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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図7.1.4
7.1.5
コンテキストの拡張
ここまでで、コンテキストに会話履歴を用いることで、ユーザとAI の自然な対話を実現す
ることができるようになりました。しかし、コンテキストの利用は会話履歴に限定されるわけ
ではありません。テキストで表現可能なあらゆる情報をコンテキストに含めることができま
す。追加のコンテキストを活用することで、LLMは学習時にアクセスできなかった情報を用
いて、より適切な回答を生成することができます。利用可能な情報には、ユーザ固有のデー
タ、例えば個人の好み、過去の購入履歴、地理的位置、カレンダーの予定、健康状態や活動
データなど、多岐にわたる情報が考えられます。
まずは、コンテキストに任意の情報を追加する方法を学びましょう。ここでは、LangChain
の機能を用いて、次の方針でコンテキストを追加します。
プロンプトテンプレートを使ったチェーンを作成する
プロンプトテンプレートには変数として追加のコンテキスト情報を含める
チェーンを使ってLLM に問い合わせる
この方針でリスト 7.1.3 を拡張したプログラムをリスト 7.1.4 に示します。網掛けした箇所
がリスト7.1.3 との主な差分です。以降、本項ではこの差分を中心に説明します。
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7
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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.