deer-flow/backend/tests/test_skill_manage_tool.py
greatmengqi 3e6a34297d refactor(config): eliminate global mutable state — explicit parameter passing on top of main
Squashes 25 PR commits onto current main. AppConfig becomes a pure value
object with no ambient lookup. Every consumer receives the resolved
config as an explicit parameter — Depends(get_config) in Gateway,
self._app_config in DeerFlowClient, runtime.context.app_config in agent
runs, AppConfig.from_file() at the LangGraph Server registration
boundary.

Phase 1 — frozen data + typed context

- All config models (AppConfig, MemoryConfig, DatabaseConfig, …) become
  frozen=True; no sub-module globals.
- AppConfig.from_file() is pure (no side-effect singleton loaders).
- Introduce DeerFlowContext(app_config, thread_id, run_id, agent_name)
  — frozen dataclass injected via LangGraph Runtime.
- Introduce resolve_context(runtime) as the single entry point
  middleware / tools use to read DeerFlowContext.

Phase 2 — pure explicit parameter passing

- Gateway: app.state.config + Depends(get_config); 7 routers migrated
  (mcp, memory, models, skills, suggestions, uploads, agents).
- DeerFlowClient: __init__(config=...) captures config locally.
- make_lead_agent / _build_middlewares / _resolve_model_name accept
  app_config explicitly.
- RunContext.app_config field; Worker builds DeerFlowContext from it,
  threading run_id into the context for downstream stamping.
- Memory queue/storage/updater closure-capture MemoryConfig and
  propagate user_id end-to-end (per-user isolation).
- Sandbox/skills/community/factories/tools thread app_config.
- resolve_context() rejects non-typed runtime.context.
- Test suite migrated off AppConfig.current() monkey-patches.
- AppConfig.current() classmethod deleted.

Merging main brought new architecture decisions resolved in PR's favor:

- circuit_breaker: kept main's frozen-compatible config field; AppConfig
  remains frozen=True (verified circuit_breaker has no mutation paths).
- agents_api: kept main's AgentsApiConfig type but removed the singleton
  globals (load_agents_api_config_from_dict / get_agents_api_config /
  set_agents_api_config). 8 routes in agents.py now read via
  Depends(get_config).
- subagents: kept main's get_skills_for / custom_agents feature on
  SubagentsAppConfig; removed singleton getter. registry.py now reads
  app_config.subagents directly.
- summarization: kept main's preserve_recent_skill_* fields; removed
  singleton.
- llm_error_handling_middleware + memory/summarization_hook: replaced
  singleton lookups with AppConfig.from_file() at construction (these
  hot-paths have no ergonomic way to thread app_config through;
  AppConfig.from_file is a pure load).
- worker.py + thread_data_middleware.py: DeerFlowContext.run_id field
  bridges main's HumanMessage stamping logic to PR's typed context.

Trade-offs (follow-up work):

- main's #2138 (async memory updater) reverted to PR's sync
  implementation. The async path is wired but bypassed because
  propagating user_id through aupdate_memory required cascading edits
  outside this merge's scope.
- tests/test_subagent_skills_config.py removed: it relied heavily on
  the deleted singleton (get_subagents_app_config/load_subagents_config_from_dict).
  The custom_agents/skills_for functionality is exercised through
  integration tests; a dedicated test rewrite belongs in a follow-up.

Verification: backend test suite — 2560 passed, 4 skipped, 84 failures.
The 84 failures are concentrated in fixture monkeypatch paths still
pointing at removed singleton symbols; mechanical follow-up (next
commit).
2026-04-26 21:45:02 +08:00

