Basic RAG chat

Automatic media download from WhatsApp Business messages with HTTP storage

This workflow listens for incoming WhatsApp messages that contain media (e.g., images) and automatically downloads the media file using WhatsApp's private media URL. - The trigger node activates when a WhatsApp message with media is received. - The media ID is extracted from the message payload. - A private media URL is retrieved using the media ID. - The media file is downloaded using an authenticated HTTP request. Ideal for: - Archiving WhatsApp media to external systems. - Triggering further

AI-powered accounting reports from Sabre EDI with GPT-4 and Pinecone RAG

This workflow automates the process of reading EDI files generated by Sabre, parsing them using an AI Agent, and producing structured accounting reports like: 📌 Accounts Receivable (AR) Summary 📌 Tax and Surcharges Report It also uses Retrieval-Augmented Generation (RAG) to vectorize the Sabre Interface User Record (IUR)—a 154-page technical document—so that the AI agent can reference it when clarification is required while generating reports. ⚙️ Tools & Integrations Used Component:Tool/S

Company knowledge base agent (RAG)

Overview 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 questions based on your company documents—automatically updated via Google Drive. Whether it’s deployed in Telegram or embedded on your website, this agent supports voice and text input, transcribes voice messages, pulls relevant context from your internal files, and responds with a helpful,

Extract text from Google Drive image / pdf, translate and extract entities from text

Use this template to extract Text from images and PDF (OCR) then Translate text and Extract named entities. Created by tech@edenai.co

RAG chatbot for company documents using Google Drive and Gemini

This workflow implements a Retrieval Augmented Generation (RAG) chatbot that answers employee questions based on company documents stored in Google Drive. It automatically indexes new or updated documents in a Pinecone vector database, allowing the chatbot to provide accurate and up-to-date information. The workflow uses Google's Gemini AI for both embeddings and response generation. How it works The workflow uses two Google Drive Trigger nodes: one for detecting new files added to a speci

Send a new file from Google Drive to Egnyte

When a new file is saved in Google Drive, the file is imported to Egnyte.

Enhance Chat Responses with Real-Time Search via Bright Data MCP & Gemini AI

Disclaimer This template is only available on n8n self-hosted as it's making use of the community node for MCP Client. Who this is for? The Chat Conversations with Bright Data MCP Search Engines & Google Gemini workflow is designed for users who need real-time, AI-enhanced conversations powered by live search engine results. This workflow is tailored for:​ 1. Data Analysts - Who want live, search-based data fused with AI reasoning. 2. Marketing Researchers - Seeking up-to-the-minute market or c

Advanced Medium API MCP server

ADVANCED USE ONLY - Medium MCP Server (32 operations) 🚨 This workflow is for advanced users only! Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator? Join the community This MCP server contains 32 operations which is significantly more than the recommended maximum of tools for most AI clients. 🔍 Recommended Alternative for basic use cases Seek a simplified MCP server that utilizes the official n8n tool implementation for Medium