"""Практическое задание №3: память разговора + подтверждение вызовов инструментов.""" from __future__ import annotations import os from dotenv import load_dotenv from langchain.agents import create_agent from langchain.tools import tool from langchain_openai import ChatOpenAI from langgraph.checkpoint.memory import MemorySaver from rich.console import Console load_dotenv() console = Console() llm = ChatOpenAI( model=os.getenv("OPENAI_MODEL", "openai/gpt-oss-20b:free"), base_url=os.getenv("OPENAI_BASE_URL", "https://openrouter.ai/api/v1"), api_key=os.getenv("OPENAI_API_KEY", "fake"), temperature=0.0, ) @tool def get_price(city: str, date: str = "сегодня") -> str: """Узнать примерную цену/стоимость покупок или погодные условия в городе на дату.""" return f"{city}, {date}: ориентировочно 150–300 руб. за базовую корзину." memory = MemorySaver() agent = create_agent( model=llm, tools=[get_price], system_prompt="Ты помощник по планированию покупок и погоде. Помни контекст разговора.", checkpointer=memory, interrupt_before=["tools"], ) def _print_pending_tool(config: dict) -> None: state = agent.get_state(config) messages = state.values.get("messages", []) if not messages: return last = messages[-1] tool_calls = getattr(last, "tool_calls", None) or [] if not tool_calls: return tc = tool_calls[0] name = tc.get("name") if isinstance(tc, dict) else getattr(tc, "name", "?") args = tc.get("args") if isinstance(tc, dict) else getattr(tc, "args", {}) console.print("\n --- --- --- ") console.print(f"{name}({args})") console.print(f"Агент хочет вызвать утилиту {name}({args})") def _print_updates(chunk_data: dict) -> None: for node_name, update in chunk_data.items(): if node_name == "__interrupt__": continue if not isinstance(update, dict): continue messages = update.get("messages", []) for msg in messages: tool_calls = getattr(msg, "tool_calls", None) or [] for tc in tool_calls: name = tc.get("name") if isinstance(tc, dict) else getattr(tc, "name", "?") args = tc.get("args") if isinstance(tc, dict) else getattr(tc, "args", {}) console.print(f"\n --- --- --- ") console.print(f"{name}({args})") def ask_and_run(user_input: dict | None, config: dict) -> None: """Запуск или возобновление агента с обработкой паузы перед tools.""" for chunk in agent.stream( user_input, config=config, stream_mode=["messages", "updates"], ): state = agent.get_state(config) if not isinstance(chunk, tuple) or len(chunk) != 2: continue chunk_type, chunk_data = chunk if chunk_type == "messages": if isinstance(chunk_data, tuple) and len(chunk_data) >= 1: token = chunk_data[0] content = getattr(token, "content", None) if content: console.print(content, end="") if chunk_type == "updates" and isinstance(chunk_data, dict): _print_updates(chunk_data) if "__interrupt__" in chunk_data and state.next == ("tools",): _print_pending_tool(config) answer = input("Разрешить? (Y/n): ").strip().lower() if answer in ("", "y", "yes", "д", "да"): ask_and_run(None, config) else: console.print("Отменено") return console.print() def main() -> None: config = {"configurable": {"thread_id": "разговор-1"}} console.print( "Чат с агентом (память + подтверждение tools). " "Введите 'exit' для выхода.\n" ) while True: user_text = input("\nВы: ").strip() if user_text.lower() == "exit": break if not user_text: continue ask_and_run({"messages": [{"role": "human", "content": user_text}]}, config) if __name__ == "__main__": main()