return request.param if hasattr(request, "param") else []
+
+
+@fixture
+def override_env_param_dict(request: Any) -> dict[str, str]:
+    """Fixture that returns a dict of environment variables to override."""
+    return request.param if hasattr(request, "param") else {}
+
+
+@fixture()
+def foundry_unit_test_env(monkeypatch, exclude_list, override_env_param_dict):  # type: ignore
+    """Fixture to set environment variables for Foundry settings."""
+
+    if exclude_list is None:
+        exclude_list = []
+
+    if override_env_param_dict is None:
+        override_env_param_dict = {}
+
+    env_vars = {
+        "FOUNDRY_PROJECT_ENDPOINT": "https://test-project.services.ai.azure.com/",
+        "FOUNDRY_MODEL": "test-gpt-4o",
+    }
+
+    env_vars.update(override_env_param_dict)  # type: ignore
+
+    for key, value in env_vars.items():
+        if key in exclude_list:
+            monkeypatch.delenv(key, raising=False)  # type: ignore
+            continue
+        monkeypatch.setenv(key, value)  # type: ignore
+
+    return env_vars
+
+
+@fixture
+def mock_agents_client() -> MagicMock:
+    """Fixture that provides a mock AgentsClient."""
+    mock_client = MagicMock()
+
+    # Mock agents property
+    mock_client.create_agent = AsyncMock()
+    mock_client.delete_agent = AsyncMock()
+
+    # Mock agent creation response
+    mock_agent = MagicMock()
+    mock_agent.id = "test-agent-id"
+    mock_client.create_agent.return_value = mock_agent
+
+    # Mock threads property
+    mock_client.threads = MagicMock()
+    mock_client.threads.create = AsyncMock()
+    mock_client.messages.create = AsyncMock()
+
+    # Mock runs property
+    mock_client.runs = MagicMock()
+    mock_client.runs.list = AsyncMock()
+    mock_client.runs.cancel = AsyncMock()
+    mock_client.runs.stream = AsyncMock()
+    mock_client.runs.submit_tool_outputs_stream = AsyncMock()
+
+    return mock_client
+
+
+@fixture
+def mock_azure_credential() -> MagicMock:
+    """Fixture that provides a mock AsyncTokenCredential."""
+    return MagicMock()

python/packages/foundry/tests/test_foundry_agent.py

@@ -0,0 +1,374 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Tests for FoundryAgentClient and FoundryAgent classes."""
+
+from typing import Any
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+from agent_framework._tools import tool
+
+
+class TestRawFoundryAgentChatClient:
+    """Tests for RawFoundryAgentChatClient."""
+
+    def test_init_requires_agent_name(self) -> None:
+        """Test that agent_name is required."""
+        from agent_framework_foundry._foundry_agent_client import RawFoundryAgentChatClient
+
+        with pytest.raises(ValueError, match="Agent name is required"):
+            RawFoundryAgentChatClient(
+                project_client=MagicMock(),
+            )
+
+    def test_init_with_agent_name(self) -> None:
+        """Test construction with agent_name and project_client."""
+        from agent_framework_foundry._foundry_agent_client import RawFoundryAgentChatClient
+
+        mock_project = MagicMock()
+        mock_project.get_openai_client.return_value = MagicMock()
+
+        client = RawFoundryAgentChatClient(
+            project_client=mock_project,
+            agent_name="test-agent",
+            agent_version="1.0",
+        )
+
+        assert client.agent_name == "test-agent"
+        assert client.agent_version == "1.0"
+
+    def test_get_agent_reference_with_version(self) -> None:
+        """Test agent reference includes version when provided."""
+        from agent_framework_foundry._foundry_agent_client import RawFoundryAgentChatClient
+
+        mock_project = MagicMock()
+        mock_project.get_openai_client.return_value = MagicMock()
+
+        client = RawFoundryAgentChatClient(
+            project_client=mock_project,
+            agent_name="my-agent",
+            agent_version="2.0",
+        )
+
+        ref = client._get_agent_reference()
+        assert ref == {"name": "my-agent", "version": "2.0", "type": "agent_reference"}
+
+    def test_get_agent_reference_without_version(self) -> None:
+        """Test agent reference omits version for HostedAgents."""
+        from agent_framework_foundry._foundry_agent_client import RawFoundryAgentChatClient
+
+        mock_project = MagicMock()
+        mock_project.get_openai_client.return_value = MagicMock()
+
+        client = RawFoundryAgentChatClient(
+            project_client=mock_project,
+            agent_name="hosted-agent",
+        )
+
+        ref = client._get_agent_reference()
+        assert ref == {"name": "hosted-agent", "type": "agent_reference"}
+        assert "version" not in ref
+
+    def test_as_agent_returns_foundry_agent_and_preserves_client_type(self) -> None:
+        """Test that as_agent() wraps the client in FoundryAgent using the same client class."""
+        from agent_framework_foundry._foundry_agent import FoundryAgent
+        from agent_framework_foundry._foundry_agent_client import RawFoundryAgentChatClient
+
+        class CustomClient(RawFoundryAgentChatClient):
+            pass
+
+        mock_project = MagicMock()
+        mock_project.get_openai_client.return_value = MagicMock()
+
+        client = CustomClient(
+            project_client=mock_project,
+            agent_name="test-agent",
+            agent_version="1.0",
+        )
+
+        agent = client.as_agent(instructions="You are helpful.")
