AI Agents

Automated workflow

38 nodes 210 123 Automatic trigger
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Workflow Description

An intelligent workflow that combines AI agents with document processing and contextual memory. Loads texts, splits them into chunks, embeds them in a vector database, and enables the agent to answer complex queries accurately across multiple platforms.

How it works

  1. 1.Load documents and split them into processable text chunks
  2. 2.Convert texts into vector embeddings and store them in the database
  3. 3.Activate an AI agent with contextual memory to handle user queries
  4. 4.Automatically publish results to X or other distribution channels

Use cases

  • Build a smart assistant that answers customer questions based on company documents
  • Automate generation and sharing of relevant content on social media

Requirements

  • OpenAI API key for language model operations
  • Active Qdrant vector database or embeddings service

Service Value

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

Apps Used

Embeddings Document Default Data Loader Text Splitter Twitter/X Split In Batches Vector Store AI Agent Memory Chat Trigger OpenAI Tool

Details

Trigger Automatic trigger
Nodes 38
Apps 11
Views 210
Downloads 123

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 (38)

/

When clicking ‘Test workflow’

Manual Trigger

#1

Embeddings Mistral Cloud

Embeddings Mistral Cloud

#2

Default Data Loader

Document Default Data Loader

#3

Recursive Character Text Splitter

Text Splitter Recursive Character Text Splitter

#4

Get Tax Code Zip File

HTTP Request

#5

Extract Zip Files

Compression

#6

Files as Items

Split Out

#7

Extract PDF Contents

Extract From File

#8

Extract From Chapter

Set

#9

Map To Sections

Set

#10

Execute Workflow Trigger

Execute Workflow Trigger

#11

Get Mistral Embeddings

HTTP Request

#12

Content Chunking @ 50k Chars

Set

#13

Split Out Chunks

Split Out

#14

For Each Section...

Split In Batches

#15

Sections To List

Split Out

#16

Only Valid Sections

Filter

#17

Use Qdrant Search API1

HTTP Request

#18

Use Qdrant Scroll API

HTTP Request

#19

Get Search Response

Set

#20

Sticky Note

Sticky Note

#21

Sticky Note1

Sticky Note

#22

Sticky Note2

Sticky Note

#23

Qdrant Vector Store

Vector Store Qdrant

#24

Sticky Note3

Sticky Note

#25

Sticky Note4

Sticky Note

#26

AI Agent

Agent

#27

Window Buffer Memory

Memory Buffer Window

#28

When chat message received

Chat Trigger

#29

Window Buffer Memory1

Memory Buffer Window

#30

OpenAI Chat Model

OpenAI

#31

1sec

Wait

#32

Ask Tool

Tool Workflow

#33

Search Tool

Tool Workflow

#34

Switch

Switch

#35

Get Ask Response

Set

#36

Sticky Note5

Sticky Note

#37

Sticky Note6

Sticky Note

#38