Python: [BREAKING] Moved to a single get_response and run API (#3379)

* WIP * big update to new ResponseStream model * fixed tests and typing * fixed tests and typing * fixed tools typevar import * fix * mypy fix * mypy fixes and some cleanup * fix missing quoted names * and client * fix imports agui * fix anthropic override * fix agui * fix ag ui * fix import * fix anthropic types * fix mypy * refactoring * updated typing * fix 3.11 * fixes * redid layering of chat clients and agents * redid layering of chat clients and agents * Fix lint, type, and test issues after rebase - Add @overload decorators to AgentProtocol.run() for type compatibility - Add missing docstring params (middleware, function_invocation_configuration) - Fix TODO format (TD002) by adding author tags - Fix broken observability tests from upstream: - Replace non-existent use_instrumentation with direct instantiation - Replace non-existent use_agent_instrumentation with AgentTelemetryLayer mixin - Fix get_streaming_response to use get_response(stream=True) - Add AgentInitializationError import - Update streaming exception tests to match actual behavior * Fix AgentExecutionException import error in test_agents.py - Replace non-existent AgentExecutionException with AgentRunException * Fix test import and asyncio deprecation issues - Add 'tests' to pythonpath in ag-ui pyproject.toml for utils_test_ag_ui import - Replace deprecated asyncio.get_event_loop().run_until_complete with asyncio.run * Fix azure-ai test failures - Update _prepare_options patching to use correct class path - Fix test_to_azure_ai_agent_tools_web_search_missing_connection to clear env vars * Convert ag-ui utils_test_ag_ui.py to conftest.py - Move test utilities to conftest.py for proper pytest discovery - Update all test imports to use conftest instead of utils_test_ag_ui - Remove old utils_test_ag_ui.py file - Revert pythonpath change in pyproject.toml * fix: use relative imports for ag-ui test utilities * fix agui * Rename Bare*Client to Raw*Client and BaseChatClient - Renamed BareChatClient to BaseChatClient (abstract base class) - Renamed BareOpenAIChatClient to RawOpenAIChatClient - Renamed BareOpenAIResponsesClient to RawOpenAIResponsesClient - Renamed BareAzureAIClient to RawAzureAIClient - Added warning docstrings to Raw* classes about layer ordering - Updated README in samples/getting_started/agents/custom with layer docs - Added test for span ordering with function calling * Fix layer ordering: FunctionInvocationLayer before ChatTelemetryLayer This ensures each inner LLM call gets its own telemetry span, resulting in the correct span sequence: chat -> execute_tool -> chat Updated all production clients and test mocks to use correct ordering: - ChatMiddlewareLayer (first) - FunctionInvocationLayer (second) - ChatTelemetryLayer (third) - BaseChatClient/Raw...Client (fourth) * Remove run_stream usage * Fix conversation_id propagation * Python: Add BaseAgent implementation for Claude Agent SDK (#3509) * Added ClaudeAgent implementation * Updated streaming logic * Small updates * Small update * Fixes * Small fix * Naming improvements * Updated imports * Addressed comments * Updated package versions * Update Claude agent connector layering * fix test and plugin * Store function middleware in invocation layer * Fix telemetry streaming and ag-ui tests * Remove legacy ag-ui tests folder * updates * Remove terminate flag from FunctionInvocationContext, use MiddlewareTermination instead - Remove terminate attribute from FunctionInvocationContext - Add result attribute to MiddlewareTermination to carry function results - FunctionMiddlewarePipeline.execute() now lets MiddlewareTermination propagate - _auto_invoke_function captures context.result in exception before re-raising - _try_execute_function_calls catches MiddlewareTermination and sets should_terminate - Fix handoff middleware to append to chat_client.function_middleware directly - Update tests to use raise MiddlewareTermination instead of context.terminate - Add middleware flow documentation in samples/concepts/tools/README.md - Fix ag-ui to use FunctionMiddlewarePipeline instead of removed create_function_middleware_pipeline * fix: remove references to removed terminate flag in purview tests, add type ignore * fix: move _test_utils.py from package to test folder * fix: call get_final_response() to trigger context provider notification in streaming test * fix: correct broken links in tools README * docs: clarify default middleware behavior in summary table * fix: ensure inner stream result hooks are called when using map()/from_awaitable() * Fix mypy type errors * Address PR review comments on observability.py - Remove TODO comment about unconsumed streams, add explanatory note instead - Remove redundant _close_span cleanup hook (already called in _finalize_stream) - Clarify behavior: cleanup hooks run after stream iteration, if stream is not consumed the span remains open until garbage collected * Remove gen_ai.client.operation.duration from span attributes Duration is a metrics-only attribute per OpenTelemetry semantic conventions. It should be recorded to the histogram but not set as a span attribute. * Remove duration from _get_response_attributes, pass directly to _capture_response Duration is a metrics-only attribute. It's now passed directly to _capture_response instead of being included in the attributes dict that gets set on the span. * Remove redundant _close_span cleanup hook in AgentTelemetryLayer _finalize_stream already calls _close_span() in its finally block, so adding it as a separate cleanup hook is redundant. * Use weakref.finalize to close span when stream is garbage collected If a user creates a streaming response but never consumes it, the cleanup hooks won't run. Now we register a weak reference finalizer that will close the span when the stream object is garbage collected, ensuring spans don't leak in this scenario. * Fix _get_finalizers_from_stream to use _result_hooks attribute Renamed function to _get_result_hooks_from_stream and fixed it to look for the _result_hooks attribute which is the correct name in ResponseStream class. * Add missing asyncio import in