Templates / Query business data with OpenAI chatbot using RAG and text-to-SQL via Peliqan

Query business data with OpenAI chatbot using RAG and text-to-SQL via Peliqan

Needs changes

by Peliqan ✓ · 710 views · created 2025-07-30 · Internal Wiki, AI Chatbot

Needs changes. This template uses 1 thing(s) that n8n 3.0 removes: AI Agent v1 (old agent modes). 1 breaking item(s) found. Static check, last run 2026-10-19.

What this workflow does

This AI workflow has 13 nodes and runs when a chat message arrives (plus 1 other trigger). Along the way it connects OpenAI Chat Model, Embeddings OpenAI, Supabase Vector Store and Peliqan (community).

How it runs

Trigger: When a chat message arrives (plus 1 other trigger).

  1. AI Agent: runs an AI agent, with model: OpenAI Chat Model; 2 tools (Execute an SQL query via Peliqan, Supabase Vector Store); memory: Simple Memory
  2. Get table data (Peliqan): uses Peliqan
  3. Supabase Vector Store: stores documents in the Supabase vector store, with embeddings: Embeddings OpenAI; document loader: Default Data Loader

Services it uses

OpenAI Chat ModelEmbeddings OpenAISupabase Vector StorePeliqan (community)

Before you upgrade to n8n 3.0

1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:

  • AI Agent v1 (old agent modes) in AI Agent (v1.6): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.

Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).

Removed in 3.0Replace with
AI Agent v1 (old agent modes)
AI Agent (v1.6)
Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.

Nodes used (11)

From the author

How it works This template is an end-to-end demo of a chatbot using business data from multiple sources (e.g. Notion, Chargebee, Hubspot etc.) with RAG + SQL. Peliqan.io is used as a "cache" of all business data. Peliqan uses one-click ELT to sync all your…

Excerpt from Peliqan's description on n8n.io.

View the original on n8n.io → Check your own copy

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