Python: Bump Python package versions for 1.2.0 release (#5468 )

* Bump Python package versions for 1.2.0 release Released tier bumps 1.1.1 -> 1.2.0 (core, openai, foundry, root) to reflect additive public APIs landed since 1.1.0: functional workflow API (#4238) and FunctionTool SKIP_PARSING sentinel (#5424). All beta packages stamped 1.0.0b260424, alpha packages 1.0.0a260424. All 26 non-core agent-framework-core floors raised to >=1.2.0,<2. CHANGELOG consolidates the never-tagged 1.1.1 entries with the post-merge additions into [1.2.0]. * Update CHANGELOG footer links for 1.2.0 Advance [Unreleased] comparison base from python-1.1.0 to python-1.2.0 and add a [1.2.0] reference link comparing python-1.1.0...python-1.2.0 so the heading links resolve correctly. * Fix CHANGELOG: restore [1.1.1] section and add proper [1.2.0] Previous commit incorrectly renamed the [1.1.1] header to [1.2.0], which wiped the historical 1.1.1 entries and wrongly attributed them to 1.2.0. This restores [1.1.1] to its origin/main content and adds a new [1.2.0] section above containing only the commits in python-1.1.1..HEAD: - #4238 functional workflow API - #5142 GitHub Copilot OpenTelemetry - #2403 A2A bridge support - #5070 oauth_consent_request events in Foundry clients - #5447 FoundryAgent hosted agent sessions - #5459 hosting server dependency upgrade + types - #5389 AG-UI reasoning/multimodal parsing fix - #5440 stop [TOOLBOXES] warning spam - #5455 user agent prefix fix Also corrects the [1.2.0] compare base to python-1.1.1 (not 1.1.0) and adds the missing [1.1.1] reference link.
Python: Surface oauth_consent_request events from Responses API in Foundry clients (#5070 )
2026-06-16 21:04:09 +08:00 · 2026-04-24 19:54:59 +09:00 · 2026-04-24 09:59:14 +00:00 · 2026-04-24 09:41:20 +00:00 · 2026-04-24 09:25:03 +00:00
70 changed files with 5287 additions and 282 deletions
@@ -7,6 +7,23 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

 ## [Unreleased]

+## [1.2.0] - 2026-04-24
+
+### Added
+- **agent-framework-core**: Add functional workflow API ([#4238](https://github.com/microsoft/agent-framework/pull/4238))
+- **agent-framework-core**, **agent-framework-github-copilot**: Add OpenTelemetry integration for `GitHubCopilotAgent` ([#5142](https://github.com/microsoft/agent-framework/pull/5142))
+- **agent-framework-a2a**: Add Agent Framework to A2A bridge support ([#2403](https://github.com/microsoft/agent-framework/pull/2403))
+- **agent-framework-foundry**: Surface `oauth_consent_request` events from Responses API in Foundry clients ([#5070](https://github.com/microsoft/agent-framework/pull/5070))
+
+### Changed
+- **agent-framework-core**, **agent-framework-foundry**: Update `FoundryAgent` for hosted agent sessions ([#5447](https://github.com/microsoft/agent-framework/pull/5447))
+- **agent-framework-foundry-hosting**: Upgrade hosting server dependency and add more type support ([#5459](https://github.com/microsoft/agent-framework/pull/5459))
+
+### Fixed
+- **agent-framework-ag-ui**: Fix reasoning role and multimodal media parsing to follow specification ([#5389](https://github.com/microsoft/agent-framework/pull/5389))
+- **agent-framework-foundry**: Stop emitting `[TOOLBOXES]` warning for every `FoundryChatClient` call ([#5440](https://github.com/microsoft/agent-framework/pull/5440))
+- **agent-framework-anthropic**, **agent-framework-azure-ai-search**, **agent-framework-azure-cosmos**: Fix user agent prefix ([#5455](https://github.com/microsoft/agent-framework/pull/5455))
+
 ## [1.1.1] - 2026-04-23

 ### Added
@@ -26,8 +43,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - **agent-framework-openai**: Exclude null `file_id` from `input_image` payload to prevent schema 400 errors ([#5125](https://github.com/microsoft/agent-framework/pull/5125))
 - **agent-framework-foundry**: Reconcile Toolbox hosted-tool payloads with the Responses API ([#5414](https://github.com/microsoft/agent-framework/pull/5414))
 - **agent-framework-ag-ui**: Pass client `thread_id` as `session_id` when constructing `AgentSession` ([#5384](https://github.com/microsoft/agent-framework/pull/5384))
- **agent-framework-hyperlight**: Thread-confine `WasmSandbox` interactions via per-entry `ThreadPoolExecutor` to eliminate the PyO3 `unsendable` panic when touched from asyncio worker threads
-  ([#5424](https://github.com/microsoft/agent-framework/pull/5424))
+- **agent-framework-hyperlight**: Thread-confine `WasmSandbox` interactions via per-entry `ThreadPoolExecutor` to eliminate the PyO3 `unsendable` panic when touched from asyncio worker threads ([#5424](https://github.com/microsoft/agent-framework/pull/5424))

 ## [1.1.0] - 2026-04-21

@@ -961,7 +977,9 @@ Release candidate for **agent-framework-core** and **agent-framework-azure-ai**

 For more information, see the [announcement blog post](https://devblogs.microsoft.com/foundry/introducing-microsoft-agent-framework-the-open-source-engine-for-agentic-ai-apps/).

-[Unreleased]: https://github.com/microsoft/agent-framework/compare/python-1.1.0...HEAD
+[Unreleased]: https://github.com/microsoft/agent-framework/compare/python-1.2.0...HEAD
+[1.2.0]: https://github.com/microsoft/agent-framework/compare/python-1.1.1...python-1.2.0
+[1.1.1]: https://github.com/microsoft/agent-framework/compare/python-1.1.0...python-1.1.1
 [1.1.0]: https://github.com/microsoft/agent-framework/compare/python-1.0.1...python-1.1.0
 [1.0.1]: https://github.com/microsoft/agent-framework/compare/python-1.0.0...python-1.0.1
 [1.0.0]: https://github.com/microsoft/agent-framework/compare/python-1.0.0rc6...python-1.0.0
@@ -4,7 +4,7 @@ description = "A2A integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "a2a-sdk>=0.3.5,<0.3.24",
 ]

@@ -1,6 +1,6 @@
 [project]
 name = "agent-framework-ag-ui"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 description = "AG-UI protocol integration for Agent Framework"
 readme = "README.md"
 license-files = ["LICENSE"]
@@ -22,7 +22,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "ag-ui-protocol>=0.1.16,<0.2",
    "fastapi>=0.115.0,<0.133.1",
    "uvicorn[standard]>=0.30.0,<0.42.0"
@@ -4,7 +4,7 @@ description = "Anthropic integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "anthropic>=0.80.0,<0.80.1",
 ]

@@ -4,7 +4,7 @@ description = "Azure AI Search integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "azure-search-documents>=11.7.0b2,<11.7.0b3",
 ]

@@ -4,7 +4,7 @@ description = "Azure Cosmos DB history provider integration for Microsoft Agent
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "azure-cosmos>=4.3.0,<5",
 ]

@@ -4,7 +4,7 @@ description = "Azure Functions integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -22,7 +22,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "agent-framework-durabletask",
    "azure-functions>=1.24.0,<2",
    "azure-functions-durable>=1.3.1,<2",
@@ -4,7 +4,7 @@ description = "Amazon Bedrock integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "boto3>=1.35.0,<2.0.0",
    "botocore>=1.35.0,<2.0.0",
 ]
@@ -4,7 +4,7 @@ description = "OpenAI ChatKit integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -22,7 +22,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "openai-chatkit>=1.4.1,<2.0.0",
 ]

@@ -4,7 +4,7 @@ description = "Claude Agent SDK integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "claude-agent-sdk>=0.1.36,<0.1.49",
 ]

@@ -4,7 +4,7 @@ description = "Copilot Studio integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "microsoft-agents-copilotstudio-client>=0.3.1,<0.3.2",
 ]

@@ -213,6 +213,15 @@ from ._workflows._executor import (
    handler,
 )
 from ._workflows._function_executor import FunctionExecutor, executor
+from ._workflows._functional import (
+    FunctionalWorkflow,
+    FunctionalWorkflowAgent,
+    RunContext,
+    StepWrapper,
+    get_run_context,
+    step,
+    workflow,
+)
 from ._workflows._request_info_mixin import response_handler
 from ._workflows._runner import Runner
 from ._workflows._runner_context import (
@@ -332,6 +341,8 @@ __all__ = [
    "FunctionMiddleware",
    "FunctionMiddlewareTypes",
    "FunctionTool",
+    "FunctionalWorkflow",
+    "FunctionalWorkflowAgent",
    "GeneratedEmbeddings",
    "GraphConnectivityError",
    "HistoryProvider",
@@ -354,6 +365,7 @@ __all__ = [
    "ResponseStream",
    "Role",
    "RoleLiteral",
+    "RunContext",
    "Runner",
    "RunnerContext",
    "SecretString",
@@ -366,6 +378,7 @@ __all__ = [
    "SkillScriptRunner",
    "SkillsProvider",
    "SlidingWindowStrategy",
+    "StepWrapper",
    "SubWorkflowRequestMessage",
    "SubWorkflowResponseMessage",
    "SummarizationStrategy",
@@ -424,6 +437,7 @@ __all__ = [
    "evaluator",
    "executor",
    "function_middleware",
+    "get_run_context",
    "handler",
    "included_messages",
    "included_token_count",
@@ -439,6 +453,7 @@ __all__ = [
    "register_state_type",
    "resolve_agent_id",
    "response_handler",
+    "step",
    "tool",
    "tool_call_args_match",
    "tool_called_check",
@@ -447,4 +462,5 @@ __all__ = [
    "validate_tool_mode",
    "validate_tools",
    "validate_workflow_graph",
+    "workflow",
 ]
@@ -48,6 +48,7 @@ class ExperimentalFeature(str, Enum):

    EVALS = "EVALS"
    FILE_HISTORY = "FILE_HISTORY"
+    FUNCTIONAL_WORKFLOWS = "FUNCTIONAL_WORKFLOWS"
    SKILLS = "SKILLS"
    TOOLBOXES = "TOOLBOXES"

@@ -2,6 +2,7 @@

 from __future__ import annotations

+import contextlib
 import logging
 import os
 from typing import Any, Final
@@ -60,13 +61,12 @@ def _detect_hosted_environment() -> None:
    global _hosted_env_detected
    if _hosted_env_detected:
        return
-    _hosted_env_detected = True

-    env_value = os.environ.get(_FOUNDRY_HOSTING_ENV_VAR)
-    if env_value is not None:
+    if (env_value := os.environ.get(_FOUNDRY_HOSTING_ENV_VAR)) is not None:
        # Env var exists — trust its value and skip the fallback.
        if env_value:
            _add_user_agent_prefix(_HOSTED_USER_AGENT_PREFIX)
+            _hosted_env_detected = True
        return

    # Env var not set — fall back to AgentConfig as a second layer of defense.
@@ -78,13 +78,12 @@ def _detect_hosted_environment() -> None:
            return
    except (ModuleNotFoundError, ValueError):
        return
-    try:
+    with contextlib.suppress(ImportError, AttributeError):
        from azure.ai.agentserver.core import AgentConfig  # pyright: ignore[reportMissingImports]

        if AgentConfig.from_env().is_hosted:
            _add_user_agent_prefix(_HOSTED_USER_AGENT_PREFIX)
-    except (ImportError, AttributeError):
-        pass
+            _hosted_env_detected = True


 def get_user_agent() -> str:
@@ -120,6 +120,7 @@ WorkflowEventType = Literal[
    "executor_invoked",  # Executor handler was called (use .executor_id, .data)
    "executor_completed",  # Executor handler completed (use .executor_id, .data)
    "executor_failed",  # Executor handler raised error (use .executor_id, .details)
+    "executor_bypassed",  # Executor skipped via cache hit during replay (use .executor_id, .data)
    # Orchestration event types (use .data for typed payload)
    "group_chat",  # Group chat orchestrator events (use .data as GroupChatRequestSentEvent | GroupChatResponseReceivedEvent) # noqa: E501
    "handoff_sent",  # Handoff routing events (use .data as HandoffSentEvent)
@@ -148,6 +149,7 @@ class WorkflowEvent(Generic[DataT]):
    - `WorkflowEvent.executor_invoked(executor_id)` - executor handler called
    - `WorkflowEvent.executor_completed(executor_id)` - executor handler completed
    - `WorkflowEvent.executor_failed(executor_id, details)` - executor handler failed
+    - `WorkflowEvent.executor_bypassed(executor_id)` - executor skipped via cache hit

    The generic parameter DataT represents the type of the event's data payload:
    - Lifecycle events: `WorkflowEvent[None]` (data is None)
@@ -318,6 +320,11 @@ class WorkflowEvent(Generic[DataT]):
        """Create an 'executor_failed' event when an executor handler raises an error."""
        return WorkflowEvent("executor_failed", executor_id=executor_id, data=details, details=details)

+    @classmethod
+    def executor_bypassed(cls, executor_id: str, data: DataT | None = None) -> WorkflowEvent[DataT]:
+        """Create an 'executor_bypassed' event when a step is skipped via cache hit during replay."""
+        return cls("executor_bypassed", executor_id=executor_id, data=data)
+
    # ==========================================================================
    # Property for type-safe access
    # ==========================================================================
@@ -340,10 +340,10 @@ class Workflow(DictConvertible):
                # Emit explicit start/status events to the stream
                with _framework_event_origin():
                    started = WorkflowEvent.started()
-                yield started
+                yield started  # noqa: RUF070
                with _framework_event_origin():
                    in_progress = WorkflowEvent.status(WorkflowRunState.IN_PROGRESS)
-                yield in_progress
+                yield in_progress  # noqa: RUF070

                # Reset context for a new run if supported
                if reset_context:
@@ -388,7 +388,7 @@ class Workflow(DictConvertible):
                        emitted_in_progress_pending = True
                        with _framework_event_origin():
                            pending_status = WorkflowEvent.status(WorkflowRunState.IN_PROGRESS_PENDING_REQUESTS)
-                        yield pending_status
+                        yield pending_status  # noqa: RUF070
                # Workflow runs until idle - emit final status based on whether requests are pending
                if saw_request:
                    with _framework_event_origin():
@@ -409,10 +409,10 @@ class Workflow(DictConvertible):
                details = WorkflowErrorDetails.from_exception(exc)
                with _framework_event_origin():
                    failed_event = WorkflowEvent.failed(details)
-                yield failed_event
+                yield failed_event  # noqa: RUF070
                with _framework_event_origin():
                    failed_status = WorkflowEvent.status(WorkflowRunState.FAILED)
-                yield failed_status
+                yield failed_status  # noqa: RUF070
                span.add_event(
                    name=OtelAttr.WORKFLOW_ERROR,
                    attributes={
@@ -14,6 +14,7 @@ from typing import Any
 _IMPORTS: dict[str, tuple[str, str]] = {
    "AnthropicFoundryClient": ("agent_framework_anthropic", "agent-framework-anthropic"),
    "FoundryAgent": ("agent_framework_foundry", "agent-framework-foundry"),
+    "FoundryAgentOptions": ("agent_framework_foundry", "agent-framework-foundry"),
    "FoundryChatClient": ("agent_framework_foundry", "agent-framework-foundry"),
    "FoundryChatOptions": ("agent_framework_foundry", "agent-framework-foundry"),
    "FoundryEmbeddingClient": ("agent_framework_foundry", "agent-framework-foundry"),
@@ -4,7 +4,7 @@ description = "Microsoft Agent Framework for building AI Agents with Python. Thi
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.1.1"
+version = "1.2.0"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -529,11 +529,12 @@ class TestFunctionExecutor:
        assert "@handler on instance methods" in str(exc_info.value)

    async def test_async_staticmethod_detection_behavior(self):
-        """Document the behavior of asyncio.iscoroutinefunction with staticmethod descriptors.
+        """Document the behavior of inspect.iscoroutinefunction with staticmethod descriptors.

