More type fixues

src/crewai/agents/langchain_agent_adapter.py

@@ -286,7 +286,7 @@ class LangChainAgentAdapter(BaseAgent):
             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.
+        # 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(
                 self.langchain_agent.agent, "tools"
@@ -297,14 +297,14 @@ class LangChainAgentAdapter(BaseAgent):
 
         used_tools = []
         try:
-            # Import the CrewAI Tool class and name it differently to avoid type assignment issues.
-            from crewai.tools.base_tool import Tool as CrewToolClass
+            # Import the CrewAI Tool class using a local variable name to avoid reassigning the imported type.
+            from crewai.tools.base_tool import Tool as CrewToolLocal
         except ImportError:
-            CrewToolClass = None  # No type annotation here
+            CrewToolLocal = None  # type: Optional[Type[BaseTool]]
 
         for tool in raw_tools:
             # If the tool is a CrewAI Tool, convert it to a LangChain compatible tool.
-            if CrewToolClass is not None and isinstance(tool, CrewToolClass):
+            if CrewToolLocal is not None and isinstance(tool, CrewToolLocal):
                 used_tools.append(tool.to_langchain())
             else:
                 used_tools.append(tool)

src/crewai/tools/base_tool.py

@@ -189,38 +189,13 @@ class BaseTool(BaseModel, ABC):
 
         return origin.__name__
 
-    # def to_langchain(self) -> Any:
-    #     """
-    #     Convert this CrewAI Tool instance into a LangChain-compatible tool.
-    #     Returns a concrete subclass of LangChain's BaseTool.
-    #     """
-    #     try:
-    #         from langchain_core.tools import Tool as LC_Tool
-    #     except ImportError as e:
-    #         raise ImportError(
-    #             "LangChain library not found. Please run `uv add langchain` to add LangChain support."
-    #         ) from e
-
-    #     # Capture the function in a local variable to avoid referencing None.
-    #     tool_func = self.func
-
-    #     class ConcreteLangChainTool(LC_Tool):
-    #         def _run(self, *args, **kwargs):
-    #             return tool_func(*args, **kwargs)
-
-    #     # Do not pass callback_manager; let LC_Tool use its default.
-    #     print("Creating concrete langchain tool")
-    #     return ConcreteLangChainTool(
-    #         name=self.name,
-    #         description=self.description,
-    #         func=self._run,
-    #         args_schema=self.args_schema,
-    #     )
-
     @property
     def get(self) -> Callable[[str, Any], Any]:
-        # Returns a callable that looks up attributes on the instance.
-        return lambda key, default=None: getattr(self, key, default)
+        # Instead of an inline lambda, we define a helper function with explicit types.
+        def _getter(key: str, default: Any = None) -> Any:
+            return getattr(self, key, default)
+
+        return _getter
 
 
 class Tool(BaseTool):