Build an AI Documentation Expert Bot Using RAG, Gemini, and Supabase
Create an AI chatbot that specializes in the official n8n documentation using a Retrieval-Augmented Generation (RAG) pipeline. This workflow scrapes, processes, and stores documentation in a Supabase vector store, allowing the AI to provide accurate, context-based answers.
This workflow is divided into two main parts: indexing and chat interaction. In the indexing phase, the workflow scrapes the n8n documentation, processes it into manageable chunks, and stores these chunks in a Supabase vector store as embeddings. During the chat interaction phase, the AI uses these embeddings to retrieve relevant information and answer user queries accurately, ensuring responses are grounded in the documentation.
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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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