        This test explains why the unwrapping is necessary when decorators are stacked.
        """
        import asyncio
+        import inspect

        # When @staticmethod is applied, it creates a descriptor
        async def my_async_func():
@@ -544,19 +545,19 @@ class TestFunctionExecutor:
        static_wrapped = staticmethod(my_async_func)

        # Direct check on descriptor object fails (this is the bug)
-        assert not asyncio.iscoroutinefunction(static_wrapped)  # type: ignore[reportDeprecated]
+        assert not inspect.iscoroutinefunction(static_wrapped)
        assert isinstance(static_wrapped, staticmethod)

        # But unwrapping __func__ reveals the async function
        unwrapped = static_wrapped.__func__
-        assert asyncio.iscoroutinefunction(unwrapped)  # type: ignore[reportDeprecated]
+        assert inspect.iscoroutinefunction(unwrapped)

        # When accessed via class attribute, Python's descriptor protocol
        # automatically unwraps it, so it works:
        class C:
            async_static = static_wrapped

-        assert asyncio.iscoroutinefunction(C.async_static)  # type: ignore[reportDeprecated]  # Works via descriptor protocol
+        assert inspect.iscoroutinefunction(C.async_static)  # Works via descriptor protocol


 class TestExecutorExplicitTypes:
@@ -4,7 +4,7 @@ description = "Declarative specification support for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -22,7 +22,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "powerfx>=0.0.32,<0.0.35; python_version < '3.14'",
    "pyyaml>=6.0,<7.0",
 ]
@@ -4,7 +4,7 @@ description = "Debug UI for Microsoft Agent Framework with OpenAI-compatible API
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://github.com/microsoft/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-     "agent-framework-core>=1.1.1,<2",
+     "agent-framework-core>=1.2.0,<2",
     "openai>=1.99.0,<3",
     "opentelemetry-sdk>=1.39.0,<2",
     "fastapi>=0.115.0,<0.133.1",
@@ -655,7 +655,13 @@ async def test_devui_streaming_renderer_memory_is_bounded(
        )

        try:
-            websocket_url = await _get_devtools_websocket_url(debug_port)
+            try:
+                websocket_url = await _get_devtools_websocket_url(debug_port)
+            except RuntimeError as exc:
+                return_code = browser_process.poll()
+                if return_code is not None:
+                    pytest.skip(f"Chromium exited before DevTools became available (code {return_code}).")
+                pytest.skip(str(exc))

            async with websocket_connect(websocket_url, max_size=None) as websocket:
                client = _CDPClient(websocket)
@@ -4,7 +4,7 @@ description = "Durable Task integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -22,7 +22,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "durabletask>=1.3.0,<2",
    "durabletask-azuremanaged>=1.3.0,<2",
    "python-dateutil>=2.8.0,<3",
@@ -2,7 +2,7 @@

 import importlib.metadata

-from ._agent import FoundryAgent, RawFoundryAgent, RawFoundryAgentChatClient
+from ._agent import FoundryAgent, FoundryAgentOptions, RawFoundryAgent, RawFoundryAgentChatClient
 from ._chat_client import FoundryChatClient, FoundryChatOptions, RawFoundryChatClient
 from ._embedding_client import (
    FoundryEmbeddingClient,
@@ -25,6 +25,7 @@ except importlib.metadata.PackageNotFoundError:

 __all__ = [
    "FoundryAgent",
+    "FoundryAgentOptions",
    "FoundryChatClient",
    "FoundryChatOptions",
    "FoundryEmbeddingClient",
@@ -16,8 +16,10 @@ from typing import TYPE_CHECKING, Any, ClassVar, Generic, cast

 from agent_framework import (
    AgentMiddlewareLayer,
+    AgentSession,
    ChatAndFunctionMiddlewareTypes,
    ChatMiddlewareLayer,
+    ChatResponseUpdate,
    ContextProvider,
    FunctionInvocationConfiguration,
    FunctionInvocationLayer,
@@ -34,6 +36,8 @@ from azure.ai.projects.aio import AIProjectClient
 from azure.core.credentials import TokenCredential
 from azure.core.credentials_async import AsyncTokenCredential

+from agent_framework_foundry._oauth_helpers import try_parse_oauth_consent_event
+
 from ._tools import _sanitize_foundry_response_tool  # pyright: ignore[reportPrivateUsage]

 if sys.version_info >= (3, 13):
@@ -52,11 +56,13 @@ else:
 if TYPE_CHECKING:
    from agent_framework import (
        Agent,
+        AgentRunInputs,
        ChatAndFunctionMiddlewareTypes,
        ContextProvider,
        MiddlewareTypes,
        ToolTypes,
    )
+    from agent_framework._agents import _RunContext  # pyright: ignore[reportPrivateUsage]

 logger: logging.Logger = logging.getLogger("agent_framework.foundry")

@@ -81,14 +87,54 @@ class FoundryAgentSettings(TypedDict, total=False):
    agent_version: str | None


+class FoundryAgentOptions(OpenAIChatOptions, total=False):
+    """Microsoft Foundry agent-specific chat options.
+
+    Extends ``OpenAIChatOptions`` with hosted-agent session configuration used by
+    ``FoundryAgent`` / ``RawFoundryAgent``.
+
+    Keyword Args:
+        extra_body: Additional request body values sent to the Responses API.
+        isolation_key: Isolation key used when lazily creating a hosted-agent
+            session through ``project_client.beta.agents.create_session(...)``.
+    """
+
+    extra_body: dict[str, Any]
+    isolation_key: str
+
+
 FoundryAgentOptionsT = TypeVar(
    "FoundryAgentOptionsT",
    bound=TypedDict,  # type: ignore[valid-type]
-    default="OpenAIChatOptions",
+    default="FoundryAgentOptions",
    covariant=True,
 )


+def _merge_extra_body(extra_body: Any | None, *, additions: Mapping[str, Any] | None = None) -> dict[str, Any]:
+    """Normalize and merge provider-specific extra_body values."""
+    if extra_body is None:
+        merged: dict[str, Any] = {}
+    elif isinstance(extra_body, Mapping):
+        merged = dict(cast(Mapping[str, Any], extra_body))
+    else:
+        raise TypeError(f"extra_body must be a mapping when provided, got {type(extra_body).__name__}.")
+
+    if additions:
+        merged.update(additions)
+    return merged
+
+
+def _uses_foundry_agent_session(conversation_id: Any) -> bool:
+    """Return whether a conversation_id should be treated as a Foundry agent session id."""
+    return (
+        isinstance(conversation_id, str)
+        and bool(conversation_id)
+        and not conversation_id.startswith("resp_")
+        and not conversation_id.startswith("conv_")
+    )
+
+
 class RawFoundryAgentChatClient(  # type: ignore[misc]
    RawOpenAIChatClient[FoundryAgentOptionsT],
    Generic[FoundryAgentOptionsT],
@@ -167,13 +213,15 @@ class RawFoundryAgentChatClient(  # type: ignore[misc]
        )

        resolved_endpoint = settings.get("project_endpoint")
-        self.agent_name = settings.get("agent_name")
-        self.agent_version = settings.get("agent_version")
+        agent_name_setting = settings.get("agent_name")
+        self.agent_version: str | None = settings.get("agent_version")
+        self.allow_preview = allow_preview or False

-        if not self.agent_name:
+        if not agent_name_setting:
            raise ValueError(
                "Agent name is required. Set via 'agent_name' parameter or 'FOUNDRY_AGENT_NAME' environment variable."
            )
+        self.agent_name = agent_name_setting

        # Create or use provided project client
        self._should_close_client = False
@@ -197,11 +245,13 @@ class RawFoundryAgentChatClient(  # type: ignore[misc]
            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()
-
+        openai_client_kwargs: dict[str, Any] = {}
+        if default_headers:
+            openai_client_kwargs["default_headers"] = dict(default_headers)
+        if allow_preview:
+            openai_client_kwargs["agent_name"] = self.agent_name
        super().__init__(
-            async_client=async_client,
+            async_client=self.project_client.get_openai_client(**openai_client_kwargs),
            default_headers=default_headers,
            instruction_role=instruction_role,
            compaction_strategy=compaction_strategy,
@@ -209,13 +259,6 @@ class RawFoundryAgentChatClient(  # type: ignore[misc]
            additional_properties=additional_properties,
        )

-    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,
@@ -270,7 +313,7 @@ class RawFoundryAgentChatClient(  # type: ignore[misc]
        options: Mapping[str, Any],
        **kwargs: Any,
    ) -> dict[str, Any]:
-        """Prepare options for the Responses API, injecting agent reference and validating tools."""
+        """Prepare options for the Responses API and validate client-side tools."""
        # Validate tools — only FunctionTool allowed
        tools = options.get("tools", [])
        if tools:
@@ -292,18 +335,61 @@ class RawFoundryAgentChatClient(  # type: ignore[misc]
        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()}
+        # Merge caller-supplied extra_body with any agent-specific request payload.
+        conversation_id = options.get("conversation_id")
+        extra_body = _merge_extra_body(run_options.pop("extra_body", None))
+        if _uses_foundry_agent_session(conversation_id):
+            run_options.pop("previous_response_id", None)
+            run_options.pop("conversation", None)
+            extra_body["agent_session_id"] = conversation_id
+        if extra_body:
+            run_options["extra_body"] = extra_body
+
+        run_options.pop("isolation_key", None)

        # Strip tools from request body - Foundry API rejects requests with both
-        # agent_reference and tools present. FunctionTools are invoked client-side
+        # agent endpoint and tools present. FunctionTools are invoked client-side
        # by the function invocation layer, not sent to the service.
-        run_options.pop("tools", None)
-        run_options.pop("tool_choice", None)
-        run_options.pop("parallel_tool_calls", None)
+        run_options.pop("model", None)
+        if not self.allow_preview:
+            run_options.pop("tools", None)
+            run_options.pop("tool_choice", None)
+            run_options.pop("parallel_tool_calls", None)

        return run_options

+    @override
+    def _parse_response_from_openai(
+        self,
+        response: Any,
+        options: dict[str, Any],
+    ) -> Any:
+        parsed_response = super()._parse_response_from_openai(response, options)
+        if _uses_foundry_agent_session(options.get("conversation_id")):
+            parsed_response.conversation_id = None
+        return parsed_response
+
+    @override
+    def _parse_chunk_from_openai(
+        self,
+        event: Any,
+        options: dict[str, Any],
+        function_call_ids: dict[int, tuple[str, str]],
+        seen_reasoning_delta_item_ids: set[str] | None = None,
+    ) -> ChatResponseUpdate:
+        """Parse streaming events while preserving hosted-agent session state."""
+        update = try_parse_oauth_consent_event(event, self.model)
+        if update is None:
+            update = super()._parse_chunk_from_openai(
+                event,
+                options,
+                function_call_ids,
+                seen_reasoning_delta_item_ids,
+            )
+        if _uses_foundry_agent_session(options.get("conversation_id")):
+            update.conversation_id = None
+        return update
+
    @override
    def _check_model_presence(self, options: dict[str, Any]) -> None:
        """Skip model check — model is configured on the Foundry agent."""
@@ -368,6 +454,26 @@ class RawFoundryAgentChatClient(  # type: ignore[misc]

        return transformed

+    async def get_agent_version(self) -> str | None:
+        """Return the agent version if available, else None."""
+        if self.agent_version is not None:
+            return self.agent_version
+        if not self.allow_preview:
+            return None
+        agent_details = await cast(Any, self.project_client.beta.agents).get(  # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType]
+            agent_name=self.agent_name
+        )
+        versions_object = getattr(agent_details, "versions", None)
+        if not isinstance(versions_object, Mapping):
+            raise TypeError("Foundry agent details did not include a versions mapping.")
+        versions = cast(Mapping[str, Any], versions_object)
+        latest_version = versions.get("latest")
+        agent_version = getattr(cast(Any, latest_version), "version", None)
+        if not isinstance(agent_version, str):
+            raise TypeError("Foundry agent details did not include a latest version string.")
+        self.agent_version = agent_version
+        return agent_version
+
    async def close(self) -> None:
        """Close the project client if we created it."""
        if self._should_close_client:
@@ -395,7 +501,7 @@ class _FoundryAgentChatClient(  # type: ignore[misc]
            client = FoundryAgentClient(
                project_endpoint="https://your-project.services.ai.azure.com",
                agent_name="my-prompt-agent",
-                agent_version="1.0",
+                agent_version="1",
                credential=AzureCliCredential(),
            )

@@ -477,7 +583,7 @@ class RawFoundryAgent(  # type: ignore[misc]
            agent = RawFoundryAgent(
                project_endpoint="https://your-project.services.ai.azure.com",
                agent_name="my-prompt-agent",
-                agent_version="1.0",
+                agent_version="1",
                credential=AzureCliCredential(),
            )
            result = await agent.run("Hello!")
@@ -570,7 +676,7 @@ class RawFoundryAgent(  # type: ignore[misc]
            client=client,  # type: ignore[arg-type]
            instructions=instructions,
            id=id,
-            name=name,
+            name=name or agent_name,
            description=description,
            tools=tools,  # type: ignore[arg-type]
            default_options=cast(FoundryAgentOptionsT | None, default_options),
@@ -582,6 +688,81 @@ class RawFoundryAgent(  # type: ignore[misc]
            additional_properties=dict(additional_properties) if additional_properties is not None else None,
        )

+    def _resolve_service_session_isolation_key(self, isolation_key: str | None = None) -> str:
+        """Resolve the isolation key from an explicit value or default_options."""
+        resolved_isolation_key = (
+            isolation_key if isolation_key is not None else self.default_options.get("isolation_key")
+        )
+        if resolved_isolation_key is None:
+            raise ValueError("isolation_key is required. Pass it explicitly or set default_options['isolation_key'].")
+        return resolved_isolation_key
+
+    async def _create_service_session_id(
+        self,
+        *,
+        isolation_key: str | None = None,
+    ) -> str:
+        """Create a hosted Foundry service session and return the service session ID."""
+        if not isinstance(self.client, RawFoundryAgentChatClient):
+            raise TypeError("_create_service_session_id requires a RawFoundryAgentChatClient-based client.")
+        if not self.client.allow_preview:
+            raise RuntimeError("Hosted Foundry service sessions require allow_preview=True.")
+
+        create_session_kwargs: dict[str, Any] = {
+            "agent_name": self.client.agent_name,
+            "isolation_key": self._resolve_service_session_isolation_key(isolation_key),
+        }
+        if version := await self.client.get_agent_version():
+            from azure.ai.projects.models import VersionRefIndicator
+
+            create_session_kwargs["version_indicator"] = VersionRefIndicator(agent_version=version)  # type: ignore
+
+        service_session = await self.client.project_client.beta.agents.create_session(**create_session_kwargs)
+        agent_session_id = getattr(service_session, "agent_session_id", None)
+        if not isinstance(agent_session_id, str) or not agent_session_id:
+            raise ValueError("Hosted Foundry session creation did not return a non-empty agent_session_id.")
+
+        return agent_session_id
+
+    @override
+    async def _prepare_run_context(
+        self,
+        *,
+        messages: AgentRunInputs | None,
+        session: AgentSession | None,
+        tools: ToolTypes | Callable[..., Any] | Sequence[ToolTypes | Callable[..., Any]] | None,
+        options: Mapping[str, Any] | None,
+        compaction_strategy: CompactionStrategy | None,
+        tokenizer: TokenizerProtocol | None,
+        function_invocation_kwargs: Mapping[str, Any] | None,
+        client_kwargs: Mapping[str, Any] | None,
+    ) -> _RunContext:
+        runtime_options = dict(options) if options else {}
+        effective_options = {
+            **{key: value for key, value in self.default_options.items() if value is not None},
+            **{key: value for key, value in runtime_options.items() if value is not None},
+        }
+
+        if (
+            session is not None
+            and session.service_session_id is None
+            and effective_options.get("isolation_key") is not None
+        ):
+            session.service_session_id = await self._create_service_session_id(
+                isolation_key=cast(str | None, effective_options.get("isolation_key")),
+            )
+
+        return await super()._prepare_run_context(
+            messages=messages,
+            session=session,
+            tools=tools,
+            options=runtime_options,
+            compaction_strategy=compaction_strategy,
+            tokenizer=tokenizer,
+            function_invocation_kwargs=function_invocation_kwargs,
+            client_kwargs=client_kwargs,
+        )
+
    async def configure_azure_monitor(
        self,
        enable_sensitive_data: bool = False,
@@ -708,6 +889,19 @@ class FoundryAgent(  # type: ignore[misc]
    ) -> None:
        """Initialize a Foundry Agent with full middleware and telemetry.

