import asyncio
from collections.abc import AsyncIterator, Callable, Sequence
from typing import Any, cast

from pydantic import BaseModel, Field

from zhenxun.services.ai.core.messages import PromptInput
from zhenxun.services.ai.flow.base import BaseRunnable
from zhenxun.services.ai.flow.workflow.base import BaseNode
from zhenxun.services.ai.flow.workflow.types import (
    BaseFailurePolicy,
    StepInput,
    StepOutput,
    StepType,
)
from zhenxun.services.ai.run import RunContext
from zhenxun.services.ai.run.di import DependencyInjector
from zhenxun.services.log import logger

NodeSource = BaseNode | BaseRunnable | Callable
"""工作流节点来源，可以是图元、可执行引擎或原生函数"""


class Step(BaseNode):
    """
    工作流中的最小执行单元门面 (Facade)。
    对外部隐藏了 AgentNode 和 FunctionNode 的具体实现。
    当实例化 Step 时，底层会自动根据 executor 的类型返回专属的节点对象。
    """

    def __new__(cls, *args, **kwargs):
        if cls is Step:
            executor = kwargs.get("executor")
            if executor is None and len(args) > 1:
                executor = args[1]

            from zhenxun.services.ai.flow.base import BaseRunnable

            if isinstance(executor, BaseRunnable):
                return object.__new__(RunnableNode)
            elif callable(executor):
                return object.__new__(FunctionNode)
        return object.__new__(cls)

    def __init__(
        self,
        name: str | None = None,
        executor: NodeSource | None = None,
        prompt: PromptInput | None = None,
        requires_confirmation: bool = False,
        confirmation_message: str | None = None,
        failure_policy: BaseFailurePolicy | None = None,
    ):
        """
        初始化工作流单元步骤（门面）。

        参数:
            name: 步骤的名称，为空则自动取执行器的名称，默认 None。
            executor: 该步骤要运行的核心执行器（支持 RunnableNode 或 Callable 依赖注入）。
            prompt: 该步骤的初始输入或提示词定义，默认 None。
            requires_confirmation: 标记该节点在执行前是否需要人工介入授权，默认 False。
            confirmation_message: 挂起等待授权时展示的提示文案，默认 None。
            failure_policy: 该节点执行失败时的错误处理策略，默认使用中断策略。
        """  # noqa: E501
        actual_name = name or getattr(
            executor, "name", getattr(executor, "__name__", "unnamed_step")
        )
        super().__init__(
            name=actual_name,
            requires_confirmation=requires_confirmation,
            confirmation_message=confirmation_message,
            failure_policy=failure_policy,
        )
        self.executor = executor
        self.prompt = prompt

    @property
    def node_type(self) -> StepType:
        return StepType.STEP

    async def run_stream(
        self, step_input: StepInput, context: RunContext
    ) -> AsyncIterator[Any]:
        if False:
            yield None
        raise NotImplementedError(
            "This is a facade. Real execution happens in subclasses."
        )


class RunnableNode(Step):
    """专门处理 Agent/Team/Workflow 等 BaseRunnable 状态机执行的私有节点"""

    async def run_stream(
        self, step_input: StepInput, context: RunContext
    ) -> AsyncIterator[Any]:
        import copy

        from zhenxun.services.ai.flow.base import BaseRunnable
        from zhenxun.services.ai.run import Task

        executor = cast(BaseRunnable, self.executor)
        prompt_data = self.prompt if self.prompt is not None else step_input.input

        if isinstance(prompt_data, Task):
            prompt_data = copy.copy(prompt_data)
            if step_input.previous_step_content:
                prev_content = str(step_input.previous_step_content)
                prompt_data.description = (
                    f"### 🔙 [上游节点执行输出]\n{prev_content}\n\n"
                    f"### 🎯 [当前需执行的任务]\n{prompt_data.description}"
                )
            context.run.user_input = prompt_data.description
        else:
            if step_input.previous_step_content:
                prompt_data = (
                    f"[上游节点执行输出]:\n{step_input.previous_step_content}\n\n"
                    f"[当前需执行的任务]:\n{prompt_data or ''}"
                )
            context.run.user_input = str(prompt_data) if prompt_data else ""

