"""
Agent configuration for the Human‑in‑the‑Loop example.

The agent uses :class:`langchain.agents.middleware.HumanInTheLoopMiddleware` to pause whenever a tool is called.  The middleware automatically builds an interrupt payload that contains the name of the tool, its arguments and the allowed decisions (approve / reject / edit).  The caller can then resume execution by sending a ``Command`` with the chosen decisions.
"""
import os
from langchain_openai import ChatOpenAI
from langchain.agents import create_agent
from langchain.agents.middleware import HumanInTheLoopMiddleware
from langgraph.checkpoint.memory import MemorySaver
from langgraph.types import Command

# LLM – BroJS
llm = ChatOpenAI(
    model="openai/gpt-oss-20b:free",
    base_url="https://platform.brojs.ru/jrnl-bh/api/inference/v1",
    api_key=os.getenv("JOURNAL_MCP_PAT"),
    temperature=0.5,
)

# Tool import – defined in tools.py
from tools import get_weather

memory = MemorySaver()
agent = create_agent(
    llm=llm,
    tools=[get_weather],
    system_prompt="Ты полезный ассистент.",
    middleware=[
        HumanInTheLoopMiddleware(
            interrupt_on={"get_weather": True},
            description_prefix="Подтвердите вызов инструмента",
        ),
    ],
    checkpointer=memory,
)

# Helper to run a single user query with HIL loop

def run_query(user_msg: str, thread_id: str = "session-1"):
    config = {"configurable": {"thread_id": thread_id}}
    result = agent.invoke({"messages": [{"role": "human", "content": user_msg}]}, config)

    # Loop while the agent is paused for a decision
    while "__interrupt__" in result:
        interrupt_value = result["__interrupt__"][0].value
        action_requests = interrupt_value.get("action_requests", [])
        decisions = []
        print("\n--- Подтверждение вызова инструмента ---")
        for idx, act in enumerate(action_requests):
            name = act["name"]
            args = act.get("args", {})
            desc = act.get("description", "")
            print(f"{idx+1}. Инструмент: {name}")
            print(f"   Аргументы: {args}")
            if desc:
                print(f"   Описание: {desc}")
        # Simple approve/reject per action
        for idx, act in enumerate(action_requests):
            while True:
                choice = input("a=approve, r=reject (e=edit не поддерживается): ").strip().lower()
                if choice == "a":
                    decisions.append({"type": "approve"})
                    break
                elif choice == "r":
                    msg = input("Причина отказа: ")
                    decisions.append({"type": "reject", "message": msg})
                    break
        # Resume execution with collected decisions
        result = agent.invoke(Command(resume={"decisions": decisions}), config)
    # Final answer
    final_msg = result["messages"][-1].content
    print("\nОтвет агента:")
    print(final_msg)
    return final_msg

if __name__ == "__main__":
    run_query("Какая погода в Казани сегодня?")