LangGraph

from typing import TypedDict

import promptguard
promptguard.init()  # reads PROMPTGUARD_API_KEY

from langchain_openai import ChatOpenAI
from langgraph.graph import END, START, StateGraph

llm = ChatOpenAI(model="gpt-5-nano")


class State(TypedDict):
    question: str
    answer: str


def answer(state: State) -> dict:
    return {"answer": llm.invoke(state["question"]).content}


graph = StateGraph(State)
graph.add_node("answer", answer)
graph.add_edge(START, "answer")
graph.add_edge("answer", END)
app = graph.compile()

app.invoke({"question": "What is prompt injection?"})

from promptguard.integrations.langchain import PromptGuardRunnable

guard = PromptGuardRunnable().as_runnable()


def answer(state: State) -> dict:
    question = guard.invoke(state["question"])
    return {"answer": llm.invoke(question).content}