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"""
LangGraph definition for the multi-agent algebra chatbot.
Flow: OCR (if image) -> Planner -> Executor -> Synthetic
"""
from langgraph.graph import StateGraph, END
from backend.agent.state import AgentState
from backend.agent.nodes import (
ocr_agent_node,
planner_node,
parallel_executor_node,
synthetic_agent_node,
wolfram_tool_node,
code_tool_node,
route_agent,
)
def build_graph() -> StateGraph:
"""Build and compile the LangGraph for the multi-agent algebra chatbot."""
# Create the graph
workflow = StateGraph(AgentState)
# Add all nodes (NO reasoning_agent - deprecated)
workflow.add_node("ocr_agent", ocr_agent_node)
workflow.add_node("planner", planner_node)
workflow.add_node("executor", parallel_executor_node)
workflow.add_node("synthetic_agent", synthetic_agent_node)
workflow.add_node("wolfram_tool", wolfram_tool_node)
workflow.add_node("code_tool", code_tool_node)
# Set entry point - OCR first (will pass through if no images)
workflow.set_entry_point("ocr_agent")
# OCR -> Always route to Planner
workflow.add_conditional_edges(
"ocr_agent",
route_agent,
{
"planner": "planner",
"done": END,
"end": END,
}
)
# Planner -> Executor (if tools needed) OR Done (if all direct answered)
workflow.add_conditional_edges(
"planner",
route_agent,
{
"executor": "executor",
"done": END, # All-direct case: planner answered directly
"end": END,
}
)
# Executor -> Synthetic (combine results)
workflow.add_conditional_edges(
"executor",
route_agent,
{
"synthetic_agent": "synthetic_agent",
"done": END,
"end": END,
}
)
# Wolfram -> retry, fallback to code, or go to synthetic
workflow.add_conditional_edges(
"wolfram_tool",
route_agent,
{
"wolfram_tool": "wolfram_tool", # Retry
"code_tool": "code_tool", # Fallback
"synthetic_agent": "synthetic_agent",
"end": END,
}
)
# Code -> go to synthetic (after execution/fixes)
workflow.add_conditional_edges(
"code_tool",
route_agent,
{
"synthetic_agent": "synthetic_agent",
"end": END,
}
)
# Synthetic -> end
workflow.add_edge("synthetic_agent", END)
return workflow.compile()
# Create the compiled graph
agent_graph = build_graph()
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