graph.py

"""LangGraph workflow definition"""

from langgraph.graph import StateGraph, END
from state import AgentState
from agents.manager import manager_agent
from agents.planner import planner_agent
from agents.analyzer import analyzer_agent
from agents.delegator import delegator_agent
from agents.executor import executor_agent
from agents.reviewer import reviewer_agent
from agents.reporter import reporter_agent

def create_workflow():
    """Build the multi-agent workflow graph"""
    
    # Initialize graph
    workflow = StateGraph(AgentState)
    
    # Add all agent nodes
    workflow.add_node("manager", manager_agent)
    workflow.add_node("planner", planner_agent)
    workflow.add_node("analyzer", analyzer_agent)
    workflow.add_node("delegator", delegator_agent)
    workflow.add_node("executor", executor_agent)
    workflow.add_node("reviewer", reviewer_agent)
    workflow.add_node("reporter", reporter_agent)
    
    # Define routing function
    def route_from_manager(state: AgentState) -> str:
        """Route based on manager's decision"""
        next_agent = state.get("current_agent", "end")
        
        if next_agent == "end":
            return END
        
        return next_agent
    
    # Set entry point
    workflow.set_entry_point("manager")
    
    # Manager routes to all agents conditionally
    workflow.add_conditional_edges(
        "manager",
        route_from_manager,
        {
            "planner": "planner",
            "analyzer": "analyzer",
            "delegator": "delegator",
            "executor": "executor",
            "reviewer": "reviewer",
            "reporter": "reporter",
            END: END
        }
    )
    
    # All agents return to manager for next routing decision
    for agent in ["planner", "analyzer", "delegator", "executor", "reviewer", "reporter"]:
        workflow.add_edge(agent, "manager")
    
    # Compile the graph
    return workflow.compile()

# Create the app
app = create_workflow()