Two-Stage RAG Chatbot: OpenAI & Supabase Vector Search
A multi-stage retrieval chatbot that filters files by description before precise vector search, enhancing AI response accuracy for large document sets.
This n8n workflow builds a sophisticated two-stage document retrieval system integrated with OpenAI and Supabase vector store. It starts by querying file metadata descriptions via a Supabase RPC function to identify the most relevant files based on user input similarity scores. Only these top-matching files are then used for deeper vector similarity searches on document chunks, drastically reducing noise and improving retrieval precision.
The benefits include optimized performance for handling
- Platform
- n8n
- Category
- Website Building
- Price
- $22.99
- Creator
- QualityWorkflows
- OpenAI
- Supabase
- Vector Search
- RAG
- Chatbot
- Retrieval
- AI Agent
- Document Search
- n8n
- Agentic AI
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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