RAG Chatbot for Procurement: Supabase + TogetherAI + Openrouter
Ingests Google Docs into Supabase embeddings via TogetherAI, then powers a RAG chatbot for accurate procurement queries using chat triggers and similarity search.
This workflow implements a Retrieval-Augmented Generation (RAG) chatbot tailored for commerce and procurement. The first part (run once) fetches content from Google Docs, splits it into 1000-char chunks using a code node, generates embeddings with TogetherAI's API, and stores them in a Supabase 'embed' table for persistent vector storage.
The second part activates on chat messages: it embeds the user query with TogetherAI, performs a vector similarity search via Supabase RPC to retrieve top 5 r
- Platform
- n8n
- Category
- Commerce
- Price
- $24.99
- Creator
- Fred Garcia
- RAG
- Chatbot
- Supabase
- TogetherAI
- Openrouter
- Embeddings
- Google Docs
- Vector Search
- AI Automation
- Procurement
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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