test_request_info_mixin.py * Fix leftover merge conflict marker in image_generation sample * Update integration tests * Fix integration tests: increase max_iterations from 1 to 2 Tests with tool_choice options require at least 2 iterations: 1. First iteration to get function call and execute the tool 2. Second iteration to get the final text response With max_iterations=1, streaming tests would return early with only the function call/result but no final text content. * Fix duplicate function call error in conversation-based APIs When using conversation_id (for Responses/Assistants APIs), the server already has the function call message from the previous response. We should only send the new function result message, not all messages including the function call which would cause a duplicate ID error. Fix: When conversation_id is set, only send the last message (the tool result) instead of all response.messages. * Add regression test for conversation_id propagation between tool iterations Port test from PR #3664 with updates for new streaming API pattern. Tests that conversation_id is properly updated in options dict during function invocation loop iterations. * Fix tool_choice=required to return after tool execution When tool_choice is 'required', the user's intent is to force exactly one tool call. After the tool executes, return immediately with the function call and result - don't continue to call the model again. This fixes integration tests that were failing with empty text responses because with tool_choice=required, the model would keep returning function calls instead of text. Also adds regression tests for: - conversation_id propagation between tool iterations (from PR #3664) - tool_choice=required returns after tool execution * Document tool_choice behavior in tools README - Add table explaining tool_choice values (auto, none, required) - Explain why tool_choice=required returns immediately after tool execution - Add code example showing the difference between required and auto - Update flow diagram to show the early return path for tool_choice=required * Fix tool_choice=None behavior - don't default to 'auto' Remove the hardcoded default of 'auto' for tool_choice in ChatAgent init. When tool_choice is not specified (None), it will now not be sent to the API, allowing the API's default behavior to be used. Users who want tool_choice='auto' can still explicitly set it either in default_options or at runtime. Fixes #3585 * Fix tool_choice=none should not remove tools In OpenAI Assistants client, tools were not being sent when tool_choice='none'. This was incorrect - tool_choice='none' means the model won't call tools, but tools should still be available in the request (they may be used later in the conversation). Fixes #3585 * Add test for tool_choice=none preserving tools Adds a regression test to ensure that when tool_choice='none' is set but tools are provided, the tools are still sent to the API. This verifies the fix for #3585. * Fix tool_choice=none should not remove tools in all clients Apply the same fix to OpenAI Responses client and Azure AI client: - OpenAI Responses: Remove else block that popped tool_choice/parallel_tool_calls - Azure AI: Remove tool_choice != 'none' check when adding tools When tool_choice='none', the model won't call tools, but tools should still be sent to the API so they're available for future turns. Also update README to clarify tool_choice=required supports multiple tools. Fixes #3585 * Keep tool_choice even when tools is None Move tool_choice processing outside of the 'if tools' block in OpenAI Responses client so tool_choice is sent to the API even when no tools are provided. * Update test to match new parallel_tool_calls behavior Changed test_prepare_options_removes_parallel_tool_calls_when_no_tools to test_prepare_options_preserves_parallel_tool_calls_when_no_tools to reflect that parallel_tool_calls is now preserved even when no tools are present, consistent with the tool_choice behavior. * Fix ChatMessage API and Role enum usage after rebase - Update ChatMessage instantiation to use keyword args (role=, text=, contents=) - Fix Role enum comparisons to use .value for string comparison - Add created_at to AgentResponse in error handling - Fix AgentResponse.from_updates -> from_agent_run_response_updates - Fix DurableAgentStateMessage.from_chat_message to convert Role enum to string - Add Role import where needed * Fix additional ChatMessage API and method name changes - Fix ChatMessage usage in workflow files (use text= instead of contents= for strings) - Fix AgentResponse.from_updates -> from_agent_run_response_updates in workflow files - Fix test files for ChatMessage and Role enum usage * Fix remaining ChatMessage API usage in test files * Fix more ChatMessage and Role API changes in source and test files - Fix ChatMessage in _magentic.py replan method - Fix Role enum comparison in test assertions - Fix remaining test files with old ChatMessage syntax * Fix ChatMessage and Role API changes across packages - Add Role import where missing - Fix ChatMessage signature: positional args to keyword args (role=, text=, contents=) - Fix Role enum comparisons: .role.value instead of .role string - Fix FinishReason enum usage in ag-ui event converters - Rename AgentResponse.from_updates to from_agent_run_response_updates in ag-ui Fixes API compatibility after Types API Review improvements merge * Fix ChatMessage and Role API changes in github_copilot tests * Fix ChatMessage and Role API changes in redis and github_copilot packages - Fix redis provider: Role enum comparison using .value - Fix redis tests: ChatMessage signature and Role comparisons - Fix github_copilot tests: ChatMessage signature and Role comparisons - Update docstring examples in redis chat message store * Fix ChatMessage and Role API changes in devui package - Fix executor: ChatMessage signature change - Fix conversations: Role enum to string conversion in two places - Fix tests: ChatMessage signatures and Role comparisons * Fix ChatMessage and Role API changes in a2a and lab packages - Fix a2a tests: Role comparisons and ChatMessage signatures - Fix lab tau2 source: Role enum comparison in