Python: fix: honor include_in_function_choices in Anthropic, Bedrock, Google AI, and Vertex AI tool formatters

python/semantic_kernel/agents/bedrock/action_group_utils.py

@@ -29,6 +29,7 @@ def kernel_function_metadata_to_bedrock_function_schema(function_metadata: Kerne
         "parameters": {
             parameter.name: kernel_function_parameter_to_bedrock_function_parameter(parameter)
             for parameter in function_metadata.parameters
+            if parameter.include_in_function_choices
         },
         # This field controls whether user confirmation is required to invoke the function.
         # If this is set to "ENABLED", the user will be prompted to confirm the function invocation.

python/semantic_kernel/connectors/ai/anthropic/services/utils.py

@@ -151,7 +151,7 @@ def kernel_function_metadata_to_function_call_format(metadata: KernelFunctionMet
         "description": metadata.description or "",
         "input_schema": {
             "type": "object",
-            "properties": {p.name: p.schema_data for p in metadata.parameters},
-            "required": [p.name for p in metadata.parameters if p.is_required],
+            "properties": {p.name: p.schema_data for p in metadata.parameters if p.include_in_function_choices},
+            "required": [p.name for p in metadata.parameters if p.is_required and p.include_in_function_choices],
         },
     }

python/semantic_kernel/connectors/ai/bedrock/services/model_provider/utils.py

@@ -196,8 +196,14 @@ def update_settings_from_function_choice_configuration(
                     "inputSchema": {
                         "json": {
                             "type": "object",
-                            "properties": {param.name: param.schema_data for param in function.parameters},
-                            "required": [p.name for p in function.parameters if p.is_required],
+                            "properties": {
+                                param.name: param.schema_data
+                                for param in function.parameters
+                                if param.include_in_function_choices
+                            },
+                            "required": [
+                                p.name for p in function.parameters if p.is_required and p.include_in_function_choices
+                            ],
                         }
                     },
                 }

python/semantic_kernel/connectors/ai/google/google_ai/services/utils.py

@@ -149,17 +149,18 @@ def format_tool_message(message: ChatMessageContent) -> list[Part]:
 def kernel_function_metadata_to_google_ai_function_call_format(metadata: KernelFunctionMetadata) -> dict[str, Any]:
     """Convert the kernel function metadata to function calling format."""
     parameters: dict[str, Any] | None = None
-    if metadata.parameters:
+    visible_parameters = [p for p in metadata.parameters if p.include_in_function_choices]
+    if visible_parameters:
         properties = {}
-        for param in metadata.parameters:
+        for param in visible_parameters:
             if param.name is None:
                 continue
             prop_schema = sanitize_schema_for_google_ai(param.schema_data) if param.schema_data else param.schema_data
             properties[param.name] = prop_schema
         parameters = {
             "type": "object",
             "properties": properties,
-            "required": [p.name for p in metadata.parameters if p.is_required and p.name is not None],
+            "required": [p.name for p in visible_parameters if p.is_required and p.name is not None],
         }
     return {
         "name": metadata.custom_fully_qualified_name(GEMINI_FUNCTION_NAME_SEPARATOR),

python/semantic_kernel/connectors/ai/google/vertex_ai/services/utils.py

@@ -139,8 +139,9 @@ def format_tool_message(message: ChatMessageContent) -> list[Part]:
 def kernel_function_metadata_to_vertex_ai_function_call_format(metadata: KernelFunctionMetadata) -> FunctionDeclaration:
     """Convert the kernel function metadata to function calling format."""
     properties: dict[str, Any] = {}
-    if metadata.parameters:
-        for param in metadata.parameters:
+    visible_parameters = [p for p in metadata.parameters if p.include_in_function_choices]
+    if visible_parameters:
+        for param in visible_parameters:
             if param.name is None:
                 continue
             prop_schema = sanitize_schema_for_google_ai(param.schema_data) if param.schema_data else param.schema_data
@@ -151,7 +152,7 @@ def kernel_function_metadata_to_vertex_ai_function_call_format(metadata: KernelF
         parameters={
             "type": "object",
             "properties": properties,
-            "required": [p.name for p in metadata.parameters if p.is_required and p.name is not None],
+            "required": [p.name for p in visible_parameters if p.is_required and p.name is not None],
         },
     )
 

