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7.1.6
7.1.7
マルチモーダルへの対応
ここまでのプログラムは、テキストデータを対象としていました。しかし、マルチモーダル
LLMは、画像や音声などの他のデータ形式にも対応することができます。ここでは、画像を
プロンプトの一部として利用できるようにプログラムを拡張します。また、画像データもヒン
トにRAG を使って回答を生成することを考えます。
画像データを用いてインデックスを検索する方法には、画像データから埋め込みベクトルを
生成し、そのベクトルを使ってインデックスを検索します。画像データから直接埋め込みベク
トルを作成する実装もあり得ますが、ここでは画像データを一旦テキストデータに変換してか
らインデックスを作成します。これは、本書執筆時点では
OpenAIEmbeddings
クラスはテキス
トデータのみを受け付けることができるためです。代わりに画像データをテキストデータに変
換する部分にマルチモーダルLLM を使用します。この方針で拡張したプログラムをリスト
7.1.7に示します。
340
7
リスト7.1.7
import streamlit as st
from langchain_openai import ChatOpenAI ...
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