Quick overview This workflow collects resume PDFs and a job description via an n8n form, generates embeddings with Google Gemini, calculates cosine similarity between each resume and the job description, and returns a CSV-style ranked list of filenames. How it works Receives resume PDF uploads and a job description text through an n8n Form trigger. Creates a semantic embedding for the job description using the Google Gemini Embeddings API (gemini-embedding-2). Splits the uploaded files into individual resume items and converts each PDF binary to a Base64 string. Sends each Base64-encoded PDF to the Google Gemini Embeddings API to generate a multimodal embedding for the resume. Calculates cosine similarity between the job description embedding and each resume embedding, then sorts resumes from most similar to least similar. Returns a CSV-formatted ranking (Rank, File Name) in the form completion response. Setup Create and add a Google Gemini (PaLM) API credential in n8n with an API key that can access the gemini-embedding-2 model. Ensure the Google Gemini credential is selected on both HTTP requests that create the job description embedding and the resume embeddings.
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