+
+        assert isinstance(agent, FoundryAgent)
+        assert agent.name == "test-agent"
+        assert isinstance(agent.client, CustomClient)
+        assert agent.client.project_client is mock_project
+        assert agent.client.agent_name == "test-agent"
+        assert agent.client.agent_version == "1.0"
+
+        named_agent = client.as_agent(name="display-name", instructions="You are helpful.")
+        assert named_agent.name == "display-name"
+        assert named_agent.client.agent_name == "test-agent"
+
+    async def test_prepare_options_validates_tools(self) -> None:
+        """Test that _prepare_options rejects non-FunctionTool objects."""
+        from agent_framework import Message
+
+        from agent_framework_foundry._foundry_agent_client import RawFoundryAgentChatClient
+
+        mock_project = MagicMock()
+        mock_project.get_openai_client.return_value = MagicMock()
+
+        client = RawFoundryAgentChatClient(
+            project_client=mock_project,
+            agent_name="test-agent",
+        )
+
+        # A dict tool should be rejected
+        with pytest.raises(TypeError, match="Only FunctionTool objects are accepted"):
+            await client._prepare_options(
+                messages=[Message(role="user", contents="hi")],
+                options={"tools": [{"type": "function", "function": {"name": "bad"}}]},
+            )
+
+    async def test_prepare_options_accepts_function_tools(self) -> None:
+        """Test that _prepare_options accepts FunctionTool objects."""
+        from agent_framework import Message
+
+        from agent_framework_foundry._foundry_agent_client import RawFoundryAgentChatClient
+
+        mock_project = MagicMock()
+        mock_openai = MagicMock()
+        mock_project.get_openai_client.return_value = mock_openai
+
+        client = RawFoundryAgentChatClient(
+            project_client=mock_project,
+            agent_name="test-agent",
+        )
+
+        @tool(approval_mode="never_require")
+        def my_func() -> str:
+            """A test function."""
+            return "ok"
+
+        # Should not raise — patch the parent's _prepare_options
+        with patch(
+            "agent_framework_openai._chat_client.RawOpenAIChatClient._prepare_options",
+            new_callable=AsyncMock,
+            return_value={},
+        ):
+            result = await client._prepare_options(
+                messages=[Message(role="user", contents="hi")],
+                options={"tools": [my_func]},
+            )
+            assert "extra_body" in result
+            assert result["extra_body"]["agent_reference"]["name"] == "test-agent"
+
+    def test_check_model_presence_is_noop(self) -> None:
+        """Test that _check_model_presence does nothing (model is on service)."""
+        from agent_framework_foundry._foundry_agent_client import RawFoundryAgentChatClient
+
+        mock_project = MagicMock()
+        mock_project.get_openai_client.return_value = MagicMock()
+
+        client = RawFoundryAgentChatClient(
+            project_client=mock_project,
+            agent_name="test-agent",
+        )
+
+        options: dict[str, Any] = {}
+        client._check_model_presence(options)
+        assert "model" not in options
+
+
+class TestFoundryAgentChatClient:
+    """Tests for _FoundryAgentChatClient (full middleware)."""
+
+    def test_init(self) -> None:
+        """Test construction of the full-middleware client."""
+        from agent_framework_foundry._foundry_agent_client import _FoundryAgentChatClient
+
+        mock_project = MagicMock()
+        mock_project.get_openai_client.return_value = MagicMock()
+
+        client = _FoundryAgentChatClient(
+            project_client=mock_project,
+            agent_name="test-agent",
+            agent_version="1.0",
+        )
+
+        assert client.agent_name == "test-agent"
+
+
+class TestRawFoundryAgent:
+    """Tests for RawFoundryAgent."""
+
+    def test_init_creates_client(self) -> None:
+        """Test that RawFoundryAgent creates a client internally."""
+        from agent_framework_foundry._foundry_agent import RawFoundryAgent
+
+        mock_project = MagicMock()
+        mock_project.get_openai_client.return_value = MagicMock()
+
+        agent = RawFoundryAgent(
+            project_client=mock_project,
+            agent_name="test-agent",
+            agent_version="1.0",
+        )
+
+        assert agent.client is not None
+        assert agent.client.agent_name == "test-agent"
+
+    def test_init_with_custom_client_type(self) -> None:
+        """Test that client_type parameter is respected."""
+        from agent_framework_foundry._foundry_agent import RawFoundryAgent
+        from agent_framework_foundry._foundry_agent_client import RawFoundryAgentChatClient
+
+        mock_project = MagicMock()
+        mock_project.get_openai_client.return_value = MagicMock()
+
+        agent = RawFoundryAgent(
+            project_client=mock_project,
+            agent_name="test-agent",
+            client_type=RawFoundryAgentChatClient,
+        )
+
+        assert isinstance(agent.client, RawFoundryAgentChatClient)
+
+    def test_init_rejects_invalid_client_type(self) -> None:
+        """Test that invalid client_type raises TypeError."""
