Loop Over Items — Beginner Example

This workflow introduces beginners to one of the most fundamental concepts in n8n: looping over items . Using a simple use case—generating LinkedIn captions for content ideas—it demonstrates how to split a dataset into individual items, process them with AI, and collect the output for review or export.

✅ Key Features

• 🧪 Create Dummy Data : Simulate a small dataset of content ideas.
• 🔁 Loop Over Items : Process each row independently using the SplitInBatches node.
• 🧠 AI Caption Creation : Automatically generate LinkedIn captions using OpenAI.
• 🧰 Tool Integration : Enhance AI output with creativity-injection tools.
• 🧾 Final Output Set : Collect the original idea and generated caption.

🧰 What You'll Need

• ✅ An OpenAI API key
• ✅ The LangChain nodes enabled in your n8n instance
• ✅ Basic knowledge of how to trigger and run workflows in n8n

🔧 Step-by-Step Setup

1️⃣ Run Workflow

• Node : Manual Trigger (Run Workflow)
• Purpose : Manually start the workflow for testing or learning.

2️⃣ Create Random Data

• Node : Create Random Data (Code)
• What it does : Simulates incoming data with multiple content ideas.
• Code :

 return [
 {
 json: {
 row_number: 2,
 id: 1,
 Date: '2025-07-30',
 idea: 'n8n rises to the top',
 caption: '',
 complete: ''
 }
 },
 {
 json: {
 row_number: 3,
 id: 2,
 Date: '2025-07-31',
 idea: 'n8n nodes',
 caption: '',
 complete: ''
 }
 },
 {
 json: {
 row_number: 4,
 id: 3,
 Date: '2025-08-01',
 idea: 'n8n use cases for marketing',
 caption: '',
 complete: ''
 }
 }
 ];

3️⃣ Loop Over Items

• Node : Loop Over Items (SplitInBatches)
• Purpose : Sends one record at a time to the next node.
• Why It Matters : Loops in n8n are created using this node when you want to iterate over multiple items.

4️⃣ Create Captions with AI

• Node : Create Captions (LangChain Agent)
• Prompt :

 idea: {{ $json.idea }}

• System Message :

 You are a helpful assistant creating captions for a LinkedIn post. Please create a LinkedIn caption for the idea.

• Model : GPT-4o Mini or GPT-3.5
• Credentials Required :
  • OpenAI Credential
    • Go to: OpenAI API Keys
    • Create a key and add it in n8n under credentials as “OpenAi account”

5️⃣ Inject Creativity (Optional)

• Node : Tool: Inject Creativity (LangChain Tool)
• Purpose : Demonstrates optional LangChain tools that can enhance or manipulate input/output.
• Why It's Cool : A great way to show chaining tools to AI agents.

6️⃣ Output Table

• Node : Output Table (Set)
• Purpose : Combines original ideas and generated captions into final structure.
• Fields :
  • idea : = {{ $('Create Random Data').item.json.idea }}
  • output : = {{ $json.output }}

💡 Educational Value

This workflow demonstrates:

• Creating dynamic inputs with the Code node
• Using SplitInBatches to simulate looping
• Sending dynamic prompts to an AI model
• Using Set to structure the output data

Beginners will understand how item-level processing works in n8n and how powerful looping combined with AI can be.

📬 Need Help or Want to Customize This?

Robert Breen
Automation Consultant | AI Workflow Designer | n8n Expert
📧 robert@ynteractive.com
🌐 ynteractive.com
🔗 LinkedIn

🏷️ Tags

n8n loops OpenAI LangChain workflow training beginner LinkedIn automation caption generator