        final_result = None
        sandbox_context = context.clone_for_member(self.name)

        async with executor.run_stream(
            prompt=prompt_data, context=sandbox_context
        ) as stream_result:
            async for event in stream_result.stream_events():
                from zhenxun.services.ai.run.models import AgentRunEnd

                if isinstance(event, AgentRunEnd):
                    final_result = event.result
                yield event

        context.state.update(sandbox_context.state)
        yield StepOutput(
            content=final_result.output if final_result else "无返回",
            success=True,
        )


class FunctionNode(Step):
    """专门处理 Python Callable 依赖注入与执行的私有节点"""

    async def run_stream(
        self, step_input: StepInput, context: RunContext
    ) -> AsyncIterator[Any]:
        context.run.user_input = str(step_input.input) if step_input.input else ""

        executor = cast(Callable, self.executor)
        res = await DependencyInjector.invoke(
            executor, {"step_input": step_input}, context
        )

        if isinstance(res, StepOutput):
            yield res
        else:
            yield StepOutput(content=res, success=True)


class StepMeta(BaseModel):
    """承载工作流节点装饰器元数据的内部模型"""

    name: str | None = None
    requires_confirmation: bool = False
    confirmation_message: str | None = None
    failure_policy: Any = None


class ConditionMeta(BaseModel):
    name: str | None = None
    if_true: list[Any] = Field(default_factory=list)
    if_false: list[Any] = Field(default_factory=list)


class RouterMeta(BaseModel):
    name: str | None = None
    choices: list[Any] = Field(default_factory=list)


class Steps(BaseNode):
    """串行执行的工作流容器。按照列表顺序依次执行。"""

    def __init__(self, steps: Sequence[NodeSource], name: str = "StepsGroup"):
        """
        初始化串行工作流容器。

        参数:
            steps: 依次串行执行的节点/执行器列表。
            name: 该串行容器 of 名称，默认 "StepsGroup"。
        """
        super().__init__(name=name)
        self.steps = [NodeFactory.build(step) for step in steps]

    @property
    def node_type(self) -> StepType:
        return StepType.STEPS

    async def run_stream(
        self, step_input: StepInput, context: RunContext
    ) -> AsyncIterator[Any]:
        current_input = StepInput(
            input=step_input.input,
            previous_step_content=step_input.previous_step_content,
            additional_data=step_input.additional_data.copy(),
        )

        all_outputs: list[StepOutput] = []
        for step_obj in self.steps:
            out_box: list[StepOutput] = []
            async for event in self._forward_stream(
                step_obj.aexecute_stream(current_input, context), out_box
            ):
                yield event
            step_out = out_box[0] if out_box else None

            if step_out:
                all_outputs.append(step_out)
                current_input.previous_step_content = step_out.content
                if step_out.stop:
                    break

        yield StepOutput(
            content=all_outputs[-1].content if all_outputs else "No steps executed",
            success=all(o.success for o in all_outputs),
            is_paused=any(getattr(o, "is_paused", False) for o in all_outputs),
            steps=all_outputs,
        )


class Condition(BaseNode):
    """根据条件函数的返回结果，决定走向 steps 还是 else_steps"""

    def __init__(
        self,
        evaluator: Any,
        steps: Sequence[NodeSource],
        else_steps: Sequence[NodeSource] | None = None,
        name: str = "ConditionGroup",
    ):
        """
        初始化条件分支节点。

        参数:
            evaluator: 用于评估条件真假的布尔值、表达式或可调用函数。
            steps: 当 evaluator 求值为真时，将执行的步骤序列。
            else_steps: 当 evaluator 求值为假时，将执行的备用步骤序列，默认 None。
            name: 该条件分支容器的名称，默认 "ConditionGroup"。
        """
        super().__init__(name=name)
        self.evaluator = evaluator
        self.steps = [NodeFactory.build(step) for step in steps]
        self.else_steps = [NodeFactory.build(step) for step in (else_steps or [])]

