OpenAI Embeddings → Google Drive Trigger

• Create a Google Drive folder to watch. • Connect your Google Drive account in n8n and authorize access. • Point the Google Drive Trigger node to this folder (new/modified files trigger the flow).

RAG_Ingest. Uses httpRequest, vectorStoreSupabase, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 73 nodes.

This n8n template automatically classifies incoming emails (Sales, Support, Internal, Finance, Promotions) and routes them to a dedicated OpenAI LLM Agent for processing. Depending on the category, th

Automate Outreach Prospect automates finding, enriching, and messaging potential partners (like restaurants, malls, and bars) using Apify Google Maps scraping, Perplexity enrichment, OpenAI LLMs, Goog

Chat with docs - 5minAI New version. Uses httpRequest, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, embeddingsOpenAi. Event-driven trigger; 62 nodes.

I prepared a detailed guide that illustrates the entire process of building an AI agent using Supabase and Google Drive within N8N workflows.

Auto repost job with RAG is a workflow designed to automatically extract, process, and publish job listings from monitored sources using Google Drive, OpenAI, Supabase, and WordPress. This integration

RAG AI Agent Template V5. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, googleDrive. Event-driven trigger; 56 nodes.

Automatically extract job listings from any website URL, format them with AI, and publish directly to WordPress. Just send a URL via Telegram, and watch as the workflow scrapes the job details, enhanc

OIL Rag. Uses lmChatOpenAi, embeddingsOpenAi, agent, telegramTrigger. Event-driven trigger; 53 nodes.

Turn your docs into an AI-powered internal or public-facing assistant. This chatbot workflow uses RAG (Retrieval-Augmented Generation) with Supabase vector search to answer employee or customer questi

Reranks #1. Uses googleDrive, vectorStoreSupabase, embeddingsOpenAi, documentDefaultDataLoader. Event-driven trigger; 48 nodes.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

This n8n workflow automates the process of ingesting files from Google Drive into a Supabase database, preparing them for a knowledge base system. It supports text-based files (PDF, DOCX, TXT, etc.) a

Ultimate Agentic RAG AI Agent Template. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, stickyNote. Event-driven trigger; 42 nodes.

📺 Full walkthrough video: https://youtu.be/r5kN_la0O7I

🛠️ How It Works: System Architecture Workflow ini bekerja melalui empat lapisan proses utama yang terintegrasi secara otomatis: Input Processing & Routing Telegram Trigger: Menangkap setiap pesan masu

This RAG workflow allows you to build a smart chat assistant that can answer user questions based on any collection of documents you provide. It automatically imports and processes files from Google D

Indoor Farming Agent. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, toolVectorStore. Webhook trigger; 36 nodes.

This workflow is perfect for: Businesses and teams who need an automated solution to organize, analyze, and retrieve insights from their internal documents. Researchers who want to quickly analyze and

This n8n workflow implements a fully automated Retrieval-Augmented Generation (RAG) pipeline powered by Google Drive, OpenAI embeddings, and Pinecone.

This n8n workflow automates the process of ingesting documents from multiple sources (Google Drive and web forms) into a Qdrant vector database for semantic search capabilities. It handles batch proce

This workflow creates a conversational assistant that can answer questions based on your Google Drive documents. It automatically processes various file types and uses Retrieval-Augmented Generation (

This workflow is built for individuals, teams, and businesses that receive regular inquiries via email and want to automate responses in a way that’s intelligent, brand-aligned, and always up to date.