flip_messages, log_messages, sliding_window - Fix lab tau2 tests: ChatMessage signatures and Role comparisons * Remove duplicate test files from ag-ui/tests (tests are in ag_ui_tests) * Fix ChatMessage and Role API changes across packages After rebasing on upstream/main which merged PR #3647 (Types API Review improvements), fix all packages to use the new API: - ChatMessage: Use keyword args (role=, text=, contents=) instead of positional args - Role: Compare using .value attribute since it's now an enum Packages fixed: - ag-ui: Fixed Role value extraction bugs in _message_adapters.py - anthropic: Fixed ChatMessage and Role comparisons in tests - azure-ai: Fixed Role comparison in _client.py - azure-ai-search: Fixed ChatMessage and Role in source/tests - bedrock: Fixed ChatMessage signatures in tests - chatkit: Fixed ChatMessage and Role in source/tests - copilotstudio: Fixed ChatMessage and Role in tests - declarative: Fixed ChatMessage in _executors_agents.py - mem0: Fixed ChatMessage and Role in source/tests - purview: Fixed ChatMessage in source/tests * Fix mypy errors for ChatMessage and Role API changes - durabletask: Use str() fallback in role value extraction - core: Fix ChatMessage in _orchestrator_helpers.py to use keyword args - core: Add type ignore for _conversation_state.py contents deserialization - ag-ui: Fix type ignore comments (call-overload instead of arg-type) - azure-ai-search: Fix get_role_value type hint to accept Any - lab: Move get_role_value to module level with Any type hint * Improve CI test timeout configuration - Increase job timeout from 10 to 15 minutes - Reduce per-test timeout to 60s (was 900s/300s) - Add --timeout_method thread for better timeout handling - Add --timeout-verbose to see which tests are slow - Reduce retries from 3 to 2 and delay from 10s to 5s This ensures individual test timeouts are shorter than the job timeout, providing better visibility when tests hang. With 60s timeout and 2 retries, worst case per test is ~180s. * Fix ChatMessage API usage in docstrings and source - Fix ChatMessage positional args in docstrings: _serialization.py, _threads.py, _middleware.py - Fix ChatMessage in tau2 runner.py - Fix role comparison in _orchestrator_helpers.py to use .value - Fix role comparison in _group_chat.py docstring example - Fix role assertions in test_durable_entities.py to use .value * Revert tool_choice/parallel_tool_calls changes - must be removed when no tools OpenAI API requires tool_choice and parallel_tool_calls to only be present when tools are specified. Restored the logic that removes these options when there are no tools. - Restored check in _chat_client.py to remove tool_choice and parallel_tool_calls when no tools present - Restored same logic in _responses_client.py - Reverted test to expect the correct behavior * fixed issue in tests * fix: resolve merge conflict markers in ag-ui tests * fix: restructure ag-ui tests and fix Role/FinishReason to use string types * fix: streaming function invocation and middleware termination - Refactor streaming function invocation to use get_final_response() on inner streams - Fix MiddlewareTermination to accept result parameter for passing results - Fix _AutoHandoffMiddleware to use MiddlewareTermination instead of context.terminate - Fix AgentMiddlewareLayer.run() to properly forward function/chat middleware - Remove duplicate middleware registration in AgentMiddlewareLayer.__init__ - Fix exception handling in _auto_invoke_function to properly capture termination - Fix mypy errors in core package - Update tests to use stream=True parameter for unified run API * fix all tests command * Refactor integration tests to use pytest fixtures - Merge testutils.py into conftest.py for azurefunctions integration tests - Merge dt_testutils.py into conftest.py for durabletask integration tests - Convert all integration tests to use fixtures instead of direct imports (fixes ModuleNotFoundError with --import-mode=importlib) - Add sample_helper fixture for azurefunctions tests - Add agent_client_factory and orchestration_helper fixtures for durabletask - Integration tests now skip with descriptive messages when services unavailable - Restructure devui tests into tests/devui/ with proper conftest.py - Add test organization guidelines to CODING_STANDARD.md - Remove __init__.py from test directories per pytest best practices * Fix pytest_collection_modifyitems to only skip integration tests The hook was skipping all tests in the test session, not just integration tests. Now it only skips items in the integration_tests directory. * Fix mem0 tests failing on Python 3.13 Use patch.object on the imported module instead of @patch with string path to ensure the mock takes effect regardless of import timing. * fix mem0 * another attempt for mem0 * fix for mem0 * fix mem0 * Increase worker initialization wait time in durabletask tests Increase from 2 to 8 seconds to allow time for: - Python startup and module imports - Azure OpenAI client creation - Agent registration with DTS worker - Worker connection to DTS This helps prevent test failures in CI where the first tests may run before the worker is fully ready to process requests. * Fix streaming test to use ResponseStream with finalizer The _consume_stream method now expects a ResponseStream that can provide a final AgentResponse via get_final_response(). Update the test to use ResponseStream with AgentResponse.from_updates as the finalizer. * Fix MockToolCallingAgent to use new ResponseStream API and update samples * small updates to run_stream to run * fix sub workflow * temp fix for az func test --------- Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com>
2026-06-16 21:04:09 +08:00 · 2026-02-05 20:09:58 +00:00
parent d1205896a1
commit 3dc59c83b5
372 changed files with 11583 additions and 9465 deletions
@@ -6,9 +6,9 @@ import json
 import logging
 import sys
 import uuid
-from collections.abc import AsyncIterable, MutableSequence
+from collections.abc import AsyncIterable, Awaitable, Mapping, MutableSequence, Sequence
 from functools import wraps
-from typing import TYPE_CHECKING, Any, Generic, cast
+from typing import TYPE_CHECKING, Any, Generic, TypedDict, cast

