chore: import upstream snapshot with attribution

application/agents/workflows/node_agent.py

@@ -0,0 +1,81 @@
+"""Workflow Node Agents - defines specialized agents for workflow nodes."""
+
+from typing import Dict, List, Optional, Type
+
+from application.agents.agentic_agent import AgenticAgent
+from application.agents.base import BaseAgent
+from application.agents.classic_agent import ClassicAgent
+from application.agents.research_agent import ResearchAgent
+from application.agents.workflows.schemas import AgentType
+
+
+class _WorkflowNodeMixin:
+    """Common __init__ for all workflow node agents."""
+
+    def __init__(
+        self,
+        endpoint: str,
+        llm_name: str,
+        model_id: str,
+        api_key: str,
+        tool_ids: Optional[List[str]] = None,
+        **kwargs,
+    ):
+        super().__init__(
+            endpoint=endpoint,
+            llm_name=llm_name,
+            model_id=model_id,
+            api_key=api_key,
+            **kwargs,
+        )
+        # Scope the executor to exactly the node's configured tools. Agents
+        # fetch their toolset via ``tool_executor.get_tools()``, so the scope
+        # must live on the executor — it resolves builtin synthetic ids
+        # (Artifact / Code Executor / Read Document) and ``user_tools`` rows
+        # alike, and an empty list means the node's LLM gets no tools.
+        self.tool_executor.allowed_tool_ids = [str(t) for t in (tool_ids or [])]
+
+
+class WorkflowNodeClassicAgent(_WorkflowNodeMixin, ClassicAgent):
+    pass
+
+
+class WorkflowNodeAgenticAgent(_WorkflowNodeMixin, AgenticAgent):
+    pass
+
+
+class WorkflowNodeResearchAgent(_WorkflowNodeMixin, ResearchAgent):
+    pass
+
+
+class WorkflowNodeAgentFactory:
+
+    _agents: Dict[AgentType, Type[BaseAgent]] = {
+        AgentType.CLASSIC: WorkflowNodeClassicAgent,
+        AgentType.REACT: WorkflowNodeClassicAgent,  # backwards compat
+        AgentType.AGENTIC: WorkflowNodeAgenticAgent,
+        AgentType.RESEARCH: WorkflowNodeResearchAgent,
+    }
+
+    @classmethod
+    def create(
+        cls,
+        agent_type: AgentType,
+        endpoint: str,
+        llm_name: str,
+        model_id: str,
+        api_key: str,
+        tool_ids: Optional[List[str]] = None,
+        **kwargs,
+    ) -> BaseAgent:
+        agent_class = cls._agents.get(agent_type)
+        if not agent_class:
+            raise ValueError(f"Unsupported agent type: {agent_type}")
+        return agent_class(
+            endpoint=endpoint,
+            llm_name=llm_name,
+            model_id=model_id,
+            api_key=api_key,
+            tool_ids=tool_ids,
+            **kwargs,
+        )