    @property
    def node_type(self) -> StepType:
        return StepType.CONDITION

    async def run_stream(
        self, step_input: StepInput, context: RunContext
    ) -> AsyncIterator[Any]:
        if callable(self.evaluator):
            condition_result = await DependencyInjector.invoke(
                self.evaluator, {"step_input": step_input}, context
            )
        else:
            condition_result = bool(self.evaluator)

        target_steps = self.steps if condition_result else self.else_steps
        branch_name = "if" if condition_result else "else"

        if not target_steps:
            yield StepOutput(
                content=f"条件求值为 {condition_result}，无对应步骤需执行。",
                success=True,
            )
            return

        steps_container = Steps(
            steps=target_steps, name=f"{self.name}_{branch_name}_branch"
        )
        out_box: list[StepOutput] = []
        async for event in self._forward_stream(
            steps_container.aexecute_stream(step_input, context), out_box
        ):
            yield event
        if out_box:
            yield out_box[0]


class Router(BaseNode):
    """根据选择器函数的返回值(名称)，从候选项中挑选步骤执行"""

    def __init__(
        self, choices: Sequence[NodeSource], selector: Any, name: str = "RouterGroup"
    ):
        """
        初始化选择路由器节点。

        参数:
            choices: 包含所有候选执行路由分支的步骤序列。
            selector: 用于决定路由流向的匹配值、或者是返回分支名称的动态选择器函数。
            name: 该路由器容器的名称，默认 "RouterGroup"。
        """
        super().__init__(name=name)
        self.choices = [NodeFactory.build(c) for c in choices]
        self.selector = selector
        self._choice_map = {}
        for c in self.choices:
            if c.name:
                self._choice_map[c.name] = c

    @property
    def node_type(self) -> StepType:
        return StepType.ROUTER

    async def run_stream(
        self, step_input: StepInput, context: RunContext
    ) -> AsyncIterator[Any]:
        if callable(self.selector):
            selected = await DependencyInjector.invoke(
                self.selector, {"step_input": step_input}, context
            )
        else:
            selected = self.selector

        if not isinstance(selected, list):
            selected = [selected]

        target_steps = []
        for s in selected:
            if isinstance(s, str):
                if s in self._choice_map:
                    target_steps.append(self._choice_map[s])
                else:
                    logger.warning(f"Router '{self.name}' 选择了未知的步骤: '{s}'")
            else:
                target_steps.append(NodeFactory.build(s))

        if not target_steps:
            yield StepOutput(content="没有命中任何有效路由分支。", success=True)
            return

        steps_container = Steps(steps=target_steps, name=f"{self.name}_routed_steps")
        out_box: list[StepOutput] = []
        async for event in self._forward_stream(
            steps_container.aexecute_stream(step_input, context), out_box
        ):
            yield event
        if out_box:
            yield out_box[0]


class Loop(BaseNode):
    """循环执行工作流，直至达到最大次数或满足结束条件"""

    def __init__(
        self,
        steps: Sequence[NodeSource],
        max_iterations: int = 3,
        end_condition: Any = None,
        name: str = "LoopGroup",
    ):
        """
        初始化循环控制器节点。

        参数:
            steps: 每次循环中需要顺序运行的步骤序列。
            max_iterations: 最大允许循环执行的迭代次数上限，默认 3。
            end_condition: 决定是否可以提前终止循环的条件布尔值或可调用判定函数，
                默认 None。
            name: 该循环容器的名称，默认 "LoopGroup"。
        """
        super().__init__(name=name)
        self.steps = [NodeFactory.build(step) for step in steps]
        self.max_iterations = max_iterations
        self.end_condition = end_condition