 import httpx
 from agent_framework import (
@@ -18,10 +18,11 @@ from agent_framework import (
    ChatResponseUpdate,
    Content,
    FunctionTool,
-    use_chat_middleware,
-    use_function_invocation,
+    ResponseStream,
 )
-from agent_framework.observability import use_instrumentation
+from agent_framework._middleware import ChatMiddlewareLayer
+from agent_framework._tools import FunctionInvocationConfiguration, FunctionInvocationLayer
+from agent_framework.observability import ChatTelemetryLayer

 from ._event_converters import AGUIEventConverter
 from ._http_service import AGUIHttpService
@@ -42,6 +43,8 @@ else:
    from typing_extensions import Self, TypedDict  # pragma: no cover

 if TYPE_CHECKING:
+    from agent_framework._middleware import ChatAndFunctionMiddlewareTypes
+
    from ._types import AGUIChatOptions

 logger: logging.Logger = logging.getLogger(__name__)
@@ -67,35 +70,51 @@ TAGUIChatOptions = TypeVar(
 def _apply_server_function_call_unwrap(chat_client: TBaseChatClient) -> TBaseChatClient:
    """Class decorator that unwraps server-side function calls after tool handling."""

-    original_get_streaming_response = chat_client.get_streaming_response
-
-    @wraps(original_get_streaming_response)
-    async def streaming_wrapper(self: Any, *args: Any, **kwargs: Any) -> AsyncIterable[ChatResponseUpdate]:
-        async for update in original_get_streaming_response(self, *args, **kwargs):
-            _unwrap_server_function_call_contents(cast(MutableSequence[Content | dict[str, Any]], update.contents))
-            yield update
-
-    chat_client.get_streaming_response = streaming_wrapper  # type: ignore[assignment]
-
    original_get_response = chat_client.get_response

