Resume PDF turned into an image and screened by Gemini

Newversion 1 · updated 2026-11-12

Resume PDF turned into an image and screened by Gemini, picture 1

An n8n workflow that turns a resume PDF into one image and asks Google Gemini whether the candidate fits a role. Because the model sees a picture, text hidden in the PDF should not steer the verdict.

Resume PDF turned into an image and screened by Gemini is an n8n workflow in the Business category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page or copy its JSON, then import it into an n8n canvas. Nothing runs until you activate it in n8n.

At a glance

Runs in

n8n Cloud: import the file into a new workflow there
Your own n8n server: the same file and steps, with GraphicsMagick installed if you do not use n8n’s Docker image
Stirling PDF: run it on your own server and put its address in the HTTP Request node
Another role: change the role in the chain’s first message to screen for a different job

Platform

n8nWorkflow automation, in n8n’s cloud or on your own server

Connects 3 apps

How it works

Trigger

A manual run

You start it by hand:

A click on Test workflow
The resume is the PDF picked in the Google Drive node

Actions

The resume PDF is downloaded from Google Drive
A Stirling PDF server turns the PDF into one JPG image at 300 dpi
The image is shrunk to 75 percent
Google Gemini looks at the image and judges the candidate for the role of plumber
The answer, a yes or no with a reason, goes to a true route or a false route

Result

A verdict of true or false with a short reason, sent to a true or a false output

Integrations

What you need before you start.

Google Drive

File storage

Holds the resume and downloads it as a PDF.

NeedsA Google Drive credential

Stirling PDF

PDF converter

Turns the PDF into one image of all its pages.

NeedsA Stirling PDF server of your own and its address

Google Gemini

Vision model

Looks at the image and judges the candidate for the role.

NeedsA Gemini API key, in a Google Gemini(PaLM) API credential

Workflow check

Checked by Mindket on 13 Nov 2026

Steps: 6 steps, starting by hand
AI: 1 step calls an AI model: Candidate Resume Analyser
Sign-ins: Signs in to: Google Drive and Google Gemini
API keys: No API key is left in the file
Step types: Mindket’s checker reads all 6 of its step types

Read from the workflow’s file, not from a run.

About

What it is

This n8n workflow screens a resume by looking at a picture of it instead of reading its text. It downloads the PDF from Google Drive and sends it to a Stirling PDF server, which returns one image of the pages. The image is shrunk to 75 percent. A Google Gemini vision model then judges the candidate for the role of plumber and returns a yes or no with a reason. Eight nodes do the work, beside five sticky notes.

Who it suits

Recruiters and small hiring teams who screen many resumes and worry about hidden text that tries to sway an automated filter. Skip it if you cannot run your own Stirling PDF server, because resumes hold personal data. The check is only as good as the role description you write.

Who uses it, and how

Industry	Who uses it	How they use it	Example
Recruitment	Recruiters	Screen a stack of resumes before a person reads them	A recruiter runs each new PDF through the workflow and reads only those marked as a fit.
Construction	Site managers	Shortlist applicants for trade roles	A manager sets the role to electrician and checks which candidates qualify for an interview.
Hospitality	Hotel managers	Sort seasonal applicants quickly	A manager changes the role to receptionist and screens fifty resumes before a hiring day.
Staffing	Agency coordinators	Add a second check against manipulated resumes	A coordinator compares the image-based verdict with the text-based filter already in use.

You need basic n8n skills and three things: a Google Drive account, a Gemini API key and a Stirling PDF server of your own.

Where to use it

Any n8n that can reach Google Drive, a Stirling PDF server and the Gemini API will run it. The Edit Image node needs GraphicsMagick, which n8n’s own Docker images include.

n8n Cloud: import the file into a new workflow there
Your own n8n server: the same file and steps, with GraphicsMagick installed if you do not use n8n’s Docker image
Stirling PDF: run it on your own server and put its address in the HTTP Request node
Another role: change the role in the chain’s first message to screen for a different job

Setup

Download saves a zip with workflow.json and Mindket’s setup notes in your downloads folder. Three services are involved.