+        from agent_framework_foundry._foundry_agent import RawFoundryAgent
+
+        with pytest.raises(TypeError, match="must be a subclass of RawFoundryAgentChatClient"):
+            RawFoundryAgent(
+                project_client=MagicMock(),
+                agent_name="test-agent",
+                client_type=object,  # type: ignore[arg-type]
+            )
+
+    def test_init_with_function_tools(self) -> None:
+        """Test that FunctionTool and callables are accepted."""
+        from agent_framework_foundry._foundry_agent import RawFoundryAgent
+
+        mock_project = MagicMock()
+        mock_project.get_openai_client.return_value = MagicMock()
+
+        @tool(approval_mode="never_require")
+        def my_func() -> str:
+            """A test function."""
+            return "ok"
+
+        agent = RawFoundryAgent(
+            project_client=mock_project,
+            agent_name="test-agent",
+            tools=[my_func],
+        )
+
+        assert agent.default_options.get("tools") is not None
+
+
+class TestFoundryAgent:
+    """Tests for FoundryAgent (full middleware)."""
+
+    def test_init(self) -> None:
+        """Test construction of the full-middleware agent."""
+        from agent_framework_foundry._foundry_agent import FoundryAgent
+
+        mock_project = MagicMock()
+        mock_project.get_openai_client.return_value = MagicMock()
+
+        agent = FoundryAgent(
+            project_client=mock_project,
+            agent_name="test-agent",
+            agent_version="1.0",
+        )
+
+        assert agent.client is not None
+        assert agent.client.agent_name == "test-agent"
+
+    def test_init_with_middleware(self) -> None:
+        """Test that agent-level middleware is accepted."""
+        from agent_framework import ChatContext, ChatMiddleware
+
+        from agent_framework_foundry._foundry_agent import FoundryAgent
+
+        mock_project = MagicMock()
+        mock_project.get_openai_client.return_value = MagicMock()
+
+        class MyMiddleware(ChatMiddleware):
+            async def process(self, context: ChatContext) -> None:
+                pass
+
+        agent = FoundryAgent(
+            project_client=mock_project,
+            agent_name="test-agent",
+            middleware=[MyMiddleware()],
+        )
+
+        assert agent.client is not None
+
+
+class TestFoundryChatClientToolMethods:
+    """Tests for RawFoundryChatClient tool factory methods."""
+
+    def test_get_code_interpreter_tool(self) -> None:
+        """Test code interpreter tool creation."""
+        from agent_framework_foundry._foundry_chat_client import RawFoundryChatClient
+
+        tool_obj = RawFoundryChatClient.get_code_interpreter_tool()
+        assert tool_obj is not None
+
+    def test_get_code_interpreter_tool_with_file_ids(self) -> None:
+        """Test code interpreter tool with file IDs."""
+        from agent_framework_foundry._foundry_chat_client import RawFoundryChatClient
+
+        tool_obj = RawFoundryChatClient.get_code_interpreter_tool(file_ids=["file-abc123"])
+        assert tool_obj is not None
+
+    def test_get_file_search_tool(self) -> None:
+        """Test file search tool creation."""
+        from agent_framework_foundry._foundry_chat_client import RawFoundryChatClient
+
+        tool_obj = RawFoundryChatClient.get_file_search_tool(vector_store_ids=["vs_abc123"])
+        assert tool_obj is not None
+
+    def test_get_file_search_tool_requires_vector_store_ids(self) -> None:
+        """Test that empty vector_store_ids raises ValueError."""
+        from agent_framework_foundry._foundry_chat_client import RawFoundryChatClient
+
+        with pytest.raises(ValueError, match="vector_store_ids"):
+            RawFoundryChatClient.get_file_search_tool(vector_store_ids=[])
+
+    def test_get_web_search_tool(self) -> None:
+        """Test web search tool creation."""
+        from agent_framework_foundry._foundry_chat_client import RawFoundryChatClient
+
+        tool_obj = RawFoundryChatClient.get_web_search_tool()
+        assert tool_obj is not None
+
+    def test_get_web_search_tool_with_location(self) -> None:
+        """Test web search tool with user location."""
+        from agent_framework_foundry._foundry_chat_client import RawFoundryChatClient
+
+        tool_obj = RawFoundryChatClient.get_web_search_tool(
+            user_location={"city": "Seattle", "country": "US"},
+            search_context_size="high",
+        )
+        assert tool_obj is not None
+
+    def test_get_image_generation_tool(self) -> None:
+        """Test image generation tool creation."""
+        from agent_framework_foundry._foundry_chat_client import RawFoundryChatClient
+
+        tool_obj = RawFoundryChatClient.get_image_generation_tool()
+        assert tool_obj is not None
+
+    def test_get_mcp_tool(self) -> None:
+        """Test MCP tool creation."""
+        from agent_framework_foundry._foundry_chat_client import RawFoundryChatClient
+
+        tool_obj = RawFoundryChatClient.get_mcp_tool(
+            name="my_mcp",
+            url="https://mcp.example.com",
+        )
+        assert tool_obj is not None
+
+    def test_get_mcp_tool_with_connection_id(self) -> None:
+        """Test MCP tool with project connection ID."""
