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DATASTAX JAPAN合同会社
DataStaxは、2010年の創業以来、NoSQLデータベースApache Cassandraを中心とするテクノロジースタックを提供しています。CassandraとPulsarの機能をマネージドサービスとして提供するAstraでは、生成AIとの関係で注目を集めているベクトル検索機能を提供しています。
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ベクトル検索における5つの困難な問題とCassandra/AstraDBによるその解決
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OpenAI API + LangChain + DataStax AstraDB + LangSmith + Streamlit サンプルアプリケーション紹介
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生成AIアプリ開発フレームワークLangChain入門
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【生成AIアプリのためのベクトル検索】 ⑧ 分類問題へのLLMの適用
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【生成AIアプリのためのベクトル検索】 ⑦ ユースケース: セマンティック検索とチャット
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【生成AIアプリのためのベクトル検索】⑥ RAG AIアプリケーションの実装〜生成プロセスの実行
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【生成AIアプリのためのベクトル検索】⑤ RAG AIアプリケーションの実装〜ナレッジベースの作成
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【生成AIアプリのためのベクトル検索】④ 検索拡張生成(RAG)パターン
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LLMフレームワークとCassandraとを統合するCassIO概要
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【生成AIアプリのためのベクトル検索】③ ベクトル検索の概念的理解
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【生成AIアプリのためのベクトル検索】② 従来のAIアプリケーションと生成AIアプリケーションの構築手順の違い
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【生成AIアプリのためのベクトル検索】① プロローグ
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Apache Pulsarのストリーミング処理開発を助けるPulsar Transformations紹介
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特徴量エンジンKaskadaの宣言型クエリ言語Fenl~関数一覧
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ストリーミングとLLMの統合〜LangStream紹介
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特徴量エンジンKaskadaリファレンス〜スペックファイル
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特徴量エンジンKaskadaの宣言型クエリ言語Fenl〜シンタックス
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特徴量エンジンKaskada利用イメージ: 機械学習モデルのトレーニング
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