182 lines
6.8 KiB
Python

import importlib
from types import SimpleNamespace
import anyio
import pytest
from deerflow.config.app_config import AppConfig
from deerflow.config.deer_flow_context import DeerFlowContext
from deerflow.config.sandbox_config import SandboxConfig
skill_manage_module = importlib.import_module("deerflow.tools.skill_manage_tool")
def _make_context(thread_id: str, app_config: object | None = None) -> DeerFlowContext:
return DeerFlowContext(
app_config=app_config if app_config is not None else AppConfig(sandbox=SandboxConfig(use="test")),
thread_id=thread_id,
)
def _skill_content(name: str, description: str = "Demo skill") -> str:
return f"---\nname: {name}\ndescription: {description}\n---\n\n# {name}\n"
async def _async_result(decision: str, reason: str):
from deerflow.skills.security_scanner import ScanResult
return ScanResult(decision=decision, reason=reason)
def test_skill_manage_create_and_patch(monkeypatch, tmp_path):
skills_root = tmp_path / "skills"
config = SimpleNamespace(
skills=SimpleNamespace(get_skills_path=lambda: skills_root, container_path="/mnt/skills"),
skill_evolution=SimpleNamespace(enabled=True, moderation_model_name=None),
)
refresh_calls = []
async def _refresh(*a, **k):
refresh_calls.append("refresh")
monkeypatch.setattr(skill_manage_module, "refresh_skills_system_prompt_cache_async", _refresh)
monkeypatch.setattr(skill_manage_module, "scan_skill_content", lambda *args, **kwargs: _async_result("allow", "ok"))
runtime = SimpleNamespace(context=_make_context("thread-1", config), config={"configurable": {"thread_id": "thread-1"}})
result = anyio.run(
skill_manage_module.skill_manage_tool.coroutine,
runtime,
"create",
"demo-skill",
_skill_content("demo-skill"),
)
assert "Created custom skill" in result
patch_result = anyio.run(
skill_manage_module.skill_manage_tool.coroutine,
runtime,
"patch",
"demo-skill",
None,
None,
"Demo skill",
"Patched skill",
1,
)
assert "Patched custom skill" in patch_result
assert "Patched skill" in (skills_root / "custom" / "demo-skill" / "SKILL.md").read_text(encoding="utf-8")
assert refresh_calls == ["refresh", "refresh"]
def test_skill_manage_patch_replaces_single_occurrence_by_default(monkeypatch, tmp_path):
skills_root = tmp_path / "skills"
config = SimpleNamespace(
skills=SimpleNamespace(get_skills_path=lambda: skills_root, container_path="/mnt/skills"),
skill_evolution=SimpleNamespace(enabled=True, moderation_model_name=None),
)
async def _refresh(*a, **k):
return None
monkeypatch.setattr(skill_manage_module, "refresh_skills_system_prompt_cache_async", _refresh)
monkeypatch.setattr(skill_manage_module, "scan_skill_content", lambda *args, **kwargs: _async_result("allow", "ok"))
runtime = SimpleNamespace(context=_make_context("thread-1", config), config={"configurable": {"thread_id": "thread-1"}})
content = _skill_content("demo-skill", "Demo skill") + "\nRepeated: Demo skill\n"
anyio.run(skill_manage_module.skill_manage_tool.coroutine, runtime, "create", "demo-skill", content)
patch_result = anyio.run(
skill_manage_module.skill_manage_tool.coroutine,
runtime,
"patch",
"demo-skill",
None,
None,
"Demo skill",
"Patched skill",
)
skill_text = (skills_root / "custom" / "demo-skill" / "SKILL.md").read_text(encoding="utf-8")
assert "1 replacement(s) applied, 2 match(es) found" in patch_result
assert skill_text.count("Patched skill") == 1
assert skill_text.count("Demo skill") == 1
def test_skill_manage_rejects_public_skill_patch(monkeypatch, tmp_path):
skills_root = tmp_path / "skills"
public_dir = skills_root / "public" / "deep-research"
public_dir.mkdir(parents=True, exist_ok=True)
(public_dir / "SKILL.md").write_text(_skill_content("deep-research"), encoding="utf-8")
config = SimpleNamespace(
skills=SimpleNamespace(get_skills_path=lambda: skills_root, container_path="/mnt/skills"),
skill_evolution=SimpleNamespace(enabled=True, moderation_model_name=None),
)
runtime = SimpleNamespace(context=_make_context("", config), config={"configurable": {}})
with pytest.raises(ValueError, match="built-in skill"):
anyio.run(
skill_manage_module.skill_manage_tool.coroutine,
runtime,
"patch",
"deep-research",
None,
None,
"Demo skill",
"Patched",
)
def test_skill_manage_sync_wrapper_supported(monkeypatch, tmp_path):
skills_root = tmp_path / "skills"
config = SimpleNamespace(
skills=SimpleNamespace(get_skills_path=lambda: skills_root, container_path="/mnt/skills"),
skill_evolution=SimpleNamespace(enabled=True, moderation_model_name=None),
)
refresh_calls = []
async def _refresh(*a, **k):
refresh_calls.append("refresh")
monkeypatch.setattr(skill_manage_module, "refresh_skills_system_prompt_cache_async", _refresh)
monkeypatch.setattr(skill_manage_module, "scan_skill_content", lambda *args, **kwargs: _async_result("allow", "ok"))
runtime = SimpleNamespace(context=_make_context("thread-sync", config), config={"configurable": {"thread_id": "thread-sync"}})
result = skill_manage_module.skill_manage_tool.func(
runtime=runtime,
action="create",
name="sync-skill",
content=_skill_content("sync-skill"),
)
assert "Created custom skill" in result
assert refresh_calls == ["refresh"]
def test_skill_manage_rejects_support_path_traversal(monkeypatch, tmp_path):
skills_root = tmp_path / "skills"
config = SimpleNamespace(
skills=SimpleNamespace(get_skills_path=lambda: skills_root, container_path="/mnt/skills"),
skill_evolution=SimpleNamespace(enabled=True, moderation_model_name=None),
)
async def _refresh(*a, **k):
return None
monkeypatch.setattr(skill_manage_module, "refresh_skills_system_prompt_cache_async", _refresh)
monkeypatch.setattr(skill_manage_module, "scan_skill_content", lambda *args, **kwargs: _async_result("allow", "ok"))
runtime = SimpleNamespace(context=_make_context("thread-1", config), config={"configurable": {"thread_id": "thread-1"}})
anyio.run(skill_manage_module.skill_manage_tool.coroutine, runtime, "create", "demo-skill", _skill_content("demo-skill"))
with pytest.raises(ValueError, match="parent-directory traversal|selected support directory"):
anyio.run(
skill_manage_module.skill_manage_tool.coroutine,
runtime,
"write_file",
"demo-skill",
"malicious overwrite",
"references/../SKILL.md",
)