+        ``FoundryAgent`` supports both PromptAgents and HostedAgents. PromptAgents
+        typically provide ``agent_version`` directly. HostedAgents can omit
+        ``agent_version`` and, when they need preview-only session APIs, should
+        opt in with ``allow_preview=True`` when this class creates the underlying
+        ``AIProjectClient``. If you pass ``project_client`` explicitly, it must
+        already be configured for preview APIs before being passed to
+        ``FoundryAgent``.
+
+        To lazily create HostedAgent service sessions inside the agent, pass an
+        ``isolation_key`` through ``default_options`` (or per-run options). The
+        agent stores the resulting HostedAgent session ID in
+        ``AgentSession.service_session_id`` and reuses it on subsequent runs.
+
        Keyword Args:
            project_endpoint: The Foundry project endpoint URL.
            agent_name: The name of the Foundry agent to connect to.
@@ -715,6 +909,9 @@ class FoundryAgent(  # type: ignore[misc]
            credential: Azure credential for authentication.
            project_client: An existing AIProjectClient to use.
            allow_preview: Enables preview opt-in on internally-created AIProjectClient.
+                Set this to ``True`` for HostedAgents that need preview-only
+                session APIs, including lazy service session creation from
+                ``isolation_key``.
            tools: Function tools to provide to the agent. Only ``FunctionTool`` objects are accepted.
            context_providers: Optional context providers.
            middleware: Optional agent-level middleware.
@@ -726,6 +923,8 @@ class FoundryAgent(  # type: ignore[misc]
            description: Optional local description for the local agent wrapper.
            instructions: Optional instructions for the local agent wrapper.
            default_options: Default chat options for the local agent wrapper.
+                ``FoundryAgentOptions`` can include ``isolation_key`` and
+                ``extra_body`` when working with HostedAgents.
            require_per_service_call_history_persistence: Whether to require per-service-call
                chat history persistence when using local history providers.
            function_invocation_configuration: Optional function invocation configuration override.
@@ -9,6 +9,7 @@ from typing import TYPE_CHECKING, Any, ClassVar, Generic, Literal

 from agent_framework import (
    ChatMiddlewareLayer,
+    ChatResponseUpdate,
    Content,
    FunctionInvocationConfiguration,
    FunctionInvocationLayer,
@@ -33,6 +34,8 @@ from azure.ai.projects.models import MCPTool as FoundryMCPTool
 from azure.core.credentials import TokenCredential
 from azure.core.credentials_async import AsyncTokenCredential

+from agent_framework_foundry._oauth_helpers import try_parse_oauth_consent_event
+
 from ._tools import _sanitize_foundry_response_tool, fetch_toolbox  # pyright: ignore[reportPrivateUsage]

 if sys.version_info >= (3, 13):
@@ -204,9 +207,13 @@ class RawFoundryChatClient(  # type: ignore[misc]
                project_client_kwargs["allow_preview"] = allow_preview
            project_client = AIProjectClient(**project_client_kwargs)

+        openai_kwargs: dict[str, Any] = {}
+        if default_headers:
+            openai_kwargs["default_headers"] = default_headers
+
        super().__init__(
            model=resolved_model,
-            async_client=project_client.get_openai_client(),
+            async_client=project_client.get_openai_client(**openai_kwargs),
            default_headers=default_headers,
            instruction_role=instruction_role,
            compaction_strategy=compaction_strategy,
@@ -237,6 +244,20 @@ class RawFoundryChatClient(  # type: ignore[misc]
        response_tools = super()._prepare_tools_for_openai(tools)
        return [_sanitize_foundry_response_tool(tool_item) for tool_item in response_tools]

+    @override
+    def _parse_chunk_from_openai(
+        self,
+        event: Any,
+        options: dict[str, Any],
+        function_call_ids: dict[int, tuple[str, str]],
+        seen_reasoning_delta_item_ids: set[str] | None = None,
+    ) -> ChatResponseUpdate:
+        """Parse streaming event, intercepting oauth_consent_request items."""
+        update = try_parse_oauth_consent_event(event, self.model)
+        if update is not None:
+            return update
+        return super()._parse_chunk_from_openai(event, options, function_call_ids, seen_reasoning_delta_item_ids)
+
    async def configure_azure_monitor(
        self,
        enable_sensitive_data: bool = False,
@@ -0,0 +1,75 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+from __future__ import annotations
+
+import logging
+from typing import Any
+from urllib.parse import urlparse
+
+from agent_framework import ChatResponseUpdate, Content
+
+logger = logging.getLogger(__name__)
+
+
+def _validate_consent_link(consent_link: str, item_id: str) -> str:
+    """Validate a consent link is HTTPS with a valid netloc.
+
+    Returns the link unchanged if valid, or an empty string if not.
+    """
+    parsed = urlparse(consent_link)
+    if parsed.scheme.lower() != "https" or not parsed.netloc:
+        logger.warning(
+            "Skipping oauth_consent_request with non-HTTPS consent_link (item id=%s)",
+            item_id,
+        )
+        return ""
+    return consent_link
+
+
+def try_parse_oauth_consent_event(event: Any, model: str) -> ChatResponseUpdate | None:
+    """Parse an oauth_consent_request from a streaming event, if present.
+
+    Returns a ``ChatResponseUpdate`` when *event* is a
+    ``response.output_item.added`` carrying an ``oauth_consent_request`` item
+    or a top-level ``response.oauth_consent_requested`` event,
+    or ``None`` so the caller can fall through to the base implementation.
+    """
+    consent_link: str = ""
+    raw_item: Any = None
+
+    event_type = getattr(event, "type", None)
+
+    if event_type == "response.output_item.added" and getattr(event.item, "type", None) == "oauth_consent_request":
+        raw_item = event.item
+        consent_link = getattr(raw_item, "consent_link", None) or ""
+    elif event_type == "response.oauth_consent_requested":
+        raw_item = event
+        consent_link = getattr(event, "consent_link", None) or ""
+    else:
+        return None
+
+    item_id = getattr(raw_item, "id", "<unknown>")
+
+    if consent_link:
+        consent_link = _validate_consent_link(consent_link, item_id)
+
+    contents: list[Content] = []
+    if consent_link:
+        contents.append(
+            Content.from_oauth_consent_request(
+                consent_link=consent_link,
+                raw_representation=raw_item,
+            )
+        )
+    else:
+        logger.warning(
+            "Received oauth_consent_request output without valid consent_link (item id=%s)",
+            item_id,
+        )
+
+    return ChatResponseUpdate(
+        contents=contents,
+        role="assistant",
+        model=model,
+        raw_representation=event,
+    )
@@ -4,7 +4,7 @@ description = "Microsoft Foundry integrations for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.1.1"
+version = "1.2.0"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "agent-framework-openai>=1.1.0,<2",
    "azure-ai-inference>=1.0.0b9,<1.0.0b10",
    "azure-ai-projects>=2.1.0,<3.0",
@@ -5,11 +5,22 @@ from __future__ import annotations
 import inspect
 import os
 import sys
+from types import SimpleNamespace
 from typing import Any
 from unittest.mock import AsyncMock, MagicMock, patch

 import pytest
-from agent_framework import AgentResponse, ChatContext, ChatMiddleware, Message, tool
+from agent_framework import (
+    AgentResponse,
+    AgentSession,
+    ChatContext,
+    ChatMiddleware,
+    ChatResponse,
+    ChatResponseUpdate,
+    Message,
+    tool,
+)
+from agent_framework_openai._chat_client import RawOpenAIChatClient
 from azure.core.exceptions import ResourceNotFoundError
 from azure.identity import AzureCliCredential

@@ -54,7 +65,7 @@ def test_raw_foundry_agent_chat_client_init_requires_agent_name() -> None:


 def test_raw_foundry_agent_chat_client_init_with_agent_name() -> None:
-    """Test construction with agent_name and project_client."""
+    """Test construction with agent_name and project_client without preview agent binding."""

    mock_project = MagicMock()
    mock_project.get_openai_client.return_value = MagicMock()
@@ -67,6 +78,27 @@ def test_raw_foundry_agent_chat_client_init_with_agent_name() -> None:

    assert client.agent_name == "test-agent"
    assert client.agent_version == "1.0"
+    mock_project.get_openai_client.assert_called_once_with()
+
+
+def test_raw_foundry_agent_chat_client_init_passes_agent_name_when_preview_enabled() -> None:
+    """Test preview-enabled clients bind the OpenAI client to the agent endpoint."""
+
+    mock_project = MagicMock()
+    mock_project.get_openai_client.return_value = MagicMock()
+
+    client = RawFoundryAgentChatClient(
+        project_client=mock_project,
+        agent_name="hosted-agent",
+        allow_preview=True,
+        default_headers={"x-test": "1"},
+    )
+
+    assert client.agent_name == "hosted-agent"
+    mock_project.get_openai_client.assert_called_once_with(
+        agent_name="hosted-agent",
+        default_headers={"x-test": "1"},
+    )


 def test_raw_foundry_agent_chat_client_init_uses_explicit_parameters() -> None:
@@ -80,38 +112,6 @@ def test_raw_foundry_agent_chat_client_init_uses_explicit_parameters() -> None:
    assert all(parameter.kind != inspect.Parameter.VAR_KEYWORD for parameter in signature.parameters.values())


-def test_raw_foundry_agent_chat_client_get_agent_reference_with_version() -> None:
-    """Test agent reference includes version when provided."""
-
-    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_raw_foundry_agent_chat_client_get_agent_reference_without_version() -> None:
-    """Test agent reference omits version for HostedAgents."""
-
-    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_raw_foundry_agent_chat_client_as_agent_preserves_client_type() -> None:
    """Test that as_agent() wraps the client in FoundryAgent using the same client class."""

@@ -196,12 +196,11 @@ async def test_raw_foundry_agent_chat_client_prepare_options_accepts_function_to
            options={"tools": [my_func]},
        )

-    assert "extra_body" in result
-    assert result["extra_body"]["agent_reference"]["name"] == "test-agent"
+    assert result == {}


-async def test_raw_foundry_agent_chat_client_prepare_options_strips_tools() -> None:
-    """Test that _prepare_options strips tools, tool_choice, and parallel_tool_calls from run_options."""
+async def test_raw_foundry_agent_chat_client_prepare_options_strips_client_side_fields() -> None:
+    """Test that _prepare_options strips model and tool-loop fields from run_options."""

    mock_project = MagicMock()
    mock_openai = MagicMock()
@@ -222,6 +221,7 @@ async def test_raw_foundry_agent_chat_client_prepare_options_strips_tools() -> N
        "agent_framework_openai._chat_client.RawOpenAIChatClient._prepare_options",
        new_callable=AsyncMock,
        return_value={
+            "model": "gpt-4.1",
            "tools": [{"type": "function", "function": {"name": "my_func"}}],
            "tool_choice": "auto",
            "parallel_tool_calls": True,
@@ -232,11 +232,94 @@ async def test_raw_foundry_agent_chat_client_prepare_options_strips_tools() -> N
            options={"tools": [my_func]},
        )

+    assert "model" not in result
    assert "tools" not in result
    assert "tool_choice" not in result
    assert "parallel_tool_calls" not in result
-    assert "extra_body" in result
-    assert result["extra_body"]["agent_reference"]["name"] == "test-agent"
+    assert result == {}
+
+
+async def test_raw_foundry_agent_chat_client_prepare_options_maps_agent_session_id_to_extra_body() -> None:
+    """Test that service_session_id is forwarded as agent_session_id for hosted sessions."""
+
+    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",
+    )
+
+    with patch(
+        "agent_framework_openai._chat_client.RawOpenAIChatClient._prepare_options",
+        new_callable=AsyncMock,
+        return_value={
+            "extra_body": {"custom": "value"},
+            "previous_response_id": "should-be-removed",
+        },
+    ):
+        result = await client._prepare_options(
+            messages=[Message(role="user", contents="hi")],
+            options={"conversation_id": "agent-session-123", "isolation_key": "iso-key"},
+        )
+
+    assert result["extra_body"] == {
+        "custom": "value",
+        "agent_session_id": "agent-session-123",
+    }
+    assert "previous_response_id" not in result
+    assert "conversation" not in result
+    assert "isolation_key" not in result
+
+
+def test_raw_foundry_agent_chat_client_parse_response_suppresses_conversation_id_for_agent_sessions() -> None:
+    """Test that agent-session continuations do not overwrite session.service_session_id."""
+
+    mock_project = MagicMock()
+    mock_project.get_openai_client.return_value = MagicMock()
+
+    client = RawFoundryAgentChatClient(
+        project_client=mock_project,
+        agent_name="test-agent",
+    )
+
+    parsed = ChatResponse(conversation_id="resp_123")
+    with patch(
+        "agent_framework_openai._chat_client.RawOpenAIChatClient._parse_response_from_openai",
+        return_value=parsed,
+    ):
+        result = client._parse_response_from_openai(
+            response=MagicMock(),
+            options={"conversation_id": "agent-session-123"},
+        )
+
+    assert result.conversation_id is None
+
+
+def test_raw_foundry_agent_chat_client_parse_chunk_suppresses_conversation_id_for_agent_sessions() -> None:
+    """Test that agent-session stream updates do not overwrite session.service_session_id."""
+
+    mock_project = MagicMock()
+    mock_project.get_openai_client.return_value = MagicMock()
+
+    client = RawFoundryAgentChatClient(
+        project_client=mock_project,
+        agent_name="test-agent",
+    )
+
+    parsed = ChatResponseUpdate(conversation_id="resp_123")
+    with patch(
+        "agent_framework_openai._chat_client.RawOpenAIChatClient._parse_chunk_from_openai",
+        return_value=parsed,
+    ):
+        result = client._parse_chunk_from_openai(
+            event=MagicMock(type="response.output_text.delta"),
+            options={"conversation_id": "agent-session-123"},
+            function_call_ids={},
+        )
+
+    assert result.conversation_id is None


 def test_raw_foundry_agent_chat_client_check_model_presence_is_noop() -> None:
@@ -366,6 +449,74 @@ def test_raw_foundry_agent_init_with_function_tools() -> None:
    assert agent.default_options.get("tools") is not None


+async def test_raw_foundry_agent_prepare_run_context_creates_service_session_from_isolation_key() -> None:
+    """Test that RawFoundryAgent lazily creates a hosted session and stores it on service_session_id."""
+
+    mock_project = MagicMock()
+    mock_project.get_openai_client.return_value = MagicMock()
+    mock_project.beta = SimpleNamespace(
+        agents=SimpleNamespace(
+            create_session=AsyncMock(return_value=SimpleNamespace(agent_session_id="agent-session-123"))
+        )
+    )
+
+    agent = RawFoundryAgent(
+        project_client=mock_project,
+        agent_name="test-agent",
+        agent_version="1.0",
+        allow_preview=True,
+    )
+    session = AgentSession()
+
+    with patch(
+        "agent_framework._agents.RawAgent._prepare_run_context",
+        new=AsyncMock(return_value={"ok": True}),
+    ) as mock_prepare_run_context:
+        result = await agent._prepare_run_context(
+            messages="hi",
+            session=session,
+            tools=None,
+            options={"isolation_key": "iso-key"},
+            compaction_strategy=None,
+            tokenizer=None,
+            function_invocation_kwargs=None,
+            client_kwargs=None,
+        )
+
+    assert result == {"ok": True}
+    assert session.service_session_id == "agent-session-123"
+    mock_project.beta.agents.create_session.assert_awaited_once()
+    create_session_kwargs = mock_project.beta.agents.create_session.await_args.kwargs
+    assert create_session_kwargs["agent_name"] == "test-agent"
+    assert create_session_kwargs["isolation_key"] == "iso-key"
+    assert "version_indicator" in create_session_kwargs
+    mock_prepare_run_context.assert_awaited_once()
+
+
+async def test_raw_foundry_agent_prepare_run_context_requires_preview_for_hosted_sessions() -> None:
+    """Test that hosted-agent sessions require allow_preview=True."""
+
+    mock_project = MagicMock()
+    mock_project.get_openai_client.return_value = MagicMock()
+
+    agent = RawFoundryAgent(
+        project_client=mock_project,
+        agent_name="test-agent",
+    )
+
+    with pytest.raises(RuntimeError, match="allow_preview=True"):
+        await agent._prepare_run_context(
+            messages="hi",
+            session=AgentSession(),
+            tools=None,
+            options={"isolation_key": "iso-key"},
+            compaction_strategy=None,
+            tokenizer=None,
+            function_invocation_kwargs=None,
+            client_kwargs=None,
+        )
+
+
 def test_foundry_agent_init() -> None:
    """Test construction of the full-middleware agent."""

@@ -483,9 +634,10 @@ async def test_foundry_agent_configure_azure_monitor_import_error() -> None:
@pytest.mark.flaky
@pytest.mark.integration
@skip_if_foundry_agent_integration_tests_disabled
+@pytest.mark.skip(reason="Test agent seems to have disappeared from the test environment; needs investigation.")
 async def test_foundry_agent_basic_run() -> None:
    """Smoke-test FoundryAgent against a real configured agent."""
-    async with FoundryAgent(credential=AzureCliCredential()) as agent:
+    async with FoundryAgent(credential=AzureCliCredential(), allow_preview=True) as agent:
        response = await agent.run("Please respond with exactly: 'This is a response test.'")

