Block 1 - When clicking ‘Test workflow’
- Type / Role
- n8n-nodes-base.manualTrigger - manualTrigger
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
This workflow automates the creation of AI generated virtual try on images for fashion eCommerce stores. Instead of relying on expensive and time consuming photoshoots, the system uses AI to genera...
n8n-nodes-base.manualtrigger, n8n-nodes-base.httprequest, n8n-nodes-base.stickynote, n8n-nodes-base.woocommerce, n8n-nodes-base.googlesheets, n8n-nodes-base.wait, n8n-nodes-base.if, n8n-nodes-base.googledrive
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Davide.
Original n8n.io sourceThis workflow automates the creation of AI-generated virtual try-on images for fashion eCommerce stores. Instead of relying on expensive and time-consuming photoshoots, the system uses AI to generate realistic images of models wearing selected clothing items.
This n8n workflow automates the process of generating AI-powered virtual try-on images for a WooCommerce store. It fetches product data from a Google Sheet, uses the Fal.ai Nano Banana model to create an image of a model wearing the clothing item, and then updates both the Google Sheet and the WooCommerce product with the final generated image.
The workflow operates in a sequential, loop-based manner to process multiple products from a spreadsheet. Here is the logical flow:
Manual Trigger & Data Fetch: The workflow starts manually (e.g., by clicking "Test workflow"). It first reads data from a specified Google Sheet, looking for rows where the "IMAGE RESULT" column is empty.
Loop Processing: It loops over each row of data fetched from the sheet. Each row should contain URLs for a model image and a product image, along with a WooCommerce product ID.
API Request to Generate Image: For each item in the loop, the workflow sends a POST request to the Fal.ai Nano Banana API. The request includes the two image URLs and a prompt instructing the AI to create a photo of the model wearing the submitted clothing item.
Polling for Completion: The AI processing is asynchronous. The workflow enters a polling loop: it waits for 60 seconds and then checks the status of the processing request. If the status is not COMPLETED, it waits and checks again. This loop continues until the image is ready.
Fetching and Storing the Result: Once the status is COMPLETED, the workflow retrieves the URL of the generated image, downloads the image file, and uploads it to a designated folder in Google Drive.
Updating Systems: The workflow then performs two crucial update steps:
Loop Continuation: After processing one item, the workflow loops back to process the next row in the Google Sheet until all items are complete.
To make this workflow functional, you need to configure three main connections:
Step 1: Prepare the Google Sheet
IMAGE MODEL, IMAGE PRODUCT, PRODUCT ID, and IMAGE RESULT.IMAGE RESULT column must be left blank; the workflow will fill it automatically.Step 2: Configure the Fal.ai API Key
Value field in the Header Auth to be Key YOURAPIKEY (replacing YOURAPIKEY with your actual key).Step 3: Set Up WooCommerce API
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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 | Auto-generate virtual AI try-on images for WooCommerce with Gemini Nano Banana |
|---|---|
| Complexity | advanced |
| Nodes | 20 |
| Categories | Content Creation, Multimodal AI |
| Author | Davide |
| Published | 29 Aug 2025 |
Use the JSON export at /data/workflows/8022/8022.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.
This workflow automates the creation of AI generated virtual try on images for fashion eCommerce stores. Instead of relying on expensive and time consuming photoshoots, the system uses AI to genera...
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.