How to deploy a LangGraph agent to production in 5 minutes

import os

from langchain_core.tools import tool
from langchain_google_genai import ChatGoogleGenerativeAI
from langgraph.graph import MessagesState, START, StateGraph
from langgraph.prebuilt import tools_condition


@tool
def add(a: float, b: float) -> float:
    """Add two numbers together."""
    return a + b


@tool
def multiply(a: float, b: float) -> float:
    """Multiply two numbers together."""
    return a * b


model = ChatGoogleGenerativeAI(
    model="gemini-2.5-flash",
    google_api_key=os.getenv("GEMINI_API_KEY"),
)

tools = [add, multiply]


async def call_model(state: MessagesState):
    model_with_tools = model.bind_tools(tools)
    response = await model_with_tools.ainvoke(state["messages"])
    return {"messages": [response]}


async def call_tools(state: MessagesState):
    from langchain_core.messages import ToolMessage

    tools_by_name = {t.name: t for t in tools}
    last_message = state["messages"][-1]
    results = []
    for tool_call in last_message.tool_calls:
        t = tools_by_name[tool_call["name"]]
        result = await t.ainvoke(tool_call["args"])
        results.append(
            ToolMessage(
                content=str(result),
                tool_call_id=tool_call["id"],
                name=tool_call["name"],
            )
        )
    return {"messages": results}


workflow = StateGraph(MessagesState)
workflow.add_node("call_model", call_model)
workflow.add_node("tools", call_tools)
workflow.add_edge(START, "call_model")
workflow.add_conditional_edges("call_model", tools_condition)
workflow.add_edge("tools", "call_model")

server:
  api:
    port: 8800

agent:
  type: LANGGRAPH
  config:
    name: "Production Chatbot"
    graph_definition: "./agent/agent.py:workflow"
    checkpointer:
      type: postgres
      db_url: "postgresql://postgres:postgres@localhost:5432/agent_memory"

guardrails:
  input:
    - config_id: detect_pii
      pii_entities: ["EMAIL_ADDRESS", "PHONE_NUMBER", "CREDIT_CARD"]
    - config_id: ban_list
      banned_words: ["ignore previous instructions", "system prompt"]

observability:
  - provider: LANGFUSE
    enabled: true
    config:
      host: "https://cloud.langfuse.com"
      public_key: "pk-lf-your-public-key"
      secret_key: "sk-lf-your-secret-key"
      run_name: "production-chatbot"