    @property
    def node_type(self) -> StepType:
        return StepType.LOOP

    async def run_stream(
        self, step_input: StepInput, context: RunContext
    ) -> AsyncIterator[Any]:
        logger.debug(
            f"  🔁 开始循环: [Loop] `{self.name}` (最大 {self.max_iterations} 次)"
        )

        iteration = 0
        all_results: list[StepOutput] = []
        current_input = StepInput(
            input=step_input.input,
            previous_step_content=step_input.previous_step_content,
            additional_data=step_input.additional_data.copy(),
        )

        while iteration < self.max_iterations:
            logger.debug(f"  ┃  🔄 第 {iteration + 1} 次迭代...")

            steps_container = Steps(
                steps=self.steps, name=f"{self.name}_iter_{iteration + 1}"
            )
            out_box: list[StepOutput] = []
            async for event in self._forward_stream(
                steps_container.aexecute_stream(current_input, context), out_box
            ):
                yield event
            iter_output = out_box[0] if out_box else None

            should_stop = False
            if iter_output:
                all_results.append(iter_output)
                if self.end_condition:
                    if callable(self.end_condition):
                        should_stop = await DependencyInjector.invoke(
                            self.end_condition,
                            {"iteration_results": iter_output.steps or [iter_output]},
                            context,
                        )
                    else:
                        should_stop = bool(self.end_condition)

                iteration += 1
                if should_stop or iter_output.stop:
                    break
                current_input.previous_step_content = iter_output.content
            else:
                iteration += 1
                break

        yield StepOutput(
            content=all_results[-1].content if all_results else "No iterations run",
            success=all(o.success for o in all_results),
            is_paused=any(getattr(o, "is_paused", False) for o in all_results),
            steps=all_results,
        )

        logger.debug(f"  ✅ 循环结束: [Loop] `{self.name}` (共执行 {iteration} 次)")


class Parallel(BaseNode):
    """并发执行的工作流容器。无序地并发执行内部所有步骤，并最终聚合成一个输出。"""

    def __init__(self, *args: NodeSource | str, name: str | None = None):
        """
        初始化并发工作流容器。

        参数:
            *args: 并发执行的任务节点/执行器，支持混入字符串覆盖作为 Parallel 的名字。
            name: 该并发容器的名称，默认 "ParallelGroup"。
        """
        super().__init__(name=name or "ParallelGroup")
        self.steps = []
        for arg in args:
            if isinstance(arg, str):
                self.name = arg
            else:
                self.steps.append(NodeFactory.build(arg))

    @property
    def node_type(self) -> StepType:
        return StepType.PARALLEL

    async def run_stream(
        self, step_input: StepInput, context: RunContext
    ) -> AsyncIterator[Any]:
        logger.debug(f"  🔀 [并发] `{self.name}` 开启了 {len(self.steps)} 个并发任务")

        queue = asyncio.Queue()
        bg_tasks = []

        async def worker(idx: int, s_obj: Any, c_ctx: RunContext):
            try:
                async for evt in s_obj.aexecute_stream(step_input, c_ctx):
                    await queue.put(("event", evt))
            except asyncio.CancelledError:
                pass
            except Exception as e:
                await queue.put(("error", e, getattr(s_obj, "name", f"step_{idx}")))
            finally:
                await queue.put(
                    ("done", idx, c_ctx.state, getattr(c_ctx, "upstream_results", {}))
                )

        for i, step_obj in enumerate(self.steps):
            child_context = context.clone_for_execution()
            task = asyncio.create_task(worker(i, step_obj, child_context))
            bg_tasks.append(task)

        completed = 0
        all_outputs: list[StepOutput] = []
        aggregated_content_parts = [f"## 并发执行结果汇总 [{self.name}]\n"]
        has_any_failure = False
        early_stopped = False

