Create a Local Chatbot with Retrieval-Augmented Generation Using PDF Files
Build a fully local chatbot using n8n, Ollama, and Qdrant that leverages Retrieval-Augmented Generation (RAG) to answer questions based on your PDF documents.
This workflow allows you to create a chatbot that can process and understand PDF files using a semantic database. By uploading PDF files to the Qdrant database, the chatbot can retrieve relevant information to answer user queries. The workflow integrates data ingestion, text splitting, and embedding to enhance the chatbot's ability to understand and respond accurately.
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How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
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