    @wraps(original_get_response)
-    async def response_wrapper(self: Any, *args: Any, **kwargs: Any) -> ChatResponse:
-        response: ChatResponse[Any] = await original_get_response(self, *args, **kwargs)  # type: ignore[var-annotated]
+    def response_wrapper(
+        self, *args: Any, stream: bool = False, **kwargs: Any
+    ) -> Awaitable[ChatResponse] | ResponseStream[ChatResponseUpdate, ChatResponse]:
+        if stream:
+            stream_response = original_get_response(self, *args, stream=True, **kwargs)
+            if isinstance(stream_response, ResponseStream):
+                return stream_response.with_transform_hook(_map_update)
+            return ResponseStream(_stream_wrapper_impl(stream_response))
+        return _response_wrapper_impl(self, original_get_response, *args, **kwargs)
+
+    async def _response_wrapper_impl(self, original_func: Any, *args: Any, **kwargs: Any) -> ChatResponse:
+        """Non-streaming wrapper implementation."""
+        response = await original_func(self, *args, stream=False, **kwargs)
        if response.messages:
            for message in response.messages:
                _unwrap_server_function_call_contents(cast(MutableSequence[Content | dict[str, Any]], message.contents))
-        return response
+        return response  # type: ignore[no-any-return]
+
+    async def _stream_wrapper_impl(stream: Any) -> AsyncIterable[ChatResponseUpdate]:
+        """Streaming wrapper implementation."""
+        if isinstance(stream, Awaitable):
+            stream = await stream
+        async for update in stream:
+            _unwrap_server_function_call_contents(cast(MutableSequence[Content | dict[str, Any]], update.contents))
+            yield update
+
+    def _map_update(update: ChatResponseUpdate) -> ChatResponseUpdate:
+        _unwrap_server_function_call_contents(cast(MutableSequence[Content | dict[str, Any]], update.contents))
+        return update

    chat_client.get_response = response_wrapper  # type: ignore[assignment]
    return chat_client


@_apply_server_function_call_unwrap
-@use_function_invocation
-@use_instrumentation
-@use_chat_middleware
-class AGUIChatClient(BaseChatClient[TAGUIChatOptions], Generic[TAGUIChatOptions]):
+class AGUIChatClient(
+    ChatMiddlewareLayer[TAGUIChatOptions],
+    FunctionInvocationLayer[TAGUIChatOptions],
+    ChatTelemetryLayer[TAGUIChatOptions],
+    BaseChatClient[TAGUIChatOptions],
+    Generic[TAGUIChatOptions],
+):
    """Chat client for communicating with AG-UI compliant servers.

    This client implements the BaseChatClient interface and automatically handles:
@@ -103,6 +122,7 @@ class AGUIChatClient(BaseChatClient[TAGUIChatOptions], Generic[TAGUIChatOptions]
    - State synchronization between client and server
    - Server-Sent Events (SSE) streaming
    - Event conversion to Agent Framework types
+    - MiddlewareTypes, telemetry, and function invocation support

    Important: Message History Management
        This client sends exactly the messages it receives to the server. It does NOT
@@ -115,10 +135,10 @@ class AGUIChatClient(BaseChatClient[TAGUIChatOptions], Generic[TAGUIChatOptions]
    Important: Tool Handling (Hybrid Execution - matches .NET)
        1. Client tool metadata sent to server - LLM knows about both client and server tools
        2. Server has its own tools that execute server-side
-        3. When LLM calls a client tool, @use_function_invocation executes it locally
+        3. When LLM calls a client tool, function invocation executes it locally
        4. Both client and server tools work together (hybrid pattern)

-        The wrapping ChatAgent's @use_function_invocation handles client tool execution
+        The wrapping ChatAgent's function invocation handles client tool execution
        automatically when the server's LLM decides to call them.

    Examples:
@@ -159,7 +179,7 @@ class AGUIChatClient(BaseChatClient[TAGUIChatOptions], Generic[TAGUIChatOptions]