+        from agent_framework_foundry._foundry_chat_client import RawFoundryChatClient
+
+        tool_obj = RawFoundryChatClient.get_mcp_tool(
+            name="github_mcp",
+            project_connection_id="conn_abc123",
+            description="GitHub MCP via Foundry",
+        )
+        assert tool_obj is not None

python/packages/foundry/tests/test_foundry_memory_provider.py

@@ -10,7 +10,7 @@ import pytest
 from agent_framework import AGENT_FRAMEWORK_USER_AGENT, AgentResponse, Message
 from agent_framework._sessions import AgentSession, SessionContext
 
-from agent_framework_azure_ai._foundry_memory_provider import FoundryMemoryProvider
+from agent_framework_foundry._foundry_memory_provider import FoundryMemoryProvider
 
 
 @pytest.fixture
@@ -81,7 +81,7 @@ class TestInit:
     def test_init_with_project_endpoint_and_credential(
         self, mock_project_client: AsyncMock, mock_credential: Mock
     ) -> None:
-        with patch("agent_framework_azure_ai._foundry_memory_provider.AIProjectClient") as mock_ai_project_client:
+        with patch("agent_framework_foundry._foundry_memory_provider.AIProjectClient") as mock_ai_project_client:
             mock_ai_project_client.return_value = mock_project_client
             provider = FoundryMemoryProvider(
                 project_endpoint="https://test.project.endpoint",
@@ -100,7 +100,7 @@ class TestInit:
 
     def test_init_requires_project_endpoint_without_project_client(self) -> None:
         with (
-            patch("agent_framework_azure_ai._foundry_memory_provider.load_settings") as mock_load_settings,
+            patch("agent_framework_foundry._foundry_memory_provider.load_settings") as mock_load_settings,
             patch.dict(os.environ, {}, clear=True),
             pytest.raises(ValueError, match="project endpoint is required"),
         ):

python/packages/foundry_local/AGENTS.md

@@ -11,7 +11,7 @@ Integration with Azure AI Foundry Local for local model inference.
 ## Usage
 
 ```python
-from agent_framework_foundry_local import FoundryLocalClient
+from agent_framework.foundry import FoundryLocalClient
 
 client = FoundryLocalClient(model_id="your-local-model")
 response = await client.get_response("Hello")
@@ -20,5 +20,5 @@ response = await client.get_response("Hello")
 ## Import Path
 
 ```python
-from agent_framework_foundry_local import FoundryLocalClient
+from agent_framework.foundry import FoundryLocalClient
 ```

python/packages/foundry_local/README.md

@@ -10,4 +10,4 @@ and see the [README](https://github.com/microsoft/agent-framework/tree/main/pyth
 
 ## Foundry Local Sample
 
-See the [Foundry Local provider sample](../../samples/02-agents/providers/foundry_local/foundry_local_agent.py) for a runnable example.
+See the [Foundry Local provider sample](../../samples/02-agents/providers/foundry/foundry_local_agent.py) for a runnable example.

python/packages/foundry_local/agent_framework_foundry_local/_foundry_local_client.py

@@ -15,7 +15,7 @@ from agent_framework import (
 )
 from agent_framework._settings import load_settings
 from agent_framework.observability import ChatTelemetryLayer
-from agent_framework.openai._chat_client import RawOpenAIChatClient
+from agent_framework_openai._chat_completion_client import RawOpenAIChatCompletionClient
 from foundry_local import FoundryLocalManager
 from foundry_local.models import DeviceType
 from openai import AsyncOpenAI
@@ -126,21 +126,21 @@ class FoundryLocalSettings(TypedDict, total=False):
             (Env var FOUNDRY_LOCAL_MODEL_ID)
     """
 
-    model_id: str | None
+    model: str | None
 
 
 class FoundryLocalClient(
     FunctionInvocationLayer[FoundryLocalChatOptionsT],
     ChatMiddlewareLayer[FoundryLocalChatOptionsT],
     ChatTelemetryLayer[FoundryLocalChatOptionsT],
-    RawOpenAIChatClient[FoundryLocalChatOptionsT],
+    RawOpenAIChatCompletionClient[FoundryLocalChatOptionsT],
     Generic[FoundryLocalChatOptionsT],
 ):
     """Foundry Local Chat completion class with middleware, telemetry, and function invocation support."""
 
     def __init__(
         self,
-        model_id: str | None = None,
+        model: str | None = None,
         *,
         bootstrap: bool = True,
         timeout: float | None = None,
@@ -155,7 +155,7 @@ class FoundryLocalClient(
         """Initialize a FoundryLocalClient.
 
         Keyword Args:
-            model_id: The Foundry Local model ID or alias to use. If not provided,
+            model: The Foundry Local model ID or alias to use. If not provided,
                 it will be loaded from the FoundryLocalSettings.
             bootstrap: Whether to start the Foundry Local service if not already running.
                 Default is True.