python/tests/unit/agents/bedrock_agent/test_action_group_utils.py

@@ -4,13 +4,16 @@
 
 from semantic_kernel.agents.bedrock.action_group_utils import (
     BEDROCK_FUNCTION_ALLOWED_PARAMETER_TYPES,
+    kernel_function_metadata_to_bedrock_function_schema,
     kernel_function_parameter_type_to_bedrock_function_parameter_type,
     kernel_function_to_bedrock_function_schema,
     parse_function_result_contents,
     parse_return_control_payload,
 )
 from semantic_kernel.connectors.ai.function_choice_behavior import FunctionChoiceBehavior
 from semantic_kernel.contents.function_result_content import FunctionResultContent
+from semantic_kernel.functions.kernel_function_metadata import KernelFunctionMetadata
+from semantic_kernel.functions.kernel_parameter_metadata import KernelParameterMetadata
 from semantic_kernel.kernel import Kernel
 
 
@@ -35,6 +38,27 @@ def test_kernel_function_to_bedrock_function_schema(kernel_with_function: Kernel
     }
 
 
+def test_kernel_function_metadata_to_bedrock_function_schema_skips_params_excluded_from_function_choices():
+    metadata = KernelFunctionMetadata(
+        name="lookup",
+        description="Look up a user",
+        is_prompt=False,
+        parameters=[
+            KernelParameterMetadata(name="query", schema_data={"type": "string"}, is_required=True),
+            KernelParameterMetadata(
+                name="token",
+                schema_data={"type": "string"},
+                is_required=True,
+                include_in_function_choices=False,
+            ),
+        ],
+    )
+
+    result = kernel_function_metadata_to_bedrock_function_schema(metadata)
+
+    assert list(result["parameters"]) == ["query"]
+
+
 def test_kernel_function_parameter_type_to_bedrock_function_parameter_type():
     # Test the conversion of kernel function parameter type to bedrock function parameter type
     schema_data = {"type": "string"}

python/tests/unit/connectors/ai/anthropic/services/test_anthropic_utils.py

@@ -0,0 +1,30 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+from semantic_kernel.connectors.ai.anthropic.services.utils import kernel_function_metadata_to_function_call_format
+from semantic_kernel.functions.kernel_function_metadata import KernelFunctionMetadata
+from semantic_kernel.functions.kernel_parameter_metadata import KernelParameterMetadata
+
+
+def test_function_call_format_skips_params_excluded_from_function_choices() -> None:
+    metadata = KernelFunctionMetadata(
+        name="lookup",
+        description="Look up a user",
+        is_prompt=False,
+        parameters=[
+            KernelParameterMetadata(
+                name="query", description="What to look up", schema_data={"type": "string"}, is_required=True
+            ),
+            KernelParameterMetadata(
+                name="token",
+                description="Internal",
+                schema_data={"type": "string"},
+                is_required=True,
+                include_in_function_choices=False,
+            ),
+        ],
+    )
+
+    result = kernel_function_metadata_to_function_call_format(metadata)
+
+    assert list(result["input_schema"]["properties"]) == ["query"]
+    assert result["input_schema"]["required"] == ["query"]

python/tests/unit/connectors/ai/bedrock/services/test_bedrock_model_provider_utils.py

@@ -25,6 +25,8 @@
 from semantic_kernel.contents.utils.author_role import AuthorRole
 from semantic_kernel.contents.utils.finish_reason import FinishReason
 from semantic_kernel.exceptions.service_exceptions import ServiceInvalidRequestError
+from semantic_kernel.functions.kernel_function_metadata import KernelFunctionMetadata
+from semantic_kernel.functions.kernel_parameter_metadata import KernelParameterMetadata
 from semantic_kernel.kernel import Kernel
 