    assert isinstance(response, AgentResponse)
@@ -496,6 +648,7 @@ async def test_foundry_agent_basic_run() -> None:
@pytest.mark.flaky
@pytest.mark.integration
@skip_if_foundry_agent_integration_tests_disabled
+@pytest.mark.skip(reason="Test agent seems to have disappeared from the test environment; needs investigation.")
 async def test_foundry_agent_custom_client_run() -> None:
    """Smoke-test FoundryAgent against a real configured agent."""
    async with FoundryAgent(credential=AzureCliCredential(), client_type=RawFoundryAgentChatClient) as agent:
@@ -504,3 +657,158 @@ async def test_foundry_agent_custom_client_run() -> None:
    assert isinstance(response, AgentResponse)
    assert response.text is not None
    assert "response test" in response.text.lower()
+
+
+def test_parse_chunk_surfaces_oauth_consent_request() -> None:
+    """An oauth_consent_request output item surfaces as Content with consent_link."""
+
+    mock_project = MagicMock()
+    mock_project.get_openai_client.return_value = MagicMock()
+
+    client = RawFoundryAgentChatClient(
+        project_client=mock_project,
+        agent_name="test-agent",
+    )
+
+    mock_event = MagicMock()
+    mock_event.type = "response.output_item.added"
+    mock_item = MagicMock()
+    mock_item.type = "oauth_consent_request"
+    mock_item.consent_link = "https://consent-host.example.com/login?data=abc123"
+    mock_item.id = "oauth-item-1"
+    mock_event.item = mock_item
+    mock_event.output_index = 0
+
+    update = client._parse_chunk_from_openai(mock_event, {}, {})
+
+    consent_contents = [c for c in update.contents if c.type == "oauth_consent_request"]
+    assert len(consent_contents) == 1
+    assert consent_contents[0].consent_link == "https://consent-host.example.com/login?data=abc123"
+    assert update.role == "assistant"
+    assert update.raw_representation is mock_event
+
+
+def test_parse_chunk_skips_non_https_oauth_consent() -> None:
+    """An oauth_consent_request with a non-HTTPS link is rejected."""
+
+    mock_project = MagicMock()
+    mock_project.get_openai_client.return_value = MagicMock()
+
+    client = RawFoundryAgentChatClient(
+        project_client=mock_project,
+        agent_name="test-agent",
+    )
+
+    mock_event = MagicMock()
+    mock_event.type = "response.output_item.added"
+    mock_item = MagicMock()
+    mock_item.type = "oauth_consent_request"
+    mock_item.consent_link = "http://insecure.example.com/login"
+    mock_item.id = "oauth-item-2"
+    mock_event.item = mock_item
+    mock_event.output_index = 0
+
+    update = client._parse_chunk_from_openai(mock_event, {}, {})
+
+    consent_contents = [c for c in update.contents if c.type == "oauth_consent_request"]
+    assert len(consent_contents) == 0
+
+
+def test_parse_chunk_handles_missing_consent_link() -> None:
+    """An oauth_consent_request without a consent_link produces no content."""
+
+    mock_project = MagicMock()
+    mock_project.get_openai_client.return_value = MagicMock()
+
+    client = RawFoundryAgentChatClient(
+        project_client=mock_project,
+        agent_name="test-agent",
+    )
+
+    mock_event = MagicMock()
+    mock_event.type = "response.output_item.added"
+    mock_item = MagicMock()
+    mock_item.type = "oauth_consent_request"
+    mock_item.consent_link = None
+    mock_item.id = "oauth-item-3"
+    mock_event.item = mock_item
+    mock_event.output_index = 0
+
+    update = client._parse_chunk_from_openai(mock_event, {}, {})
+
+    consent_contents = [c for c in update.contents if c.type == "oauth_consent_request"]
+    assert len(consent_contents) == 0
+
+
+def test_parse_chunk_handles_empty_string_consent_link() -> None:
+    """An oauth_consent_request with empty-string consent_link produces no content."""
+
+    mock_project = MagicMock()
+    mock_project.get_openai_client.return_value = MagicMock()
+
+    client = RawFoundryAgentChatClient(
+        project_client=mock_project,
+        agent_name="test-agent",
+    )
+
+    mock_event = MagicMock()
+    mock_event.type = "response.output_item.added"
+    mock_item = MagicMock()
+    mock_item.type = "oauth_consent_request"
+    mock_item.consent_link = ""
+    mock_item.id = "oauth-item-4"
+    mock_event.item = mock_item
+    mock_event.output_index = 0
+
+    update = client._parse_chunk_from_openai(mock_event, {}, {})
+
+    consent_contents = [c for c in update.contents if c.type == "oauth_consent_request"]
+    assert len(consent_contents) == 0
+
+
+def test_parse_chunk_delegates_non_oauth_events_to_super() -> None:
+    """Non-oauth events are delegated to super()._parse_chunk_from_openai()."""
+
+    mock_project = MagicMock()
+    mock_project.get_openai_client.return_value = MagicMock()
+
+    client = RawFoundryAgentChatClient(
+        project_client=mock_project,
+        agent_name="test-agent",
+    )
+
+    mock_event = MagicMock()
+    mock_event.type = "response.output_text.delta"
+
+    with patch.object(
+        RawOpenAIChatClient,
+        "_parse_chunk_from_openai",
+        return_value=MagicMock(),
+    ) as mock_super:
+        client._parse_chunk_from_openai(mock_event, {}, {})
+        mock_super.assert_called_once_with(mock_event, {}, {}, None)
+
+
+def test_parse_chunk_surfaces_oauth_consent_requested_event() -> None:
+    """A top-level response.oauth_consent_requested event surfaces as Content."""
+
+    mock_project = MagicMock()
+    mock_project.get_openai_client.return_value = MagicMock()
+
+    client = RawFoundryAgentChatClient(
+        project_client=mock_project,
+        agent_name="test-agent",
+    )
+
+    mock_event = MagicMock()
+    mock_event.type = "response.oauth_consent_requested"
+    mock_event.consent_link = "https://consent-host.example.com/authorize?code=xyz"
+    mock_event.id = "consent-event-1"
+
+    update = client._parse_chunk_from_openai(mock_event, {}, {})
+
+    consent_contents = [c for c in update.contents if c.type == "oauth_consent_request"]
+    assert len(consent_contents) == 1
+    assert consent_contents[0].consent_link == "https://consent-host.example.com/authorize?code=xyz"
+    assert update.role == "assistant"
+    assert update.raw_representation is mock_event
@@ -15,6 +15,7 @@ from agent_framework import ChatResponse, Content, Message, SupportsChatGetRespo
 from agent_framework._telemetry import get_user_agent
 from agent_framework.exceptions import ChatClientException, ChatClientInvalidRequestException
 from agent_framework_openai import OpenAIContentFilterException
+from agent_framework_openai._chat_client import RawOpenAIChatClient
 from azure.ai.projects.models import MCPTool as FoundryMCPTool
 from azure.core.exceptions import ResourceNotFoundError
 from azure.identity import AzureCliCredential
@@ -993,3 +994,165 @@ def test_get_mcp_tool_with_connection_id() -> None:
        description="GitHub MCP via Foundry",
    )
    assert tool_obj is not None
+
+
+def test_parse_chunk_surfaces_oauth_consent_request() -> None:
+    """An oauth_consent_request output item surfaces as Content with consent_link."""
+
+    mock_project = MagicMock()
+    mock_openai = _make_mock_openai_client()
+    mock_project.get_openai_client.return_value = mock_openai
+
+    client = RawFoundryChatClient(
+        project_client=mock_project,
+        model="test-model",
+    )
+
+    mock_event = MagicMock()
+    mock_event.type = "response.output_item.added"
+    mock_item = MagicMock()
+    mock_item.type = "oauth_consent_request"
+    mock_item.consent_link = "https://consent-host.example.com/login?data=abc123"
+    mock_item.id = "oauth-item-1"
+    mock_event.item = mock_item
+    mock_event.output_index = 0
+
+    update = client._parse_chunk_from_openai(mock_event, {}, {})
+
+    consent_contents = [c for c in update.contents if c.type == "oauth_consent_request"]
+    assert len(consent_contents) == 1
+    assert consent_contents[0].consent_link == "https://consent-host.example.com/login?data=abc123"
+    assert update.role == "assistant"
+    assert update.raw_representation is mock_event
+    assert update.model == "test-model"
+
+
+def test_parse_chunk_skips_non_https_oauth_consent() -> None:
+    """An oauth_consent_request with a non-HTTPS link is rejected."""
+
+    mock_project = MagicMock()
+    mock_openai = _make_mock_openai_client()
+    mock_project.get_openai_client.return_value = mock_openai
+
+    client = RawFoundryChatClient(
+        project_client=mock_project,
+        model="test-model",
+    )
+
+    mock_event = MagicMock()
+    mock_event.type = "response.output_item.added"
+    mock_item = MagicMock()
+    mock_item.type = "oauth_consent_request"
+    mock_item.consent_link = "http://insecure.example.com/login"
+    mock_item.id = "oauth-item-2"
+    mock_event.item = mock_item
+    mock_event.output_index = 0
+
+    update = client._parse_chunk_from_openai(mock_event, {}, {})
+
+    consent_contents = [c for c in update.contents if c.type == "oauth_consent_request"]
+    assert len(consent_contents) == 0
+
+
+def test_parse_chunk_handles_missing_consent_link() -> None:
+    """An oauth_consent_request without a consent_link produces no content."""
+
+    mock_project = MagicMock()
+    mock_openai = _make_mock_openai_client()
+    mock_project.get_openai_client.return_value = mock_openai
+
+    client = RawFoundryChatClient(
+        project_client=mock_project,
+        model="test-model",
+    )
+
+    mock_event = MagicMock()
+    mock_event.type = "response.output_item.added"
+    mock_item = MagicMock()
+    mock_item.type = "oauth_consent_request"
+    mock_item.consent_link = None
+    mock_item.id = "oauth-item-3"
+    mock_event.item = mock_item
+    mock_event.output_index = 0
+
+    update = client._parse_chunk_from_openai(mock_event, {}, {})
+
+    consent_contents = [c for c in update.contents if c.type == "oauth_consent_request"]
+    assert len(consent_contents) == 0
+
+
+def test_parse_chunk_handles_empty_string_consent_link() -> None:
+    """An oauth_consent_request with empty-string consent_link produces no content."""
+
+    mock_project = MagicMock()
+    mock_openai = _make_mock_openai_client()
+    mock_project.get_openai_client.return_value = mock_openai
+
+    client = RawFoundryChatClient(
+        project_client=mock_project,
+        model="test-model",
+    )
+
+    mock_event = MagicMock()
+    mock_event.type = "response.output_item.added"
+    mock_item = MagicMock()
+    mock_item.type = "oauth_consent_request"
+    mock_item.consent_link = ""
+    mock_item.id = "oauth-item-4"
+    mock_event.item = mock_item
+    mock_event.output_index = 0
+
+    update = client._parse_chunk_from_openai(mock_event, {}, {})
+
+    consent_contents = [c for c in update.contents if c.type == "oauth_consent_request"]
+    assert len(consent_contents) == 0
+
+
+def test_parse_chunk_delegates_non_oauth_events_to_super() -> None:
+    """Non-oauth events are delegated to super()._parse_chunk_from_openai()."""
+
+    mock_project = MagicMock()
+    mock_openai = _make_mock_openai_client()
+    mock_project.get_openai_client.return_value = mock_openai
+
+    client = RawFoundryChatClient(
+        project_client=mock_project,
+        model="test-model",
+    )
+
+    mock_event = MagicMock()
+    mock_event.type = "response.output_text.delta"
+
+    with patch.object(
+        RawOpenAIChatClient,
+        "_parse_chunk_from_openai",
+        return_value=MagicMock(),
+    ) as mock_super:
+        client._parse_chunk_from_openai(mock_event, {}, {})
+        mock_super.assert_called_once_with(mock_event, {}, {}, None)
+
+
+def test_parse_chunk_surfaces_oauth_consent_requested_event() -> None:
+    """A top-level response.oauth_consent_requested event surfaces as Content."""
+
+    mock_project = MagicMock()
+    mock_openai = _make_mock_openai_client()
+    mock_project.get_openai_client.return_value = mock_openai
+
+    client = RawFoundryChatClient(
+        project_client=mock_project,
+        model="test-model",
+    )
+
+    mock_event = MagicMock()
+    mock_event.type = "response.oauth_consent_requested"
+    mock_event.consent_link = "https://consent-host.example.com/authorize?code=xyz"
+    mock_event.id = "consent-event-1"
+
+    update = client._parse_chunk_from_openai(mock_event, {}, {})
+
+    consent_contents = [c for c in update.contents if c.type == "oauth_consent_request"]
+    assert len(consent_contents) == 1
+    assert consent_contents[0].consent_link == "https://consent-host.example.com/authorize?code=xyz"
+    assert update.role == "assistant"
+    assert update.raw_representation is mock_event
@@ -198,6 +198,7 @@ class TestRawFoundryEmbeddingClient:
                    "FOUNDRY_MODELS_API_KEY": "env-key",
                    "FOUNDRY_EMBEDDING_MODEL": "env-model",
                },
+                clear=True,
            ),
            patch("agent_framework_foundry._embedding_client.EmbeddingsClient"),
            patch("agent_framework_foundry._embedding_client.ImageEmbeddingsClient"),
@@ -0,0 +1,164 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+from __future__ import annotations
+
+import logging
+from typing import Any
+from unittest.mock import MagicMock
+
+import pytest
+
+from agent_framework_foundry._oauth_helpers import _validate_consent_link, try_parse_oauth_consent_event
+
+# region _validate_consent_link tests
+
+
+def test_validate_consent_link_accepts_valid_https() -> None:
+    """A valid HTTPS URL with a netloc passes validation."""
+    link = "https://consent.example.com/auth?code=123"
+    assert _validate_consent_link(link, "item-1") == link
+
+
+def test_validate_consent_link_rejects_http(caplog: pytest.LogCaptureFixture) -> None:
+    """An HTTP link is rejected and a warning is logged."""
+    with caplog.at_level(logging.WARNING):
+        result = _validate_consent_link("http://insecure.example.com/login", "item-2")
+    assert result == ""
+    assert "non-HTTPS" in caplog.text
+    assert "item-2" in caplog.text
+
+
+def test_validate_consent_link_rejects_empty_netloc(caplog: pytest.LogCaptureFixture) -> None:
+    """An HTTPS URL with an empty netloc (e.g. https:///path) is rejected."""
+    with caplog.at_level(logging.WARNING):
+        result = _validate_consent_link("https:///path", "item-3")
+    assert result == ""
+    assert "non-HTTPS" in caplog.text
+    assert "item-3" in caplog.text
+
+
+def test_validate_consent_link_rejects_non_url(caplog: pytest.LogCaptureFixture) -> None:
+    """A non-URL string is rejected."""
+    with caplog.at_level(logging.WARNING):
+        result = _validate_consent_link("not-a-url", "item-4")
+    assert result == ""
+
+
+# endregion
+
+# region try_parse_oauth_consent_event tests
+
+
+def _make_output_item_event(
+    *,
+    item_type: str = "oauth_consent_request",
+    consent_link: Any = "https://consent.example.com/auth",
+    item_id: str = "oauth-item-1",
+) -> MagicMock:
+    """Create a mock ``response.output_item.added`` event."""
+    event = MagicMock()
+    event.type = "response.output_item.added"
+    item = MagicMock()
+    item.type = item_type
+    item.consent_link = consent_link
+    item.id = item_id
+    event.item = item
+    return event
+
+
+def _make_top_level_event(
+    *,
+    consent_link: Any = "https://consent.example.com/authorize",
+    event_id: str = "consent-event-1",
+) -> MagicMock:
+    """Create a mock ``response.oauth_consent_requested`` event."""
+    event = MagicMock()
+    event.type = "response.oauth_consent_requested"
+    event.consent_link = consent_link
+    event.id = event_id
+    return event
+
+
+def test_returns_none_for_unrelated_event() -> None:
+    """An event with a non-oauth type returns None."""
+    event = MagicMock()
+    event.type = "response.output_text.delta"
+    assert try_parse_oauth_consent_event(event, "model-x") is None
+
+
+def test_returns_none_for_event_without_type() -> None:
+    """An event object missing a 'type' attribute returns None."""
+    event = object()  # no type attribute
+    assert try_parse_oauth_consent_event(event, "model-x") is None
+
+
+def test_parses_output_item_added_with_valid_link() -> None:
+    """A response.output_item.added event with a valid HTTPS link produces Content."""
+    event = _make_output_item_event()
+    update = try_parse_oauth_consent_event(event, "test-model")
+
+    assert update is not None
+    assert update.role == "assistant"
+    assert update.model == "test-model"
+    assert update.raw_representation is event
+    consent = [c for c in update.contents if c.type == "oauth_consent_request"]
+    assert len(consent) == 1
+    assert consent[0].consent_link == "https://consent.example.com/auth"
+
+
+def test_parses_top_level_consent_requested_event() -> None:
+    """A response.oauth_consent_requested event produces Content."""
+    event = _make_top_level_event()
+    update = try_parse_oauth_consent_event(event, "test-model")
+
+    assert update is not None
+    consent = [c for c in update.contents if c.type == "oauth_consent_request"]
+    assert len(consent) == 1
+    assert consent[0].consent_link == "https://consent.example.com/authorize"
+
+
+def test_empty_contents_for_non_https_link(caplog: pytest.LogCaptureFixture) -> None:
+    """A non-HTTPS consent_link produces an update with empty contents and logs a warning."""
+    event = _make_output_item_event(consent_link="http://bad.example.com/login", item_id="item-http")
+    with caplog.at_level(logging.WARNING):
+        update = try_parse_oauth_consent_event(event, "test-model")
+
+    assert update is not None
+    assert len(update.contents) == 0
+    assert "non-HTTPS" in caplog.text
+
+
+def test_empty_contents_for_missing_consent_link(caplog: pytest.LogCaptureFixture) -> None:
+    """A None consent_link produces an update with empty contents and logs a warning."""
+    event = _make_output_item_event(consent_link=None, item_id="item-none")
+    with caplog.at_level(logging.WARNING):
+        update = try_parse_oauth_consent_event(event, "test-model")
+
+    assert update is not None
+    assert len(update.contents) == 0
+    assert "without valid consent_link" in caplog.text
+
+
+def test_empty_contents_for_empty_string_consent_link(caplog: pytest.LogCaptureFixture) -> None:
+    """An empty-string consent_link produces an update with empty contents and logs a warning."""
+    event = _make_output_item_event(consent_link="", item_id="item-empty")
+    with caplog.at_level(logging.WARNING):
+        update = try_parse_oauth_consent_event(event, "test-model")
+
+    assert update is not None
+    assert len(update.contents) == 0
+    assert "without valid consent_link" in caplog.text
+
+
+def test_empty_contents_for_https_empty_netloc(caplog: pytest.LogCaptureFixture) -> None:
+    """An HTTPS URL with empty netloc (https:///path) is rejected."""
+    event = _make_output_item_event(consent_link="https:///path", item_id="item-no-netloc")
+    with caplog.at_level(logging.WARNING):
+        update = try_parse_oauth_consent_event(event, "test-model")
+
+    assert update is not None
+    assert len(update.contents) == 0
+    assert "non-HTTPS" in caplog.text
+
+
+# endregion
@@ -172,12 +172,7 @@ class ResponsesHostServer(ResponsesAgentServerHost):
        self._agent = agent
        self.response_handler(self._handle_response)  # pyright: ignore[reportUnknownMemberType]