        .. code-block:: python

-            async for update in client.get_streaming_response("Tell me a story"):
+            async for update in client.get_response("Tell me a story", stream=True):
                if update.contents:
                    for content in update.contents:
                        if hasattr(content, "text"):
@@ -196,6 +216,8 @@ class AGUIChatClient(BaseChatClient[TAGUIChatOptions], Generic[TAGUIChatOptions]
        http_client: httpx.AsyncClient | None = None,
        timeout: float = 60.0,
        additional_properties: dict[str, Any] | None = None,
+        middleware: Sequence["ChatAndFunctionMiddlewareTypes"] | None = None,
+        function_invocation_configuration: FunctionInvocationConfiguration | None = None,
        **kwargs: Any,
    ) -> None:
        """Initialize the AG-UI chat client.
@@ -205,9 +227,16 @@ class AGUIChatClient(BaseChatClient[TAGUIChatOptions], Generic[TAGUIChatOptions]
            http_client: Optional httpx.AsyncClient instance. If None, one will be created.
            timeout: Request timeout in seconds (default: 60.0)
            additional_properties: Additional properties to store
+            middleware: Optional middleware to apply to the client.
+            function_invocation_configuration: Optional function invocation configuration override.
            **kwargs: Additional arguments passed to BaseChatClient
        """
-        super().__init__(additional_properties=additional_properties, **kwargs)
+        super().__init__(
+            additional_properties=additional_properties,
+            middleware=middleware,
+            function_invocation_configuration=function_invocation_configuration,
+            **kwargs,
+        )
        self._http_service = AGUIHttpService(
            endpoint=endpoint,
            http_client=http_client,
@@ -230,9 +259,10 @@ class AGUIChatClient(BaseChatClient[TAGUIChatOptions], Generic[TAGUIChatOptions]
        """Register a declaration-only placeholder so function invocation skips execution."""

        config = getattr(self, "function_invocation_configuration", None)
-        if not config:
+        if not isinstance(config, dict):
            return
-        if any(getattr(tool, "name", None) == tool_name for tool in config.additional_tools):
+        additional_tools = list(config.get("additional_tools", []))
+        if any(getattr(tool, "name", None) == tool_name for tool in additional_tools):
            return

        placeholder: FunctionTool[Any, Any] = FunctionTool(
@@ -240,7 +270,8 @@ class AGUIChatClient(BaseChatClient[TAGUIChatOptions], Generic[TAGUIChatOptions]
            description="Server-managed tool placeholder (AG-UI)",
            func=None,
        )
-        config.additional_tools = list(config.additional_tools) + [placeholder]
+        additional_tools.append(placeholder)
+        config["additional_tools"] = additional_tools
        registered: set[str] = getattr(self, "_registered_server_tools", set())
        registered.add(tool_name)
        self._registered_server_tools = registered  # type: ignore[attr-defined]
@@ -250,7 +281,7 @@ class AGUIChatClient(BaseChatClient[TAGUIChatOptions], Generic[TAGUIChatOptions]
        logger.debug(f"[AGUIChatClient] Registered server placeholder: {tool_name}")

    def _extract_state_from_messages(
-        self, messages: MutableSequence[ChatMessage]
+        self, messages: Sequence[ChatMessage]
    ) -> tuple[list[ChatMessage], dict[str, Any] | None]:
        """Extract state from last message if present.

@@ -297,7 +328,7 @@ class AGUIChatClient(BaseChatClient[TAGUIChatOptions], Generic[TAGUIChatOptions]
        """
        return agent_framework_messages_to_agui(messages)

-    def _get_thread_id(self, options: dict[str, Any]) -> str:
+    def _get_thread_id(self, options: Mapping[str, Any]) -> str:
        """Get or generate thread ID from chat options.

        Args:
@@ -317,43 +348,57 @@ class AGUIChatClient(BaseChatClient[TAGUIChatOptions], Generic[TAGUIChatOptions]
        return thread_id

    @override
-    async def _inner_get_response(
+    def _inner_get_response(
        self,
        *,
-        messages: MutableSequence[ChatMessage],
-        options: dict[str, Any],
+        messages: Sequence[ChatMessage],
+        stream: bool = False,
+        options: Mapping[str, Any],
        **kwargs: Any,
-    ) -> ChatResponse:
+    ) -> Awaitable[ChatResponse] | ResponseStream[ChatResponseUpdate, ChatResponse]:
        """Internal method to get non-streaming response.

        Keyword Args:
            messages: List of chat messages
+            stream: Whether to stream the response.
            options: Chat options for the request
            **kwargs: Additional keyword arguments

        Returns:
            ChatResponse object
        """
-        return await ChatResponse.from_update_generator(
-            self._inner_get_streaming_response(
-                messages=messages,
-                options=options,
-                **kwargs,
+        if stream:
+            return ResponseStream(
+                self._streaming_impl(
+                    messages=messages,
+                    options=options,
+                    **kwargs,
+                ),
+                finalizer=ChatResponse.from_updates,
            )
-        )

-    @override
-    async def _inner_get_streaming_response(
+        async def _get_response() -> ChatResponse:
+            return await ChatResponse.from_update_generator(
+                self._streaming_impl(
+                    messages=messages,
+                    options=options,
+                    **kwargs,
+                )
+            )
+
+        return _get_response()
+
+    async def _streaming_impl(
        self,
        *,
-        messages: MutableSequence[ChatMessage],
-        options: dict[str, Any],
+        messages: Sequence[ChatMessage],
+        options: Mapping[str, Any],
        **kwargs: Any,
    ) -> AsyncIterable[ChatResponseUpdate]:
        """Internal method to get streaming response.

