diff --git a/langchain/tools/base.py b/langchain/tools/base.py
index c3fab242c9..a8d4c88863 100644
--- a/langchain/tools/base.py
+++ b/langchain/tools/base.py
@@ -82,7 +82,7 @@ def _get_filtered_args(
     """Get the arguments from a function's signature."""
     schema = inferred_model.schema()["properties"]
     valid_keys = signature(func).parameters
-    return {k: schema[k] for k in valid_keys if k != "run_manager"}
+    return {k: schema[k] for k in valid_keys if k not in ("run_manager", "callbacks")}
 
 
 class _SchemaConfig:
@@ -108,6 +108,8 @@ def create_schema_from_function(
     inferred_model = validated.model  # type: ignore
     if "run_manager" in inferred_model.__fields__:
         del inferred_model.__fields__["run_manager"]
+    if "callbacks" in inferred_model.__fields__:
+        del inferred_model.__fields__["callbacks"]
     # Pydantic adds placeholder virtual fields we need to strip
     valid_properties = _get_filtered_args(inferred_model, func)
     return _create_subset_model(
diff --git a/tests/unit_tests/tools/test_base.py b/tests/unit_tests/tools/test_base.py
index e486fcc9d0..eadfbcf97c 100644
--- a/tests/unit_tests/tools/test_base.py
+++ b/tests/unit_tests/tools/test_base.py
@@ -19,6 +19,7 @@ from langchain.tools.base import (
     StructuredTool,
     ToolException,
 )
+from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
 
 
 def test_unnamed_decorator() -> None:
@@ -393,6 +394,64 @@ def test_empty_args_decorator() -> None:
     assert empty_tool_input.run({}) == "the empty result"
 
 
+def test_tool_from_function_with_run_manager() -> None:
+    """Test run of tool when using run_manager."""
+
+    def foo(bar: str, callbacks: Optional[CallbackManagerForToolRun] = None) -> str:
+        """Docstring
+        Args:
+            bar: str
+        """
+        assert callbacks is not None
+        return "foo" + bar
+
+    handler = FakeCallbackHandler()
+    tool = Tool.from_function(foo, name="foo", description="Docstring")
+
+    assert tool.run(tool_input={"bar": "bar"}, run_manager=[handler]) == "foobar"
+    assert tool.run("baz", run_manager=[handler]) == "foobaz"
+
+
+def test_structured_tool_from_function_with_run_manager() -> None:
+    """Test args and schema of structured tool when using callbacks."""
+
+    def foo(
+        bar: int, baz: str, callbacks: Optional[CallbackManagerForToolRun] = None
+    ) -> str:
+        """Docstring
+        Args:
+            bar: int
+            baz: str
+        """
+        assert callbacks is not None
+        return str(bar) + baz
+
+    handler = FakeCallbackHandler()
+    structured_tool = StructuredTool.from_function(foo)
+
+    assert structured_tool.args == {
+        "bar": {"title": "Bar", "type": "integer"},
+        "baz": {"title": "Baz", "type": "string"},
+    }
+
+    assert structured_tool.args_schema.schema() == {
+        "properties": {
+            "bar": {"title": "Bar", "type": "integer"},
+            "baz": {"title": "Baz", "type": "string"},
+        },
+        "title": "fooSchemaSchema",
+        "type": "object",
+        "required": ["bar", "baz"],
+    }
+
+    assert (
+        structured_tool.run(
+            tool_input={"bar": "10", "baz": "baz"}, run_manger=[handler]
+        )
+        == "10baz"
+    )
+
+
 def test_named_tool_decorator() -> None:
     """Test functionality when arguments are provided as input to decorator."""