I am new to N8N and I search everywhere but didn’t find any solution to my issue
When a pdf file is appearing in my google drive specific folder I am using the node google drive to download the file, but I don’t know where the file is temporary stored.
I create a specific script to transform my pdf in json format and I am using the node execute command to execute the script and get the Json result in the outpout. What I want is to say to my script where to search my google drive pdf whatever the name of this file.
I am using the last version of N8N on npm for windows et docker on linux.
In n8n, when you download a file using the Google Drive node, the file is stored in memory as binary data within the workflow’s context. This means the file isn’t saved to a physical location on your server by default. To process this file with your custom script using the Execute Command node, you’ll need to write the in-memory binary data to a temporary file, execute your script on this file, and then, if necessary, remove the temporary file after processing. Here’s how you can achieve this:
1. Writing the Binary Data to a Temporary File:
Use the “Write Binary File” node to save the in-memory binary data to a temporary location on your filesystem.
Add the “Write Binary File” Node:
Set the “Binary Property” to the name of the property holding your file (default is data).
Specify the “File Path” where you want to save the file, e.g., /tmp/downloaded_file.pdf on Unix-based systems or C:\Temp\downloaded_file.pdf on Windows.
Or you can do that by: Using the “Extract From File” Node:
n8n offers the “Extract From File” node, which can extract text content from PDF files. Here’s how to set it up:
Add the “Extract From File” Node: In your workflow, include this node to process the PDF.
Configure the Node:
Input Binary Field: Specify the field containing the PDF binary data.
Operation: Select “Extract From PDF” to extract text content.
This method is straightforward but primarily extracts plain text, which might require additional parsing to structure as JSON.