Cv resume PDF parsing with multimodal vision AI
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 8 nodes and runs manually, when you click “Execute workflow”. Along the way it connects Google Drive and Google Gemini Chat Model. It also calls stirlingpdf.io over HTTP.
How it runs
Trigger: Manually, when you click “Execute workflow”.
- Download Resume (Google Drive): download
- PDF-to-Image API (HTTP Request): calls stirlingpdf.io (POST)
- Resize Converted Image (Edit Image): resize
- Candidate Resume Analyser (Basic LLM Chain): sends a prompt to an LLM, with model: Google Gemini Chat Model; output parser: Structured Output Parser
- Should Proceed To Stage 2? (If): checks a condition and branches into true / false
Services it uses
HTTP calls to: stirlingpdf.io
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (8)
- Manual Trigger
n8n-nodes-base.manualTrigger - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - If
n8n-nodes-base.if - Google Drive
n8n-nodes-base.googleDrive - HTTP Request
n8n-nodes-base.httpRequest - Edit Image
n8n-nodes-base.editImage - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm
From the author
This n8n workflow demonstrates how we can use Multimodal LLMs to parse and extract from PDF documents in n8n. In this particular scenario, we're passing a candidate's CV/resume to an AI which filters out unqualified applications. However, this sneaky…