@@ -180,7 +180,7 @@ class FoundryLocalClient(
             .. code-block:: python
 
                 # Create a FoundryLocalClient with a specific model ID:
-                from agent_framework_foundry_local import FoundryLocalClient
+                from agent_framework.foundry import FoundryLocalClient
 
                 client = FoundryLocalClient(model_id="phi-4-mini")
 
@@ -225,7 +225,7 @@ class FoundryLocalClient(
 
                 # Using custom ChatOptions with type safety:
                 from typing import TypedDict
-                from agent_framework_foundry_local import FoundryLocalChatOptions
+                from agent_framework.foundry import FoundryLocalChatOptions
 
                 class MyOptions(FoundryLocalChatOptions, total=False):
                     my_custom_option: str
@@ -242,25 +242,23 @@ class FoundryLocalClient(
         settings = load_settings(
             FoundryLocalSettings,
             env_prefix="FOUNDRY_LOCAL_",
-            required_fields=["model_id"],
-            model_id=model_id,
+            required_fields=["model"],
+            model=model,
             env_file_path=env_file_path,
             env_file_encoding=env_file_encoding,
         )
-        model_id_setting: str = settings["model_id"]  # type: ignore[assignment]  # pyright: ignore[reportTypedDictNotRequiredAccess]
+        model_setting: str = settings["model"]  # type: ignore[assignment]  # pyright: ignore[reportTypedDictNotRequiredAccess]
 
         manager = FoundryLocalManager(bootstrap=bootstrap, timeout=timeout)
         model_info = manager.get_model_info(
-            alias_or_model_id=model_id_setting,
+            alias_or_model_id=model_setting,
             device=device,
         )
         if model_info is None:
             message = (
-                f"Model with ID or alias '{model_id_setting}:{device.value}' not found in Foundry Local."
+                f"Model with ID or alias '{model_setting}:{device.value}' not found in Foundry Local."
                 if device
-                else (
-                    f"Model with ID or alias '{model_id_setting}' for your current device not found in Foundry Local."
-                )
+                else (f"Model with ID or alias '{model_setting}' for your current device not found in Foundry Local.")
             )
             raise ValueError(message)
         if prepare_model:
@@ -268,8 +266,8 @@ class FoundryLocalClient(
             manager.load_model(alias_or_model_id=model_info.id, device=device)
 
         super().__init__(
-            model_id=model_info.id,
-            client=AsyncOpenAI(base_url=manager.endpoint, api_key=manager.api_key),
+            model=model_info.id,
+            async_client=AsyncOpenAI(base_url=manager.endpoint, api_key=manager.api_key),
             additional_properties=additional_properties,
             middleware=middleware,
             function_invocation_configuration=function_invocation_configuration,

python/packages/foundry_local/pyproject.toml

@@ -24,6 +24,7 @@ classifiers = [
 ]
 dependencies = [
     "agent-framework-core>=1.0.0rc5",
+    "agent-framework-openai>=1.0.0rc5",
     "foundry-local-sdk>=0.5.1,<0.5.2",
 ]
 

python/packages/foundry_local/tests/conftest.py

@@ -27,7 +27,7 @@ def foundry_local_unit_test_env(monkeypatch: Any, exclude_list: list[str], overr
         override_env_param_dict = {}
 
     env_vars = {
-        "FOUNDRY_LOCAL_MODEL_ID": "test-model-id",
+        "FOUNDRY_LOCAL_MODEL": "test-model-id",
     }
 
     env_vars.update(override_env_param_dict)

python/packages/foundry_local/tests/test_foundry_local_client.py

@@ -6,8 +6,8 @@ import pytest
 from agent_framework import SupportsChatGetResponse
 from agent_framework._settings import load_settings
 from agent_framework.exceptions import SettingNotFoundError
+from agent_framework.foundry import FoundryLocalClient
 
-from agent_framework_foundry_local import FoundryLocalClient
 from agent_framework_foundry_local._foundry_local_client import FoundryLocalSettings
 
 # Settings Tests
@@ -17,7 +17,7 @@ def test_foundry_local_settings_init_from_env(foundry_local_unit_test_env: dict[
     """Test FoundryLocalSettings initialization from environment variables."""
     settings = load_settings(FoundryLocalSettings, env_prefix="FOUNDRY_LOCAL_")
 
-    assert settings["model_id"] == foundry_local_unit_test_env["FOUNDRY_LOCAL_MODEL_ID"]
+    assert settings["model"] == foundry_local_unit_test_env["FOUNDRY_LOCAL_MODEL"]
 
 
 def test_foundry_local_settings_init_with_explicit_values() -> None:
@@ -25,29 +25,29 @@ def test_foundry_local_settings_init_with_explicit_values() -> None:
     settings = load_settings(
         FoundryLocalSettings,
         env_prefix="FOUNDRY_LOCAL_",
-        model_id="custom-model-id",
+        model="custom-model-id",
     )
 
-    assert settings["model_id"] == "custom-model-id"
+    assert settings["model"] == "custom-model-id"
 
 
-@pytest.mark.parametrize("exclude_list", [["FOUNDRY_LOCAL_MODEL_ID"]], indirect=True)
-def test_foundry_local_settings_missing_model_id(foundry_local_unit_test_env: dict[str, str]) -> None:
+@pytest.mark.parametrize("exclude_list", [["FOUNDRY_LOCAL_MODEL"]], indirect=True)
+def test_foundry_local_settings_missing_model(foundry_local_unit_test_env: dict[str, str]) -> None:
     """Test FoundryLocalSettings when model_id is missing raises error."""
