PDF-Inhalte parsen, normieren, extrahieren und in Pinecone für RAG speichern

• •Google Drive API-Anmeldedaten
• •Möglicherweise sind Ziel-API-Anmeldedaten erforderlich
• •OpenAI API Key
• •Pinecone API Key

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        "content": "## Normalized Content\n\n* Removes noise\n* Reduces duplication\n* Improves retrieval quality \n* Preserves context \n* Consistent format \n* Prevents wasted tokens \n\n**Note : Update the code based in your requirement**"
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        "content": "## Try It Out!  \n### This n8n template demonstrates how to normalize, index, and query insurance PDFs using AI and Pinecone for a full **RAG (Retrieval-Augmented Generation)** workflow.  \n\n### Use cases include: creating **chatbots or Q&A systems** for structured documents, extracting insights from insurance policies, or managing compliance/legal PDFs efficiently.  \n\n---\n\n## How it works\n* New PDFs are automatically detected from a **Google Drive** folder.  \n* PDFs are sent to **LlamaIndex Cloud** for parsing → returns clean Markdown text.  \n* Text is normalized to remove headers, footers, page numbers, and formatting artifacts.  \n* The normalized text is split into chunks (~1200 characters with 150-character overlap) for better embedding.  \n* **OpenAI embeddings** are generated for each chunk.  \n* Chunks and metadata are stored in **Pinecone** for semantic search.  \n* A **Chat Agent** queries Pinecone to retrieve answers from your document vector database.  \n\n---\n\n### How to use\n* Update the folder name in google drive trigger node. \n* Place a pdf file in the same folder in google drive.\n* Customize the `Normalized Content` function node to adjust regex for headers/footers specific to your documents.  \n* Adjust chunk size or metadata namespace in the Pinecone node to fit your project needs.  \n\n---\n\n### Requirements\n* Google Drive account for PDF source files.  \n* **LlamaIndex Cloud** account (parsing API key).  \n* **Pinecone** account for vector storage.  \n* **OpenAI** account for model and embeddings.   \n\n---\n\n### Need Help?  \nask in the [n8n Forum](https://community.n8n.io/)!  \n\nHappy Automating! 🚀\n"
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        "content": "## Extract Data"
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