Fix more type issues

src/crewai/agents/langchain_agent_adapter.py

@@ -280,8 +280,12 @@ class LangChainAgentAdapter(BaseAgent):
                 "LangGraph library not found. Please run `uv add langgraph` to add LangGraph support."
             ) from e
 
-        # Ensure raw_tools is always a list, even if tools and self.tools are None.
-        raw_tools = tools or self.tools or []
+        # Ensure raw_tools is always a list.
+        raw_tools: List[Any] = (
+            tools
+            if tools is not None
+            else (self.tools if self.tools is not None else [])
+        )
         # Fallback: if raw_tools is still empty, try to extract them from the wrapped langchain agent.
         if not raw_tools:
             if hasattr(self.langchain_agent, "agent") and hasattr(
@@ -293,14 +297,14 @@ class LangChainAgentAdapter(BaseAgent):
 
         used_tools = []
         try:
-            # Import the CrewAI Tool class.
-            from crewai.tools.base_tool import Tool as CrewTool
+            # Import the CrewAI Tool class and name it differently to avoid type assignment issues.
+            from crewai.tools.base_tool import Tool as CrewToolClass
         except ImportError:
-            CrewTool: Optional[Type[BaseTool]] = None  # Explicitly annotate as Optional
+            CrewToolClass = None  # No type annotation here
 
         for tool in raw_tools:
             # If the tool is a CrewAI Tool, convert it to a LangChain compatible tool.
-            if CrewTool is not None and isinstance(tool, CrewTool):
+            if CrewToolClass is not None and isinstance(tool, CrewToolClass):
                 used_tools.append(tool.to_langchain())
             else:
                 used_tools.append(tool)

src/crewai/tools/base_tool.py

@@ -19,6 +19,13 @@ from crewai.tools.structured_tool import CrewStructuredTool
 warnings.filterwarnings("ignore", category=PydanticDeprecatedSince20)
 
 
+# Define a helper function with an explicit signature
+def default_cache_function(
+    _args: Optional[Any] = None, _result: Optional[Any] = None
+) -> bool:
+    return True
+
+
 class BaseTool(BaseModel, ABC):
     class _ArgsSchemaPlaceholder(PydanticBaseModel):
         pass
@@ -37,9 +44,9 @@ class BaseTool(BaseModel, ABC):
     description_updated: bool = False
     """Flag to check if the description has been updated."""
     cache_function: Callable[[Optional[Any], Optional[Any]], bool] = (
-        lambda _args=None, _result=None: True
+        default_cache_function
     )
-    """Function that will be used to determine if the tool should be cached, should return a boolean. If None, the tool will be cached."""
+    """Function used to determine if the tool should be cached."""
     result_as_answer: bool = False
     """Flag to check if the tool should be the final agent answer."""