-    with pytest.raises(SettingNotFoundError, match="Required setting 'model_id'"):
+    with pytest.raises(SettingNotFoundError, match="Required setting 'model'"):
         load_settings(
             FoundryLocalSettings,
             env_prefix="FOUNDRY_LOCAL_",
-            required_fields=["model_id"],
+            required_fields=["model"],
         )
 
 
 def test_foundry_local_settings_explicit_overrides_env(foundry_local_unit_test_env: dict[str, str]) -> None:
     """Test that explicit values override environment variables."""
-    settings = load_settings(FoundryLocalSettings, env_prefix="FOUNDRY_LOCAL_", model_id="override-model-id")
+    settings = load_settings(FoundryLocalSettings, env_prefix="FOUNDRY_LOCAL_", model="override-model-id")
 
-    assert settings["model_id"] == "override-model-id"
-    assert settings["model_id"] != foundry_local_unit_test_env["FOUNDRY_LOCAL_MODEL_ID"]
+    assert settings["model"] == "override-model-id"
+    assert settings["model"] != foundry_local_unit_test_env["FOUNDRY_LOCAL_MODEL"]
 
 
 # Client Initialization Tests
@@ -59,9 +59,9 @@ def test_foundry_local_client_init(mock_foundry_local_manager: MagicMock) -> Non
         "agent_framework_foundry_local._foundry_local_client.FoundryLocalManager",
         return_value=mock_foundry_local_manager,
     ):
-        client = FoundryLocalClient(model_id="test-model-id")
+        client = FoundryLocalClient(model="test-model-id")
 
-        assert client.model_id == "test-model-id"
+        assert client.model == "test-model-id"
         assert client.manager is mock_foundry_local_manager
         assert isinstance(client, SupportsChatGetResponse)
 
@@ -72,7 +72,7 @@ def test_foundry_local_client_init_with_bootstrap_false(mock_foundry_local_manag
         "agent_framework_foundry_local._foundry_local_client.FoundryLocalManager",
         return_value=mock_foundry_local_manager,
     ) as mock_manager_class:
-        FoundryLocalClient(model_id="test-model-id", bootstrap=False)
+        FoundryLocalClient(model="test-model-id", bootstrap=False)
 
         mock_manager_class.assert_called_once_with(
             bootstrap=False,
@@ -86,7 +86,7 @@ def test_foundry_local_client_init_with_timeout(mock_foundry_local_manager: Magi
         "agent_framework_foundry_local._foundry_local_client.FoundryLocalManager",
         return_value=mock_foundry_local_manager,
     ) as mock_manager_class:
-        FoundryLocalClient(model_id="test-model-id", timeout=60.0)
+        FoundryLocalClient(model="test-model-id", timeout=60.0)
 
         mock_manager_class.assert_called_once_with(
             bootstrap=True,
@@ -105,7 +105,7 @@ def test_foundry_local_client_init_model_not_found(mock_foundry_local_manager: M
         ),
         pytest.raises(ValueError, match="not found in Foundry Local"),
     ):
-        FoundryLocalClient(model_id="unknown-model")
+        FoundryLocalClient(model="unknown-model")
 
 
 def test_foundry_local_client_uses_model_info_id(mock_foundry_local_manager: MagicMock) -> None:
@@ -118,9 +118,9 @@ def test_foundry_local_client_uses_model_info_id(mock_foundry_local_manager: Mag
         "agent_framework_foundry_local._foundry_local_client.FoundryLocalManager",
         return_value=mock_foundry_local_manager,
     ):
-        client = FoundryLocalClient(model_id="model-alias")
+        client = FoundryLocalClient(model="model-alias")
 
-        assert client.model_id == "resolved-model-id"
+        assert client.model == "resolved-model-id"
 
 
 def test_foundry_local_client_init_from_env(
@@ -133,7 +133,7 @@ def test_foundry_local_client_init_from_env(
     ):
         client = FoundryLocalClient()
 
-        assert client.model_id == foundry_local_unit_test_env["FOUNDRY_LOCAL_MODEL_ID"]
+        assert client.model == foundry_local_unit_test_env["FOUNDRY_LOCAL_MODEL"]
 
 
 def test_foundry_local_client_init_with_device(mock_foundry_local_manager: MagicMock) -> None:
@@ -144,7 +144,7 @@ def test_foundry_local_client_init_with_device(mock_foundry_local_manager: Magic
         "agent_framework_foundry_local._foundry_local_client.FoundryLocalManager",
         return_value=mock_foundry_local_manager,
     ):
-        FoundryLocalClient(model_id="test-model-id", device=DeviceType.CPU)
+        FoundryLocalClient(model="test-model-id", device=DeviceType.CPU)
 
         mock_foundry_local_manager.get_model_info.assert_called_once_with(
             alias_or_model_id="test-model-id",
@@ -173,7 +173,7 @@ def test_foundry_local_client_init_model_not_found_with_device(mock_foundry_loca
         ),
         pytest.raises(ValueError, match="unknown-model:GPU.*not found"),
     ):
-        FoundryLocalClient(model_id="unknown-model", device=DeviceType.GPU)
+        FoundryLocalClient(model="unknown-model", device=DeviceType.GPU)
 
 
 def test_foundry_local_client_init_with_prepare_model_false(mock_foundry_local_manager: MagicMock) -> None:
@@ -182,7 +182,7 @@ def test_foundry_local_client_init_with_prepare_model_false(mock_foundry_local_m
         "agent_framework_foundry_local._foundry_local_client.FoundryLocalManager",
         return_value=mock_foundry_local_manager,
     ):
-        FoundryLocalClient(model_id="test-model-id", prepare_model=False)
+        FoundryLocalClient(model="test-model-id", prepare_model=False)
 
         mock_foundry_local_manager.download_model.assert_not_called()
         mock_foundry_local_manager.load_model.assert_not_called()
@@ -194,7 +194,7 @@ def test_foundry_local_client_init_calls_download_and_load(mock_foundry_local_ma
         "agent_framework_foundry_local._foundry_local_client.FoundryLocalManager",
         return_value=mock_foundry_local_manager,
     ):
-        FoundryLocalClient(model_id="test-model-id")
+        FoundryLocalClient(model="test-model-id")
 
         mock_foundry_local_manager.download_model.assert_called_once_with(
             alias_or_model_id="test-model-id",

python/packages/lab/lightning/samples/train_math_agent.py

@@ -140,8 +140,9 @@ def evaluate(result: AgentResponse, ground_truth: str) -> float:
 AGENT_INSTRUCTION = """
 Solve the following math problem. Use the calculator tool to help you calculate math expressions.
