This workflow introduces beginners to one of the most fundamental concepts in n8n: looping over items. Using a simple u…
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. An n8n automation workflow template by Robert Breen.
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