Enhance AI Responses with Advanced Multi-Query RAG Using Supabase and GPT-5

This workflow leverages Supabase and GPT-5 to create a sophisticated Retrieval-Augmented Generation (RAG) system. It breaks down complex queries into sub-queries, filters irrelevant data, and synthesizes comprehensive answers, enhancing the AI's ability to handle intricate questions.

This advanced RAG system is designed for AI and automation developers seeking to build high-quality Q&A bots or research agents. By decoupling the AI agent from the knowledge base, it allows for multi-query decomposition and relevance-based filtering. The workflow ensures that only high-quality, relevant data is used to synthesize answers, improving the coherence and quality of responses. The architecture also provides flexibility for customization, such as integrating different vector stores or
Platform
n8n
Category
AI
Price
$14.99
Creator
Fatima Ahmed

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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