66 lines
1.9 KiB
Python
66 lines
1.9 KiB
Python
from __future__ import annotations
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from typing import TypedDict
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from langgraph.graph import END, START, StateGraph
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from langgraph.types import Command, interrupt
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class GameState(TypedDict):
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scene: str
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inventory: list[str]
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decision: str
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def intro(state: GameState) -> GameState:
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return {
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"scene": "Вы стоите у двери лаборатории AI-агента.",
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"inventory": state.get("inventory", []),
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"decision": "",
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}
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def ask_human(state: GameState) -> GameState:
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decision = interrupt(
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{
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"scene": state["scene"],
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"question": "Открыть дверь или осмотреть коридор?",
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"options": ["open", "look"],
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}
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)
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return {**state, "decision": str(decision)}
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def resolve(state: GameState) -> GameState:
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inventory = list(state.get("inventory", []))
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if state.get("decision") == "open":
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inventory.append("access_card")
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scene = "Дверь открыта, агент получил access_card."
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else:
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scene = "Вы нашли подсказку на стене и вернулись к двери."
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return {**state, "scene": scene, "inventory": inventory}
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def build_graph():
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graph = StateGraph(GameState)
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graph.add_node("intro", intro)
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graph.add_node("ask_human", ask_human)
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graph.add_node("resolve", resolve)
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graph.add_edge(START, "intro")
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graph.add_edge("intro", "ask_human")
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graph.add_edge("ask_human", "resolve")
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graph.add_edge("resolve", END)
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return graph.compile()
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def main() -> None:
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graph = build_graph()
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config = {"configurable": {"thread_id": "demo-game"}}
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print(graph.invoke({"scene": "", "inventory": [], "decision": ""}, config=config))
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print("Resume example:")
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print(graph.invoke(Command(resume="open"), config=config)) # type: ignore[name-defined]
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if __name__ == "__main__":
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main()
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