| """Graph-Aufbau der agentischen Sanduhr (Mockup). |
| |
| build_graph(checkpointer=None): |
| - checkpointer=None → für `langgraph dev` (Studio injiziert eigene Persistenz) |
| - checkpointer=... → für direkten Invoke/Tests (interrupt braucht einen Saver) |
| """ |
|
|
| from __future__ import annotations |
|
|
| from langgraph.graph import END, START, StateGraph |
|
|
| from .nodes import ( |
| automation_output, |
| execute_with_codex, |
| fan_out_research, |
| hai_owner_packet, |
| human_escalation, |
| intake_router, |
| learning_agent, |
| meta_agent, |
| park, |
| priority_gate, |
| research_subagent, |
| research_with_opus, |
| route_after_verifier, |
| route_thought, |
| verifier_mediator, |
| ) |
| from .state import ThoughtState |
|
|
|
|
| def build_graph(checkpointer=None): |
| g = StateGraph(ThoughtState) |
|
|
| |
| g.add_node("intake_router", intake_router) |
| g.add_node("priority_gate", priority_gate) |
| g.add_node("execute_with_codex", execute_with_codex) |
| g.add_node("research_with_opus", research_with_opus) |
| g.add_node("research_subagent", research_subagent) |
| g.add_node("learning_agent", learning_agent) |
| g.add_node("meta_agent", meta_agent) |
| g.add_node("park", park) |
| g.add_node("verifier_mediator", verifier_mediator) |
| g.add_node("human_escalation", human_escalation) |
| g.add_node("hai_owner_packet", hai_owner_packet) |
| g.add_node("automation_output", automation_output) |
|
|
| |
| g.add_edge(START, "intake_router") |
| g.add_edge("intake_router", "priority_gate") |
|
|
| |
| g.add_conditional_edges( |
| "priority_gate", |
| route_thought, |
| { |
| "execute_with_codex": "execute_with_codex", |
| "research_with_opus": "research_with_opus", |
| "learning_agent": "learning_agent", |
| "meta_agent": "meta_agent", |
| "park": "park", |
| }, |
| ) |
|
|
| |
| g.add_conditional_edges("research_with_opus", fan_out_research, ["research_subagent"]) |
| g.add_edge("research_subagent", "verifier_mediator") |
|
|
| |
| g.add_edge("execute_with_codex", "verifier_mediator") |
| g.add_edge("learning_agent", "verifier_mediator") |
| g.add_edge("meta_agent", "verifier_mediator") |
|
|
| |
| g.add_edge("park", END) |
|
|
| |
| g.add_conditional_edges( |
| "verifier_mediator", |
| route_after_verifier, |
| {"human_escalation": "human_escalation", "hai_owner_packet": "hai_owner_packet"}, |
| ) |
| g.add_edge("human_escalation", "hai_owner_packet") |
|
|
| |
| g.add_edge("hai_owner_packet", "automation_output") |
| g.add_edge("automation_output", END) |
|
|
| return g.compile(checkpointer=checkpointer) |
|
|
|
|
| |
| graph = build_graph() |
|
|
