Template to get your public IP address and push it to Namecheaps Dynamic DNS per subdomain. Open "yourdomain.com" Insert your domain and your Namecheap DDNS password Open "subdomains" Replaces and insert your subdomains Execute Workflow Have fun!
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See all General Automation→Tiny tiny Rss (aka tt-rss) Feed to Mastodon
Every 10 minutes look at your published news in your Tiny tiny RSS public feed and make a toot on your mastodon. You'll need: Your mastondon URL instance Your mastondon access token Your Tiny Tiny RSS public published feed URL
Sync Etsy customers with Meta custom audiences using hashed emails
Quick overview This workflow runs daily to fetch recent Etsy receipt emails via an Etsy Shop Operations sub-workflow, normalizes and SHA-256 hashes the emails, and either previews the hashed payload or uploads it to a Meta Custom Audience using the Meta Graph API. How it works Runs every day on a schedule. Sets sync parameters (lookback window, maximum receipts, dry-run mode, Meta audience ID, and API version). Requests recent Etsy receipt records from a connected Etsy Shop Operations workflow and extracts buyer/payment email addresses. Normalizes, deduplicates, and SHA-256 hashes the email addresses to build a Meta Custom Audience upload payload. If dry-run is enabled, returns counts and a small sample of hashes for verification. If dry-run is disabled, sends the hashed EMAIL payload to the Meta Graph API endpoint for the specified Custom Audience. Setup Configure and connect the “Get Etsy customer receipts” execute-workflow step to an Etsy Shop Operations (PRO) workflow that returns receipt records including buyer/payment emails. Create or choose a Meta Custom Audience and paste its ID into the configuration values. Add a Meta access token to the HTTP header auth for the upload r
Rank resumes by job description similarity using Gemini embeddings
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. Use the workflo