-    @staticmethod
-    def _is_streaming_request(request: CreateResponse) -> bool:
-        """Check if the request is a streaming request."""
-        return request.stream is not None and request.stream is True
-
-    def _handle_response(
+    async def _handle_response(
        self,
        request: CreateResponse,
        context: ResponseContext,
@@ -186,11 +181,10 @@ class ResponsesHostServer(ResponsesAgentServerHost):
        """Handle the creation of a response."""
        if self._is_workflow_agent:
            # Workflow agents are handled differently because they require checkpoint restoration
-            return self._handle_workflow_agent(request, context)
+            return self._handle_inner_workflow(request, context)
+        return self._handle_inner_agent(request, context)

-        return self._handle_regular_agent(request, context)
-
-    async def _handle_regular_agent(
+    async def _handle_inner_agent(
        self,
        request: CreateResponse,
        context: ResponseContext,
@@ -200,25 +194,24 @@ class ResponsesHostServer(ResponsesAgentServerHost):
        input_messages = _items_to_messages(input_items)

        history = await context.get_history()
-        messages: list[str | Content | Message] = [*_output_items_to_messages(history), *input_messages]
+        run_kwargs: dict[str, Any] = {"messages": [*_output_items_to_messages(history), *input_messages]}
+        is_streaming_request = request.stream is not None and request.stream is True

        chat_options, are_options_set = _to_chat_options(request)

-        is_streaming_request = self._is_streaming_request(request)
        response_event_stream = ResponseEventStream(response_id=context.response_id, model=request.model)

        yield response_event_stream.emit_created()
        yield response_event_stream.emit_in_progress()

+        if are_options_set and not isinstance(self._agent, RawAgent):
+            logger.warning("Agent doesn't support runtime options. They will be ignored.")
+        else:
+            run_kwargs["options"] = chat_options
+
        if not is_streaming_request:
            # Run the agent in non-streaming mode
-            if isinstance(self._agent, RawAgent):
-                raw_agent = cast("RawAgent[Any]", self._agent)  # type: ignore[redundant-cast]  # pyright: ignore[reportUnknownMemberType]
-                response = await raw_agent.run(messages, stream=False, options=chat_options)
-            else:
-                if are_options_set:
-                    logger.warning("Agent doesn't support runtime options. They will be ignored.")
-                response = await self._agent.run(messages, stream=False)
+            response = await self._agent.run(stream=False, **run_kwargs)  # type: ignore[reportUnknownMemberType]

            for message in response.messages:
                for content in message.contents:
@@ -228,20 +221,12 @@ class ResponsesHostServer(ResponsesAgentServerHost):
            yield response_event_stream.emit_completed()
            return

-        # Run the agent in streaming mode
-        if isinstance(self._agent, RawAgent):
-            raw_agent = cast("RawAgent[Any]", self._agent)  # type: ignore[redundant-cast]  # pyright: ignore[reportUnknownMemberType]
-            response_stream = raw_agent.run(messages, stream=True, options=chat_options)
-        else:
-            if are_options_set:
-                logger.warning("Agent doesn't support runtime options. They will be ignored.")
-            response_stream = self._agent.run(messages, stream=True)
-
        # Track the current active output item builder for streaming;
        # lazily created on matching content, closed when a different type arrives.
        tracker = _OutputItemTracker(response_event_stream)

-        async for update in response_stream:
+        # Run the agent in streaming mode
+        async for update in self._agent.run(stream=True, **run_kwargs):  # type: ignore[reportUnknownMemberType]
            for content in update.contents:
                for event in tracker.handle(content):
                    yield event
@@ -256,7 +241,7 @@ class ResponsesHostServer(ResponsesAgentServerHost):

        yield response_event_stream.emit_completed()

-    async def _handle_workflow_agent(
+    async def _handle_inner_workflow(
        self,
        request: CreateResponse,
        context: ResponseContext,
@@ -269,8 +254,7 @@ class ResponsesHostServer(ResponsesAgentServerHost):
        """
        input_items = await context.get_input_items()
        input_messages = _items_to_messages(input_items)
-
-        is_streaming_request = self._is_streaming_request(request)
+        is_streaming_request = request.stream is not None and request.stream is True

        _, are_options_set = _to_chat_options(request)
        if are_options_set:
@@ -311,7 +295,8 @@ class ResponsesHostServer(ResponsesAgentServerHost):
        response_event_stream = ResponseEventStream(response_id=context.response_id, model=request.model)

        # Create a new checkpoint storage for this response based on the following rules:
-        # - If no previous response ID or conversation ID is provided, create a new checkpoint storage for this response
+        # - If no previous response ID or conversation ID is provided,
+        #   create a new checkpoint storage for this response
        # - If a previous response ID is provided, create a new checkpoint storage for this response
        # - If a conversation ID is provided, reuse the existing checkpoint storage for the conversation
        context_id = context.conversation_id or context.response_id
@@ -333,14 +318,12 @@ class ResponsesHostServer(ResponsesAgentServerHost):
            yield response_event_stream.emit_completed()
            return

-        # Run the agent in streaming mode
-        response_stream = self._agent.run(input_messages, stream=True, checkpoint_storage=checkpoint_storage)
-
        # Track the current active output item builder for streaming;
        # lazily created on matching content, closed when a different type arrives.
        tracker = _OutputItemTracker(response_event_stream)

-        async for update in response_stream:
+        # Run the workflow agent in streaming mode
+        async for update in self._agent.run(input_messages, stream=True, checkpoint_storage=checkpoint_storage):
            for content in update.contents:
                for event in tracker.handle(content):
                    yield event
@@ -355,7 +338,6 @@ class ResponsesHostServer(ResponsesAgentServerHost):

        await self._delete_not_latest_checkpoints(checkpoint_storage, self._agent.workflow.name)
        yield response_event_stream.emit_completed()
-        return

    @staticmethod
    async def _delete_not_latest_checkpoints(checkpoint_storage: FileCheckpointStorage, workflow_name: str) -> None:
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "azure-ai-agentserver-core==2.0.0b3",
    "azure-ai-agentserver-responses==1.0.0b5",
    "azure-ai-agentserver-invocations==1.0.0b3",
@@ -41,9 +41,10 @@ def _make_agent(
    *,
    response: AgentResponse | None = None,
    stream_updates: list[AgentResponseUpdate] | None = None,
+    raw_agent: bool = True,
 ) -> MagicMock:
    """Create a mock agent implementing SupportsAgentRun."""
-    agent = MagicMock(spec=RawAgent)
+    agent = MagicMock(spec=RawAgent) if raw_agent else MagicMock()
    agent.id = "test-agent"
    agent.name = "Test Agent"
    agent.description = "A mock agent for testing"
@@ -267,10 +268,18 @@ class TestNonStreaming:

    async def test_chat_options_forwarded(self) -> None:
        agent = _make_agent(
-            response=AgentResponse(messages=[Message(role="assistant", contents=[Content.from_text("ok")])])
+            response=AgentResponse(messages=[Message(role="assistant", contents=[Content.from_text("ok")])]),
+            raw_agent=True,
        )
        server = _make_server(agent)
-        resp = await _post(server, stream=False, temperature=0.5, top_p=0.9, max_output_tokens=1024)
+        resp = await _post(
+            server,
+            stream=False,
+            temperature=0.5,
+            top_p=0.9,
+            max_output_tokens=1024,
+            parallel_tool_calls=True,
+        )

        assert resp.status_code == 200
        agent.run.assert_awaited_once()
@@ -280,6 +289,7 @@ class TestNonStreaming:
        assert options["temperature"] == 0.5
        assert options["top_p"] == 0.9
        assert options["max_tokens"] == 1024
+        assert options["allow_multiple_tool_calls"] is True


 # endregion
@@ -289,6 +299,31 @@ class TestNonStreaming:


 class TestStreaming:
+    async def test_chat_options_forwarded(self) -> None:
+        agent = _make_agent(
+            stream_updates=[AgentResponseUpdate(contents=[Content.from_text("ok")], role="assistant")],
+            raw_agent=True,
+        )
+        server = _make_server(agent)
+        resp = await _post(
+            server,
+            stream=True,
+            temperature=0.5,
+            top_p=0.9,
+            max_output_tokens=1024,
+            parallel_tool_calls=True,
+        )
+
+        assert resp.status_code == 200
+        agent.run.assert_called_once()
+        call_kwargs = agent.run.call_args.kwargs
+        assert call_kwargs["stream"] is True
+        options = call_kwargs["options"]
+        assert options["temperature"] == 0.5
+        assert options["top_p"] == 0.9
+        assert options["max_tokens"] == 1024
+        assert options["allow_multiple_tool_calls"] is True
+
    async def test_basic_text_streaming(self) -> None:
        agent = _make_agent(
            stream_updates=[
@@ -1426,7 +1461,7 @@ class TestMultiTurnMixedContent:
        assert body["status"] == "completed"

        # Verify agent received text + image
-        messages = agent.run.call_args.args[0]
+        messages = agent.run.call_args.kwargs["messages"]
        assert len(messages) == 1
        assert messages[0].role == "user"
        assert len(messages[0].contents) == 2
@@ -1464,7 +1499,7 @@ class TestMultiTurnMixedContent:
        body = resp.json()
        assert body["status"] == "completed"

-        messages = agent.run.call_args.args[0]
+        messages = agent.run.call_args.kwargs["messages"]
        assert len(messages) == 1
        assert len(messages[0].contents) == 2
        assert messages[0].contents[0].type == "text"
@@ -1501,7 +1536,7 @@ class TestMultiTurnMixedContent:
        body = resp.json()
        assert body["status"] == "completed"

-        messages = agent.run.call_args.args[0]
+        messages = agent.run.call_args.kwargs["messages"]
        assert len(messages) == 1
        assert len(messages[0].contents) == 2
        assert messages[0].contents[0].type == "text"
@@ -1542,7 +1577,7 @@ class TestMultiTurnMixedContent:
        body = resp.json()
        assert body["status"] == "completed"

-        messages = agent.run.call_args.args[0]
+        messages = agent.run.call_args.kwargs["messages"]
        assert len(messages) == 3
        assert messages[0].role == "user"
        assert messages[0].contents[0].type == "text"
@@ -1591,7 +1626,7 @@ class TestMultiTurnMixedContent:
        assert body2["status"] == "completed"

        # Verify second call receives history from turn 1 + text+image input
-        second_call_messages = agent.run.call_args_list[1].args[0]
+        second_call_messages = agent.run.call_args_list[1].kwargs["messages"]
        # History: output message from turn 1 ("Send me an image")
        # Input: message with text + image
        assert len(second_call_messages) >= 2
@@ -1652,7 +1687,7 @@ class TestMultiTurnMixedContent:
        assert resp2.json()["status"] == "completed"

        # Verify turn 2 received history including function call/result
-        second_call_messages = agent.run.call_args_list[1].args[0]
+        second_call_messages = agent.run.call_args_list[1].kwargs["messages"]
        roles = [m.role for m in second_call_messages]
        assert "assistant" in roles
        assert "tool" in roles
@@ -1703,7 +1738,7 @@ class TestMultiTurnMixedContent:
        assert resp2.json()["status"] == "completed"

        # Verify history includes the reasoning and text from turn 1
-        second_call_messages = agent.run.call_args_list[1].args[0]
+        second_call_messages = agent.run.call_args_list[1].kwargs["messages"]
        assert len(second_call_messages) >= 2  # history + new input

    async def test_multi_turn_with_mixed_content_and_streaming(self) -> None:
@@ -1795,7 +1830,7 @@ class TestMultiTurnMixedContent:
        body = resp.json()
        assert body["status"] == "completed"

-        messages = agent.run.call_args.args[0]
+        messages = agent.run.call_args.kwargs["messages"]
        assert len(messages) == 2
        assert messages[0].role == "user"
        assert messages[0].contents[0].type == "text"
@@ -1867,7 +1902,7 @@ class TestMultiTurnMixedContent:
        assert resp3.json()["status"] == "completed"

        # Verify turn 3 received full history from turns 1+2 plus new image input
-        third_call_messages = agent.run.call_args_list[2].args[0]
+        third_call_messages = agent.run.call_args_list[2].kwargs["messages"]
        # Should have: history from turn 1 (assistant text) + history from turn 2
        # (function_call, function_call_output, text) + new input (text + image)
        assert len(third_call_messages) >= 5
@@ -1918,7 +1953,7 @@ class TestMultiTurnMixedContent:
        body = resp.json()
        assert body["status"] == "completed"

-        messages = agent.run.call_args.args[0]
+        messages = agent.run.call_args.kwargs["messages"]
        assert len(messages) == 1
        assert len(messages[0].contents) == 2
        assert messages[0].contents[0].type == "text"
@@ -1982,7 +2017,7 @@ class TestMultiTurnMixedContent:
        assert resp2.json()["status"] == "completed"

        # Verify turn 2 received history from turn 1 + new text+file input
-        second_call_messages = agent.run.call_args_list[1].args[0]
+        second_call_messages = agent.run.call_args_list[1].kwargs["messages"]
        assert len(second_call_messages) >= 2

        # History should include the assistant response from turn 1
@@ -2050,7 +2085,7 @@ class TestMultiTurnMixedContent:
        assert resp2.json()["status"] == "completed"

        # Verify turn 2 received history with function call + new text+image
-        second_call_messages = agent.run.call_args_list[1].args[0]
+        second_call_messages = agent.run.call_args_list[1].kwargs["messages"]
        # History should contain function_call and function_result from turn 1
        fc_contents = [
            c for m in second_call_messages if m.role == "assistant" for c in m.contents if c.type == "function_call"
@@ -4,7 +4,7 @@ description = "Foundry Local integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "agent-framework-openai>=1.1.0,<2",
    "foundry-local-sdk>=0.5.1,<0.5.2",
 ]
@@ -4,7 +4,7 @@ description = "Google Gemini integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0a260423"
+version = "1.0.0a260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -24,7 +24,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2.0",
+    "agent-framework-core>=1.2.0,<2.0",
    "google-genai>=1.0.0,<2.0.0",
 ]

@@ -285,8 +285,10 @@ def test_vertex_ai_requires_project_and_location_together(monkeypatch: pytest.Mo
        GeminiChatClient(model="gemini-2.5-flash")


-async def test_missing_model_raises_on_get_response() -> None:
+async def test_missing_model_raises_on_get_response(monkeypatch: pytest.MonkeyPatch) -> None:
    """Raises ValueError at call time when no model is set on the client or in options."""
+    monkeypatch.delenv("GEMINI_MODEL", raising=False)
+    monkeypatch.delenv("GOOGLE_MODEL", raising=False)
    client, mock = _make_gemini_client(model=None)  # type: ignore[arg-type]
    mock.aio.models.generate_content = AsyncMock()

@@ -4,7 +4,7 @@ description = "GitHub Copilot integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "github-copilot-sdk>=0.2.1,<=0.2.1; python_version >= '3.11'",
 ]

@@ -207,9 +207,7 @@ class TestGitHubCopilotAgentInit:

    def test_default_options_returns_independent_copy(self) -> None:
        """Test that mutating the returned dict does not affect internal state."""
-        agent: GitHubCopilotAgent[GitHubCopilotOptions] = GitHubCopilotAgent(
-            default_options={"model": "gpt-5.1-mini"}
-        )
+        agent: GitHubCopilotAgent[GitHubCopilotOptions] = GitHubCopilotAgent(default_options={"model": "gpt-5.1-mini"})
        opts = agent.default_options
        opts["model"] = "mutated"
        assert agent._settings.get("model") == "gpt-5.1-mini"
@@ -4,7 +4,7 @@ description = "Hyperlight CodeAct integrations for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0a260423"
+version = "1.0.0a260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -22,7 +22,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "hyperlight-sandbox>=0.3.0,<0.4",
    "hyperlight-sandbox-backend-wasm>=0.3.0,<0.4 ; ((sys_platform == 'linux' and platform_machine == 'x86_64') or (sys_platform == 'win32' and platform_machine == 'AMD64')) and python_version < '3.14'",
    "hyperlight-sandbox-python-guest>=0.3.0,<0.4",
@@ -4,7 +4,7 @@ description = "Experimental modules for Microsoft Agent Framework"
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -22,7 +22,7 @@ classifiers = [
  "Programming Language :: Python :: 3.14",
 ]
 dependencies = [
-  "agent-framework-core>=1.1.1,<2",
+  "agent-framework-core>=1.2.0,<2",
 ]

 [project.optional-dependencies]
@@ -4,7 +4,7 @@ description = "Mem0 integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "mem0ai>=1.0.0,<2",
 ]

@@ -4,7 +4,7 @@ description = "Ollama integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://learn.microsoft.com/en-us/agent-framework/"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "ollama>=0.5.3,<0.5.4",
 ]

@@ -4,7 +4,7 @@ description = "OpenAI integrations for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.1.1"
+version = "1.2.0"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "openai>=1.99.0,<3",
 ]