        while completed < len(self.steps):
            msg_type, *data = await queue.get()
            if msg_type == "event":
                if isinstance(data[0], StepOutput):
                    out = cast(StepOutput, data[0])
                    all_outputs.append(out)
                    if not out.success:
                        has_any_failure = True
                    status_icon = "✅ 成功" if out.success else "❌ 失败"
                    aggregated_content_parts.append(
                        f"### {status_icon}: {out.step_name}\n{out.content}"
                    )
                    if out.stop and not early_stopped:
                        early_stopped = True
                        logger.info(
                            f"并行分支 '{out.step_name}' 请求终止，"
                            "正在取消其他并发任务..."
                        )
                        for t in bg_tasks:
                            if not t.done():
                                t.cancel()
                else:
                    yield data[0]
            elif msg_type == "error":
                err, s_name = data
                logger.error(f"并发步骤 '{s_name}' 执行崩溃: {err}")
                out = StepOutput(
                    step_name=s_name,
                    step_type=StepType.STEP,
                    content=f"执行崩溃: {err}",
                    success=False,
                    error=str(err),
                )
                all_outputs.append(out)
                has_any_failure = True
                aggregated_content_parts.append(f"### ❌ 失败: {s_name}\n{err}")
            elif msg_type == "done":
                _, child_state, child_upstream_results = data
                context.state.update(child_state)
                context.upstream_results.update(child_upstream_results)
                completed += 1

        yield StepOutput(
            content="\n\n".join(aggregated_content_parts),
            success=not has_any_failure,
            is_paused=any(getattr(o, "is_paused", False) for o in all_outputs),
            steps=all_outputs,
            stop=any(getattr(o, "stop", False) for o in all_outputs),
        )

        logger.debug(f"  ✅ [并发] `{self.name}` 执行完毕")


class NodeFactory:
    """统一节点装配工厂"""

    @classmethod
    def _create_step(
        cls,
        executor: NodeSource,
        name: str | None = None,
        requires_confirmation: bool = False,
        confirmation_message: str | None = None,
        failure_policy: Any = None,
    ) -> BaseNode:
        """底层物理实例化分发"""
        from zhenxun.services.ai.flow.base import BaseRunnable

        kwargs = {
            "name": name,
            "executor": executor,
            "requires_confirmation": requires_confirmation,
            "confirmation_message": confirmation_message,
            "failure_policy": failure_policy,
        }
        if isinstance(executor, BaseRunnable):
            return RunnableNode(**kwargs)
        elif callable(executor):
            return FunctionNode(**kwargs)
        raise ValueError(f"执行器类型 {type(executor)} 无法转换为叶子节点(Step)。")

    @staticmethod
    def build(item: NodeSource, name: str | None = None) -> BaseNode:
        if isinstance(item, BaseNode):
            if name and item.name in (
                "unnamed_step",
                "StepsGroup",
                "ParallelGroup",
                "ConditionGroup",
                "RouterGroup",
                "LoopGroup",
            ):
                item.name = name
            return item

        if isinstance(item, BaseRunnable) or callable(item):
            cond_meta = getattr(item, "__workflow_condition_meta__", None)
            if cond_meta:
                final_name = name or cond_meta.name or "ConditionGroup"
                return Condition(
                    evaluator=item,
                    steps=cond_meta.if_true,
                    else_steps=cond_meta.if_false,
                    name=final_name,
                )

            router_meta = getattr(item, "__workflow_router_meta__", None)
            if router_meta:
                final_name = name or router_meta.name or "RouterGroup"
                return Router(
                    selector=item,
                    choices=router_meta.choices,
                    name=final_name,
                )

            step_meta = getattr(item, "__workflow_step_meta__", None)
            if step_meta:
                final_name = name or step_meta.name
                return NodeFactory._create_step(
                    executor=item,
                    name=final_name,
                    requires_confirmation=step_meta.requires_confirmation,
                    confirmation_message=step_meta.confirmation_message,
                    failure_policy=step_meta.failure_policy,
                )

            return NodeFactory._create_step(executor=item, name=name)

        raise ValueError(
            f"无法将类型 {type(item)} 装配为工作流节点。"
            "支持的类型：BaseRunnable, Callable 或 BaseNode。"
        )