How can I save multiple images from an n8n form submission into Google Cloud Storage?

Below is one approach to ensuring every image is processed individually. In many cases, the form submission returns a single item that holds an object with several binary properties (one per image). To loop over them, you can use a Code node to split that binary object into separate items. Then, when you pass them downstream (for example, to an S3 or Google Cloud Storage node), each item will have one binary file that can be processed and saved.

Below is an example Code node snippet you can use:

JSCopied
// Get the current item (the form submission)
// Assuming that all images are held in the binary property
const item = items[0];
const binaries = item.binary;
const newItems = [];

// Loop over each binary property (each image)
for (const key in binaries) {
	if (binaries.hasOwnProperty(key)) {
		newItems.push({
			json: {
				// You can pass additional info here if needed, for example the key name
				fileKey: key
			},
			binary: {
				// Create a new binary field (named "data" in this example) with the file data
				data: binaries[key]
			}
		});
	}
}

return newItems;

How This Works

1. Extracting the Binary Object: The Code node grabs the sole item from the input. This item comes with a binary property that contains all images in different keys.
2. Looping over Each Image: For each property inside the binary object, a new item is created. Each new item now has a binary property (e.g. data) holding one image.
3. Downstream Processing: With these new items, you can now pass them to a node that uploads the binary data to an S3 bucket or Google Cloud Storage. Each item is processed independently.

Next Steps

• After this split, add the node that handles file uploads (e.g. a node configured for Google Cloud Storage or an S3 node).
• Ensure that the node you use for uploading is set to use the binary field you defined (in this example, data).

This method helps when your number of binary images is dynamic. By splitting the binary data into individual items, every image in the submission will be looped and processed, ensuring that none are skipped.

For more details on handling binary data with n8n, you can refer to the documentation on binary data management and transformation nodes.