February 2025
Intermediate
376 pages
9h 25m
Japanese
Content preview from 仕組みからわかる大規模言語モデル 生成AI時代のソフトウェア開発入門
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状態グラフの定義
次に、状態グラフを定義します。
workflow = StateGraph(AgentState)
workflow.add_node("Salesman", salesman_node)
workflow.add_node("SHED", shed_node)
workflow.add_conditional_edges(
"Salesman",
route,
{
"continue": "SHED",
"finish": END,
},
)
workflow.add_edge("SHED", "Salesman")
workflow.set_entry_point("Salesman")
graph = workflow.compile()
ここでは、
Salesman
ノードと
SHED
ノードを追加し、
route
関数を使って条件付きのエッジを
追加しています。
route
関数が
"continue"
を返せば
SHED
ノードに、
"finish"
を返せば
END
ノー
ドに遷移します。
SHED
ノードからは無条件で
Salesman
ノードに遷移します。また、エントリ
ポイントには
Salesman
ノードを設定し、グラフをコンパイルします。
状態グラフの実行
最後に、状態グラフを実行します。
graph.invoke({"messages": []})
初期状態として空のメッセージを渡して、ワークフローを実行します。訪問販売員と主夫が
会話を繰り返し、訪問販売員が営業を終了すると判断したところでシミュレーションが終了し ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.