What you need first

Need	Detail
n8n	On n8n Cloud or on a server of your own, with GraphicsMagick for the resize step
Google Drive	A Google Drive credential, and a resume saved there as a PDF
Stirling PDF	A Stirling PDF server of your own that n8n can reach
Gemini	An API key, saved in a Google Gemini(PaLM) API credential

In n8n, create a workflow, open its menu, choose Import from File and pick workflow.json.
Run Stirling PDF on a server you control, for example with Docker, and note its address.
In PDF-to-Image API, replace <YOUR_STIRLING_PDF_HOST> in the address with that host.
Add a Google Drive credential and select it in Download Resume. Put your resume’s file ID in the node, in place of <YOUR_DRIVE_FILE_ID>.
Add a Google Gemini(PaLM) API credential and select it in Google Gemini Chat Model.
Change the role in the first message of Candidate Resume Analyser if you are not screening plumbers.
Run it with When clicking ‘Test workflow’.

How to use it

Run the workflow by hand. The picture of the resume goes to Gemini, and the answer comes back as is_qualified and reason. The node Should Proceed To Stage 2? then sends the item to its true or false output.

What to change for a different result

To change	Where
The role and the questions asked	The first message in `Candidate Resume Analyser`
The model	`modelName` in `Google Gemini Chat Model`
The sharpness of the picture	`dpi` in `PDF-to-Image API`
The size of the picture	`width` and `height` in `Resize Converted Image`
The resume file	`fileId` in `Download Resume`
What happens after the verdict	The two outputs of `Should Proceed To Stage 2?`, which lead nowhere yet

Example

A recruiter picks a resume PDF from Google Drive and runs the workflow with the role set to plumber.

The chain returns is_qualified as true or false with a short reason. A resume with white text that tells the AI to approve it is judged on what a person would see on the page, so the hidden text should not sway the verdict.

For newcomers and experts

If you are new. n8n draws a workflow as boxes joined by lines, and each box, a node, does one job. A vision model is an AI that can look at a picture. This workflow gives it a picture of the resume rather than the resume’s text.

For experts. The chain is a Basic LLM Chain version 1.4 with an image message that reads the binary field data, and a structured output parser version 1.2 that returns {output: {is_qualified, reason}}. The IF node reads $json.output.is_qualified.

Where to look closer

Node	What it does	What to know
`Download Resume`	Downloads the PDF from Google Drive	The file arrives as binary in the field `data`
`PDF-to-Image API`	Posts the PDF to Stirling PDF and gets a JPG back	The setting `single` puts all pages in one image, at 300 dpi
`Resize Converted Image`	Shrinks the picture to 75 percent	It needs GraphicsMagick on the machine that runs n8n
`Candidate Resume Analyser`	Sends the picture and the role message to Gemini	The model sees the picture, not the PDF’s text layer
`Should Proceed To Stage 2?`	Splits the item by the verdict	Both outputs are empty, so add your next steps there

Good to know

The model was replaced and the address of the converter was removed. Mindket did not run this workflow.

Model: the file used models/gemini-1.5-pro-latest, which Google’s models page, read on 12 November 2026, no longer lists. Mindket’s copy uses models/gemini-3.8-flash, which the page lists as stable with image and PDF input
Why a picture: Gemini 3.8 can read a PDF directly, but then it also reads any hidden text layer. The picture shows only what a person would see on the page
Privacy: the original pointed at a public Stirling PDF server. Mindket’s copy has a placeholder, so run your own. The resume goes to that server and then to Google
One image: the single setting joins all pages into one picture (Stirling PDF’s source), so a long resume gives a tall image
Limits: the check cannot catch text that is visible on the page, and the verdict can be wrong, so a person should read the resumes of people it turns down
The file holds no credential and no Drive file ID

README and files

README