feat: fix tests and adapt code for args

src/crewai/tools/structured_tool.py

@@ -152,7 +152,10 @@ class CrewStructuredTool:
                 continue
 
             # Skip **kwargs parameters
-            if param.kind == inspect.Parameter.VAR_KEYWORD:
+            if param.kind in (
+                inspect.Parameter.VAR_KEYWORD,
+                inspect.Parameter.VAR_POSITIONAL,
+            ):
                 continue
 
             # Only validate required parameters without defaults
@@ -214,22 +217,17 @@ class CrewStructuredTool:
                 None, lambda: self.func(**parsed_args, **kwargs)
             )
 
+    def _run(self, *args, **kwargs) -> Any:
+        """Legacy method for compatibility."""
+        # Convert args/kwargs to our expected format
+        input_dict = dict(zip(self.args_schema.model_fields.keys(), args))
+        input_dict.update(kwargs)
+        return self.invoke(input_dict)
+
     def invoke(
-        self,
+        self, input: Union[str, dict], config: Optional[dict] = None, **kwargs: Any
-        input: Union[str, dict],
-        config: Optional[dict] = None,
-        **kwargs: Any,
     ) -> Any:
-        """Synchronously invoke the tool.
+        """Main method for tool execution."""
-
-        Args:
-            input: The input arguments
-            config: Optional configuration
-            **kwargs: Additional keyword arguments
-
-        Returns:
-            The result of the tool execution
-        """
         parsed_args = self._parse_args(input)
         return self.func(**parsed_args, **kwargs)
 

tests/tools/test_base_tool.py

@@ -1,4 +1,5 @@
 from typing import Callable
+
 from crewai.tools import BaseTool, tool
 
 
@@ -21,8 +22,7 @@ def test_creating_a_tool_using_annotation():
         my_tool.func("What is the meaning of life?") == "What is the meaning of life?"
     )
 
-    # Assert the langchain tool conversion worked as expected
+    converted_tool = my_tool.to_structured_tool()
-    converted_tool = my_tool.to_langchain()
     assert converted_tool.name == "Name of my tool"
 
     assert (
@@ -41,9 +41,7 @@ def test_creating_a_tool_using_annotation():
 def test_creating_a_tool_using_baseclass():
     class MyCustomTool(BaseTool):
         name: str = "Name of my tool"
-        description: str = (
+        description: str = "Clear description for what this tool is useful for, you agent will need this information to use it."
-            "Clear description for what this tool is useful for, you agent will need this information to use it."
-        )
 
         def _run(self, question: str) -> str:
             return question
@@ -61,8 +59,7 @@ def test_creating_a_tool_using_baseclass():
     }
     assert my_tool.run("What is the meaning of life?") == "What is the meaning of life?"
 
-    # Assert the langchain tool conversion worked as expected
+    converted_tool = my_tool.to_structured_tool()
-    converted_tool = my_tool.to_langchain()
     assert converted_tool.name == "Name of my tool"
 
     assert (
@@ -73,7 +70,7 @@ def test_creating_a_tool_using_baseclass():
         "question": {"title": "Question", "type": "string"}
     }
     assert (
-        converted_tool.run("What is the meaning of life?")
+        converted_tool._run("What is the meaning of life?")
         == "What is the meaning of life?"
     )
 
@@ -81,9 +78,7 @@ def test_creating_a_tool_using_baseclass():
 def test_setting_cache_function():
     class MyCustomTool(BaseTool):
         name: str = "Name of my tool"
-        description: str = (
+        description: str = "Clear description for what this tool is useful for, you agent will need this information to use it."
-            "Clear description for what this tool is useful for, you agent will need this information to use it."
-        )
         cache_function: Callable = lambda: False
 
         def _run(self, question: str) -> str:
@@ -97,9 +92,7 @@ def test_setting_cache_function():
 def test_default_cache_function_is_true():
     class MyCustomTool(BaseTool):
         name: str = "Name of my tool"
-        description: str = (
+        description: str = "Clear description for what this tool is useful for, you agent will need this information to use it."
-            "Clear description for what this tool is useful for, you agent will need this information to use it."
-        )
 
         def _run(self, question: str) -> str:
             return question