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69e310f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 | """Graph assembly.
START → supervisor ⇄ {data_agent ∥ news_agent} → writer → verify → gate → deliver → END
│ ↑ │
└──── abort (budget / iteration cap) ─────┘ one regeneration
The supervisor's conditional edge returns a *list* of node names, which is what
makes the two workers execute in the same LangGraph superstep. Their concurrent
writes are merged by the reducers declared on :class:`~app.graph.state.RunState`.
"""
from __future__ import annotations
import logging
from typing import Any
from langgraph.graph import END, START, StateGraph
from langgraph.graph.state import CompiledStateGraph
from app.graph.context import RunContext
from app.graph.data_agent import data_agent_node
from app.graph.deliver import deliver_node
from app.graph.gate import gate_node, route_after_gate
from app.graph.news_agent import news_agent_node
from app.graph.state import RunState
from app.graph.supervisor import route_from_supervisor, supervisor_node
from app.graph.verify import route_after_verify, verify_node
from app.graph.writer import writer_node
logger = logging.getLogger(__name__)
NODE_NAMES = (
"supervisor",
"data_agent",
"news_agent",
"writer",
"verify",
"gate",
"deliver",
)
def build_state_graph() -> StateGraph[RunState, RunContext, RunState, RunState]:
"""The uncompiled graph — useful for diagrams and structural tests.
``context_schema=RunContext`` declares the per-run dependency channel. Unlike
``config["configurable"]``, runtime context is not checkpoint state, so live
handles (the open MCP session, the event bus) survive a run with a
checkpointer attached.
"""
graph: StateGraph[RunState, RunContext, RunState, RunState] = StateGraph(
RunState, context_schema=RunContext
)
graph.add_node("supervisor", supervisor_node)
graph.add_node("data_agent", data_agent_node)
graph.add_node("news_agent", news_agent_node)
graph.add_node("writer", writer_node)
graph.add_node("verify", verify_node)
graph.add_node("gate", gate_node)
graph.add_node("deliver", deliver_node)
graph.add_edge(START, "supervisor")
graph.add_conditional_edges(
"supervisor",
route_from_supervisor,
["data_agent", "news_agent", "writer", END],
)
# Workers rejoin the supervisor, which re-plans from merged state.
graph.add_edge("data_agent", "supervisor")
graph.add_edge("news_agent", "supervisor")
graph.add_edge("writer", "verify")
graph.add_conditional_edges("verify", route_after_verify, ["writer", "gate"])
graph.add_conditional_edges("gate", route_after_gate, ["deliver", END])
graph.add_edge("deliver", END)
return graph
def build_graph(checkpointer: Any | None = None) -> CompiledStateGraph[Any, Any, Any, Any]:
"""Compile the graph with a checkpointer (required for the human gate)."""
return build_state_graph().compile(checkpointer=checkpointer)
def mermaid_diagram() -> str:
"""Mermaid source for the README, generated from the real graph."""
return build_state_graph().compile().get_graph().draw_mermaid()
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