"""``ConsciousnessNode.start_workflow_design`` fire workflow task 的提交逻辑。

历史上这里有一个常驻的 ``WorkflowRunningEngine`` actor 做中转，现已删除：
workflow 是一次性、有头有尾的执行，直接以 ``asyncio.create_task`` 触发
``run_workflow_task``。本测试保证 ConsciousnessNode 在工作流生成后正确 fire，
并通过 ``put_pending`` 推送 SSE 进度（节点端写 pending → API 端 SSE 读 pending）。
"""

from __future__ import annotations

import asyncio
from unittest.mock import AsyncMock, MagicMock

import pytest

from kilostar.core.work.workflow import workflow_engine as engine_module
from kilostar.core.work.workflow.workflow import KiloStarWorkflow
from kilostar.core.work.workflow.model import WorkflowMetadata


@pytest.fixture
def consciousness_instance():
    from kilostar.core.individual.consciousness_node.consciousness_node import (
        ConsciousnessNode,
    )
    from kilostar.utils.logger import get_logger

    obj = ConsciousnessNode.__new__(ConsciousnessNode)
    obj.logger = get_logger("consciousness_node")
    obj.agent = None
    return obj


@pytest.mark.asyncio
async def test_start_workflow_design_fires_run_workflow_task(
    consciousness_instance, fake_actors, monkeypatch
):
    """快乐路径：working 返回 ForWorkflowEngine，应 fire run_workflow_task 且推送 pending。"""
    from kilostar.core.individual.consciousness_node.template import (
        ForWorkflowEngine,
    )

    wf = KiloStarWorkflow(
        title="t",
        work_link=[],
        workflow_metadata=WorkflowMetadata(),
    )

    consciousness_instance.working = AsyncMock(
        return_value=ForWorkflowEngine(workflow=wf, reasoning="r")
    )

    postgres = MagicMock()
    postgres.get_all_worker_individual = AsyncMock(return_value=[])
    postgres.update_workflow_status = AsyncMock()
    fake_actors.register("postgres_database", postgres)

    pending_writes: list[tuple[str, str]] = []
    gwm = MagicMock()
    gwm.put_pending = AsyncMock(
        side_effect=lambda tid, msg: pending_writes.append((tid, msg))
    )
    fake_actors.register("global_workflow_manager", gwm)

    captured: dict = {}

    async def _fake_task(workflow_dict, trace_id):
        captured["workflow_dict"] = workflow_dict
        captured["trace_id"] = trace_id

    monkeypatch.setattr(engine_module, "run_workflow_task", _fake_task)

    await consciousness_instance.start_workflow_design("trace-123", "do something")
    # 让 create_task 调度的协程跑完
    await asyncio.sleep(0)

    assert captured["trace_id"] == "trace-123"
    assert captured["workflow_dict"]["title"] == "t"
    # SSE 推送方向必须是 pending（put_pending）
    assert any("正在为您构建" in msg for _, msg in pending_writes)
    assert any("即将开始执行" in msg for _, msg in pending_writes)


@pytest.mark.asyncio
async def test_start_workflow_design_failed_path_marks_failed(
    consciousness_instance, fake_actors, monkeypatch
):
    """working 返回 None / 不匹配类型时应推送失败提示并把 workflow 状态置为 failed。"""
    consciousness_instance.working = AsyncMock(return_value=None)

    postgres = MagicMock()
    postgres.get_all_worker_individual = AsyncMock(return_value=[])
    postgres.update_workflow_status = AsyncMock()
    fake_actors.register("postgres_database", postgres)

    pending_writes: list[tuple[str, str]] = []
    gwm = MagicMock()
    gwm.put_pending = AsyncMock(
        side_effect=lambda tid, msg: pending_writes.append((tid, msg))
    )
    fake_actors.register("global_workflow_manager", gwm)

    fired: list = []

    async def _fake_task(*a, **kw):
        fired.append((a, kw))

    monkeypatch.setattr(engine_module, "run_workflow_task", _fake_task)

    await consciousness_instance.start_workflow_design("trace-x", "cmd")
    await asyncio.sleep(0)

    assert fired == []  # 没有 fire workflow task
    postgres.update_workflow_status.assert_awaited_with("trace-x", "failed")
    assert any("生成失败" in msg for _, msg in pending_writes)