first commit

agent_dhal/agentdhal_extensions/tools/semantic_kernel/__init__.py

@@ -0,0 +1,6 @@
+from ._kernel_function_from_tool import KernelFunctionFromTool, KernelFunctionFromToolSchema
+
+__all__ = [
+    "KernelFunctionFromTool",
+    "KernelFunctionFromToolSchema",
+]

agent_dhal/agentdhal_extensions/tools/semantic_kernel/_kernel_function_from_tool.py

@@ -0,0 +1,94 @@
+from typing import Any, TypeVar
+
+from agentdhal_core import CancellationToken
+from agentdhal_core.tools import BaseTool, ToolSchema
+from pydantic import BaseModel
+
+from semantic_kernel.functions import KernelFunctionFromMethod, KernelFunctionFromPrompt, kernel_function
+from semantic_kernel.functions.kernel_parameter_metadata import KernelParameterMetadata
+from semantic_kernel.prompt_template.input_variable import InputVariable
+from semantic_kernel.prompt_template.prompt_template_config import PromptTemplateConfig
+
+InputT = TypeVar("InputT", bound=BaseModel)
+OutputT = TypeVar("OutputT", bound=BaseModel)
+
+
+class KernelFunctionFromTool(KernelFunctionFromMethod):
+    def __init__(self, tool: BaseTool[InputT, OutputT], plugin_name: str | None = None):
+        # Get the pydantic model types from the tool
+        args_type = tool.args_type()
+        return_type = tool.return_type()
+
+        # 1) Define an async function that calls the tool
+        @kernel_function(name=tool.name, description=tool.description)
+        async def tool_method(**kwargs: dict[str, Any]) -> Any:
+            return await tool.run_json(kwargs, cancellation_token=CancellationToken())
+
+        # Parse schema for parameters
+        parameters_meta: list[KernelParameterMetadata] = []
+        properties = tool.schema.get("parameters", {}).get("properties", {})
+
+        # Get the field types from the pydantic model
+        field_types = args_type.model_fields
+
+        for prop_name, prop_info in properties.items():
+            assert prop_name in field_types, f"Property {prop_name} not found in Tool {tool.name}"
+            assert isinstance(prop_info, dict), f"Property {prop_name} is not a dict in Tool {tool.name}"
+
+            # Get the actual type from the pydantic model field
+            field_type = field_types[prop_name]
+            parameters_meta.append(
+                KernelParameterMetadata(
+                    name=prop_name,
+                    description=field_type.description or "",
+                    default_value=field_type.get_default(),
+                    type=prop_info.get("type", "string"),  # type: ignore
+                    type_object=field_type.annotation,
+                    is_required=field_type.is_required(),
+                )
+            )
+
+        # Create return parameter metadata
+        return_parameter = KernelParameterMetadata(
+            name="return",
+            description=f"Result from '{tool.name}' tool",
+            default_value=None,
+            type="object" if issubclass(return_type, BaseModel) else "string",
+            type_object=return_type,
+            is_required=True,
+        )
+
+        # Initialize the parent class
+        super().__init__(
+            method=tool_method,
+            plugin_name=plugin_name,
+            parameters=parameters_meta,
+            return_parameter=return_parameter,
+            additional_metadata=None,
+        )
+
+        self._tool = tool
+
+
+class KernelFunctionFromToolSchema(KernelFunctionFromPrompt):
+    def __init__(self, tool_schema: ToolSchema, plugin_name: str | None = None):
+        properties = tool_schema.get("parameters", {}).get("properties", {})
+        required = properties.get("required", [])
+
+        prompt_template_config = PromptTemplateConfig(
+            name=tool_schema.get("name", ""),
+            description=tool_schema.get("description", ""),
+            input_variables=[
+                InputVariable(
+                    name=prop_name, description=prop_info.get("description", ""), is_required=prop_name in required
+                )
+                for prop_name, prop_info in properties.items()
+            ],
+        )
+
+        super().__init__(
+            function_name=tool_schema.get("name", ""),
+            plugin_name=plugin_name,
+            description=tool_schema.get("description", ""),
+            prompt_template_config=prompt_template_config,
+        )