mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-01-07 15:18:29 +00:00
feat: fix tests and adapt code for args
This commit is contained in:
@@ -152,7 +152,10 @@ class CrewStructuredTool:
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continue
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# Skip **kwargs parameters
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if param.kind == inspect.Parameter.VAR_KEYWORD:
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if param.kind in (
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inspect.Parameter.VAR_KEYWORD,
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inspect.Parameter.VAR_POSITIONAL,
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):
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continue
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# Only validate required parameters without defaults
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@@ -214,22 +217,17 @@ class CrewStructuredTool:
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None, lambda: self.func(**parsed_args, **kwargs)
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)
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def _run(self, *args, **kwargs) -> Any:
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"""Legacy method for compatibility."""
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# Convert args/kwargs to our expected format
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input_dict = dict(zip(self.args_schema.model_fields.keys(), args))
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input_dict.update(kwargs)
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return self.invoke(input_dict)
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def invoke(
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self,
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input: Union[str, dict],
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config: Optional[dict] = None,
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**kwargs: Any,
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self, input: Union[str, dict], config: Optional[dict] = None, **kwargs: Any
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) -> Any:
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"""Synchronously invoke the tool.
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Args:
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input: The input arguments
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config: Optional configuration
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**kwargs: Additional keyword arguments
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Returns:
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The result of the tool execution
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"""
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"""Main method for tool execution."""
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parsed_args = self._parse_args(input)
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return self.func(**parsed_args, **kwargs)
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@@ -1,4 +1,5 @@
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from typing import Callable
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from crewai.tools import BaseTool, tool
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@@ -21,8 +22,7 @@ def test_creating_a_tool_using_annotation():
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my_tool.func("What is the meaning of life?") == "What is the meaning of life?"
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)
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# Assert the langchain tool conversion worked as expected
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converted_tool = my_tool.to_langchain()
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converted_tool = my_tool.to_structured_tool()
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assert converted_tool.name == "Name of my tool"
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assert (
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@@ -41,9 +41,7 @@ def test_creating_a_tool_using_annotation():
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def test_creating_a_tool_using_baseclass():
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class MyCustomTool(BaseTool):
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name: str = "Name of my tool"
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description: str = (
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"Clear description for what this tool is useful for, you agent will need this information to use it."
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)
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description: str = "Clear description for what this tool is useful for, you agent will need this information to use it."
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def _run(self, question: str) -> str:
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return question
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@@ -61,8 +59,7 @@ def test_creating_a_tool_using_baseclass():
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}
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assert my_tool.run("What is the meaning of life?") == "What is the meaning of life?"
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# Assert the langchain tool conversion worked as expected
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converted_tool = my_tool.to_langchain()
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converted_tool = my_tool.to_structured_tool()
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assert converted_tool.name == "Name of my tool"
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assert (
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@@ -73,7 +70,7 @@ def test_creating_a_tool_using_baseclass():
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"question": {"title": "Question", "type": "string"}
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}
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assert (
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converted_tool.run("What is the meaning of life?")
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converted_tool._run("What is the meaning of life?")
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== "What is the meaning of life?"
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)
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@@ -81,9 +78,7 @@ def test_creating_a_tool_using_baseclass():
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def test_setting_cache_function():
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class MyCustomTool(BaseTool):
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name: str = "Name of my tool"
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description: str = (
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"Clear description for what this tool is useful for, you agent will need this information to use it."
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)
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description: str = "Clear description for what this tool is useful for, you agent will need this information to use it."
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cache_function: Callable = lambda: False
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def _run(self, question: str) -> str:
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@@ -97,9 +92,7 @@ def test_setting_cache_function():
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def test_default_cache_function_is_true():
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class MyCustomTool(BaseTool):
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name: str = "Name of my tool"
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description: str = (
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"Clear description for what this tool is useful for, you agent will need this information to use it."
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)
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description: str = "Clear description for what this tool is useful for, you agent will need this information to use it."
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def _run(self, question: str) -> str:
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return question
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