@@ -355,6 +355,7 @@ async def test_integration_web_search() -> None:
@pytest.mark.integration
@skip_if_azure_openai_integration_tests_disabled
@_with_azure_openai_debug()
+@pytest.mark.skip(reason="Azure OpenAI with files raises 500 error. Needs investigation.")
 async def test_integration_client_file_search() -> None:
    async with AzureCliCredential() as credential:
        client = OpenAIChatClient(credential=credential)
@@ -380,6 +381,7 @@ async def test_integration_client_file_search() -> None:
@pytest.mark.integration
@skip_if_azure_openai_integration_tests_disabled
@_with_azure_openai_debug()
+@pytest.mark.skip(reason="Azure OpenAI with files raises 500 error. Needs investigation.")
 async def test_integration_client_file_search_streaming() -> None:
    async with AzureCliCredential() as credential:
        client = OpenAIChatClient(credential=credential)
@@ -4,7 +4,7 @@ description = "Orchestration patterns for Microsoft Agent Framework. Includes Se
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
 ]

 [tool.uv]
@@ -4,7 +4,7 @@ description = "Microsoft Purview (Graph dataSecurityAndGovernance) integration f
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://github.com/microsoft/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -24,7 +24,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "azure-core>=1.30.0,<2",
    "httpx>=0.27.0,<0.29",
 ]
@@ -4,7 +4,7 @@ description = "Redis integration for Microsoft Agent Framework."
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core>=1.1.1,<2",
+    "agent-framework-core>=1.2.0,<2",
    "redis>=6.4.0,<7.2.1",
    "redisvl>=0.11.0,<0.16",
    "numpy>=2.2.6,<3"
@@ -4,7 +4,7 @@ description = "Microsoft Agent Framework for building AI Agents with Python. Thi
 authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
 readme = "README.md"
 requires-python = ">=3.10"
-version = "1.1.1"
+version = "1.2.0"
 license-files = ["LICENSE"]
 urls.homepage = "https://aka.ms/agent-framework"
 urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -23,7 +23,7 @@ classifiers = [
  "Typing :: Typed",
 ]
 dependencies = [
-    "agent-framework-core[all]==1.1.1",
+    "agent-framework-core[all]==1.2.0",
 ]

 [dependency-groups]
@@ -0,0 +1,49 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""
+Functional Workflow with Agents — Call agents inside @workflow
+
+This sample shows how to call agents inside a functional workflow.
+Agent calls are just regular async function calls — no special wrappers needed.
+"""
+
+import asyncio
+
+from agent_framework import Agent, workflow
+from agent_framework.foundry import FoundryChatClient
+from azure.identity import AzureCliCredential
+
+# <create_agents>
+client = FoundryChatClient(credential=AzureCliCredential())
+
+writer = Agent(
+    name="WriterAgent",
+    instructions="Write a short poem (4 lines max) about the given topic.",
+    client=client,
+)
+
+reviewer = Agent(
+    name="ReviewerAgent",
+    instructions="Review the given poem in one sentence. Is it good?",
+    client=client,
+)
+# </create_agents>
+
+
+# <create_workflow>
+@workflow
+async def poem_workflow(topic: str) -> str:
+    """Write a poem, then review it."""
+    poem = (await writer.run(f"Write a poem about: {topic}")).text
+    review = (await reviewer.run(f"Review this poem: {poem}")).text
+    return f"Poem:\n{poem}\n\nReview: {review}"
+# </create_workflow>
+
+
+async def main() -> None:
+    result = await poem_workflow.run("a cat learning to code")
+    print(result.get_outputs()[0])
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,57 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""
+Functional Workflow Basics — Orchestrate async functions with @workflow
+
+The functional API lets you write workflows as plain Python async functions.
+No graph concepts, no edges, no executor classes — just call functions
+and use native control flow (if/else, loops, asyncio.gather).
+
+This sample builds a minimal pipeline with two steps:
+1. Convert text to uppercase
+2. Reverse the text
+
+No external services are required.
+"""
+
+import asyncio
+
+from agent_framework import workflow
+
+
+# Plain async functions — no decorators needed
+async def to_upper_case(text: str) -> str:
+    """Convert input to uppercase."""
+    return text.upper()
+
+
+async def reverse_text(text: str) -> str:
+    """Reverse the string."""
+    return text[::-1]
+
+
+# <create_workflow>
+@workflow
+async def text_workflow(text: str) -> str:
+    """Uppercase the text, then reverse it."""
+    upper = await to_upper_case(text)
+    return await reverse_text(upper)
+# </create_workflow>
+
+
+async def main() -> None:
+    # <run_workflow>
+    result = await text_workflow.run("hello world")
+    print(f"Output: {result.get_outputs()}")
+    print(f"Final state: {result.get_final_state()}")
+    # </run_workflow>
+
+    """
+    Expected output:
+      Output: ['DLROW OLLEH']
+      Final state: WorkflowRunState.IDLE
+    """
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -12,9 +12,12 @@ from agent_framework import (
 from typing_extensions import Never

 """
-First Workflow — Chain executors with edges
+First Graph Workflow — Chain executors with edges

-This sample builds a minimal workflow with two steps:
+The graph API gives you full control over execution topology: edges,
+fan-out/fan-in, switch/case, and superstep-based checkpointing.
+
+This sample builds a minimal graph workflow with two steps:
 1. Convert text to uppercase (class-based executor)
 2. Reverse the text (function-based executor)

@@ -24,8 +24,10 @@ export FOUNDRY_MODEL="gpt-4o"   # optional, defaults to gpt-4o
 | 2 | [02_add_tools.py](02_add_tools.py) | Define a function tool with `@tool` and attach it to an agent. |
 | 3 | [03_multi_turn.py](03_multi_turn.py) | Keep conversation history across turns with `AgentSession`. |
 | 4 | [04_memory.py](04_memory.py) | Add dynamic context with a custom `ContextProvider`. |
-| 5 | [05_first_workflow.py](05_first_workflow.py) | Chain executors into a workflow with edges. |
-| 6 | [06_host_your_agent.py](06_host_your_agent.py) | Host a single agent with Azure Functions. |
+| 5 | [05_functional_workflow_with_agents.py](05_functional_workflow_with_agents.py) | Call agents inside a functional workflow. |
+| 6 | [06_functional_workflow_basics.py](06_functional_workflow_basics.py) | Write a workflow as a plain async function. |
+| 7 | [07_first_graph_workflow.py](07_first_graph_workflow.py) | Chain executors into a graph workflow with edges. |
+| 8 | [08_host_your_agent.py](08_host_your_agent.py) | Host a single agent with Azure Functions. |

 Run any sample with:

@@ -75,11 +75,7 @@ def get_client(client_name: ClientName) -> SupportsChatGetResponse[Any]:
    if client_name == "azure_openai_chat_completion":
        return OpenAIChatCompletionClient(credential=AzureCliCredential())
    if client_name == "foundry_chat":
-        return FoundryChatClient(
-            project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
-            model=os.environ["FOUNDRY_MODEL"],
-            credential=AzureCliCredential(),
-        )
+        return FoundryChatClient(credential=AzureCliCredential())

    raise ValueError(f"Unsupported client name: {client_name}")

@@ -93,21 +89,6 @@ async def main(client_name: ClientName = "openai_chat") -> None:
    print(f"Client: {client_name}")
    print(f"User: {message.text}")

-    if isinstance(client, FoundryChatClient):
-        async with client:
-            if stream:
-                response_stream = client.get_response([message], stream=True, options={"tools": get_weather})
-                print("Assistant: ", end="")
-                async for chunk in response_stream:
-                    if chunk.text:
-                        print(chunk.text, end="")
-                print("")
-            else:
-                print(
-                    f"Assistant: {await client.get_response([message], stream=False, options={'tools': get_weather})}"
-                )
-        return
-
    if stream:
        response_stream = client.get_response([message], stream=True, options={"tools": get_weather})
        print("Assistant: ", end="")
@@ -30,6 +30,20 @@ Once comfortable with these, explore the rest of the samples below.

 ## Samples Overview (by directory)

+### functional
+
+Write workflows as plain Python async functions — no graph concepts, no executor classes, no edges. Use native control flow (`if`/`else`, loops, `asyncio.gather`) for branching and parallelism.
+
+| Sample | File | Concepts |
+|---|---|---|
+| Basic Pipeline | [functional/basic_pipeline.py](./functional/basic_pipeline.py) | Sequential steps as plain async functions |
+| Basic Streaming Pipeline | [functional/basic_streaming_pipeline.py](./functional/basic_streaming_pipeline.py) | Stream workflow events in real time with `run(stream=True)` |
+| Parallel Pipeline | [functional/parallel_pipeline.py](./functional/parallel_pipeline.py) | Fan-out/fan-in with `asyncio.gather` |
+| Steps and Checkpointing | [functional/steps_and_checkpointing.py](./functional/steps_and_checkpointing.py) | `@step` decorator for per-step checkpointing and observability |
+| Human-in-the-Loop Review | [functional/hitl_review.py](./functional/hitl_review.py) | HITL with `ctx.request_info()` and replay |
+| Agent Integration | [functional/agent_integration.py](./functional/agent_integration.py) | Calling agents inside workflow steps |
+| Naive Group Chat | [functional/naive_group_chat.py](./functional/naive_group_chat.py) | Simple round-robin group chat as a plain loop |
+
 ### agents

