Create a code assistant that learns from your GitHub repository using OpenAI

Selectively import workflows from GitHub, including nested folders

This template lets you selectively import n8n workflows from a GitHub repository, even when your repository uses deeply nested folder structures. Unlike most import workflows, this template does not load everything automatically. Instead, it: • Traverses all nested folders in your repository • Collects every workflow JSON file found • Dynamically generates a selection form • Allows you to choose exactly which workflows to load • Cleans incompatible fields for n8n API compatibility • Create

Create OpenAI-compatible API using GitHub models for free AI access

This n8n template shows you how to connect Github's Free Models to your existing n8n AI workflows. Whilst it is possible to use HTTP nodes to access Github Models, The aim of this template is to use it with existing n8n LLM nodes - saves the trouble of refactoring! Please note, Github states their model APIs are not intended for production usage! If you need higher rate limits, you'll need to use a paid service. How it works The approach builds a custom OpenAI compatible API around the Github M

Build a RAG system with automatic citations using Qdrant, Gemini & OpenAI

This workflow implements a Retrieval-Augmented Generation (RAG) system that: Stores vectorized documents in Qdrant, Retrieves relevant content based on user input, Generates AI answers using Google Gemini, Automatically cites the document sources (from Google Drive). --- Workflow Steps 1. Create Qdrant Collection A REST API node creates a new collection in Qdrant with specified vector size (1536) and cosine similarity. 2. Load Files from Google Drive The workflow lists all files in a Googl

AI auto-save Gmail receipts to Google Sheets + Google Drive

Who is this for? This workflow is ideal for: - For freelancers, business owners, and finance teams who receive receipts via Gmail - Automatically logs expenses for tax, - bookkeeping and year-end audits What problem is this workflow solving? When tax season hits, missing receipts create panic. This workflow keeps everything in one place. It uses AI to extract details from Gmail attachments, logs them in a Google Sheet, and stores the PDFs in Google Drive. No digging. No copying. Just everythin

Send automated emails and add rows in Google Sheets using ChatGPT completions

Automatically send personalized emails and add new rows in Google Sheets with ChatGPT. Triggered by new rows, this workflow enhances communication and data management.

Repurpose RSS blog posts into social content with OpenAI, Sheets, Gmail and Slack

Quick Overview This workflow runs daily, pulls the latest post from an RSS feed, and uses OpenAI to repurpose it into an SEO blog rewrite, a LinkedIn post, and an X/Twitter thread, then logs the drafts to Google Sheets, creates a Gmail draft, and posts a preview to Slack. How it works 1. Runs every 24 hours on a schedule. 2. Loads your RSS feed URL, audience, and brand voice settings and fetches the latest items from the RSS feed. 3. Keeps only the newest feed item to avoid processing multiple p

Production AI Playbook: Deterministic Steps & AI Steps (5 of 5)

The full end-to-end workflow that chains all patterns together. This template processes customer feedback from intake to team routing, with normalization, validation, native guardrails, AI classification, and confidence-based branching at every step. What you'll do - Send customer feedback through a webhook and watch it flow through every stage. - See the data get normalized, validated, and scanned by n8n's native Guardrails node for jailbreak attempts and PII. - Watch the AI classify feedback (

Personalise outreach emails using customer data and AI

This n8n template uses existing emails from customers as context to customise and "finetune" outreach emails to them using AI. By now, it should be common knowledge that we can leverage AI to generate unique emails but in a way, they can remain generic as the AI lacks the customer context to be truly personalised. One way to solve this is by pulling in a source of customer data - and what better way then by using existing email correspondence. How it works Customers to target are pulled from Hu