fix: keep lead agent graph factory signature compatible

backend/packages/harness/deerflow/agents/lead_agent/agent.py

@@ -314,13 +314,18 @@ def _build_middlewares(
     return middlewares
 
 
-def make_lead_agent(config: RunnableConfig, app_config: AppConfig | None = None):
+def make_lead_agent(config: RunnableConfig):
+    """LangGraph graph factory; keep the signature compatible with LangGraph Server."""
+    return _make_lead_agent(config, app_config=get_app_config())
+
+
+def _make_lead_agent(config: RunnableConfig, *, app_config: AppConfig):
     # Lazy import to avoid circular dependency
     from deerflow.tools import get_available_tools
     from deerflow.tools.builtins import setup_agent
 
     cfg = _get_runtime_config(config)
-    resolved_app_config = app_config or get_app_config()
+    resolved_app_config = app_config
 
     thinking_enabled = cfg.get("thinking_enabled", True)
     reasoning_effort = cfg.get("reasoning_effort", None)

backend/tests/test_lead_agent_model_resolution.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import inspect
 from unittest.mock import MagicMock
 
 import pytest
@@ -33,6 +34,44 @@ def _make_model(name: str, *, supports_thinking: bool) -> ModelConfig:
     )
 
 
+def test_make_lead_agent_signature_matches_langgraph_server_factory_abi():
+    assert list(inspect.signature(lead_agent_module.make_lead_agent).parameters) == ["config"]
+
+
+def test_internal_make_lead_agent_uses_explicit_app_config(monkeypatch):
+    app_config = _make_app_config([_make_model("explicit-model", supports_thinking=False)])
+
+    import deerflow.tools as tools_module
+
+    def _raise_get_app_config():
+        raise AssertionError("ambient get_app_config() must not be used when app_config is explicit")
+
+    monkeypatch.setattr(lead_agent_module, "get_app_config", _raise_get_app_config)
+    monkeypatch.setattr(tools_module, "get_available_tools", lambda **kwargs: [])
+    monkeypatch.setattr(lead_agent_module, "_build_middlewares", lambda config, model_name, agent_name=None, **kwargs: [])
+
+    captured: dict[str, object] = {}
+
+    def _fake_create_chat_model(*, name, thinking_enabled, reasoning_effort=None, app_config=None):
+        captured["name"] = name
+        captured["app_config"] = app_config
+        return object()
+
+    monkeypatch.setattr(lead_agent_module, "create_chat_model", _fake_create_chat_model)
+    monkeypatch.setattr(lead_agent_module, "create_agent", lambda **kwargs: kwargs)
+
+    result = lead_agent_module._make_lead_agent(
+        {"configurable": {"model_name": "explicit-model"}},
+        app_config=app_config,
+    )
+
+    assert captured == {
+        "name": "explicit-model",
+        "app_config": app_config,
+    }
+    assert result["model"] is not None
+
+
 def test_resolve_model_name_falls_back_to_default(monkeypatch, caplog):
     app_config = _make_app_config(
         [