 
-Output the answer when you are ready. The answer should be after three sharps (`###`), with no extra punctuations or texts. For example: ### 123
-""".strip()  # noqa: E501
+Output the answer when you are ready. The answer should be after three sharps (`###`),
+with no extra punctuations or texts. For example: ### 123
+""".strip()
 
 
 # The @rollout decorator is the key integration point with agent-lightning.

python/packages/lab/lightning/tests/test_lightning.py

@@ -8,7 +8,7 @@ from unittest.mock import AsyncMock, patch
 import pytest
 
 from agent_framework import AgentExecutor, AgentResponse, Agent, WorkflowBuilder, Workflow
-from agent_framework.openai import OpenAIChatClient
+from agent_framework.openai import OpenAIChatCompletionClient
 from openai.types.chat import ChatCompletion, ChatCompletionMessage
 from openai.types.chat.chat_completion import Choice
 
@@ -54,11 +54,11 @@ def workflow_two_agents():
         "os.environ",
         {
             "OPENAI_API_KEY": "test-key",
-            "OPENAI_CHAT_MODEL_ID": "gpt-4o",
+            "OPENAI_MODEL": "gpt-4o",
         },
     ):
-        first_chat_client = OpenAIChatClient()
-        second_chat_client = OpenAIChatClient()
+        first_chat_client = OpenAIChatCompletionClient()
+        second_chat_client = OpenAIChatCompletionClient()
 
         # Mock the OpenAI API calls
         with (

python/packages/openai/AGENTS.md

@@ -0,0 +1,34 @@
+# AGENTS.md — agent-framework-openai
+
+OpenAI integration package for Agent Framework. Contains OpenAI Responses API and Chat Completions API clients.
+
+## Package Structure
+
+```
+agent_framework_openai/
+├── __init__.py                 # Public API exports
+├── _chat_client.py             # OpenAIChatClient (Responses API) + RawOpenAIChatClient
+├── _chat_completion_client.py  # OpenAIChatCompletionClient (Chat Completions API) + RawOpenAIChatCompletionClient
+├── _embedding_client.py        # OpenAIEmbeddingClient
+├── _exceptions.py              # OpenAI-specific exceptions
+├── _shared.py                  # OpenAIBase, OpenAIConfigMixin, OpenAISettings
+├── _assistants_client.py       # OpenAIAssistantsClient (DEPRECATED)
+└── _assistant_provider.py      # OpenAIAssistantProvider (DEPRECATED)
+```
+
+## Key Classes
+
+| Class | API | Status |
+|---|---|---|
+| `OpenAIChatClient` | Responses API | Primary |
+| `OpenAIChatCompletionClient` | Chat Completions API | Primary |
+| `OpenAIEmbeddingClient` | Embeddings API | Primary |
+| `OpenAIAssistantsClient` | Assistants API | Deprecated |
+
+All clients follow the Raw + Full-Featured pattern (e.g., `RawOpenAIChatClient` + `OpenAIChatClient`).
+
+## Dependencies
+
+- `agent-framework-core` — core abstractions
+- `openai` — OpenAI Python SDK
+- `packaging` — version checking

python/packages/openai/LICENSE

@@ -0,0 +1,21 @@
+    MIT License
+
+    Copyright (c) Microsoft Corporation.
+
+    Permission is hereby granted, free of charge, to any person obtaining a copy
+    of this software and associated documentation files (the "Software"), to deal
+    in the Software without restriction, including without limitation the rights
+    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+    copies of the Software, and to permit persons to whom the Software is
+    furnished to do so, subject to the following conditions:
+
+    The above copyright notice and this permission notice shall be included in all
+    copies or substantial portions of the Software.
