102 lines
4.3 KiB
Python
102 lines
4.3 KiB
Python
import os
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from langchain_openai import ChatOpenAI
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from langgraph.checkpoint.memory import MemorySaver
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from langgraph.prebuilt import create_react_agent
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from rich.console import Console
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# ---------------------------------------------------------------
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# LLM
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# ---------------------------------------------------------------
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llm = ChatOpenAI(
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model="openai/gpt-oss-20b:free",
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base_url="https://platform.brojs.ru/jrnl-bh/api/inference/v1",
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api_key=os.getenv("JOURNAL_MCP_PAT"),
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temperature=0.0,
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)
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# ---------------------------------------------------------------
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# Helper create_agent — обёртка, как описано в инструкции
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# ---------------------------------------------------------------
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def create_agent(model, tools, system_prompt="", checkpointer=None, interrupt_before=None):
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"""Helper-функция для создания агента с памятью и interrupt."""
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kwargs = dict(model=model, tools=tools)
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if system_prompt:
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kwargs["prompt"] = system_prompt
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if checkpointer is not None:
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kwargs["checkpointer"] = checkpointer
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if interrupt_before is not None:
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kwargs["interrupt_before"] = interrupt_before
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return create_react_agent(**kwargs)
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# ---------------------------------------------------------------
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# Инструменты
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# ---------------------------------------------------------------
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from langchain.tools import tool
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@tool
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def get_price(city: str, date: str) -> str:
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"""Возвращает условную цену/погоду для города на указанную дату."""
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return f"Данные для {city} на {date}: 720 руб/кг, 18C, облачно"
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# ---------------------------------------------------------------
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# Агент с памятью и паузой перед инструментом
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# ---------------------------------------------------------------
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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 полезный ассистент. Помогай пользователю находить цены и погоду.",
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checkpointer=memory,
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interrupt_before=["tools"],
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)
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console = Console()
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# ---------------------------------------------------------------
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# ask_and_run — точная структура из задания
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# ---------------------------------------------------------------
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def ask_and_run(user_input, config):
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for chunk in agent.stream(user_input, config=config, stream_mode=["messages", "updates"]):
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state = agent.get_state(config)
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chunk_type, chunk_data = chunk
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if chunk_type == "messages":
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msg = chunk_data[0] if isinstance(chunk_data, (list, tuple)) else chunk_data
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content = getattr(msg, "content", "")
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if content and not getattr(msg, "tool_calls", None):
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console.print(content, end="")
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if chunk_type == "updates":
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console.print("\n --- --- --- \n")
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for node_data in chunk_data.values():
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for msg in node_data.get("messages", []):
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for tc in getattr(msg, "tool_calls", []):
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console.print(f"[bold]{tc['name']}({tc['args']})[/bold]")
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if "__interrupt__" in chunk_data and state.next == ("tools",):
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tool_call = state.values["messages"][-1].tool_calls[0]
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console.print(f"Агент хочет вызвать утилиту [bold]{tool_call['name']}({tool_call['args']})[/bold]")
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answer = input("Разрешить? (Y/n): ")
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if answer.lower().strip() == "y":
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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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break
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# ---------------------------------------------------------------
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# Чат-цикл
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# ---------------------------------------------------------------
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if __name__ == "__main__":
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config = {"configurable": {"thread_id": "разговор-1"}}
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console.print("[bold green]Агент запущен. Введите 'exit' для выхода.[/bold green]")
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while True:
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user_input = input("\nВы: ")
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if user_input == "exit":
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break
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ask_and_run(
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{"messages": [{"role": "human", "content": user_input}]},
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config,
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) |