refactor(config): thread app_config through create_chat_model and get_available_tools

Phase 2 P2-7 (partial, Categories E+F): the two highest-traffic factory
functions accept optional app_config kw-only parameter. When make_lead_agent
is called with explicit app_config (client / Gateway path), config flows
through to the model factory and tool registration without the functions
consulting AppConfig.current().

Fallback path (app_config=None → AppConfig.current()) preserved so LangGraph
Server registration and legacy tests keep working. Remaining community tool
factories, memory subsystem, skills/sandbox helpers are similar mechanical
migrations but were out of scope for this sitting.

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

@@ -354,8 +354,8 @@ def make_lead_agent(
     if is_bootstrap:
         # Special bootstrap agent with minimal prompt for initial custom agent creation flow
         return create_agent(
-            model=create_chat_model(name=model_name, thinking_enabled=thinking_enabled),
-            tools=get_available_tools(model_name=model_name, subagent_enabled=subagent_enabled) + [setup_agent],
+            model=create_chat_model(name=model_name, thinking_enabled=thinking_enabled, app_config=app_config),
+            tools=get_available_tools(model_name=model_name, subagent_enabled=subagent_enabled, app_config=app_config) + [setup_agent],
             middleware=_build_middlewares(app_config, config, model_name=model_name),
             system_prompt=apply_prompt_template(subagent_enabled=subagent_enabled, max_concurrent_subagents=max_concurrent_subagents, available_skills=set(["bootstrap"])),
             state_schema=ThreadState,
@@ -364,8 +364,8 @@ def make_lead_agent(
 
     # Default lead agent (unchanged behavior)
     return create_agent(
-        model=create_chat_model(name=model_name, thinking_enabled=thinking_enabled, reasoning_effort=reasoning_effort),
-        tools=get_available_tools(model_name=model_name, groups=agent_config.tool_groups if agent_config else None, subagent_enabled=subagent_enabled),
+        model=create_chat_model(name=model_name, thinking_enabled=thinking_enabled, reasoning_effort=reasoning_effort, app_config=app_config),
+        tools=get_available_tools(model_name=model_name, groups=agent_config.tool_groups if agent_config else None, subagent_enabled=subagent_enabled, app_config=app_config),
         middleware=_build_middlewares(app_config, config, model_name=model_name, agent_name=agent_name),
         system_prompt=apply_prompt_template(
             subagent_enabled=subagent_enabled, max_concurrent_subagents=max_concurrent_subagents, agent_name=agent_name, available_skills=set(agent_config.skills) if agent_config and agent_config.skills is not None else None

backend/packages/harness/deerflow/models/factory.py

@@ -30,16 +30,24 @@ def _vllm_disable_chat_template_kwargs(chat_template_kwargs: dict) -> dict:
     return disable_kwargs
 
 
-def create_chat_model(name: str | None = None, thinking_enabled: bool = False, **kwargs) -> BaseChatModel:
+def create_chat_model(
+    name: str | None = None,
+    thinking_enabled: bool = False,
+    *,
+    app_config: "AppConfig | None" = None,
+    **kwargs,
+) -> BaseChatModel:
     """Create a chat model instance from the config.
 
     Args:
         name: The name of the model to create. If None, the first model in the config will be used.
+        app_config: Application config. Falls back to AppConfig.current() when
+            omitted; new callers should pass this explicitly.
 
     Returns:
         A chat model instance.
     """
-    config = AppConfig.current()
+    config = app_config if app_config is not None else AppConfig.current()
     if name is None:
         name = config.models[0].name
     model_config = config.get_model_config(name)

backend/packages/harness/deerflow/tools/tools.py

@@ -37,6 +37,8 @@ def get_available_tools(
     include_mcp: bool = True,
     model_name: str | None = None,
     subagent_enabled: bool = False,
+    *,
+    app_config: AppConfig | None = None,
 ) -> list[BaseTool]:
     """Get all available tools from config.
 
@@ -48,11 +50,13 @@ def get_available_tools(
         include_mcp: Whether to include tools from MCP servers (default: True).
         model_name: Optional model name to determine if vision tools should be included.
         subagent_enabled: Whether to include subagent tools (task, task_status).
+        app_config: Explicit application config. Falls back to AppConfig.current()
+            when omitted; new callers should pass this explicitly.
 
     Returns:
         List of available tools.
     """
-    config = AppConfig.current()
+    config = app_config if app_config is not None else AppConfig.current()
     tool_configs = [tool for tool in config.tools if groups is None or tool.group in groups]
 
     # Do not expose host bash by default when LocalSandboxProvider is active.
@@ -125,7 +129,7 @@ def get_available_tools(
     try:
         from deerflow.tools.builtins.invoke_acp_agent_tool import build_invoke_acp_agent_tool
 
-        acp_agents = AppConfig.current().acp_agents
+        acp_agents = config.acp_agents
         if acp_agents:
             acp_tools.append(build_invoke_acp_agent_tool(acp_agents))
             logger.info(f"Including invoke_acp_agent tool ({len(acp_agents)} agent(s): {list(acp_agents.keys())})")