 | Sample                                 | File                                                                                                           | Concepts                                                                                             |
@@ -0,0 +1,107 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Calling agents inside functional workflows.
+
+Agent calls work inside @workflow as plain function calls — no decorator needed.
+Just call the agent and use the result.
+
+If you want per-step caching (so agent calls don't re-execute on HITL resume
+or crash recovery), add @step. Since each agent call hits an LLM API (time +
+money), @step is often worth it. But it's always opt-in.
+
+This sample shows both approaches side-by-side so you can see the difference.
+"""
+
+import asyncio
+
+from agent_framework import Agent, step, workflow
+from agent_framework.foundry import FoundryChatClient
+from azure.identity import AzureCliCredential
+
+# ---------------------------------------------------------------------------
+# Create agents
+# ---------------------------------------------------------------------------
+
+client = FoundryChatClient(credential=AzureCliCredential())
+
+classifier_agent = Agent(
+    name="ClassifierAgent",
+    instructions=(
+        "Classify documents into one category: Technical, Legal, Marketing, or Scientific. "
+        "Reply with only the category name."
+    ),
+    client=client,
+)
+
+writer_agent = Agent(
+    name="WriterAgent",
+    instructions="Summarize the given content in one sentence.",
+    client=client,
+)
+
+reviewer_agent = Agent(
+    name="ReviewerAgent",
+    instructions="Review the given summary in one sentence. Is it accurate and complete?",
+    client=client,
+)
+
+# ---------------------------------------------------------------------------
+# Simplest approach: call agents directly inside the workflow.
+# No @step, no wrappers — just plain function calls.
+# ---------------------------------------------------------------------------
+
+
+@workflow
+async def simple_pipeline(document: str) -> str:
+    """Process a document — agents called inline, no @step."""
+    classification = (await classifier_agent.run(f"Classify this document: {document}")).text
+    summary = (await writer_agent.run(f"Summarize: {document}")).text
+    review = (await reviewer_agent.run(f"Review this summary: {summary}")).text
+
+    return f"Classification: {classification}\nSummary: {summary}\nReview: {review}"
+
+
+# ---------------------------------------------------------------------------
+# With @step: agent results are cached. On HITL resume or checkpoint
+# recovery, completed steps return their saved result instead of calling
+# the LLM again. Worth it for expensive operations.
+# ---------------------------------------------------------------------------
+
+
+@step
+async def classify_document(doc: str) -> str:
+    return (await classifier_agent.run(f"Classify this document: {doc}")).text
+
+
+@step
+async def generate_summary(doc: str) -> str:
+    return (await writer_agent.run(f"Summarize: {doc}")).text
+
+
+@step
+async def review_summary(summary: str) -> str:
+    return (await reviewer_agent.run(f"Review this summary: {summary}")).text
+
+
+@workflow
+async def cached_pipeline(document: str) -> str:
+    """Same pipeline, but @step caches each agent call."""
+    classification = await classify_document(document)
+    summary = await generate_summary(document)
+    review = await review_summary(summary)
+
+    return f"Classification: {classification}\nSummary: {summary}\nReview: {review}"
+
+
+async def main():
+    # Simple version — agents called inline
+    result = await simple_pipeline.run("This is a technical document about machine learning...")
+    print(result.get_outputs()[0])
+
+    # Cached version — same result, but steps won't re-execute on resume
+    result = await cached_pipeline.run("This is a technical document about machine learning...")
+    print(f"\nCached: {result.get_outputs()[0]}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,58 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Basic sequential pipeline using the functional workflow API.
+
+The simplest possible workflow: plain async functions orchestrated by @workflow.
+No @step decorator needed — just write Python.
+"""
+
+import asyncio
+
+from agent_framework import workflow
+
+
+# These are plain async functions — no decorators needed.
+# They run normally inside the workflow, just like any other Python function.
+async def fetch_data(url: str) -> dict[str, str | int]:
+    """Simulate fetching data from a URL."""
+    return {"url": url, "content": f"Data from {url}", "status": 200}
+
+
+async def transform_data(data: dict[str, str | int]) -> str:
+    """Transform raw data into a summary string."""
+    return f"[{data['status']}] {data['content']}"
+
+
+# @workflow turns this async function into a FunctionalWorkflow object.
+# Without it, this is just a normal async function. With it, you get:
+#   - .run() that returns a WorkflowRunResult with events and outputs
+#   - .run(stream=True) for streaming events in real time
+#   - .as_agent() to use this workflow anywhere an agent is expected
+#
+# The function's first parameter receives the input from .run("...").
+# Add a `ctx: RunContext` parameter only if you need HITL, state, or custom events.
+@workflow
+async def data_pipeline(url: str) -> str:
+    """A simple sequential data pipeline."""
+    raw = await fetch_data(url)
+    summary = await transform_data(raw)
+
+    # This is just a function — plain Python works between calls.
+    # No need to wrap every operation in a separate async function.
+    is_valid = len(summary) > 0 and "[200]" in summary
+    tag = "VALID" if is_valid else "INVALID"
+
+    # Returning a value automatically emits it as an output.
+    # Callers retrieve it via result.get_outputs().
+    return f"[{tag}] {summary}"
+
+
+async def main():
+    # .run() is provided by @workflow — a plain async function wouldn't have it
+    result = await data_pipeline.run("https://example.com/api/data")
+    print("Output:", result.get_outputs()[0])
+    print("State:", result.get_final_state())
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,63 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Basic streaming pipeline using the functional workflow API.
+
+Stream workflow events in real time with run(stream=True).
+"""
+
+import asyncio
+
+from agent_framework import workflow
+
+
+# Plain async functions — no decorators needed for simple helpers.
+async def fetch_data(url: str) -> dict[str, str | int]:
+    """Simulate fetching data from a URL."""
+    return {"url": url, "content": f"Data from {url}", "status": 200}
+
+
+async def transform_data(data: dict[str, str | int]) -> str:
+    """Transform raw data into a summary string."""
+    return f"[{data['status']}] {data['content']}"
+
+
+async def validate_result(summary: str) -> bool:
+    """Validate the transformed result."""
+    return len(summary) > 0 and "[200]" in summary
+
+
+# @workflow enables .run(stream=True), which returns a ResponseStream
+# you can iterate over with `async for`. Without @workflow, you'd just
+# have a normal async function with no streaming capability.
+@workflow
+async def data_pipeline(url: str) -> str:
+    """A simple sequential data pipeline."""
+    raw = await fetch_data(url)
+    summary = await transform_data(raw)
+    is_valid = await validate_result(summary)
+
+    return f"{summary} (valid={is_valid})"
+
+
+async def main():
+    # run(stream=True) returns a ResponseStream that yields events as they
+    # are produced. The raw stream includes lifecycle events (started, status)
+    # alongside application events — filter by event.type to find what you need.
+    stream = data_pipeline.run("https://example.com/api/data", stream=True)
+    async for event in stream:
+        if event.type == "output":
+            print(f"Output: {event.data}")
+
+    # After iteration, get_final_response() returns the WorkflowRunResult
+    result = await stream.get_final_response()
+    print(f"Final state: {result.get_final_state()}")
+
+    """
+    Expected output:
+      Output: [200] Data from https://example.com/api/data (valid=True)
+      Final state: WorkflowRunState.IDLE
+    """
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,84 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Human-in-the-loop review pipeline using functional workflows.
+
+Demonstrates ctx.request_info() for pausing the workflow to wait for
+external input and resuming with run(responses={...}).
+
+HITL works with or without @step. The difference is what happens on resume:
+- Without @step: every function re-executes from the top (fine for cheap calls).
+- With @step: completed functions return their saved result instantly.
+
+This sample uses @step on write_draft() because it simulates an expensive
+operation that shouldn't re-run just because the workflow was paused.
+"""
+
+import asyncio
+
+from agent_framework import RunContext, WorkflowRunState, step, workflow
+
+
+# @step saves the result. When the workflow resumes after the HITL pause,
+# this returns its saved result instead of running the expensive operation again.
+#
+# In a real workflow you might call an agent here instead:
+#   @step
+#   async def write_draft(topic: str) -> str:
+#       return (await writer_agent.run(f"Write a draft about: {topic}")).text
+@step
+async def write_draft(topic: str) -> str:
+    """Simulate writing a draft — expensive, shouldn't re-run on resume."""
+    print(f"  write_draft executing for '{topic}'")
+    return f"Draft document about '{topic}': Lorem ipsum dolor sit amet..."
+
+
+@step
+async def revise_draft(draft: str, feedback: str) -> str:
+    """Revise the draft based on feedback."""
+    return f"Revised: {draft[:50]}... [Applied feedback: {feedback}]"
+
+
+@workflow
+async def review_pipeline(topic: str, ctx: RunContext) -> str:
+    """Write a draft, get human review, then revise."""
+    draft = await write_draft(topic)
+
+    # ctx.request_info() suspends the workflow here. The caller gets back
+    # a WorkflowRunResult with state IDLE_WITH_PENDING_REQUESTS and can
+    # inspect the pending request via result.get_request_info_events().
+    feedback = await ctx.request_info(
+        {"draft": draft, "instructions": "Please review this draft"},
+        response_type=str,
+        request_id="review_request",
+    )
+
+    # This only executes after the caller resumes with run(responses={...}).
+    # write_draft above returns its saved result (thanks to @step),
+    # request_info returns the provided response, and we continue here.
+    return await revise_draft(draft, feedback)
+
+
+async def main():
+    # Phase 1: Run until the workflow pauses for human input
+    print("=== Phase 1: Initial run ===")
+    result1 = await review_pipeline.run("AI Safety")
+
+    # If request_info() was reached, the state is IDLE_WITH_PENDING_REQUESTS.
+    # If the workflow completed without hitting request_info(), it would be IDLE.
+    print(f"State: {(final_state := result1.get_final_state())}")
+    assert final_state == WorkflowRunState.IDLE_WITH_PENDING_REQUESTS
+
+    requests = result1.get_request_info_events()
+    print(f"Pending request: {requests[0].request_id}")
+
+    # Phase 2: Resume with the human's response
+    print("\n=== Phase 2: Resume with feedback ===")
+    print("(write_draft should NOT execute again — saved by @step)")
+    result2 = await review_pipeline.run(responses={"review_request": "Add more details about alignment research"})
+
+    print(f"State: {result2.get_final_state()}")
+    print(f"Output: {result2.get_outputs()[0]}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,82 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Naive group chat using the functional workflow API.
+
+A simple round-robin group chat where agents take turns responding.
+Because it's just a function, you control the loop, the turn order,
+and the termination condition with plain Python — no framework abstractions.
+
+Compare this with the graph-based GroupChat orchestration to see how the
+functional API lets you start simple and add complexity only when needed.
+"""
+
+import asyncio
+
+from agent_framework import Agent, Message, workflow
+from agent_framework.foundry import FoundryChatClient
+from azure.identity import AzureCliCredential
+
+# ---------------------------------------------------------------------------
+# Create agents
+# ---------------------------------------------------------------------------
+
+client = FoundryChatClient(credential=AzureCliCredential())
+
+expert = Agent(
+    name="PythonExpert",
+    instructions=(
+        "You are a Python expert in a group discussion. "
+        "Answer questions about Python and refine your answer based on feedback. "
+        "Keep responses concise (2-3 sentences)."
+    ),
+    client=client,
+)
+
+critic = Agent(
+    name="Critic",
+    instructions=(
+        "You are a constructive critic in a group discussion. "
+        "Point out edge cases, gotchas, or missing nuances in the previous answer. "
+        "If the answer is solid, say so briefly."
+    ),
+    client=client,
+)
+
+summarizer = Agent(
+    name="Summarizer",
+    instructions=(
+        "You are a summarizer in a group discussion. "
+        "After the discussion, provide a final concise summary that incorporates "
+        "the expert's answer and the critic's feedback. Keep it to 2-3 sentences."
+    ),
+    client=client,
+)
+
+# ---------------------------------------------------------------------------
+# A naive group chat is just a loop — no special framework needed
+# ---------------------------------------------------------------------------
+
+
+@workflow
+async def group_chat(question: str) -> str:
+    """Round-robin group chat: expert answers, critic reviews, summarizer wraps up."""
+    participants = [expert, critic, summarizer]
+    # Passing list[Message] keeps roles/authorship intact between turns,
+    # instead of stringifying everything into a single prompt.
+    conversation: list[Message] = [Message("user", [question])]
+
+    # Simple round-robin: each agent sees the full conversation so far
+    for agent in participants:
+        response = await agent.run(conversation)
+        conversation.extend(response.messages)
+
+    return "\n\n".join(f"{m.author_name or m.role}: {m.text}" for m in conversation)
+
+
+async def main():
+    result = await group_chat.run("What's the difference between a list and a tuple in Python?")
+    print(result.get_outputs()[0])
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,66 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Parallel pipeline using asyncio.gather with functional workflows.
+
+Fan-out/fan-in uses native Python concurrency via asyncio.gather.
+No @step needed — still just plain async functions.
+"""
+
+import asyncio
+
+from agent_framework import workflow
+
+
+# Plain async functions — asyncio.gather handles the concurrency,
+# no framework primitives needed for parallelism.
+async def research_web(topic: str) -> str:
+    """Simulate web research."""
+    await asyncio.sleep(0.05)
+    return f"Web results for '{topic}': 10 articles found"
+
+
+async def research_papers(topic: str) -> str:
+    """Simulate academic paper search."""
+    await asyncio.sleep(0.05)
+    return f"Papers on '{topic}': 3 relevant papers"
+
+
+async def research_news(topic: str) -> str:
+    """Simulate news search."""
+    await asyncio.sleep(0.05)
+    return f"News about '{topic}': 5 recent articles"
+
+
+async def synthesize(sources: list[str]) -> str:
+    """Combine research results into a summary."""
+    return "Research Summary:\n" + "\n".join(f"  - {s}" for s in sources)
+
+
+# @workflow wraps the orchestration logic so you get .run(), streaming,
+# and events. The functions it calls are plain Python — no decorators
+# needed just because they're inside a workflow.
+@workflow
+async def research_pipeline(topic: str) -> str:
+    """Fan-out to three research tasks, then synthesize results."""
+    # asyncio.gather runs all three concurrently — this is standard Python,
+    # not a framework concept. Use it the same way you would anywhere else.
+    #
+    # Tip: if any of these were wrapped with @step (e.g. an expensive agent call),
+    # the pattern is identical — @step composes with asyncio.gather, so each
+    # branch is independently cached on HITL resume or checkpoint restore.
+    web, papers, news = await asyncio.gather(
+        research_web(topic),
+        research_papers(topic),
+        research_news(topic),
+    )
+
+    return await synthesize([web, papers, news])
+
+
+async def main():
+    result = await research_pipeline.run("AI agents")
+    print(result.get_outputs()[0])
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,97 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Introducing @step: per-step checkpointing and observability.
+
+The previous samples used plain functions — and that works. Workflows support
+HITL (ctx.request_info) and checkpointing regardless of whether you use @step.
+
+The difference: without @step, a resumed workflow re-executes every function
+call from the top. That's fine for cheap functions. But for expensive operations
+(API calls, agent runs, etc.) you don't want to pay that cost again.
+
+@step saves each function's result so it skips re-execution on resume:
+- On HITL resume, completed steps return their saved result instantly.
+- On crash recovery from a checkpoint, earlier step results are restored.
+- Each step emits executor_invoked/executor_completed events for observability.
+
+@step is opt-in. Plain functions still work alongside @step in the same workflow.
+"""
+
+import asyncio
+
+from agent_framework import InMemoryCheckpointStorage, step, workflow
+
+# Track call counts to show which functions actually execute on resume
+fetch_calls = 0
+transform_calls = 0
+
+
+# @step saves this function's result. On resume, it returns the saved
+# result instead of re-executing — useful because this is expensive.
+@step
+async def fetch_data(url: str) -> dict[str, str | int]:
+    """Expensive operation — @step prevents re-execution on resume."""
+    global fetch_calls
+    fetch_calls += 1
+    print(f"  fetch_data called (call #{fetch_calls})")
+    return {"url": url, "content": f"Data from {url}", "status": 200}
+
+
+@step
+async def transform_data(data: dict[str, str | int]) -> str:
+    """Another expensive operation — @step saves the result."""
+    global transform_calls
+    transform_calls += 1
+    print(f"  transform_data called (call #{transform_calls})")
+    return f"[{data['status']}] {data['content']}"
+
+
+# No @step — this is cheap, so it just re-runs on resume. That's fine.
+async def validate_result(summary: str) -> bool:
+    """Cheap validation — no @step needed."""
+    return len(summary) > 0 and "[200]" in summary
+
+
+storage = InMemoryCheckpointStorage()
+
+
+# checkpoint_storage tells @workflow where to persist step results.
+# Each @step saves a checkpoint after it completes.
+@workflow(checkpoint_storage=storage)
+async def data_pipeline(url: str) -> str:
+    """Mix of @step functions and plain functions."""
+    raw = await fetch_data(url)
+    summary = await transform_data(raw)
+    is_valid = await validate_result(summary)
+
+    return f"{summary} (valid={is_valid})"
+
+
+async def main():
+    # --- Run 1: Everything executes normally ---
+    print("=== Run 1: Fresh execution ===")
+    result = await data_pipeline.run("https://example.com/api/data")
+    print(f"Output: {result.get_outputs()[0]}")
+    print(f"fetch_calls={fetch_calls}, transform_calls={transform_calls}")
+
+    # @step functions emit executor events; plain functions don't.
+    print("\nEvents:")
+    for event in result:
+        if event.type in ("executor_invoked", "executor_completed"):
+            print(f"  {event.type}: {event.executor_id}")
+
+    # --- Run 2: Restore from checkpoint ---
+    # The workflow re-executes, but @step functions return saved results.
+    # Only validate_result() (no @step) actually runs again.
+    print("\n=== Run 2: Restored from checkpoint ===")
+    latest = await storage.get_latest(workflow_name="data_pipeline")
+    assert latest is not None
+
+    result2 = await data_pipeline.run(checkpoint_id=latest.checkpoint_id)
+    print(f"Output: {result2.get_outputs()[0]}")
+    print(f"fetch_calls={fetch_calls}, transform_calls={transform_calls}")
+    print("(call counts unchanged — @step results were restored from checkpoint)")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -8,4 +8,4 @@ This folder contains a list of samples that show how to host agents using the `r
 | [02_local_tools](./02_local_tools) | An example of hosting an agent with the `responses` API and local tools including a function tool and a local shell tool. |
 | [03_remote_mcp](./03_remote_mcp) | An example of hosting an agent with the `responses` API and remote MCPs, including a GitHub MCP server and a Foundry Toolbox. |
 | [04_workflows](./04_workflows) | An example of hosting a workflow with the `responses` API. |
-| [using_deployed_agent.py](./using_deployed_agent.py) | An example of how to use the deployed agent in Agent Framework. |
+| [using_deployed_agent.py](./using_deployed_agent.py) | Connect to the deployed basic Foundry agent with `FoundryAgent`, `allow_preview=True`, and version `v2`. |
@@ -1,50 +1,146 @@
 # Copyright (c) Microsoft. All rights reserved.

+from __future__ import annotations
+
 import asyncio
+import os
+from collections.abc import Mapping
+from typing import Any, cast

-from agent_framework import Agent, AgentResponse, AgentResponseUpdate, ResponseStream
-from agent_framework.openai import OpenAIChatClient
-from typing_extensions import Any
+from agent_framework import AgentSession
+from agent_framework.foundry import FoundryAgent
+from azure.ai.projects.aio import AIProjectClient
+from azure.ai.projects.models import VersionRefIndicator
+from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
+
+load_dotenv()

 """
-This script demonstrates how to talk to a deployed agent using the OpenAIChatClient.
+This sample demonstrates how to connect to the deployed basic Foundry agent with
+`FoundryAgent`.
+
+The sample uses environment variables for configuration, which can be set in a .env file or in the environment directly:
+Environment variables:
+    FOUNDRY_PROJECT_ENDPOINT: Azure AI Foundry project endpoint.
+    FOUNDRY_AGENT_NAME: Hosted agent name.
+    FOUNDRY_AGENT_VERSION: Hosted agent version. Optional, defaults to latest if not specified.
+
+After you deploy one of the agents in this directory, you can run this sample
+to connect to it and have a conversation.
+
+Note: The `allow_preview=True` flag is required to connect to the new hosted
+agents, as this is a preview feature in Foundry.

-Depending on where you have deployed your agent (local or Foundry Hosting), you may
-need to change the base_url when initializing the OpenAIChatClient.
 """


-async def print_streaming_response(streaming_response: ResponseStream[AgentResponseUpdate, AgentResponse[Any]]) -> None:
-    async for chunk in streaming_response:
-        if chunk.text:
-            print(chunk.text, end="", flush=True)
+async def create_hosted_agent_session(
+    *,
+    agent: FoundryAgent,
+    project_client: AIProjectClient,
+    agent_name: str,
+    agent_version: str | None,
+    isolation_key: str,
+) -> AgentSession:
+    """Create a hosted-agent service session and wrap it in an AgentSession."""
+    create_session_kwargs: dict[str, Any] = {
+        "agent_name": agent_name,
+        "isolation_key": isolation_key,
+    }
+    resolved_agent_version = agent_version
+    if resolved_agent_version is None:
+        agent_details = await cast(Any, project_client.beta.agents).get(  # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType]
+            agent_name=agent_name
+        )
+        versions = getattr(agent_details, "versions", None)
+        if not isinstance(versions, Mapping):
+            raise ValueError("Hosted agent details did not include a versions mapping.")
+        latest_version = getattr(cast(Any, versions.get("latest")), "version", None)
+        if not isinstance(latest_version, str) or not latest_version:
+            raise ValueError("Hosted agent details did not include a latest version string.")
+        resolved_agent_version = latest_version
+
+    create_session_kwargs["version_indicator"] = VersionRefIndicator(agent_version=resolved_agent_version)
+    service_session = await project_client.beta.agents.create_session(**create_session_kwargs)
+    agent_session_id = getattr(service_session, "agent_session_id", None)
+    if not isinstance(agent_session_id, str) or not agent_session_id:
+        raise ValueError("Hosted agent session creation did not return a non-empty agent_session_id.")
+
+    return agent.get_session(agent_session_id)


 async def main() -> None:
-    agent = Agent(client=OpenAIChatClient(base_url="http://localhost:8088"))
-    session = agent.create_session()
+    credential = AzureCliCredential()
+    project_endpoint = os.environ["FOUNDRY_PROJECT_ENDPOINT"]
+    agent_name = os.environ["FOUNDRY_AGENT_NAME"]
+    agent_version = os.getenv("FOUNDRY_AGENT_VERSION")
+    isolation_key = "my-isolation-key"

-    # First turn
-    query = "Hi!"
-    print(f"User: {query}")
-    print("Agent: ", end="", flush=True)
-    streaming_response = agent.run(query, session=session, stream=True)
-    await print_streaming_response(streaming_response)
+    project_client = AIProjectClient(
+        endpoint=project_endpoint,
+        credential=credential,
+        allow_preview=True,
+    )
+    async with (
+        project_client,
+        FoundryAgent(
+            project_client=project_client,
+            agent_name=agent_name,
+            agent_version=agent_version,
+            allow_preview=True,
+        ) as agent,
+    ):
+        session = await create_hosted_agent_session(
+            agent=agent,
+            project_client=project_client,
+            agent_name=agent_name,
+            agent_version=agent_version,
+            isolation_key=isolation_key,
+        )

-    # Second turn
-    query = "Your name is Javis. What can you do?"
-    print(f"\nUser: {query}")
-    print("Agent: ", end="", flush=True)
-    streaming_response = agent.run(query, session=session, stream=True)
-    await print_streaming_response(streaming_response)
+        try:
+            # 1. Send the first turn.
+            query = "Hi!"
+            print(f"User: {query}")
+            print("Agent: ", end="", flush=True)
+            async for chunk in agent.run(query, session=session, stream=True):
+                if chunk.text:
+                    print(chunk.text, end="", flush=True)

-    # Third turn
-    query = "What is your name?"
-    print(f"\nUser: {query}")
-    print("Agent: ", end="", flush=True)
-    streaming_response = agent.run(query, session=session, stream=True)
-    await print_streaming_response(streaming_response)
+            # 2. Continue the conversation with the same deployed agent session.
+            query = "Your name is Javis. What can you do?"
+            print(f"\nUser: {query}")
+            print("Agent: ", end="", flush=True)
+            async for chunk in agent.run(query, session=session, stream=True):
+                if chunk.text:
+                    print(chunk.text, end="", flush=True)
+
+            # 3. Ask a follow-up question in the same session.
+            query = "What is your name?"
+            print(f"\nUser: {query}")
+            print("Agent: ", end="", flush=True)
+            async for chunk in agent.run(query, session=session, stream=True):
+                if chunk.text:
+                    print(chunk.text, end="", flush=True)
+        finally:
+            if session.service_session_id is not None:
+                await project_client.beta.agents.delete_session(
+                    agent_name=agent_name,
+                    session_id=session.service_session_id,
+                    isolation_key=isolation_key,
+                )


 if __name__ == "__main__":
    asyncio.run(main())
+
+"""
+Sample output:
+User: Hi!
+Agent: Hello! How can I help you today?
+User: Your name is Javis. What can you do?
+Agent: I can answer questions and help with tasks using the instructions configured on the deployed agent.
+User: What is your name?
+Agent: My name is Javis.
+"""
@@ -20,8 +20,10 @@ Start with `01-get-started/` and work through the numbered files:
 2. **[02_add_tools.py](./01-get-started/02_add_tools.py)** — Add function tools with `@tool`
 3. **[03_multi_turn.py](./01-get-started/03_multi_turn.py)** — Multi-turn conversations with `AgentSession`
 4. **[04_memory.py](./01-get-started/04_memory.py)** — Agent memory with `ContextProvider`
-5. **[05_first_workflow.py](./01-get-started/05_first_workflow.py)** — Build a workflow with executors and edges
-6. **[06_host_your_agent.py](./01-get-started/06_host_your_agent.py)** — Host your agent via Azure Functions
+5. **[05_functional_workflow_with_agents.py](./01-get-started/05_functional_workflow_with_agents.py)** — Call agents inside a functional workflow
+6. **[06_functional_workflow_basics.py](./01-get-started/06_functional_workflow_basics.py)** — Write a workflow as a plain async function
+7. **[07_first_graph_workflow.py](./01-get-started/07_first_graph_workflow.py)** — Build a workflow with executors and edges
+8. **[08_host_your_agent.py](./01-get-started/08_host_your_agent.py)** — Host your agent via Azure Functions