+
+    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+    SOFTWARE

python/packages/openai/README.md

@@ -0,0 +1,17 @@
+# agent-framework-openai
+
+OpenAI integration for Microsoft Agent Framework. Provides chat clients for the OpenAI Responses API and Chat Completions API.
+
+## Installation
+
+```bash
+pip install agent-framework-openai
+```
+
+## Usage
+
+```python
+from agent_framework.openai import OpenAIChatClient
+
+client = OpenAIChatClient(model_id="gpt-4o")
+```

python/packages/openai/agent_framework_openai/__init__.py

@@ -0,0 +1,87 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""OpenAI integration for Microsoft Agent Framework.
+
+This package provides OpenAI client implementations for the Agent Framework,
+including clients for the Responses API and Chat Completions API.
+"""
+
+import importlib.metadata
+import sys
+
+if sys.version_info >= (3, 13):
+    from warnings import deprecated  # type: ignore # pragma: no cover
+else:
+    from typing_extensions import deprecated  # type: ignore # pragma: no cover
+
+from ._assistant_provider import OpenAIAssistantProvider
+from ._assistants_client import (
+    AssistantToolResources,
+    OpenAIAssistantsClient,
+    OpenAIAssistantsOptions,
+)
+from ._chat_client import (
+    OpenAIChatClient,
+    OpenAIChatOptions,
+    OpenAIContinuationToken,
+    RawOpenAIChatClient,
+)
+from ._chat_completion_client import (
+    OpenAIChatCompletionClient,
+    OpenAIChatCompletionOptions,
+    RawOpenAIChatCompletionClient,
+)
+from ._embedding_client import OpenAIEmbeddingClient, OpenAIEmbeddingOptions
+from ._exceptions import ContentFilterResultSeverity, OpenAIContentFilterException
+from ._shared import OpenAISettings
+
+try:
+    __version__ = importlib.metadata.version("agent-framework-openai")
+except importlib.metadata.PackageNotFoundError:
+    __version__ = "0.0.0"  # Fallback for development mode
+
+# Deprecated aliases for old names — use subclasses so the warning only fires for the alias
+
+
+@deprecated(
+    "OpenAIResponsesClient is deprecated, use OpenAIChatClient instead.",
+    category=DeprecationWarning,
+)
+class OpenAIResponsesClient(OpenAIChatClient):  # type: ignore[misc]
+    """Deprecated alias for :class:`OpenAIChatClient`."""
+
+
+@deprecated(
+    "RawOpenAIResponsesClient is deprecated, use RawOpenAIChatClient instead.",
+    category=DeprecationWarning,
+)
+class RawOpenAIResponsesClient(RawOpenAIChatClient):  # type: ignore[misc]
+    """Deprecated alias for :class:`RawOpenAIChatClient`."""
+
+
+OpenAIResponsesOptions = OpenAIChatOptions
+"""Deprecated alias for :class:`OpenAIChatOptions`."""
+
+
+__all__ = [
+    "AssistantToolResources",
+    "ContentFilterResultSeverity",
+    "OpenAIAssistantProvider",
+    "OpenAIAssistantsClient",
+    "OpenAIAssistantsOptions",
+    "OpenAIChatClient",
+    "OpenAIChatCompletionClient",
+    "OpenAIChatCompletionOptions",
+    "OpenAIChatOptions",
+    "OpenAIContentFilterException",
+    "OpenAIContinuationToken",
+    "OpenAIEmbeddingClient",
+    "OpenAIEmbeddingOptions",
+    "OpenAIResponsesClient",
+    "OpenAIResponsesOptions",
+    "OpenAISettings",
+    "RawOpenAIChatClient",
+    "RawOpenAIChatCompletionClient",
+    "RawOpenAIResponsesClient",
+    "__version__",
+]

python/packages/openai/agent_framework_openai/_assistant_provider.py

@@ -6,16 +6,15 @@ import sys
 from collections.abc import Awaitable, Callable, Mapping, MutableMapping, Sequence
 from typing import TYPE_CHECKING, Any, Generic, cast
 
+from agent_framework._agents import Agent
+from agent_framework._middleware import MiddlewareTypes
+from agent_framework._sessions import BaseContextProvider
+from agent_framework._settings import SecretString, load_settings
+from agent_framework._tools import FunctionTool, ToolTypes, normalize_tools
 from openai import AsyncOpenAI
 from openai.types.beta.assistant import Assistant
 from pydantic import BaseModel
 
-from agent_framework._settings import SecretString, load_settings
-
-from .._agents import Agent
-from .._middleware import MiddlewareTypes
-from .._sessions import BaseContextProvider
-from .._tools import FunctionTool, ToolTypes, normalize_tools
 from ._assistants_client import OpenAIAssistantsClient
 from ._shared import OpenAISettings, from_assistant_tools, to_assistant_tools
 
@@ -540,7 +539,7 @@ class OpenAIAssistantProvider(Generic[OptionsCoT]):
         """
         # Create the chat client with the assistant
         client = OpenAIAssistantsClient(
-            model_id=assistant.model,
+            model=assistant.model,
             assistant_id=assistant.id,
             assistant_name=assistant.name,
             assistant_description=assistant.description,