Chat Trigger → Google Drive Trigger

This comprehensive workflow automates the complete financial document processing pipeline using AI. Upload invoices via chat, drop expense receipts into a folder, or add bank statements - the system a

• 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).

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.

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

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

This template creates a comprehensive, production-ready Retrieval-Augmented Generation (RAG) system. It builds a sophisticated AI agent that can answer questions based on documents stored in a specifi

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

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

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 implements a Retrieval-Augmented Generation (RAG) system that integrates Google Drive and Qdrant.

This workflow is your all-in-one pipeline to turn any document into a powerful searchable knowledge base using RAG (Retrieval-Augmented Generation). From the moment a file lands in your Google Drive,

Order and Delivery Support. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, toolVectorStore. Event-driven trigger; 29 nodes.

Supabase RAG AI Agent PDFs & More. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, toolVectorStore. Event-driven trigger; 29 nodes.

Answers should given only within provided text. Chat interface powered by LLM (Ollama) Retrieval-Augmented Generation (RAG) using Supabase Vector DB Multi-format file support (PDF, Excel, Google Docs,

This powerful AI automation add-on upgrades your Telegram Bot Starter Template by integrating a fully functional AI chatbot and a context-aware AI agent that answers user questions using your internal

Empower your workflows with an intelligent AI chat assistant that retrieves real-time context from Google Sheets and a Pinecone knowledge base using Retrieval-Augmented Generation (RAG). 🤖📂 This workf