        Keyword Args:
-            messages: List of chat messages
+            messages: Sequence of chat messages
            options: Chat options for the request
            **kwargs: Additional keyword arguments

@@ -368,7 +413,7 @@ class AGUIChatClient(BaseChatClient[TAGUIChatOptions], Generic[TAGUIChatOptions]
        agui_messages = self._convert_messages_to_agui_format(messages_to_send)

        # Send client tools to server so LLM knows about them
-        # Client tools execute via ChatAgent's @use_function_invocation wrapper
+        # Client tools execute via ChatAgent's function invocation wrapper
        agui_tools = convert_tools_to_agui_format(options.get("tools"))

        # Build set of client tool names (matches .NET clientToolSet)
@@ -415,12 +460,12 @@ class AGUIChatClient(BaseChatClient[TAGUIChatOptions], Generic[TAGUIChatOptions]
                            f"[AGUIChatClient] Function call: {content.name}, in client_tool_set: {content.name in client_tool_set}"  # type: ignore[attr-defined]
                        )
                        if content.name in client_tool_set:  # type: ignore[attr-defined]
-                            # Client tool - let @use_function_invocation execute it
+                            # Client tool - let function invocation execute it
                            if not content.additional_properties:  # type: ignore[attr-defined]
                                content.additional_properties = {}  # type: ignore[attr-defined]
                            content.additional_properties["agui_thread_id"] = thread_id  # type: ignore[attr-defined]
                        else:
-                            # Server tool - wrap so @use_function_invocation ignores it
+                            # Server tool - wrap so function invocation ignores it
                            logger.debug(f"[AGUIChatClient] Wrapping server tool: {content.name}")  # type: ignore[union-attr]
                            self._register_server_tool_placeholder(content.name)  # type: ignore[arg-type]
                            update.contents[i] = Content(type="server_function_call", function_call=content)  # type: ignore
@@ -590,7 +590,7 @@ def agui_messages_to_agent_framework(messages: list[dict[str, Any]]) -> list[Cha
                            arguments=arguments,
                        )
                    )
-            chat_msg = ChatMessage("assistant", contents)
+            chat_msg = ChatMessage(role="assistant", contents=contents)
            if "id" in msg:
                chat_msg.message_id = msg["id"]
            result.append(chat_msg)
@@ -620,14 +620,14 @@ def agui_messages_to_agent_framework(messages: list[dict[str, Any]]) -> list[Cha
                )
                approval_contents.append(approval_response)

-            chat_msg = ChatMessage(role, approval_contents)  # type: ignore[arg-type]
+            chat_msg = ChatMessage(role=role, contents=approval_contents)  # type: ignore[call-overload]
        else:
            # Regular text message
            content = msg.get("content", "")
            if isinstance(content, str):
-                chat_msg = ChatMessage(role, [Content.from_text(text=content)])
+                chat_msg = ChatMessage(role=role, contents=[Content.from_text(text=content)])  # type: ignore[call-overload]
            else:
-                chat_msg = ChatMessage(role, [Content.from_text(text=str(content))])
+                chat_msg = ChatMessage(role=role, contents=[Content.from_text(text=str(content))])  # type: ignore[call-overload]

        if "id" in msg:
            chat_msg.message_id = msg["id"]
@@ -671,7 +671,8 @@ def agent_framework_messages_to_agui(messages: list[ChatMessage] | list[dict[str
            continue

        # Convert ChatMessage to AG-UI format
-        role = FRAMEWORK_TO_AGUI_ROLE.get(msg.role, "user")
+        role_value: str = msg.role if hasattr(msg.role, "value") else msg.role  # type: ignore[assignment]
+        role = FRAMEWORK_TO_AGUI_ROLE.get(role_value, "user")

        content_text = ""
        tool_calls: list[dict[str, Any]] = []
@@ -79,8 +79,8 @@ def register_additional_client_tools(agent: "AgentProtocol", client_tools: list[
    if chat_client is None:
        return

-    if isinstance(chat_client, BaseChatClient) and chat_client.function_invocation_configuration is not None:
-        chat_client.function_invocation_configuration.additional_tools = client_tools
+    if isinstance(chat_client, BaseChatClient) and chat_client.function_invocation_configuration is not None:  # type: ignore[attr-defined]
+        chat_client.function_invocation_configuration["additional_tools"] = client_tools  # type: ignore[attr-defined]
        logger.debug(f"[TOOLS] Registered {len(client_tools)} client tools as additional_tools (declaration-only)")


