Files
nmfs-agents/tests/test_integration_full.py
qiuruiandClaude Sonnet 4.6 df59fc0c83 feat: NMFS Agents 全量入库(org v2 + dashboard + 多队列 + 组织架构)
包含从项目创建至今的全部代码首次入库:

核心框架:
- TaskQueue(SQLite,6 种状态,原子 dequeue)
- Executor(asyncio 并发,semaphore 限流,agent_role 路由)
- Scheduler(APScheduler,三队列独立调度)
- Watchdog(超时检测 + 优先级防饥饿)
- Scanner(项目扫描,README/TODO/CLAUDE.md 提取)

Agent 体系(20+ 角色):
- 项目交付组:architect/developer/tester/productizer
- 基础技术组:base-architect/validator/hw/os/kernel/lowlevel/system-tester
- 算法组:algo-antishake/position/nav
- 洞察组:planner/vision-analyst/media-producer
- 市场组:market-pm/sport/elder/safety
- 组织层:boss/group-leader/senior-dev/ops
- 平台扩展:nrf-dev/esp32-dev
- 三专项调研:rtp-researcher/net-researcher/kernel-analyzer

工具层:
- ProjectMemory(goals/facts/history SQLite)
- VersionPipeline(并行版本流水线 + 反幻觉门控)
- EventBus(Redis Streams,5 consumer groups)
- DailyReport(append-only 日报 + Boss 决策视图)
- AgentScorer(4 维评分:完成度/质量/自主性/协作)
- DeviceAgent(SSH rsync + 板端执行)
- EnvCollector(本机+SSH 环境采集)
- ArchVersion(快照/优化/promote/rollback)

Dashboard(React + Vite + Tailwind):
- 看板/项目/配置/洞察/日报/Visual 六标签页
- WebSocket 实时更新
- Markdown 渲染(react-markdown + remark-gfm)

测试:314 passed

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-10 07:24:19 +08:00

92 lines
3.6 KiB
Python

from __future__ import annotations
import asyncio
import pytest
from pathlib import Path
from unittest.mock import patch, MagicMock
from nmfs_agents.agents.manager import ManagerAgent
from nmfs_agents.agents.productizer import ProductizerAgent
from nmfs_agents.agents.architect import ArchitectAgent
from nmfs_agents.config import AgentsConfig, ProjectConfig, SchedulerConfig, ClaudeConfig, FeishuConfig
from nmfs_agents.core.queue import TaskQueue, Task
def _make_project(base: Path, name: str, has_issues: bool = True) -> Path:
p = base / name
p.mkdir(parents=True)
if has_issues:
(p / "README.md").write_text(f"# {name}\n## 已知问题\n- {name} 存在待修复问题\n")
else:
(p / "README.md").write_text(f"# {name}\n## 快速开始\nfoo\n")
(p / "RELEASE.md").write_text("## v0.1\n")
(p / "pyproject.toml").write_text("[project]\nname='x'\n")
(p / "tests").mkdir()
((p / "tests") / "test_a.py").write_text("def test_a(): pass\n")
return p
def _cfg(tmp_path: Path) -> tuple[AgentsConfig, TaskQueue]:
q = TaskQueue(db_path=tmp_path / "tasks.db")
yolo = _make_project(tmp_path, "yolo", has_issues=True)
emb = _make_project(tmp_path, "embedding", has_issues=False)
cfg = AgentsConfig(
projects={
"yolo": ProjectConfig(path=yolo, mode="report"),
"embedding": ProjectConfig(path=emb, mode="report"),
},
scheduler=SchedulerConfig(max_concurrent=2),
claude=ClaudeConfig(api_key="fake"),
feishu=FeishuConfig(),
devices={},
)
return cfg, q
@pytest.mark.asyncio
async def test_manager_full_cycle(tmp_path):
"""Manager 完整循环:扫描 → 入队 → 执行 → 全部 done。"""
cfg, q = _cfg(tmp_path)
manager = ManagerAgent(cfg, queue=q)
mock_result = MagicMock(status="done", summary="分析完成")
with patch("nmfs_agents.core.executor.DeveloperAgent") as MockDev:
MockDev.return_value.run.return_value = mock_result
stats = await manager.run_cycle()
assert stats["enqueued"] >= 1
assert stats["executed"] >= 1
status = manager.get_status()
assert status.get("done", 0) >= 1
def test_productizer_evaluates_real_project(tmp_path):
"""Productizer 评估真实项目结构,高质量项目应得分 >= 50。"""
cfg, q = _cfg(tmp_path)
agent = ProductizerAgent(cfg)
task = Task(project="embedding", type="productize", title="评估",
priority=3, mode="report", agent_role="productizer", id=10)
result = agent.run(task)
assert result.status == "done"
assert agent.last_report.score >= 50
def test_architect_enqueues_from_two_projects(tmp_path):
"""Architect 分析两个项目后应提取并入队预研任务。"""
from nmfs_agents.agents.developer import AgentResult
cfg, q = _cfg(tmp_path)
agent = ArchitectAgent(cfg, queue=q)
task = Task(project="ALL", type="architect", title="全局架构分析",
priority=2, mode="report", agent_role="architect", id=11)
report = "两个项目可整合。\n预研任务:\n- [预研] 视觉语义搜索引擎\n- [预研] 统一推理 SDK"
verify_ok = MagicMock(returncode=0, stdout="claude 1.0", stderr="")
with patch("subprocess.run", return_value=verify_ok), \
patch("nmfs_agents.agents.architect._run_with_log",
return_value=AgentResult(status="done", summary=report)):
result = agent.run(task)
assert result.status == "done"
with q._conn() as c:
count = c.execute(
"SELECT COUNT(*) FROM tasks WHERE type='architect'"
).fetchone()[0]
assert count >= 2