"""PAM 部署 Agent 的 LangGraph 图工厂。"""

from __future__ import annotations

from typing import Any

from .agent import PamDeployAgent
from .langgraph_runtime import GraphFlow


def build_langgraph(agent: PamDeployAgent | None = None, flow: GraphFlow = "deploy"):
    """构建兼容旧输入格式的 action 级 LangGraph 部署图。

    输入 state 支持直接传 `params`，图内会先调用 `create_state`；CLI/chat
    默认使用 `LangGraphDeploymentRuntime`，该 runtime 直接接收 `AgentState`
    并由业务 checkpoint 支撑断点续跑。
    """
    try:
        from langgraph.graph import END, START, StateGraph
    except ImportError as exc:  # pragma: no cover - 依赖可选安装状态
        raise RuntimeError("未安装 langgraph。请先执行 `pip install -e .` 安装项目依赖。") from exc

    runtime = agent or PamDeployAgent()

    def create_state_node(state: dict[str, Any]) -> dict[str, Any]:
        """根据输入参数创建 AgentState。"""
        if "agent_state" in state:
            return {"agent_state": state["agent_state"]}
        agent_state = runtime.create_state(
            params=state["params"],
            execution_strategy=state.get("execution_strategy", "hybrid_node_mcp"),
            run_id=state.get("run_id"),
            script_entry=state.get("script_entry"),
            config_path=state.get("config_path"),
            trace_file_path=state.get("trace_file_path"),
            checkpoint_path=state.get("checkpoint_path"),
            target_ips=state.get("target_ips"),
        )
        return {"agent_state": agent_state}

    def global_action_node(state: dict[str, Any]) -> dict[str, Any]:
        """执行一个全局 action。"""
        agent_state = state["agent_state"]
        action = runtime.next_global_action(agent_state)
        if action:
            runtime.run_global_action(agent_state, action)
        return {"agent_state": agent_state}

    def prepare_ip_node(state: dict[str, Any]) -> dict[str, Any]:
        """选择下一个 IP action。"""
        agent_state = state["agent_state"]
        work = runtime.next_ip_action(agent_state)
        if work is None:
            return {"agent_state": agent_state, "current_ip": "", "current_ip_action": ""}
        ip, action = work
        return {"agent_state": agent_state, "current_ip": ip, "current_ip_action": action}

    def ip_action_node(state: dict[str, Any]) -> dict[str, Any]:
        """执行一个 IP action。"""
        agent_state = state["agent_state"]
        ip = str(state.get("current_ip", ""))
        action = str(state.get("current_ip_action", ""))
        if ip and action:
            runtime.run_ip_action(agent_state, ip, action)
        return {"agent_state": agent_state, "current_ip": "", "current_ip_action": ""}

    def report_node(state: dict[str, Any]) -> dict[str, Any]:
        """渲染最终部署报告。"""
        return {
            "agent_state": state["agent_state"],
            "report": runtime.render_report(state["agent_state"]),
        }

    def route_entry(state: dict[str, Any]) -> str:
        """入口路由。"""
        agent_state = state["agent_state"]
        if agent_state.pending_confirmation:
            return "report"
        if runtime.next_global_action(agent_state):
            return "global_action"
        if flow == "global":
            return "report"
        return "prepare_ip"

    def route_after_global(state: dict[str, Any]) -> str:
        """全局 action 后路由。"""
        agent_state = state["agent_state"]
        if runtime.next_global_action(agent_state):
            return "global_action"
        if flow == "global":
            return "report"
        return "prepare_ip"

    def route_after_prepare_ip(state: dict[str, Any]) -> str:
        """IP 准备节点后路由。"""
        agent_state = state["agent_state"]
        if agent_state.pending_confirmation:
            return "report"
        if state.get("current_ip_action"):
            return "ip_action"
        return "report"

    graph = StateGraph(dict)
    graph.add_node("create_state", create_state_node)
    graph.add_node("global_action", global_action_node)
    graph.add_node("prepare_ip", prepare_ip_node)
    graph.add_node("ip_action", ip_action_node)
    graph.add_node("report", report_node)

    graph.add_edge(START, "create_state")
    graph.add_conditional_edges(
        "create_state",
        route_entry,
        {"global_action": "global_action", "prepare_ip": "prepare_ip", "report": "report"},
    )
    graph.add_conditional_edges(
        "global_action",
        route_after_global,
        {"global_action": "global_action", "prepare_ip": "prepare_ip", "report": "report"},
    )
    graph.add_conditional_edges(
        "prepare_ip",
        route_after_prepare_ip,
        {"ip_action": "ip_action", "report": "report"},
    )
    graph.add_edge("ip_action", "prepare_ip")
    graph.add_edge("report", END)
    return graph.compile()


def build_graph_or_none(agent: PamDeployAgent | None = None, flow: GraphFlow = "deploy"):
    """在未安装 LangGraph 时返回 None，便于调用方降级。"""
    try:
        return build_langgraph(agent=agent, flow=flow)
    except RuntimeError:
        return None