Query business data with OpenAI chatbot using RAG and text-to-SQL via Peliqan
Needs changesWhat 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).
- 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
- Get table data (Peliqan): uses Peliqan
- Supabase Vector Store: stores documents in the Supabase vector store, with embeddings: Embeddings OpenAI; document loader: Default Data Loader
Services it uses
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 3.0 | Replace 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)
- Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - AI Agent
@n8n/n8n-nodes-langchain.agent - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Manual Trigger
n8n-nodes-base.manualTrigger - Supabase Vector Store
@n8n/n8n-nodes-langchain.vectorStoreSupabase - Peliqan
n8n-nodes-peliqan.peliqan - Peliqan Tool
n8n-nodes-peliqan.peliqanTool
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…