Python: [BREAKING] Refactor middleware layering and split Anthropic raw client

python/packages/ag-ui/agent_framework_ag_ui/_client.py

@@ -111,8 +111,8 @@ def _map_update(update: ChatResponseUpdate) -> ChatResponseUpdate:
 
 @_apply_server_function_call_unwrap
 class AGUIChatClient(
-    ChatMiddlewareLayer[AGUIChatOptionsT],
     FunctionInvocationLayer[AGUIChatOptionsT],
+    ChatMiddlewareLayer[AGUIChatOptionsT],
     ChatTelemetryLayer[AGUIChatOptionsT],
     BaseChatClient[AGUIChatOptionsT],
     Generic[AGUIChatOptionsT],

python/packages/ag-ui/tests/ag_ui/conftest.py

@@ -45,16 +45,16 @@ def pytest_configure() -> None:
 
 
 class StreamingChatClientStub(
-    ChatMiddlewareLayer[OptionsCoT],
     FunctionInvocationLayer[OptionsCoT],
+    ChatMiddlewareLayer[OptionsCoT],
     ChatTelemetryLayer[OptionsCoT],
     BaseChatClient[OptionsCoT],
     Generic[OptionsCoT],
 ):
     """Typed streaming stub that satisfies SupportsChatGetResponse."""
 
     def __init__(self, stream_fn: StreamFn, response_fn: ResponseFn | None = None) -> None:
-        super().__init__(function_middleware=[])
+        super().__init__(middleware=[])
         self._stream_fn = stream_fn
         self._response_fn = response_fn
         self.last_session: AgentSession | None = None

python/packages/anthropic/agent_framework_anthropic/__init__.py

@@ -2,7 +2,7 @@
 
 import importlib.metadata
 
-from ._chat_client import AnthropicChatOptions, AnthropicClient
+from ._chat_client import AnthropicChatOptions, AnthropicClient, RawAnthropicClient
 
 try:
     __version__ = importlib.metadata.version(__name__)
@@ -12,5 +12,6 @@
 __all__ = [
     "AnthropicChatOptions",
     "AnthropicClient",
+    "RawAnthropicClient",
     "__version__",
 ]

python/packages/anthropic/agent_framework_anthropic/_chat_client.py

@@ -68,6 +68,7 @@
 __all__ = [
     "AnthropicChatOptions",
     "AnthropicClient",
+    "RawAnthropicClient",
     "ThinkingConfig",
 ]
 
@@ -210,14 +211,24 @@ class AnthropicSettings(TypedDict, total=False):
     chat_model_id: str | None
 
 
-class AnthropicClient(
-    ChatMiddlewareLayer[AnthropicOptionsT],
-    FunctionInvocationLayer[AnthropicOptionsT],
-    ChatTelemetryLayer[AnthropicOptionsT],
+class RawAnthropicClient(
     BaseChatClient[AnthropicOptionsT],
     Generic[AnthropicOptionsT],
 ):
-    """Anthropic Chat client with middleware, telemetry, and function invocation support."""
+    """Raw Anthropic chat client without middleware, telemetry, or function invocation support.
+
+    Warning:
+        **This class should not normally be used directly.** It does not include middleware,
+        telemetry, or function invocation support that you most likely need. If you do use it,
+        you should consider which additional layers to apply. There is a defined ordering that
+        you should follow:
+
+        1. **FunctionInvocationLayer** - Owns the tool/function calling loop and routes function middleware
+        2. **ChatMiddlewareLayer** - Applies chat middleware per model call and stays outside telemetry
+        3. **ChatTelemetryLayer** - Must stay inside chat middleware for correct per-call telemetry
+
+        Use ``AnthropicClient`` instead for a fully-featured client with all layers applied.
+    """
 
     OTEL_PROVIDER_NAME: ClassVar[str] = "anthropic"  # type: ignore[reportIncompatibleVariableOverride, misc]
 
@@ -229,12 +240,10 @@ def __init__(
         anthropic_client: AsyncAnthropic | None = None,
         additional_beta_flags: list[str] | None = None,
         additional_properties: dict[str, Any] | None = None,
-        middleware: Sequence[ChatAndFunctionMiddlewareTypes] | None = None,
-        function_invocation_configuration: FunctionInvocationConfiguration | None = None,
         env_file_path: str | None = None,
         env_file_encoding: str | None = None,
     ) -> None:
-        """Initialize an Anthropic Agent client.
+        """Initialize a raw Anthropic client.
 
