feat: 工作流画布支持草稿试运行（target=draft 执行当前草稿图）

offline-backend-20260512/backend/packages/harness/deerflow/workflows/nodes/agents.py

@@ -131,6 +131,7 @@ class _AgentInvocation:
         response_schema: dict[str, Any],
         thread_mode: str,
         failure_code: str,
+        model_name: str = "",
     ) -> NodeResult:
         run_agent = require_dep(ctx.deps.run_agent, node=node, what="智能体执行")
         coalescer = _DeltaCoalescer(ctx, node.id)
@@ -176,6 +177,7 @@ class _AgentInvocation:
                     prompt=prompt,
                     skill_names=skill_names,
                     thread_mode=thread_mode,
+                    model_name=model_name or None,
                     cancel=ctx.cancel,
                     on_delta=on_delta,
                     on_tool=on_tool,
@@ -251,9 +253,10 @@ class _AgentInvocation:
 
 class AgentNodeExecutor(_AgentInvocation):
     async def execute(self, node: WorkflowNode, ctx: RunContext) -> NodeResult:
-        agent_id = str(node.config.get("agentId") or node.config.get("agent_id") or "")
-        if not agent_id:
-            raise WorkflowError("WORKFLOW_AGENT_FAILED", "智能体节点未选择智能体", node_id=node.id)
+        # Empty agentId falls back to the runtime's built-in default agent —
+        # canvas nodes may only pick a model and a prompt.
+        agent_id = str(node.config.get("agentId") or node.config.get("agent_id") or "") or "default"
+        model_name = str(node.config.get("modelName") or node.config.get("model_name") or "")
         template = str(node.config.get("promptTemplate") or node.config.get("prompt_template") or "")
         prompt = render_template(template, ctx.state()).strip()
         if not prompt:
@@ -264,6 +267,7 @@ class AgentNodeExecutor(_AgentInvocation):
             ctx,
             agent_id=agent_id,
             prompt=prompt,
+            model_name=model_name,
             skill_names=[str(s) for s in (node.config.get("skillNames") or node.config.get("skill_names") or [])],
             response_mode=str(node.config.get("responseMode") or node.config.get("response_mode") or "text"),
             response_schema=schema if isinstance(schema, dict) else {},
@@ -285,9 +289,10 @@ class SkillNodeExecutor(_AgentInvocation):
                 node_id=node.id,
                 details={"mode": mode},
             )
-        agent_id = str(node.config.get("agentId") or node.config.get("agent_id") or "")
+        agent_id = str(node.config.get("agentId") or node.config.get("agent_id") or "") or "default"
+        model_name = str(node.config.get("modelName") or node.config.get("model_name") or "")
         skill_names = [str(s) for s in (node.config.get("skillNames") or node.config.get("skill_names") or [])]
-        if not agent_id or not skill_names:
+        if not skill_names:
             raise WorkflowError("WORKFLOW_SKILL_FAILED", "技能节点需要同时指定智能体与技能", node_id=node.id)
         template = str(node.config.get("promptTemplate") or node.config.get("prompt_template") or "")
         prompt = render_template(template, ctx.state()).strip() or f"请使用技能 {skill_names[0]} 完成任务。"
@@ -296,6 +301,7 @@ class SkillNodeExecutor(_AgentInvocation):
             ctx,
             agent_id=agent_id,
             prompt=prompt,
+            model_name=model_name,
             skill_names=skill_names,
             response_mode="text",
             response_schema={},