From acff9abc703ed8226e6c1b955485a58249aed39e Mon Sep 17 00:00:00 2001
From: lonpatovaadelina <lonpatovaadelina@mail.ru>
Date: Thu, 28 May 2026 15:50:09 +0000
Subject: [PATCH] =?UTF-8?q?=D0=94=D0=BE=D0=B1=D0=B0=D0=B2=D0=BB=D0=B5?=
 =?UTF-8?q?=D0=BD=20solution.py?=
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---
 solution.py | 120 +++-------------------------------------------------
 1 file changed, 5 insertions(+), 115 deletions(-)

diff --git a/solution.py b/solution.py
index 3f3413f..0c9bdf6 100644
--- a/solution.py
+++ b/solution.py
@@ -1,115 +1,5 @@
-from typing import TypedDict
-import json
-
-import questionary
-from langgraph.graph import StateGraph
-from langgraph.constants import START
-from langgraph.types import interrupt, Command
-from langgraph.checkpoint.memory import InMemorySaver
-from langchain_openai import ChatOpenAI
-from rich.console import Console
-
-
-# ────────────────────── Состояние графа ──────────────────────
-
-class State(TypedDict):
-    """Состояние графа."""
-    story: str                # Текст истории, генерируемый LLM
-    options: list[str]        # Варианты действий
-    choice: str | None        # Выбор пользователя
-    ending: str | None        # Концовка
-
-
-# ────────────────────── Инструмент LLM ──────────────────────
-
-llm = ChatOpenAI(model="gpt-4o-mini", temperature=0.7)
-console = Console()
-
-
-def generate_story(state: State) -> State:
-    """Генерирует начало истории и варианты действий."""
-    prompt = (
-        "Generate a short adventure intro and three choices in JSON format.\n"
-        "The JSON should have keys 'intro' (string) and 'choices' (list of strings)."
-    )
-    response = llm.invoke({"messages": [{"role": "system", "content": prompt}]}).content
-    data = json.loads(response)
-
-    state["story"] = data["intro"]
-    state["options"] = data["choices"]
-
-    # Пауза для выбора игрока
-    return interrupt(state, {
-        "type": "choice",
-        "question": f"{state['story']}\nВыберите действие:",
-        "options": state["options"],
-    })
-
-
-def finish_story(state: State) -> State:
-    """Генерирует окончание истории на основе выбранного варианта."""
-    prompt = (
-        f"Write an ending for the story based on the choice '{state['choice']}'. "
-        "Keep it concise and satisfying."
-    )
-    response = llm.invoke({"messages": [{"role": "system", "content": prompt}]}).content
-    state["ending"] = response
-    return state
-
-
-# ────────────────────── Граф ──────────────────────
-
-builder = StateGraph(State)
-builder.add_node("generate", generate_story)
-builder.add_node("finish", finish_story)
-
-builder.set_entry_point("generate")
-builder.add_edge(START, "generate")
-builder.add_conditional_edges(
-    "generate",
-    lambda x: True if x.get("choice") else None,
-    {True: "finish"},
-)
-builder.add_edge("finish", START)  # цикл можно завершить здесь
-
-graph = builder.compile(checkpointer=InMemorySaver())
-
-
-# ────────────────────── Запуск и обработка прерываний ──────────────────────
-
-def main() -> None:
-    thread_id = "interactive_story"
-
-    init_state: State = {"story": "", "options": [], "choice": None, "ending": None}
-    config = {"configurable": {"thread_id": thread_id}}
-
-    # Запускаем поток генерации
-    stream = graph.stream(Command(resume=init_state), config=config)
-
-    for chunk in stream:
-        if "__interrupt__" in chunk:
-            payload = chunk["__interrupt__"][0].value
-            answer = questionary.select(
-                payload["question"],
-                choices=payload["options"],
-            ).ask()
-            if answer is None:
-                raise RuntimeError("Пользователь отменил ввод.")
-            # Возобновляем граф с выбранным вариантом
-            stream = graph.stream(Command(resume={"choice": answer}), config=config)
-            continue
-
-        # Выводим сообщения от LLM
-        if "story" in chunk and chunk["story"]:
-            console.print(f"[bold cyan]История:[/]\n{chunk['story']}")
-        if "ending" in chunk and chunk["ending"]:
-            console.print(f"\n[bold green]Концовка:[/]\n{chunk['ending']}")
-
-    # После завершения выводим итоговую историю
-    final_state = graph.get_state(config=config)
-    full_story = f"{final_state['story']}\n\n{final_state['ending']}"
-    console.print("\n[bold magenta]Итоговая история:[/]\n" + full_story)
-
-
-if __name__ == "__main__":
-    main()
\ No newline at end of file
+langgraph
+langchain
+langchain-openai
+questionary
+rich
\ No newline at end of file