116 lines
4.0 KiB
Python
116 lines
4.0 KiB
Python
"""``ConsciousnessNode.start_workflow_design`` fire workflow task 的提交逻辑。
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历史上这里有一个常驻的 ``WorkflowRunningEngine`` actor 做中转，现已删除：
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workflow 是一次性、有头有尾的执行，直接以 ``asyncio.create_task`` 触发
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``run_workflow_task``。本测试保证 ConsciousnessNode 在工作流生成后正确 fire，
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并通过 ``put_pending`` 推送 SSE 进度（节点端写 pending → API 端 SSE 读 pending）。
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"""
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from __future__ import annotations
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import asyncio
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from unittest.mock import AsyncMock, MagicMock
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import pytest
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from kilostar.core.work.workflow import workflow_engine as engine_module
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from kilostar.core.work.workflow.workflow import KiloStarWorkflow
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from kilostar.core.work.workflow.model import WorkflowMetadata
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@pytest.fixture
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def consciousness_instance():
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from kilostar.core.individual.consciousness_node.consciousness_node import (
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ConsciousnessNode,
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)
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from kilostar.utils.logger import get_logger
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obj = ConsciousnessNode.__new__(ConsciousnessNode)
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obj.logger = get_logger("consciousness_node")
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obj.agent = None
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return obj
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@pytest.mark.asyncio
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async def test_start_workflow_design_fires_run_workflow_task(
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consciousness_instance, fake_actors, monkeypatch
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):
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"""快乐路径：working 返回 ForWorkflowEngine，应 fire run_workflow_task 且推送 pending。"""
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from kilostar.core.individual.consciousness_node.template import (
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ForWorkflowEngine,
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)
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wf = KiloStarWorkflow(
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title="t",
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work_link=[],
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workflow_metadata=WorkflowMetadata(),
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)
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consciousness_instance.working = AsyncMock(
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return_value=ForWorkflowEngine(workflow=wf, reasoning="r")
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)
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postgres = MagicMock()
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postgres.get_all_worker_individual = AsyncMock(return_value=[])
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postgres.update_workflow_status = AsyncMock()
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fake_actors.register("postgres_database", postgres)
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pending_writes: list[tuple[str, str]] = []
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gwm = MagicMock()
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gwm.put_pending = AsyncMock(
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side_effect=lambda tid, msg: pending_writes.append((tid, msg))
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)
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fake_actors.register("global_workflow_manager", gwm)
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captured: dict = {}
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async def _fake_task(workflow_dict, trace_id):
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captured["workflow_dict"] = workflow_dict
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captured["trace_id"] = trace_id
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monkeypatch.setattr(engine_module, "run_workflow_task", _fake_task)
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await consciousness_instance.start_workflow_design("trace-123", "do something")
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# 让 create_task 调度的协程跑完
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await asyncio.sleep(0)
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assert captured["trace_id"] == "trace-123"
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assert captured["workflow_dict"]["title"] == "t"
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# SSE 推送方向必须是 pending（put_pending）
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assert any("正在为您构建" in msg for _, msg in pending_writes)
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assert any("即将开始执行" in msg for _, msg in pending_writes)
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@pytest.mark.asyncio
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async def test_start_workflow_design_failed_path_marks_failed(
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consciousness_instance, fake_actors, monkeypatch
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):
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"""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。"""
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consciousness_instance.working = AsyncMock(return_value=None)
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postgres = MagicMock()
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postgres.get_all_worker_individual = AsyncMock(return_value=[])
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postgres.update_workflow_status = AsyncMock()
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fake_actors.register("postgres_database", postgres)
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pending_writes: list[tuple[str, str]] = []
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gwm = MagicMock()
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gwm.put_pending = AsyncMock(
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side_effect=lambda tid, msg: pending_writes.append((tid, msg))
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)
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fake_actors.register("global_workflow_manager", gwm)
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fired: list = []
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async def _fake_task(*a, **kw):
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fired.append((a, kw))
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monkeypatch.setattr(engine_module, "run_workflow_task", _fake_task)
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await consciousness_instance.start_workflow_design("trace-x", "cmd")
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await asyncio.sleep(0)
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assert fired == [] # 没有 fire workflow task
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postgres.update_workflow_status.assert_awaited_with("trace-x", "failed")
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assert any("生成失败" in msg for _, msg in pending_writes)
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