AI Agents

RAG on live data

34 nodes 211 125 Automatic trigger
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Workflow Description

Advanced retrieval system that ingests live data from Supabase and Notion, intelligently chunks and embeds content using OpenAI, stores vectors for semantic search, and answers user queries with language models. Processes data in batches, maintains vector store, and retrieves contextually relevant responses in real time.

How it works

  1. 1.Load live data from Supabase and Notion sources automatically
  2. 2.Split documents into semantic chunks based on token counting
  3. 3.Process chunks in batches and generate vector embeddings via OpenAI
  4. 4.Store embeddings in vector database for fast retrieval
  5. 5.Execute QA retrieval chain powered by OpenAI language models
  6. 6.Return contextual answers to user queries through chat interface

Use cases

  • Intelligent search across enterprise documents and constantly-updating databases
  • Build question-answering engine that understands context from multiple data sources
  • Automate information extraction and summarization from live data sources

Requirements

  • OpenAI API keys for embeddings and language models
  • Configured Supabase connection for data access
  • Notion or Supabase as primary data source
  • Vector storage capability in Supabase database

Service Value

Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.

Apps Used

OpenAI Text Splitter Split In Batches LLM Chain Vector Store Chat Trigger Supabase Notion Document Default Data Loader

Details

Trigger Automatic trigger
Nodes 34
Apps 9
Views 211
Downloads 125

How to Use

  1. 1.Click "Download Template"
  2. 2.Open your n8n dashboard
  3. 3.Go to Workflows > Import from File
  4. 4.Select downloaded file and configure credentials

Nodes Used (34)

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Embeddings OpenAI

OpenAI

#1

Token Splitter

Text Splitter Token Splitter

#2

Loop Over Items

Split In Batches

#3

Question and Answer Chain

Chain Retrieval Qa

#4

Vector Store Retriever

Retriever Vector Store

#5

OpenAI Chat Model

OpenAI

#6

When chat message received

Chat Trigger

#7

Schedule Trigger

Schedule Trigger

#8

Sticky Note

Sticky Note

#9

Limit

Limit

#10

Limit1

Limit

#11

Delete old embeddings if exist

Supabase

#12

Get page blocks

Notion

#13

Default Data Loader

Document Default Data Loader

#14

Sticky Note1

Sticky Note

#15

Input Reference

No Op

#16

Notion Trigger

Notion

#17

Get updated pages

Notion

#18

Sticky Note23

Sticky Note

#19

Sticky Note24

Sticky Note

#20

Sticky Note25

Sticky Note

#21

Sticky Note26

Sticky Note

#22

Sticky Note27

Sticky Note

#23

Sticky Note28

Sticky Note

#24

Supabase Vector Store1

Vector Store Supabase

#25

Sticky Note30

Sticky Note

#26

Sticky Note31

Sticky Note

#27

Supabase Vector Store

Vector Store Supabase

#28

Sticky Note32

Sticky Note

#29

Sticky Note29

Sticky Note

#30

Sticky Note33

Sticky Note

#31

Sticky Note34

Sticky Note

#32

Sticky Note35

Sticky Note

#33

Concatenate to single string

Summarize

#34