Graph II: Multiple Inputs Graph

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Objectives

1. Define a more complex AgentState containing multiple fields.
2. Create a processing node that performs operations on list data and string data.
3. Build and compile a LangGraph with multiple fields in its state.
4. Invoke the graph with structured inputs and retrieve the computed result.

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Graph II: Multiple Inputs Graph

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Goal

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Sample Input

{"values": [1, 2, 3, 4], "name": "Sanjay"}

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Sample Output

{"values": [1, 2, 3, 4], "name": "Sanjay", "result": "Hi there Sanjay! Your sum = 10"}

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Plan

1. Define the state schema (AgentState) containing values (list of integers), name (str), and result (str).
2. Define the node function process_values that extracts the fields, calculates the sum, and formats the personalized greeting.
3. Build and compile the graph.
4. Invoke the graph with multiple input values.

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Code Implementation

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1. Define the State Schema

from typing import TypedDict

class AgentState(TypedDict):
    values: list[int]
    name: str
    result: str

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2. Define the Node Function

def process_values(state: AgentState) -> AgentState:
    state["result"] = f"Hi there {state['name']}! Your sum = {sum(state['values'])}"
    return state

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3. Create the Graph

from langgraph.graph import StateGraph

graph = StateGraph(AgentState)
graph.add_node("processor", process_values)

graph.set_entry_point("processor")
graph.set_finish_point("processor")

app = graph.compile()

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4. Invoke the Graph

answers = app.invoke({"values": [1, 2, 3, 4], "name": "Sanjay"})
print(answers["result"])
# Output: Hi there Sanjay! Your sum = 10

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Exercise: Calculator Agent 🏆

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Goal

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Sample Input

{
    "name": "Vikram",
    "values": [1, 2, 3, 4],
    "operation": "*"
}

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Sample Output

"Hi Vikram, your answer is: 24"

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Plan

1. Define the state schema with name, values, operation, and result keys.
2. Write a node function that evaluates the operation field and calculates either the sum or product of the list.
3. Build, compile, and run the graph.

from typing import TypedDict
from langgraph.graph import StateGraph

# 1. State Schema
class AgentState(TypedDict):
    name: str
    values: list[int]
    operation: str
    result: str

# 2. Node Function
def calculate_node(state: AgentState) -> AgentState:
    name = state["name"]
    values = state["values"]
    op = state["operation"]
    
    if op == "+":
        ans = sum(values)
    elif op == "*":
        ans = 1
        for v in values:
            ans *= v
    else:
        ans = 0
        
    state["result"] = f"Hi {name}, your answer is: {ans}"
    return state

# 3. Create Graph
graph = StateGraph(AgentState)
graph.add_node("calculator", calculate_node)
graph.set_entry_point("calculator")
graph.set_finish_point("calculator")

# 4. Compile and Run
app = graph.compile()
output = app.invoke({
    "name": "Vikram",
    "values": [1, 2, 3, 4],
    "operation": "*"
})
print(output["result"])

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Practice & Exercises