 ## Prerequisites

@@ -96,7 +96,7 @@ wheels = [

 [[package]]
 name = "agent-framework"
-version = "1.1.1"
+version = "1.2.0"
 source = { virtual = "." }
 dependencies = [
    { name = "agent-framework-core", extra = ["all"], marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -151,7 +151,7 @@ dev = [

 [[package]]
 name = "agent-framework-a2a"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/a2a" }
 dependencies = [
    { name = "a2a-sdk", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -166,7 +166,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-ag-ui"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/ag-ui" }
 dependencies = [
    { name = "ag-ui-protocol", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -194,7 +194,7 @@ provides-extras = ["dev"]

 [[package]]
 name = "agent-framework-anthropic"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/anthropic" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -209,7 +209,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-azure-ai-search"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/azure-ai-search" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -224,7 +224,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-azure-cosmos"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/azure-cosmos" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -239,7 +239,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-azurefunctions"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/azurefunctions" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -261,7 +261,7 @@ dev = []

 [[package]]
 name = "agent-framework-bedrock"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/bedrock" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -278,7 +278,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-chatkit"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/chatkit" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -293,7 +293,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-claude"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/claude" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -308,7 +308,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-copilotstudio"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/copilotstudio" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -323,7 +323,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-core"
-version = "1.1.1"
+version = "1.2.0"
 source = { editable = "packages/core" }
 dependencies = [
    { name = "opentelemetry-api", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -395,7 +395,7 @@ provides-extras = ["all"]

 [[package]]
 name = "agent-framework-declarative"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/declarative" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -420,7 +420,7 @@ dev = [{ name = "types-pyyaml", specifier = "==6.0.12.20250915" }]

 [[package]]
 name = "agent-framework-devui"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/devui" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -458,7 +458,7 @@ provides-extras = ["dev", "all"]

 [[package]]
 name = "agent-framework-durabletask"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/durabletask" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -485,7 +485,7 @@ dev = [{ name = "types-python-dateutil", specifier = "==2.9.0.20260402" }]

 [[package]]
 name = "agent-framework-foundry"
-version = "1.1.1"
+version = "1.2.0"
 source = { editable = "packages/foundry" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -523,7 +523,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-foundry-local"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/foundry_local" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -540,7 +540,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-gemini"
-version = "1.0.0a260423"
+version = "1.0.0a260424"
 source = { editable = "packages/gemini" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -555,7 +555,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-github-copilot"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/github_copilot" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -570,7 +570,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-hyperlight"
-version = "1.0.0a260423"
+version = "1.0.0a260424"
 source = { editable = "packages/hyperlight" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -589,7 +589,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-lab"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/lab" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -670,7 +670,7 @@ dev = [

 [[package]]
 name = "agent-framework-mem0"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/mem0" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -685,7 +685,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-ollama"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/ollama" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -700,7 +700,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-openai"
-version = "1.1.1"
+version = "1.2.0"
 source = { editable = "packages/openai" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -715,7 +715,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-orchestrations"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/orchestrations" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -726,7 +726,7 @@ requires-dist = [{ name = "agent-framework-core", editable = "packages/core" }]

 [[package]]
 name = "agent-framework-purview"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/purview" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
@@ -743,7 +743,7 @@ requires-dist = [

 [[package]]
 name = "agent-framework-redis"
-version = "1.0.0b260423"
+version = "1.0.0b260424"
 source = { editable = "packages/redis" }
 dependencies = [
    { name = "agent-framework-core", marker = "sys_platform == 'darwin' or sys_platform == 'linux' or sys_platform == 'win32'" },
Author	SHA1	Message	Date
Evan MattsonandGitHub	0b69d7fd15	Python: Bump Python package versions for 1.2.0 release (#5468 ) * Bump Python package versions for 1.2.0 release Released tier bumps 1.1.1 -> 1.2.0 (core, openai, foundry, root) to reflect additive public APIs landed since 1.1.0: functional workflow API (#4238) and FunctionTool SKIP_PARSING sentinel (#5424). All beta packages stamped 1.0.0b260424, alpha packages 1.0.0a260424. All 26 non-core agent-framework-core floors raised to >=1.2.0,<2. CHANGELOG consolidates the never-tagged 1.1.1 entries with the post-merge additions into [1.2.0]. * Update CHANGELOG footer links for 1.2.0 Advance [Unreleased] comparison base from python-1.1.0 to python-1.2.0 and add a [1.2.0] reference link comparing python-1.1.0...python-1.2.0 so the heading links resolve correctly. * Fix CHANGELOG: restore [1.1.1] section and add proper [1.2.0] Previous commit incorrectly renamed the [1.1.1] header to [1.2.0], which wiped the historical 1.1.1 entries and wrongly attributed them to 1.2.0. This restores [1.1.1] to its origin/main content and adds a new [1.2.0] section above containing only the commits in python-1.1.1..HEAD: - #4238 functional workflow API - #5142 GitHub Copilot OpenTelemetry - #2403 A2A bridge support - #5070 oauth_consent_request events in Foundry clients - #5447 FoundryAgent hosted agent sessions - #5459 hosting server dependency upgrade + types - #5389 AG-UI reasoning/multimodal parsing fix - #5440 stop [TOOLBOXES] warning spam - #5455 user agent prefix fix Also corrects the [1.2.0] compare base to python-1.1.1 (not 1.1.0) and adds the missing [1.1.1] reference link.	2026-04-24 19:54:59 +09:00
Giles Odigwe GitHub Copilot Copilot Evan Mattson	7b70f80036	Python: Surface `oauth_consent_request` events from Responses API in Foundry clients (#5070 ) * Fix Foundry clients not surfacing oauth_consent_request events (#5054) Override _parse_chunk_from_openai in both RawFoundryChatClient and RawFoundryAgentChatClient to intercept response.output_item.added events with item.type == 'oauth_consent_request'. The consent link is validated (HTTPS required) and converted to Content.from_oauth_consent_request, which the AG-UI layer already knows how to emit as a CUSTOM event. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback for #5054 OAuth consent parsing - Extract shared helper (try_parse_oauth_consent_event) to avoid duplicated logic between RawFoundryChatClient and RawFoundryAgentChatClient - Use urllib.parse.urlparse() for HTTPS validation instead of case-sensitive startswith check - Sanitize log messages to avoid leaking consent_link tokens; log only item id - Add model=self.model to ChatResponseUpdate to match parent behavior - Add assertions on role, raw_representation, and model in happy-path tests - Add test for empty-string consent_link - Add test verifying non-oauth events delegate to super() Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Handle response.oauth_consent_requested top-level event (#5054) Add support for the top-level response.oauth_consent_requested stream event in addition to the response.output_item.added variant. The service may emit either form; handle both so the consent link is reliably surfaced. Extract _validate_consent_link helper within _oauth_helpers.py to reduce nesting. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #5054: Python: [Bug]: `FoundryAgent` (Responses API) Does Not Surface `oauth_consent_request` as a CUSTOM AG-UI Event * Address review feedback: defensive getattr and dedicated helper tests (#5054) - Use getattr(event, 'type', None) in try_parse_oauth_consent_event for defensive access against malformed events without a type attribute - Add test_oauth_helpers.py with unit tests for _validate_consent_link and try_parse_oauth_consent_event covering edge cases: - HTTPS URL with empty netloc (https:///path) - Warning log messages for rejected consent links - Event objects missing 'type' attribute Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #5054: Python: [Bug]: `FoundryAgent` (Responses API) Does Not Surface `oauth_consent_request` as a CUSTOM AG-UI Event * Fix mypy: match _parse_chunk_from_openai signature with superclass Add seen_reasoning_delta_item_ids parameter to _parse_chunk_from_openai overrides in both RawFoundryChatClient and RawFoundryAgentChatClient to match the updated superclass signature on main. Update super() calls and test assertions accordingly. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: Evan Mattson <evan.mattson@microsoft.com>	2026-04-24 09:59:14 +00:00
Evan Mattson GitHub Copilot Copilot	da32e8cf80	Python: (core): Add functional workflow API (#4238 ) * Add functional workflow api * cleanup * More cleanup * address copilot feedback * Address PR feedbacK * updates * PR feedback * Address review comments on functional workflow samples - Swap 05/06 get-started samples: agent workflow first (motivates why workflows exist), simple text workflow second - Rename text_pipeline → text_workflow, poem_pipeline → poem_workflow - Add @step to agent workflow sample (05) to demonstrate caching - Switch agent samples to AzureOpenAIResponsesClient with Foundry - Remove .as_agent() from agent_integration.py to focus on the key difference between inline agent calls vs @step-cached calls - Add commented-out Agent.run example in hitl_review.py - Add clarifying comment in _functional.py that event streaming is buffered (not true per-token streaming) - Add naive_group_chat.py functional sample: round-robin group chat as a plain Python loop - Update READMEs to reflect new file names and group chat sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix pyright type errors * Address PR review comments on functional workflow API 1. Allow request_info inside @step: Auto-inject RunContext into step functions that declare a RunContext parameter (by type or name 'ctx'), and expose get_run_context() for programmatic access. 2. Handle None responses: Log a warning when a response value is None, and document the behavior in request_info docstring. 3. Add executor_bypassed event type: Replace executor_invoked + executor_completed with a single executor_bypassed event when a step replays from cache, making cached vs live execution explicit. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add regression tests for PR review comments on functional workflow API The three review comments (request_info in @step, None response handling, executor_bypassed event type) were already addressed in 7da7db4e. This commit adds cross-cutting regression tests that exercise the interactions between these features: - HITL in step with caching: preceding step bypassed on resume - Full checkpoint lifecycle with HITL step (interrupt -> resume -> restore) - None response inside step-level request_info logs warning - WorkflowInterrupted from step does not emit executor_failed Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR #4238 review comments on functional workflow API Comment 1 (request_info in @step): Already supported. Added comment in StepWrapper.__call__ explaining why WorkflowInterrupted (BaseException) safely bypasses the except Exception handler. Comment 2 (None response): Added docstring to _get_response clarifying the (found, value) return tuple semantics and None handling. Comment 3 (bypass event type): executor_bypassed is already a dedicated event type in WorkflowEventType. Updated comment at the bypass site to make the deliberate event type choice explicit. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add experimental API warnings to functional workflow module Mark all public classes and decorators (workflow, step, RunContext, FunctionalWorkflow, StepWrapper, FunctionalWorkflowAgent) as experimental and subject to change or removal. * Address PR #4238 review comments from @eavanvalkenburg - RunContext docstring leads with purpose (opt-in handle for HITL, custom events, state) so readers importing it from the public surface understand its role before the mechanics (#2993513452). - Rename `06_first_functional_workflow.py` to `06_functional_workflow_basics.py`; the previous filename was confusing since it followed `05_functional_workflow_with_agents.py` (#2993531979). - Simplify `05_functional_workflow_with_agents.py` to call agents directly without a @step wrapper; the step-vs-no-step contrast lives in `03-workflows/functional/agent_integration.py`, keeping the get-started sample minimal (#2993525532). - Switch functional samples to `FoundryChatClient` for consistency with the rest of 01-get-started and 03-workflows (follow-up on #2876988570). - Use walrus in `hitl_review.py` final-state assertion (#2993572182). - Add expected-output block to `basic_streaming_pipeline.py` (#2993557609). - Clarify in `parallel_pipeline.py` that `@step` composes with `asyncio.gather` (#2993597282). - `naive_group_chat.py` threads `list[Message]` between turns instead of stringifying the transcript, preserving role/authorship (#2993583231). Drive-by: pre-commit hook sorts an unrelated import block in `samples/04-hosting/foundry-hosted-agents/responses/02_local_tools/main.py`. * Fix 10 functional-workflow API bugs from /ultrareview pass - bug_001: `ctx.request_info()` without an explicit `request_id` now derives a deterministic `auto::<index>` id from the call-counter, so HITL resume works correctly on the documented default path. A uuid was regenerated on every replay, making resume impossible. - bug_002: `StepWrapper.__call__` no longer deepcopies arguments on the cache-hit replay branch. The copy is only performed on the live-execution path (for the event log) and falls back to the original mapping if deepcopy fails, so steps whose args aren't deepcopyable (locks, sockets, sessions) can still resume from checkpoint. - bug_007: `_set_responses` now prunes each resolved `request_id` from `_pending_requests`, and the cache-hit branch in `request_info` does the same. Previously, answered requests were re-serialized into every subsequent checkpoint and the final checkpoint falsely claimed pending requests even after the workflow completed. - bug_008: `_compute_signature_hash` now mixes the function's `co_code` and `co_names` into the checkpoint signature, so changes to the workflow body invalidate older checkpoints even when steps are accessed via module / class attributes (which `_discover_step_names` can't see statically). `RunContext._record_observed_step` records observed step names for diagnostics. - bug_010: `FunctionalWorkflow.run()` docstring corrected — says "at least one of message/responses/checkpoint_id" and explicitly notes `responses` may be combined with `checkpoint_id` (the validator already allowed this). - bug_013: `FunctionalWorkflowAgent` now surfaces `request_info` events as `FunctionApprovalRequestContent` items (mirroring graph `WorkflowAgent`), threads `responses=` and `checkpoint_id=` through to the underlying workflow, and exposes `pending_requests`. Previously `.as_agent()` returned empty `AgentResponse` for HITL workflows — effectively unusable. - bug_014: `FunctionalWorkflow` now clears `_last_message`, `_last_step_cache`, and `_last_pending_request_ids` on clean completion. `run()` validates that `responses=` keys intersect the currently-pending request set (or raises with a clear error) instead of silently replaying against stale singleton state from a prior run. - bug_015: `FunctionalWorkflow.as_agent` signature now matches graph `Workflow.as_agent`: accepts `name`, `description`, `context_providers`, and `*kwargs`. `FunctionalWorkflowAgent` stores the overrides. - bug_017: `RunContext.set_state` raises `ValueError` for underscore- prefixed keys (the framework's `_step_cache` / `_original_message` keys would silently clobber user state on checkpoint save and user underscore-prefixed state was dropped on restore). Docstring documents the reserved prefix. - merged_bug_003: Workflow function arity is validated at decoration time. Multiple non-ctx parameters raise `ValueError` immediately (previously every arg past the first was silently dropped at call time). Passing a non-None `message` to a ctx-only workflow raises `ValueError` instead of silently discarding the message. Test coverage: +18 regression tests covering every fix. Full workflow suite now 766 passed, 1 skipped, 2 xfailed; full core suite 2338 passed. Deslop functional.py fix commit - Remove dead instrumentation added in the prior commit that was never consumed: `RunContext._observed_step_names`, `RunContext._record_observed_step`, `FunctionalWorkflow._runtime_step_names`, and `FunctionalWorkflowAgent._extra_kwargs`. The signature hash relies on `co_code` alone, which covers the attribute-access case without the collection-scaffolding. - Trim over-explanatory comments that restated what the code does or what it no longer does. Keep only the comments that answer "why" for the non-obvious bits (deterministic id contract, defensive deepcopy, stale replay guard). - Compress the `_compute_signature_hash` and FunctionalWorkflow `__init__` block docstrings without losing the user-facing reasoning. Net -49 lines. Regression lock preserved (766 passed, 1 skipped, 2 xfailed). * Fix functional workflow review feedback --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: Copilot <copilot@github.com>	2026-04-24 09:41:20 +00:00
Eduard van Valkenburg GitHub Copilot Copilot	62e02da698	Python: update FoundryAgent for hosted agent sessions (#5447 ) * fixes to FoundryAgent to connect to new hosted agents Co-authored-by: Copilot <copilot@github.com> * fix mypy Co-authored-by: Copilot <copilot@github.com> * Python: remove Foundry service session helpers Remove the public hosted-agent service session CRUD helpers from FoundryAgent and drop the related feature-stage inventory entry. Update the hosted-agent sample to create and delete service sessions directly through the preview AIProjectClient APIs, and tighten a few test harnesses surfaced by full workspace validation. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix from merge * fix hosted env detection Co-authored-by: Copilot <copilot@github.com> * reverted sample update * fix tests and code Co-authored-by: Copilot <copilot@github.com> * remove aenter * skipping some tests Co-authored-by: Copilot <copilot@github.com> --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>	2026-04-24 09:25:03 +00:00