Block 1 - AI Agent
- Type / Role
- @n8n/n8n-nodes-langchain.agent - agent
- Config choices
- Version 1.9
This workflow is provided as-is. Please review and test before using in production.
What This Workflow Does This n8n workflow allows you to upload a T shirt mockup design (even if it's rough or outdated), and automatically turns it into a refined, print ready artwork using the ...
@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.chattrigger, n8n-nodes-base.if, n8n-nodes-base.code, n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.openai, n8n-nodes-base.converttofile
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Thong.
Original n8n.io sourceđź§ What This Workflow Does
This n8n workflow allows you to upload a T-shirt mockup design (even if it's rough or outdated), and automatically turns it into a refined, print-ready artwork using the power of AI.
It starts with an image of a T-shirt design, analyzes it using OpenAI's vision model, and then generates a cleaner, upgraded prompt to be used with OpenAI’s image generation API (gpt-image-1). The final output is a new T-shirt graphic optimized for printing on solid black background, with no visible shirt or mockup framing.
⚙️ How It Works
User Sends a T-shirt Mockup Image Link The workflow begins when the user drops an image link (T-shirt mockup) into a chat interface or input trigger.
AI Analyzes the Image (OpenAI Vision) Using OpenAI’s GPT-4 vision capabilities, the workflow extracts the key design elements from the image:
Text Escaping for API Compatibility A JavaScript function node escapes the prompt (quotes, slashes, line breaks) to make it safe for use in downstream JSON requests.
Image Generation via GPT-Image-1 API or IMAGEN 4 from GOOGLE The final prompt is sent to OpenAI’s gpt-image-1 to generate a brand-new artwork — ideal for direct printing on a black T-shirt.
⚠️ Cost Notice for gpt-image-1 Usage
This workflow uses OpenAI's gpt-image-1 model to generate high-quality T-shirt artwork from refined prompts. Please note that this model is a paid service, and each image generation request may cost approximately $0.25 per design, depending on resolution and usage.
We strongly recommend users to review their OpenAI API usage plan and be mindful of costs when running this workflow, especially if generating in bulk or integrating into larger automation flows.
You can monitor your usage at: https://platform.openai.com/docs/models/gpt-image-1
🚀 How to Use
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
| Workflow | Redesign t-shirt mockups to print-ready files with GPT-4 vision & Imagen 4 |
|---|---|
| Complexity | intermediate |
| Nodes | 14 |
| Categories | Content Creation, Multimodal AI |
| Author | Thong |
| Published | 09 May 2025 |
Use the JSON export at /data/workflows/3959/3959.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
What This Workflow Does This n8n workflow allows you to upload a T shirt mockup design (even if it's rough or outdated), and automatically turns it into a refined, print ready artwork using the ...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Content Creation, Multimodal AI use case.