@@ -5,8 +5,9 @@
 import json
 import logging
 import uuid
+from collections.abc import Awaitable
 from dataclasses import dataclass, field
-from typing import TYPE_CHECKING, Any
+from typing import TYPE_CHECKING, Any, cast

 from ag_ui.core import (
    BaseEvent,
@@ -30,13 +31,15 @@ from agent_framework import (
    Content,
    prepare_function_call_results,
 )
-from agent_framework._middleware import extract_and_merge_function_middleware
+from agent_framework._middleware import FunctionMiddlewarePipeline
 from agent_framework._tools import (
-    FunctionInvocationConfiguration,
    _collect_approval_responses,  # type: ignore
    _replace_approval_contents_with_results,  # type: ignore
    _try_execute_function_calls,  # type: ignore
+    normalize_function_invocation_configuration,
 )
+from agent_framework._types import ResponseStream
+from agent_framework.exceptions import AgentExecutionException

 from ._message_adapters import normalize_agui_input_messages
 from ._orchestration._predictive_state import PredictiveStateHandler
@@ -601,8 +604,13 @@ async def _resolve_approval_responses(
    # Execute approved tool calls
    if approved_responses and tools:
        chat_client = getattr(agent, "chat_client", None)
-        config = getattr(chat_client, "function_invocation_configuration", None) or FunctionInvocationConfiguration()
-        middleware_pipeline = extract_and_merge_function_middleware(chat_client, run_kwargs)
+        config = normalize_function_invocation_configuration(
+            getattr(chat_client, "function_invocation_configuration", None)
+        )
+        middleware_pipeline = FunctionMiddlewarePipeline(
+            *getattr(chat_client, "function_middleware", ()),
+            *run_kwargs.get("middleware", ()),
+        )
        # Filter out AG-UI-specific kwargs that should not be passed to tool execution
        tool_kwargs = {k: v for k, v in run_kwargs.items() if k != "options"}
        try:
@@ -862,7 +870,14 @@ async def run_agent_stream(
    # Stream from agent - emit RunStarted after first update to get service IDs
    run_started_emitted = False
    all_updates: list[Any] = []  # Collect for structured output processing
-    async for update in agent.run_stream(messages, **run_kwargs):
+    response_stream = agent.run(messages, stream=True, **run_kwargs)
+    if isinstance(response_stream, ResponseStream):
+        stream = response_stream
+    else:
+        stream = await cast(Awaitable[ResponseStream[Any, Any]], response_stream)
+        if not isinstance(stream, ResponseStream):
+            raise AgentExecutionException("Chat client did not return a ResponseStream.")
+    async for update in stream:
        # Collect updates for structured output processing
        if response_format is not None:
            all_updates.append(update)
@@ -102,7 +102,7 @@ class AGUIChatOptions(ChatOptions[TResponseModel], Generic[TResponseModel], tota
        stop: Stop sequences.
        tools: List of tools - sent to server so LLM knows about client tools.
            Server executes its own tools; client tools execute locally via
-            @use_function_invocation middleware.
+            function invocation middleware.
        tool_choice: How the model should use tools.
        metadata: Metadata dict containing thread_id for conversation continuity.

@@ -165,7 +165,7 @@ def convert_agui_tools_to_agent_framework(

    Creates declaration-only FunctionTool instances (no executable implementation).
    These are used to tell the LLM about available tools. The actual execution
-    happens on the client side via @use_function_invocation.
+    happens on the client side via function invocation mixin.

    CRITICAL: These tools MUST have func=None so that declaration_only returns True.
    This prevents the server from trying to execute client-side tools.
@@ -183,7 +183,7 @@ def convert_agui_tools_to_agent_framework(
    for tool_def in agui_tools:
        # Create declaration-only FunctionTool (func=None means no implementation)
        # When func=None, the declaration_only property returns True,
-        # which tells @use_function_invocation to return the function call
+        # which tells the function invocation mixin to return the function call
        # without executing it (so it can be sent back to the client)
        func: FunctionTool[Any, Any] = FunctionTool(
            name=tool_def.get("name", ""),
@@ -209,7 +209,7 @@ def convert_tools_to_agui_format(

    This sends only the metadata (name, description, JSON schema) to the server.
    The actual executable implementation stays on the client side.
-    The @use_function_invocation decorator handles client-side execution when
+    The function invocation mixin handles client-side execution when
    the server requests a function.

    Args: