Mistral OCR を基にした完全な RAG パイソンデモ（PDF から始める）
上級
これはAI, IT Ops分野の自動化ワークフローで、34個のノードを含みます。主にSet, Code, Wait, GoogleDrive, HttpRequestなどのノードを使用、AI技術を活用したスマート自動化を実現。 Mistral OCR、Qdrant、Gemini AIを組み合わせてPDFドキュメントRAGシステムを構築
前提条件
- •Google Drive API認証情報
- •ターゲットAPIの認証情報が必要な場合あり
- •OpenAI API Key
- •Qdrantサーバー接続情報
- •Google Gemini API Key
使用ノード (34)
ワークフロープレビュー
ノード接続関係を可視化、ズームとパンをサポート
ワークフローをエクスポート
以下のJSON設定をn8nにインポートして、このワークフローを使用できます
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"content": "## STEP 4\nTest the RAG"
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},
"options": {},
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"credentials": {
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"content": "## Complete RAG system from PDF Documents with Mistral OCR, Qdrant and Gemini AI\n\nThis workflow is designed to process PDF documents using Mistral's OCR capabilities, store the extracted text in a Qdrant vector database, and enable Retrieval-Augmented Generation (RAG) for answering questions. "
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}よくある質問
このワークフローの使い方は？
上記のJSON設定コードをコピーし、n8nインスタンスで新しいワークフローを作成して「JSONからインポート」を選択、設定を貼り付けて認証情報を必要に応じて変更してください。
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上級 - 人工知能, IT運用
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ワークフロー情報
難易度
上級
ノード数34
カテゴリー2
ノードタイプ19
作成者
Davide
@n3witaliaFull-stack Web Developer based in Italy specialising in Marketing & AI-powered automations. For business enquiries, send me an email at info@n3w.it or add me on Linkedin.com/in/davideboizza
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