RAG PDF Q&A: Query Documents with Weaviate & OpenAI

Upload PDFs, embed them in Weaviate using OpenAI, and perform RAG-based Q&A for accurate, context-grounded responses.

This n8n workflow enables Retrieval-Augmented Generation (RAG) over PDF documents using Weaviate as a vector store and OpenAI for embeddings and chat. It processes a PDF (e.g., a 100+ page arXiv paper), splits it into chunks, generates embeddings, and stores them in Weaviate. Users can then query the content via a chat interface, retrieving relevant chunks and generating precise answers grounded in the document. The workflow is divided into key parts: manual PDF upload, embedding and indexing i
Platform
n8n
Category
Lifestyle
Price
$24.99
Creator
Matt Buds

How to import this workflow into n8n

  1. 1Purchase or download the workflow to get the n8n workflow JSON file.
  2. 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
  3. 3Open each node marked with a credential warning and connect your own accounts and API keys.
  4. 4Run the workflow once manually to verify the data flow, then toggle it to Active.

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