 
@@ -441,3 +443,32 @@ def test_update_settings_from_function_choice_configuration_required_one(mock_be
     assert mock_bedrock_settings.tool_choice == {"tool": {"name": "plugin-function"}}
     assert len(mock_bedrock_settings.tools) == 1
     assert mock_bedrock_settings.tools[0]["toolSpec"]["name"] == "plugin-function"
+
+
+def test_update_settings_from_function_choice_configuration_skips_params_excluded_from_function_choices() -> None:
+    metadata = KernelFunctionMetadata(
+        name="lookup",
+        description="Look up a user",
+        is_prompt=False,
+        parameters=[
+            KernelParameterMetadata(
+                name="query", description="What to look up", schema_data={"type": "string"}, is_required=True
+            ),
+            KernelParameterMetadata(
+                name="token",
+                description="Internal",
+                schema_data={"type": "string"},
+                is_required=True,
+                include_in_function_choices=False,
+            ),
+        ],
+    )
+    config = FunctionCallChoiceConfiguration()
+    config.available_functions = [metadata]
+    settings = BedrockChatPromptExecutionSettings()
+
+    update_settings_from_function_choice_configuration(config, settings, FunctionChoiceType.AUTO)
+
+    schema = settings.tools[0]["toolSpec"]["inputSchema"]["json"]
+    assert list(schema["properties"]) == ["query"]
+    assert schema["required"] == ["query"]

python/tests/unit/connectors/ai/google/google_ai/services/test_google_ai_utils.py

@@ -199,3 +199,39 @@ def test_google_ai_function_call_format_empty_parameters() -> None:
     )
     result = kernel_function_metadata_to_google_ai_function_call_format(metadata)
     assert result["parameters"] is None
+
+
+def test_google_ai_function_call_format_skips_params_excluded_from_function_choices() -> None:
+    metadata = KernelFunctionMetadata(
+        name="lookup",
+        description="Look up a user",
+        is_prompt=False,
+        parameters=[
+            KernelParameterMetadata(
+                name="query", description="What to look up", schema_data={"type": "string"}, is_required=True
+            ),
+            KernelParameterMetadata(
+                name="token",
+                description="Internal",
+                schema_data={"type": "string"},
+                is_required=True,
+                include_in_function_choices=False,
+            ),
+        ],
+    )
+    result = kernel_function_metadata_to_google_ai_function_call_format(metadata)
+    assert list(result["parameters"]["properties"]) == ["query"]
+    assert result["parameters"]["required"] == ["query"]
+
+
+def test_google_ai_function_call_format_all_params_excluded_gives_no_parameters() -> None:
+    metadata = KernelFunctionMetadata(
+        name="hidden_only",
+        description="Only hidden parameters",
+        is_prompt=False,
+        parameters=[
+            KernelParameterMetadata(name="token", schema_data={"type": "string"}, include_in_function_choices=False),
+        ],
+    )
+    result = kernel_function_metadata_to_google_ai_function_call_format(metadata)
+    assert result["parameters"] is None

python/tests/unit/connectors/ai/google/vertex_ai/services/test_vertex_ai_utils.py

@@ -197,3 +197,27 @@ def test_vertex_ai_function_call_format_empty_parameters() -> None:
     )
     result = kernel_function_metadata_to_vertex_ai_function_call_format(metadata)
     assert isinstance(result, FunctionDeclaration)
+
+
+def test_vertex_ai_function_call_format_skips_params_excluded_from_function_choices() -> None:
+    metadata = KernelFunctionMetadata(
+        name="lookup",
+        description="Look up a user",
+        is_prompt=False,
+        parameters=[
+            KernelParameterMetadata(
+                name="query", description="What to look up", schema_data={"type": "string"}, is_required=True
+            ),
+            KernelParameterMetadata(
+                name="token",
+                description="Internal",
+                schema_data={"type": "string"},
+                is_required=True,
+                include_in_function_choices=False,
+            ),
+        ],
+    )
+    result = kernel_function_metadata_to_vertex_ai_function_call_format(metadata)
+    schema = type(result).to_dict(result)["parameters"]
+    assert list(schema["properties"]) == ["query"]
+    assert schema["required"] == ["query"]