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