LangChain StructuredTool #796 - 10

docs/tools/third-party/index.md

@@ -72,6 +72,92 @@ Here's the full code combining the steps above to create and run an agent using
 --8<-- "examples/python/snippets/tools/third-party/langchain_tavily_search.py"
 ```
 
+### Example: Using LangChain's StructuredTool
+
+from google.adk.agents.llm_agent import Agent  # Import the core Agent class to create the AI assistant
+from google.adk.tools.langchain_tool import LangchainTool  # Import wrapper to make LangChain tools compatible with ADK
+from langchain_core.tools import tool  # Import decorator to quickly turn functions into LangChain tools
+from langchain_core.tools.structured import StructuredTool  # Import class for creating tools with explicit schemas
+from pydantic import BaseModel  # Import BaseModel to define structured data schemas for tool inputs
+
+
+async def add(x: int, y: int) -> int:
+    """
+    An asynchronous function that performs addition.
+    
+    Args:
+        x (int): The first number.
+        y (int): The second number.
+        
+    Returns:
+        int: The sum of x and y.
+    """
+    return x + y  # Returns the result of adding x and y
+
+
+@tool
+def minus(x: int, y: int) -> int:
+    """
+    A synchronous function decorated as a LangChain tool to perform subtraction.
+    
+    The @tool decorator automatically converts this function into a LangChain tool 
+    using the function name as the tool name and this docstring as the description.
+    
+    Args:
+        x (int): The number to subtract from.
+        y (int): The number to be subtracted.
+        
+    Returns:
+        int: The difference between x and y.
+    """
+    return x - y  # Returns the result of subtracting y from x
+
+
+class AddSchema(BaseModel):
+    """
+    Pydantic schema defining the input structure for the 'add' tool.
+    This helps the LLM understand that 'x' and 'y' must be integers.
+    """
+    x: int  # Defines 'x' as a required integer
+    y: int  # Defines 'y' as a required integer
+
+
+class MinusSchema(BaseModel):
+    """
+    Pydantic schema defining the input structure for the 'minus' tool.
+    Ensures the LLM provides the correct types when calling the subtraction tool.
+    """
+    x: int  # Defines 'x' as a required integer
+    y: int  # Defines 'y' as a required integer
+
+
+# Create a formal 'StructuredTool' from the 'add' function.
+# This method is more explicit than the @tool decorator, allowing for manual naming and schema binding.
+test_langchain_add_tool = StructuredTool.from_function(
+    func=add,                          # The actual logic (the add function defined above)
+    name="add",                        # The name the LLM will see for this tool
+    description="Adds two numbers",    # Description used by the LLM to decide when to use this tool
+    args_schema=AddSchema,             # Links the Pydantic schema to validate and describe the inputs
+)
+
+# Initialize the Root Agent (the "brain" of the application).
+root_agent = Agent(
+    model="gemini-2.0-flash-001",      # Specifies the Google Gemini model to power the agent
+    name="test_app",                   # Internal identifier/name for the agent
+    description="A helpful assistant for user questions.",  # High-level description of the agent's purpose
+    instruction=(                      # The system prompt that guides the agent's behavior
+        "You are a helpful assistant for user questions, you have access to a"
+        " tool that adds two numbers."
+    ),
+    tools=[                            # List of tools the agent is allowed to use
+        # Wraps the StructuredTool 'add' into the ADK format
+        LangchainTool(tool=test_langchain_add_tool), 
+        # Wraps the decorated '@tool' function 'minus' into the ADK format
+        LangchainTool(tool=minus),
+    ],
+)
+
+
 ## 2. Using CrewAI tools
 
 ADK provides the `CrewaiTool` wrapper to integrate tools from the CrewAI library.