[LangGraph] Router

Tool calls without Router

from IPython.display import Image, display
from langgraph.graph import StateGraph, START, END

from langchain_openai import ChatOpenAI

def multiply(a: int, b: int) -> int:
    """Multiply a and b.

    Args:
        a: first int
        b: second int
    """
    return a * b

llm = ChatOpenAI(model="gpt-4o")
llm_with_tools = llm.bind_tools([multiply])

# State
class MessagesState(MessagesState):
	# Add any keys needed beyond messages, which is pre-built
    pass

# Node
def tool_calling_llm(state: MessagesState):
	return {"messages": [llm_with_tools.invoke(state["messages"])]}

# Build graph
builder = StateGraph(MessagesState)
builder.add_node("tool_calling_llm", tool_calling_llm)

builder.add_edge(START, "tool_calling_llm")
builder.add_edge("tool_calling_llm", END)

graph = builder.compile()

# View
display(Image(graph.get_graph().draw_mermaid_png()))

• If we pass in Hello!, the LLM responds without any tool calls.

Add a node to call our tool (Router)

• (1) Add a node that will call our tool.

• (2) Add a conditional edge that will look at the chat model output, and route to our tool calling node or simply end if no tool call is performed.

• Additionally, We use the built-in ToolNode and simply pass a list of our tools to initialize it.

• We use the built-in tools_condition as our conditional edge.

from IPython.display import Image, display
from langgraph.graph import StateGraph, START, END
from langgraph.graph import MessagesState
from langgraph.prebuilt import ToolNode
from langgraph.prebuilt import tools_condition

# Node
def tool_calling_llm(state: MessagesState):
    return {"messages": [llm_with_tools.invoke(state["messages"])]}

# Build graph

## Add nodes
builder = StateGraph(MessagesState)
builder.add_node("tool_calling_llm", tool_calling_llm)
builder.add_node("tools", ToolNode([multiply]))

## Add edges
builder.add_edge(START, "tool_calling_llm")
builder.add_conditional_edges(
    "tool_calling_llm",
    # If the latest message (result) from assistant is a tool call -> tools_condition routes to tools
    # If the latest message (result) from assistant is a not a tool call -> tools_condition routes to END
    tools_condition,
)
builder.add_edge("tools", END)

## Compile
graph = builder.compile()

# View
display(Image(graph.get_graph().draw_mermaid_png()))

from langchain_core.messages import HumanMessage
messages = [HumanMessage(content="Hello, what is 2 multiplied by 2?")]
messages = graph.invoke({"messages": messages})
for m in messages['messages']:
    m.pretty_print()

= Human Message =

Hello, what is 2 multiplied by 2?
= Ai Message =
Tool Calls:
  multiply (call_4XErrexQcSFn4uFq1SdWq5GJ)
 Call ID: call_4XErrexQcSFn4uFq1SdWq5GJ
  Args:
    a: 2
    b: 2
= Tool Message =
Name: multiply

4