Beginner AI dataset generator using OpenAI + LangChain in n8n

This n8n workflow dynamically generates a realistic sample dataset based on a single topic you provide. It uses OpenAI (via LangChain) and n8n’s built-in nodes to: 1. Generate structured JSON data for 5 columns with 3–5 values each 2. Flatten that data into a single text blob 3. Infer meaningful column names via a second AI call 4. Pivot, split, merge, and rename columns automatically 5. Output a clean, labeled dataset ready for export or further processing --- ⚙️ Prerequisites 1. OpenAI API Key - Visit: https://platform.openai.com/account/api-keys - Create a new key - In n8n: Credentials → New → OpenAI API, paste key, name it “OpenAi account” 2. LangChain nodes enabled in your n8n instance 🥇 Step 1: Set Up OpenAI Credential 1. Go to OpenAI API Keys 2. Create and copy your key 3. In n8n: Credentials → New → OpenAI API → paste key as “OpenAi account” 🥈 Step 2: Manual Trigger - Add Manual Trigger to start the workflow 🥉 Step 3: Set Topic - Add a Set node named Set Topic to Search - Field: Topic = n8n use cases (or any topic you choose) ✨ Step 4: Generate Structured Data - LangChain Agent node Generate Random Data - Connect to OpenAI Chat Model1 and Tool: Inject Creativity1 - System prompt: instruct AI to output 5 columns of realistic values in JSON 🔧 Step 5: Parse AI Output - Structured Output Parser to validate JSON 🔄 Step 6: Flatten Data - Code node Outpt all Data to One Field - Joins all values into a comma-separated string for column naming 🧠 Step 7: Generate Column Names - LangChain Agent Generate Column Names - Connect to OpenAI Chat Model2 - Prompt: infer 5 column names from the string 🔢 Step 8: Pivot Names Row - Code node Pivot Column Names transforms array into { column1: name1, … } 🪓 Step 9: Split Columns - 5 SplitOut nodes to break each array back into rows per column 🔗 Step 10: Merge Rows - Merge node Merge Columns together using combineByPosition 🏷️ Step 11: Rename Columns - Set node Rename Columns assigns the AI-generated names to each column 🔗 Step 12: Final Output - Merge Append Column Names combines data and header row --- 🏁 Done! You now have a fully AI-driven, labeled dataset generated from a single topic—no external services needed. Easily extend by adding a Google Sheets or HTTP node to export. 📬 Need Help or Want to Customize This? 📧 [email protected](mailto:[email protected]) 🔗 LinkedIn