         Keyword Args:
             api_key: The Anthropic API key to use for authentication.
@@ -245,37 +254,35 @@ def __init__(
             additional_beta_flags: Additional beta flags to enable on the client.
                 Default flags are: "mcp-client-2025-04-04", "code-execution-2025-08-25".
             additional_properties: Additional properties stored on the client instance.
-            middleware: Optional middleware to apply to the client.
-            function_invocation_configuration: Optional function invocation configuration override.
             env_file_path: Path to environment file for loading settings.
             env_file_encoding: Encoding of the environment file.
 
         Examples:
             .. code-block:: python
 
-                from agent_framework.anthropic import AnthropicClient
+                from agent_framework.anthropic import RawAnthropicClient
                 from azure.identity.aio import DefaultAzureCredential
 
                 # Using environment variables
                 # Set ANTHROPIC_API_KEY=your_anthropic_api_key
                 # ANTHROPIC_CHAT_MODEL_ID=claude-sonnet-4-5-20250929
 
                 # Or passing parameters directly
-                client = AnthropicClient(
+                client = RawAnthropicClient(
                     model_id="claude-sonnet-4-5-20250929",
                     api_key="your_anthropic_api_key",
                 )
 
                 # Or loading from a .env file
-                client = AnthropicClient(env_file_path="path/to/.env")
+                client = RawAnthropicClient(env_file_path="path/to/.env")
 
                 # Or passing in an existing client
                 from anthropic import AsyncAnthropic
 
                 anthropic_client = AsyncAnthropic(
                     api_key="your_anthropic_api_key", base_url="https://custom-anthropic-endpoint.com"
                 )
-                client = AnthropicClient(
+                client = RawAnthropicClient(
                     model_id="claude-sonnet-4-5-20250929",
                     anthropic_client=anthropic_client,
                 )
@@ -289,7 +296,7 @@ class MyOptions(AnthropicChatOptions, total=False):
                     my_custom_option: str
 
 
-                client: AnthropicClient[MyOptions] = AnthropicClient(model_id="claude-sonnet-4-5-20250929")
+                client: RawAnthropicClient[MyOptions] = RawAnthropicClient(model_id="claude-sonnet-4-5-20250929")
                 response = await client.get_response("Hello", options={"my_custom_option": "value"})
 
         """
@@ -320,8 +327,6 @@ class MyOptions(AnthropicChatOptions, total=False):
         # Initialize parent
         super().__init__(
             additional_properties=additional_properties,
-            middleware=middleware,
-            function_invocation_configuration=function_invocation_configuration,
         )
 
