Enhance AI Document Retrieval with OpenAI and Supabase Vector Search
This workflow optimizes AI document retrieval by integrating OpenAI and Supabase, using a two-stage process to filter and retrieve relevant document chunks for precise AI responses.
The workflow connects to a Supabase vector store to perform multi-level retrieval. It first searches file descriptions to filter relevant files, then performs vector searches within those files to fetch precise results. This reduces irrelevant data, improves answer accuracy, and optimizes performance when dealing with large document collections. The integration with OpenAI ensures that the filtered document chunks and associated metadata are used to generate comprehensive AI-powered answers.
- Platform
- n8n
- Category
- AI
- Price
- $14.99
- Creator
- Grace Kim
- 1
- 2
- set
- code
- filter
- supabase
- aggregate
- stickyNote
- httpRequest
- manualTrigger
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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