deer-flow/backend/tests/test_memory_storage_user_isolation.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

169 lines
6.9 KiB
Python

# --- Phase 2 config-refactor test helper ---
# Memory APIs now take MemoryConfig / AppConfig explicitly. Tests construct a
# minimal config once and reuse it across call sites.
from deerflow.config.app_config import AppConfig as _TestAppConfig
from deerflow.config.memory_config import MemoryConfig as _TestMemoryConfig
from deerflow.config.sandbox_config import SandboxConfig as _TestSandboxConfig
_TEST_MEMORY_CONFIG = _TestMemoryConfig(enabled=True)
_TEST_APP_CONFIG = _TestAppConfig(sandbox=_TestSandboxConfig(use="test"), memory=_TEST_MEMORY_CONFIG)
# -------------------------------------------
"""Tests for per-user memory storage isolation."""
import pytest
from pathlib import Path
from unittest.mock import patch
from deerflow.agents.memory.storage import FileMemoryStorage, create_empty_memory
from deerflow.config.app_config import AppConfig
from deerflow.config.memory_config import MemoryConfig
from deerflow.config.sandbox_config import SandboxConfig
def _mock_app_config() -> AppConfig:
"""Build a minimal AppConfig with default (empty) memory storage_path."""
return AppConfig(sandbox=SandboxConfig(use="test"), memory=MemoryConfig(storage_path=""))
@pytest.fixture
def base_dir(tmp_path: Path) -> Path:
return tmp_path
@pytest.fixture
def storage() -> FileMemoryStorage:
return FileMemoryStorage(_TEST_MEMORY_CONFIG)
class TestUserIsolatedStorage:
def test_save_and_load_per_user(self, storage: FileMemoryStorage, base_dir: Path):
from deerflow.config.paths import Paths
paths = Paths(base_dir)
with patch("deerflow.agents.memory.storage.get_paths", return_value=paths):
memory_a = create_empty_memory()
memory_a["user"]["workContext"]["summary"] = "User A context"
storage.save(memory_a, user_id="alice")
memory_b = create_empty_memory()
memory_b["user"]["workContext"]["summary"] = "User B context"
storage.save(memory_b, user_id="bob")
loaded_a = storage.load(user_id="alice")
loaded_b = storage.load(user_id="bob")
assert loaded_a["user"]["workContext"]["summary"] == "User A context"
assert loaded_b["user"]["workContext"]["summary"] == "User B context"
def test_user_memory_file_location(self, base_dir: Path):
from deerflow.config.paths import Paths
paths = Paths(base_dir)
with patch("deerflow.agents.memory.storage.get_paths", return_value=paths):
s = FileMemoryStorage(_TEST_MEMORY_CONFIG)
memory = create_empty_memory()
s.save(memory, user_id="alice")
expected_path = base_dir / "users" / "alice" / "memory.json"
assert expected_path.exists()
def test_cache_isolated_per_user(self, base_dir: Path):
from deerflow.config.paths import Paths
paths = Paths(base_dir)
with patch("deerflow.agents.memory.storage.get_paths", return_value=paths):
s = FileMemoryStorage(_TEST_MEMORY_CONFIG)
memory_a = create_empty_memory()
memory_a["user"]["workContext"]["summary"] = "A"
s.save(memory_a, user_id="alice")
memory_b = create_empty_memory()
memory_b["user"]["workContext"]["summary"] = "B"
s.save(memory_b, user_id="bob")
loaded_a = s.load(user_id="alice")
assert loaded_a["user"]["workContext"]["summary"] == "A"
def test_no_user_id_uses_legacy_path(self, base_dir: Path):
from deerflow.config.paths import Paths
paths = Paths(base_dir)
with patch("deerflow.agents.memory.storage.get_paths", return_value=paths):
s = FileMemoryStorage(_TEST_MEMORY_CONFIG)
memory = create_empty_memory()
s.save(memory, user_id=None)
expected_path = base_dir / "memory.json"
assert expected_path.exists()
def test_user_and_legacy_do_not_interfere(self, base_dir: Path):
"""user_id=None (legacy) and user_id='alice' must use different files and caches."""
from deerflow.config.paths import Paths
paths = Paths(base_dir)
with patch("deerflow.agents.memory.storage.get_paths", return_value=paths):
s = FileMemoryStorage(_TEST_MEMORY_CONFIG)
legacy_mem = create_empty_memory()
legacy_mem["user"]["workContext"]["summary"] = "legacy"
s.save(legacy_mem, user_id=None)
user_mem = create_empty_memory()
user_mem["user"]["workContext"]["summary"] = "alice"
s.save(user_mem, user_id="alice")
assert s.load(user_id=None)["user"]["workContext"]["summary"] == "legacy"
assert s.load(user_id="alice")["user"]["workContext"]["summary"] == "alice"
def test_user_agent_memory_file_location(self, base_dir: Path):
"""Per-user per-agent memory uses the user_agent_memory_file path."""
from deerflow.config.paths import Paths
paths = Paths(base_dir)
with patch("deerflow.agents.memory.storage.get_paths", return_value=paths):
s = FileMemoryStorage(_TEST_MEMORY_CONFIG)
memory = create_empty_memory()
memory["user"]["workContext"]["summary"] = "agent scoped"
s.save(memory, "test-agent", user_id="alice")
expected_path = base_dir / "users" / "alice" / "agents" / "test-agent" / "memory.json"
assert expected_path.exists()
def test_cache_key_is_user_agent_tuple(self, base_dir: Path):
"""Cache keys must be (user_id, agent_name) tuples, not bare agent names."""
from deerflow.config.paths import Paths
paths = Paths(base_dir)
with patch("deerflow.agents.memory.storage.get_paths", return_value=paths):
s = FileMemoryStorage(_TEST_MEMORY_CONFIG)
memory = create_empty_memory()
s.save(memory, user_id="alice")
# After save, cache should have tuple key
assert ("alice", None) in s._memory_cache
def test_reload_with_user_id(self, base_dir: Path):
"""reload() with user_id should force re-read from the user-scoped file."""
from deerflow.config.paths import Paths
paths = Paths(base_dir)
with patch("deerflow.agents.memory.storage.get_paths", return_value=paths):
s = FileMemoryStorage(_TEST_MEMORY_CONFIG)
memory = create_empty_memory()
memory["user"]["workContext"]["summary"] = "initial"
s.save(memory, user_id="alice")
# Load once to prime cache
s.load(user_id="alice")
# Write updated content directly to file
user_file = base_dir / "users" / "alice" / "memory.json"
import json
updated = create_empty_memory()
updated["user"]["workContext"]["summary"] = "updated"
user_file.write_text(json.dumps(updated))
# reload should pick up the new content
reloaded = s.reload(user_id="alice")
assert reloaded["user"]["workContext"]["summary"] == "updated"