         # Initialize instance variables
@@ -1376,3 +1381,95 @@ def service_url(self) -> str:
             The service URL for the chat client, or None if not set.
         """
         return str(self.anthropic_client.base_url)
+
+
+class AnthropicClient(
+    FunctionInvocationLayer[AnthropicOptionsT],
+    ChatMiddlewareLayer[AnthropicOptionsT],
+    ChatTelemetryLayer[AnthropicOptionsT],
+    RawAnthropicClient[AnthropicOptionsT],
+    Generic[AnthropicOptionsT],
+):
+    """Anthropic chat client with middleware, telemetry, and function invocation support."""
+
+    def __init__(
+        self,
+        *,
+        api_key: str | None = None,
+        model_id: str | None = None,
+        anthropic_client: AsyncAnthropic | None = None,
+        additional_beta_flags: list[str] | None = None,
+        additional_properties: dict[str, Any] | None = None,
+        middleware: Sequence[ChatAndFunctionMiddlewareTypes] | None = None,
+        function_invocation_configuration: FunctionInvocationConfiguration | None = None,
+        env_file_path: str | None = None,
+        env_file_encoding: str | None = None,
+    ) -> None:
+        """Initialize an Anthropic client.
+
+        Keyword Args:
+            api_key: The Anthropic API key to use for authentication.
+            model_id: The ID of the model to use.
+            anthropic_client: An existing Anthropic client to use. If not provided, one will be created.
+                This can be used to further configure the client before passing it in.
+                For instance if you need to set a different base_url for testing or private deployments.
+            additional_beta_flags: Additional beta flags to enable on the client.
+                Default flags are: "mcp-client-2025-04-04", "code-execution-2025-08-25".
+            additional_properties: Additional properties stored on the client instance.
+            middleware: Optional middleware to apply to the client.
+            function_invocation_configuration: Optional function invocation configuration override.
+            env_file_path: Path to environment file for loading settings.
+            env_file_encoding: Encoding of the environment file.
+
+        Examples:
+            .. code-block:: python
+
+                from agent_framework.anthropic import AnthropicClient
+
+                # Using environment variables
+                # Set ANTHROPIC_API_KEY=your_anthropic_api_key
+                # ANTHROPIC_CHAT_MODEL_ID=claude-sonnet-4-5-20250929
+
+                # Or passing parameters directly
+                client = AnthropicClient(
+                    model_id="claude-sonnet-4-5-20250929",
+                    api_key="your_anthropic_api_key",
+                )
+
+                # Or loading from a .env file
+                client = AnthropicClient(env_file_path="path/to/.env")
+
+                # Or passing in an existing client
+                from anthropic import AsyncAnthropic
+
+                anthropic_client = AsyncAnthropic(
+                    api_key="your_anthropic_api_key", base_url="https://custom-anthropic-endpoint.com"
+                )
+                client = AnthropicClient(
+                    model_id="claude-sonnet-4-5-20250929",
+                    anthropic_client=anthropic_client,
+                )
+
+                # Using custom ChatOptions with type safety:
+                from typing import TypedDict
+                from agent_framework.anthropic import AnthropicChatOptions
+
+
+                class MyOptions(AnthropicChatOptions, total=False):
+                    my_custom_option: str
+
+
+                client: AnthropicClient[MyOptions] = AnthropicClient(model_id="claude-sonnet-4-5-20250929")
+                response = await client.get_response("Hello", options={"my_custom_option": "value"})
+        """
+        super().__init__(
+            api_key=api_key,
+            model_id=model_id,
+            anthropic_client=anthropic_client,
+            additional_beta_flags=additional_beta_flags,
+            additional_properties=additional_properties,
+            middleware=middleware,
+            function_invocation_configuration=function_invocation_configuration,
+            env_file_path=env_file_path,
+            env_file_encoding=env_file_encoding,
+        )

python/packages/anthropic/tests/test_anthropic_client.py

@@ -6,15 +6,18 @@
 
 import pytest
 from agent_framework import (
+    ChatMiddlewareLayer,
     ChatOptions,
     ChatResponseUpdate,
     Content,
+    FunctionInvocationLayer,
     Message,
     SupportsChatGetResponse,
     tool,
 )
 from agent_framework._settings import load_settings
 from agent_framework._tools import SHELL_TOOL_KIND_VALUE
+from agent_framework.observability import ChatTelemetryLayer
 from anthropic.types.beta import (
     BetaMessage,
     BetaTextBlock,
@@ -23,7 +26,7 @@
 )
 from pydantic import BaseModel, Field
 
-from agent_framework_anthropic import AnthropicClient
+from agent_framework_anthropic import AnthropicClient, RawAnthropicClient
 from agent_framework_anthropic._chat_client import AnthropicSettings
 
 # Test constants
@@ -64,6 +67,8 @@ def create_test_anthropic_client(
     client.additional_beta_flags = []
     client.chat_middleware = []
     client.function_middleware = []
+    client._cached_chat_middleware_pipeline = None
+    client._cached_function_middleware_pipeline = None
     client.function_invocation_configuration = normalize_function_invocation_configuration(None)
 
     return client
@@ -117,6 +122,19 @@ def test_anthropic_client_init_with_client(mock_anthropic_client: MagicMock) ->
     assert isinstance(client, SupportsChatGetResponse)
 
 
+def test_anthropic_client_wraps_raw_client_with_standard_layer_order() -> None:
+    """Test AnthropicClient composes the standard public layer stack around the raw client."""
+    assert issubclass(AnthropicClient, RawAnthropicClient)
+    mro = AnthropicClient.__mro__
+    assert mro.index(FunctionInvocationLayer) < mro.index(ChatMiddlewareLayer)
+    assert mro.index(ChatMiddlewareLayer) < mro.index(ChatTelemetryLayer)
+    assert mro.index(ChatTelemetryLayer) < mro.index(RawAnthropicClient)
+    # RawAnthropicClient must not include the convenience layers
+    assert not issubclass(RawAnthropicClient, FunctionInvocationLayer)
+    assert not issubclass(RawAnthropicClient, ChatMiddlewareLayer)
+    assert not issubclass(RawAnthropicClient, ChatTelemetryLayer)
+
+
 def test_anthropic_client_init_auto_create_client(
     anthropic_unit_test_env: dict[str, str],
 ) -> None:

