refactor: refactor and refine LangChainTool

PiperOrigin-RevId: 760726719

src/google/adk/tools/langchain_tool.py

@@ -13,10 +13,12 @@
 # limitations under the License.
 
 from typing import Any
-from typing import Callable
+from typing import Optional
+from typing import Union
 
 from google.genai import types
-from pydantic import model_validator
+from langchain.agents import Tool
+from langchain_core.tools import BaseTool
 from typing_extensions import override
 
 from . import _automatic_function_calling_util
@@ -24,63 +26,108 @@ from .function_tool import FunctionTool
 
 
 class LangchainTool(FunctionTool):
-  """Use this class to wrap a langchain tool.
+  """Adapter class that wraps a Langchain tool for use with ADK.
 
-  If the original tool name and description are not suitable, you can override
-  them in the constructor.
+  This adapter converts Langchain tools into a format compatible with Google's
+  generative AI function calling interface. It preserves the tool's name,
+  description, and functionality while adapting its schema.
+
+  The original tool's name and description can be overridden if needed.
+
+  Args:
+      tool: A Langchain tool to wrap (BaseTool or a tool with a .run method)
+      name: Optional override for the tool's name
+      description: Optional override for the tool's description
+
+  Examples:
+      ```python
+      from langchain.tools import DuckDuckGoSearchTool
+      from google.genai.tools import LangchainTool
+
+      search_tool = DuckDuckGoSearchTool()
+      wrapped_tool = LangchainTool(search_tool)
+      ```
   """
 
-  tool: Any
+  _langchain_tool: Union[BaseTool, object]
   """The wrapped langchain tool."""
 
-  def __init__(self, tool: Any):
-    super().__init__(tool._run)
-    self.tool = tool
-    if tool.name:
-      self.name = tool.name
-    if tool.description:
-      self.description = tool.description
+  def __init__(
+      self,
+      tool: Union[BaseTool, object],
+      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")
 
-  @model_validator(mode='before')
-  @classmethod
-  def populate_name(cls, data: Any) -> Any:
-    # Override this to not use function's signature name as it's
-    # mostly "run" or "invoke" for thir-party tools.
-    return data
+    # Determine which function to use
+    func = tool._run if hasattr(tool, '_run') else tool.run
+    super().__init__(func)
+
+    self._langchain_tool = tool
+
+    # Set name: priority is 1) explicitly provided name, 2) tool's name, 3) default
+    if name is not None:
+      self.name = name
+    elif hasattr(tool, 'name') and tool.name:
+      self.name = tool.name
+    # else: keep default from FunctionTool
+
+    # Set description: similar priority
+    if description is not None:
+      self.description = description
+    elif hasattr(tool, 'description') and tool.description:
+      self.description = tool.description
+    # else: keep default from FunctionTool
 
   @override
   def _get_declaration(self) -> types.FunctionDeclaration:
-    """Build the function declaration for the tool."""
-    from langchain.agents import Tool
-    from langchain_core.tools import BaseTool
+    """Build the function declaration for the tool.
+
+    Returns:
+        A FunctionDeclaration object that describes the tool's interface.
+
+    Raises:
+        ValueError: If the tool schema cannot be correctly parsed.
+    """
+    try:
+      # There are two types of tools:
+      # 1. BaseTool: the tool is defined in langchain_core.tools.
+      # 2. Other tools: the tool doesn't inherit any class but follow some
+      #    conventions, like having a "run" method.
+      # Handle BaseTool type (preferred Langchain approach)
+      if isinstance(self._langchain_tool, BaseTool):
+        tool_wrapper = Tool(
+            name=self.name,
+            func=self.func,
+            description=self.description,
+        )
+
+        # Add schema if available
+        if (
+            hasattr(self._langchain_tool, 'args_schema')
+            and self._langchain_tool.args_schema
+        ):
+          tool_wrapper.args_schema = self._langchain_tool.args_schema
+
+        return _automatic_function_calling_util.build_function_declaration_for_langchain(
+            False,
+            self.name,
+            self.description,
+            tool_wrapper.func,
+            getattr(tool_wrapper, 'args', None),
+        )
 
-    # There are two types of tools:
-    # 1. BaseTool: the tool is defined in langchain.tools.
-    # 2. Other tools: the tool doesn't inherit any class but follow some
-    #    conventions, like having a "run" method.
-    if isinstance(self.tool, BaseTool):
-      tool_wrapper = Tool(
-          name=self.name,
-          func=self.func,
-          description=self.description,
-      )
-      if self.tool.args_schema:
-        tool_wrapper.args_schema = self.tool.args_schema
-      function_declaration = _automatic_function_calling_util.build_function_declaration_for_langchain(
-          False,
-          self.name,
-          self.description,
-          tool_wrapper.func,
-          tool_wrapper.args,
-      )
-      return function_declaration
-    else:
       # Need to provide a way to override the function names and descriptions
       # as the original function names are mostly ".run" and the descriptions
-      # may not meet users' needs.
-      function_declaration = (
-          _automatic_function_calling_util.build_function_declaration(
-              func=self.tool.run,
-          )
+      # may not meet users' needs
+      return _automatic_function_calling_util.build_function_declaration(
+          func=self._langchain_tool.run,
       )
-      return function_declaration
+
+    except Exception as e:
+      raise ValueError(
+          f'Failed to build function declaration for Langchain tool: {e}'
+      ) from e