feat: Enhance LangchainTool to accept more forms of functions

Now the LangchainTool can wrap:

* Langchain StructuredTool (sync and async).
* Langchain @tool (sync and async).

This enhance the flexibility for user and enables async functionalities.

PiperOrigin-RevId: 784728061

Author: hangfei

contributing/samples/langchain_structured_tool_agent/agent.py

@@ -17,20 +17,31 @@
 """
 from google.adk.agents import Agent
 from google.adk.tools.langchain_tool import LangchainTool
+from langchain.tools import tool
 from langchain_core.tools.structured import StructuredTool
 from pydantic import BaseModel
 
 
-def add(x, y) -> int:
+async def add(x, y) -> int:
   return x + y
 
 
+@tool
+def minus(x, y) -> int:
+  return x - y
+
+
 class AddSchema(BaseModel):
   x: int
   y: int
 
 
-test_langchain_tool = StructuredTool.from_function(
+class MinusSchema(BaseModel):
+  x: int
+  y: int
+
+
+test_langchain_add_tool = StructuredTool.from_function(
     add,
     name="add",
     description="Adds two numbers",
@@ -45,5 +56,8 @@ class AddSchema(BaseModel):
         "You are a helpful assistant for user questions, you have access to a"
         " tool that adds two numbers."
     ),
-    tools=[LangchainTool(tool=test_langchain_tool)],
+    tools=[
+        LangchainTool(tool=test_langchain_add_tool),
+        LangchainTool(tool=minus),
+    ],
 )

src/google/adk/tools/langchain_tool.py

@@ -59,15 +59,26 @@ def __init__(
       name: Optional[str] = None,
       description: Optional[str] = None,
   ):
-    # Check if the tool has a 'run' method
     if not hasattr(tool, 'run') and not hasattr(tool, '_run'):
-      raise ValueError("Langchain tool must have a 'run' or '_run' method")
+      raise ValueError(
+          "Tool must be a Langchain tool, have a 'run' or '_run' method."
+      )
 
     # Determine which function to use
     if isinstance(tool, StructuredTool):
       func = tool.func
-    else:
+      # For async tools, func might be None but coroutine exists
+      if func is None and hasattr(tool, 'coroutine') and tool.coroutine:
+        func = tool.coroutine
+    elif hasattr(tool, '_run') or hasattr(tool, 'run'):
       func = tool._run if hasattr(tool, '_run') else tool.run
+    else:
+      raise ValueError(
+          "This is not supported. Tool must be a Langchain tool, have a 'run'"
+          " or '_run' method. The tool is: ",
+          type(tool),
+      )
+
     super().__init__(func)
     # run_manager is a special parameter for langchain tool
     self._ignore_params.append('run_manager')

tests/unittests/tools/test_langchain_tool.py

@@ -0,0 +1,101 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from unittest.mock import MagicMock
+
+from google.adk.tools.langchain_tool import LangchainTool
+from langchain.tools import tool
+from langchain_core.tools.structured import StructuredTool
+from pydantic import BaseModel
+import pytest
+
+
+@tool
+async def async_add_with_annotation(x, y) -> int:
+  """Adds two numbers"""
+  return x + y
+
+
+@tool
+def sync_add_with_annotation(x, y) -> int:
+  """Adds two numbers"""
+  return x + y
+
+
+async def async_add(x, y) -> int:
+  return x + y
+
+
+def sync_add(x, y) -> int:
+  return x + y
+
+
+class AddSchema(BaseModel):
+  x: int
+  y: int
+
+
+test_langchain_async_add_tool = StructuredTool.from_function(
+    async_add,
+    name="add",
+    description="Adds two numbers",
+    args_schema=AddSchema,
+)
+
+test_langchain_sync_add_tool = StructuredTool.from_function(
+    sync_add,
+    name="add",
+    description="Adds two numbers",
+    args_schema=AddSchema,
+)
+
+
+@pytest.mark.asyncio
+async def test_raw_async_function_works():
+  """Test that passing a raw async function to LangchainTool works correctly."""
+  langchain_tool = LangchainTool(tool=test_langchain_async_add_tool)
+  result = await langchain_tool.run_async(
+      args={"x": 1, "y": 3}, tool_context=MagicMock()
+  )
+  assert result == 4
+
+
+@pytest.mark.asyncio
+async def test_raw_sync_function_works():
+  """Test that passing a raw sync function to LangchainTool works correctly."""
+  langchain_tool = LangchainTool(tool=test_langchain_sync_add_tool)
+  result = await langchain_tool.run_async(
+      args={"x": 1, "y": 3}, tool_context=MagicMock()
+  )
+  assert result == 4
+
+
+@pytest.mark.asyncio
+async def test_raw_async_function_with_annotation_works():
+  """Test that passing a raw async function to LangchainTool works correctly."""
+  langchain_tool = LangchainTool(tool=async_add_with_annotation)
+  result = await langchain_tool.run_async(
+      args={"x": 1, "y": 3}, tool_context=MagicMock()
+  )
+  assert result == 4
+
+
+@pytest.mark.asyncio
+async def test_raw_sync_function_with_annotation_works():
+  """Test that passing a raw sync function to LangchainTool works correctly."""
+  langchain_tool = LangchainTool(tool=sync_add_with_annotation)
+  result = await langchain_tool.run_async(
+      args={"x": 1, "y": 3}, tool_context=MagicMock()
+  )
+  assert result == 4