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).

backend/packages/harness/deerflow/community/aio_sandbox/aio_sandbox_provider.py

@@ -25,8 +25,9 @@ except ImportError:  # pragma: no cover - Windows fallback
     fcntl = None  # type: ignore[assignment]
     import msvcrt
 
-from deerflow.config import get_app_config
+from deerflow.config.app_config import AppConfig
 from deerflow.config.paths import VIRTUAL_PATH_PREFIX, get_paths
+from deerflow.runtime.user_context import get_effective_user_id
 from deerflow.sandbox.sandbox import Sandbox
 from deerflow.sandbox.sandbox_provider import SandboxProvider
 
@@ -89,7 +90,8 @@ class AioSandboxProvider(SandboxProvider):
           API_KEY: $MY_API_KEY
     """
 
-    def __init__(self):
+    def __init__(self, app_config: "AppConfig"):
+        self._app_config = app_config
         self._lock = threading.Lock()
         self._sandboxes: dict[str, AioSandbox] = {}  # sandbox_id -> AioSandbox instance
         self._sandbox_infos: dict[str, SandboxInfo] = {}  # sandbox_id -> SandboxInfo (for destroy)
@@ -158,8 +160,7 @@ class AioSandboxProvider(SandboxProvider):
 
     def _load_config(self) -> dict:
         """Load sandbox configuration from app config."""
-        config = get_app_config()
-        sandbox_config = config.sandbox
+        sandbox_config = self._app_config.sandbox
 
         idle_timeout = getattr(sandbox_config, "idle_timeout", None)
         replicas = getattr(sandbox_config, "replicas", None)
@@ -270,28 +271,27 @@ class AioSandboxProvider(SandboxProvider):
         mounted Docker socket (DooD), the host Docker daemon can resolve the paths.
         """
         paths = get_paths()
-        paths.ensure_thread_dirs(thread_id)
+        user_id = get_effective_user_id()
+        paths.ensure_thread_dirs(thread_id, user_id=user_id)
 
         return [
-            (paths.host_sandbox_work_dir(thread_id), f"{VIRTUAL_PATH_PREFIX}/workspace", False),
-            (paths.host_sandbox_uploads_dir(thread_id), f"{VIRTUAL_PATH_PREFIX}/uploads", False),
-            (paths.host_sandbox_outputs_dir(thread_id), f"{VIRTUAL_PATH_PREFIX}/outputs", False),
+            (paths.host_sandbox_work_dir(thread_id, user_id=user_id), f"{VIRTUAL_PATH_PREFIX}/workspace", False),
+            (paths.host_sandbox_uploads_dir(thread_id, user_id=user_id), f"{VIRTUAL_PATH_PREFIX}/uploads", False),
+            (paths.host_sandbox_outputs_dir(thread_id, user_id=user_id), f"{VIRTUAL_PATH_PREFIX}/outputs", False),
             # ACP workspace: read-only inside the sandbox (lead agent reads results;
             # the ACP subprocess writes from the host side, not from within the container).
-            (paths.host_acp_workspace_dir(thread_id), "/mnt/acp-workspace", True),
+            (paths.host_acp_workspace_dir(thread_id, user_id=user_id), "/mnt/acp-workspace", True),
         ]
 
-    @staticmethod
-    def _get_skills_mount() -> tuple[str, str, bool] | None:
+    def _get_skills_mount(self) -> tuple[str, str, bool] | None:
         """Get the skills directory mount configuration.
 
         Mount source uses DEER_FLOW_HOST_SKILLS_PATH when running inside Docker (DooD)
         so the host Docker daemon can resolve the path.
         """
         try:
-            config = get_app_config()
-            skills_path = config.skills.get_skills_path()
-            container_path = config.skills.container_path
+            skills_path = self._app_config.skills.get_skills_path()
+            container_path = self._app_config.skills.container_path
 
             if skills_path.exists():
                 # When running inside Docker with DooD, use host-side skills path.
@@ -490,8 +490,9 @@ class AioSandboxProvider(SandboxProvider):
         across multiple processes, preventing container-name conflicts.
         """
         paths = get_paths()
-        paths.ensure_thread_dirs(thread_id)
-        lock_path = paths.thread_dir(thread_id) / f"{sandbox_id}.lock"
+        user_id = get_effective_user_id()
+        paths.ensure_thread_dirs(thread_id, user_id=user_id)
+        lock_path = paths.thread_dir(thread_id, user_id=user_id) / f"{sandbox_id}.lock"
 
         with open(lock_path, "a", encoding="utf-8") as lock_file:
             locked = False