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Python

"""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,
)