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

@@ -206,8 +206,8 @@ class AzureAIAgentOptions(ChatOptions, total=False):
 
 
 class AzureAIAgentClient(
-    ChatMiddlewareLayer[AzureAIAgentOptionsT],
     FunctionInvocationLayer[AzureAIAgentOptionsT],
+    ChatMiddlewareLayer[AzureAIAgentOptionsT],
     ChatTelemetryLayer[AzureAIAgentOptionsT],
     BaseChatClient[AzureAIAgentOptionsT],
     Generic[AzureAIAgentOptionsT],

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

@@ -97,9 +97,9 @@ class RawAzureAIClient(RawOpenAIResponsesClient[AzureAIClientOptionsT], Generic[
         you should consider which additional layers to apply. There is a defined ordering that
         you should follow:
 
-        1. **ChatMiddlewareLayer** - Should be applied first as it also prepares function middleware
-        2. **FunctionInvocationLayer** - Handles tool/function calling loop
-        3. **ChatTelemetryLayer** - Must be inside the function calling loop for correct per-call telemetry
+        1. **FunctionInvocationLayer** - Owns the tool/function calling loop and routes function middleware
+        2. **ChatMiddlewareLayer** - Applies chat middleware per model call and stays outside telemetry
+        3. **ChatTelemetryLayer** - Must stay inside chat middleware for correct per-call telemetry
 
         Use ``AzureAIClient`` instead for a fully-featured client with all layers applied.
     """
@@ -1214,8 +1214,8 @@ def as_agent(
 
 
 class AzureAIClient(
-    ChatMiddlewareLayer[AzureAIClientOptionsT],
     FunctionInvocationLayer[AzureAIClientOptionsT],
+    ChatMiddlewareLayer[AzureAIClientOptionsT],
     ChatTelemetryLayer[AzureAIClientOptionsT],
     RawAzureAIClient[AzureAIClientOptionsT],
     Generic[AzureAIClientOptionsT],

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

@@ -87,6 +87,8 @@ def create_test_azure_ai_chat_client(
     client.middleware = None
     client.chat_middleware = []
     client.function_middleware = []
+    client._cached_chat_middleware_pipeline = None
+    client._cached_function_middleware_pipeline = None
     client.otel_provider_name = "azure.ai"
     client.function_invocation_configuration = {
         "enabled": True,
@@ -151,6 +153,10 @@ def test_azure_ai_chat_client_init_auto_create_client(
     chat_client.agent_name = None
     chat_client.additional_properties = {}
     chat_client.middleware = None
+    chat_client.chat_middleware = []
+    chat_client.function_middleware = []
+    chat_client._cached_chat_middleware_pipeline = None
+    chat_client._cached_function_middleware_pipeline = None
 
     assert chat_client.agents_client is mock_agents_client
     assert chat_client.agent_id is None

python/packages/bedrock/agent_framework_bedrock/_chat_client.py

@@ -216,8 +216,8 @@ class BedrockSettings(TypedDict, total=False):
 
 
 class BedrockChatClient(
-    ChatMiddlewareLayer[BedrockChatOptionsT],
     FunctionInvocationLayer[BedrockChatOptionsT],
+    ChatMiddlewareLayer[BedrockChatOptionsT],
     ChatTelemetryLayer[BedrockChatOptionsT],
     BaseChatClient[BedrockChatOptionsT],
     Generic[BedrockChatOptionsT],

python/packages/core/agent_framework/_clients.py

@@ -966,16 +966,7 @@ def _apply_get_response_docstrings() -> None:
     from .observability import ChatTelemetryLayer
 
     apply_layered_docstring(ChatTelemetryLayer.get_response, BaseChatClient.get_response)
-    apply_layered_docstring(
-        FunctionInvocationLayer.get_response,
-        ChatTelemetryLayer.get_response,
-        extra_keyword_args={
-            "function_middleware": """
-                Optional per-call function middleware.
-                When omitted, middleware configured on the client or forwarded from higher layers is used.
-            """,
-        },
-    )
+    apply_layered_docstring(FunctionInvocationLayer.get_response, ChatTelemetryLayer.get_response)
     apply_layered_docstring(
         ChatMiddlewareLayer.get_response,
         FunctionInvocationLayer.get_response,