"""
Tools 节点 - 负责执行 tool_calls
"""

from typing import Dict, Any, Optional, List
from langchain_core.runnables.config import RunnableConfig
from langchain_core.messages import AIMessage, ToolMessage

from backend.app.main_graph.state import AgentState
from backend.app.logger import info, error, debug
from backend.app.tools import ALL_TOOLS
from backend.app.agent.stream_context import get_stream_queue


async def tools_node(state: AgentState, config: Optional[RunnableConfig] = None) -> Dict[str, Any]:
    """
    Tools 节点：执行 AIMessage.tool_calls，返回 ToolMessage 列表

    职责：
    1. 获取最后一条 AIMessage 的 tool_calls
    2. 遍历执行每个工具
    3. 记录历史（tool_call_history, tool_result_history）
    4. 更新步数 current_step += 1
    5. 发送工具开始/结束事件
    """
    queue = get_stream_queue()
    is_streaming = queue is not None

    # 获取最后一条 AIMessage
    last_message = state.messages[-1]
    if not isinstance(last_message, AIMessage) or not last_message.tool_calls:
        info("[Tools] 没有工具调用，跳过")
        return {}

    tool_calls = last_message.tool_calls
    info(f"[Tools] 执行 {len(tool_calls)} 个工具调用")

    # 获取历史记录
    tool_call_history: List[dict] = list(getattr(state, "tool_call_history", []))
    tool_result_history: List[str] = list(getattr(state, "tool_result_history", []))
    tools_used: List[str] = list(getattr(state, "tools_used", []))

    tool_messages = []

    for tc in tool_calls:
        tool_name = tc["name"]
        tool_args = tc["args"]
        tool_id = tc["id"]

        tools_used.append(tool_name)

        # 发送工具开始事件
        if is_streaming:
            await queue.put({
                "type": "custom",
                "data": {
                    "type": "tool_start",
                    "tool": tool_name,
                    "args": tool_args,
                    "id": tool_id
                }
            })

        # 查找并执行工具
        tool_result = ""
        tool_found = False

        for tool in ALL_TOOLS:
            if tool.name == tool_name:
                tool_found = True
                try:
                    tool_result = await tool.ainvoke(tool_args)
                    debug(f"[Tools] 工具 {tool_name} 执行成功")
                except Exception as e:
                    tool_result = f"工具调用出错: {str(e)}"
                    error(f"[Tools] 工具 {tool_name} 调用出错: {e}")
                break

        if not tool_found:
            tool_result = f"未找到工具: {tool_name}"
            error(f"[Tools] 未找到工具: {tool_name}")

        # 发送工具结束事件
        if is_streaming:
            await queue.put({
                "type": "custom",
                "data": {
                    "type": "tool_end",
                    "tool": tool_name,
                    "id": tool_id,
                    "result": str(tool_result)
                }
            })

        # 记录历史
        tool_call_history.append({"name": tool_name, "args": tool_args})
        tool_result_history.append(str(tool_result))

        # 创建 ToolMessage
        tool_messages.append(
            ToolMessage(content=str(tool_result), tool_call_id=tool_id, name=tool_name)
        )

    # 更新步数
    current_step = getattr(state, "current_step", 0) + 1

    return {
        "messages": tool_messages,
        "current_step": current_step,
        "tool_call_history": tool_call_history,
        "tool_result_history": tool_result_history,
        "tools_used": tools_used,
    }