# templates

name: Send personalized hotel pre-arrival messages using OpenAI, Google Sheets and Slack
author_name: Rahul Joshi
author_username: rahul08
categories: []
created_at: 2026-01-23T14:10:23.717Z
updated_at: 2026-01-23T14:10:23.717Z
url: https://n8n.io/workflows/12948
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Description
  This workflow automates a personalized pre-arrival guest experience for hotels by combining Google Sheets, OpenAI, Email, and Slack. It detects upcoming check-ins, maintains unified guest profiles for new and returning guests, and sends warm, AI-generated welcome messages exactly 2 days before arrival, ensuring a premium, consistent experience without manual effort.

  ⚠️ Deployment Disclaimer
   This workflow is intended for self-hosted n8n instances.

  ⚙️ What This Workflow Does (Step-by-Step)
   ▶️ Scheduled Daily Trigger
   Runs automatically each day to process upcoming arrivals.
  📄 Fetch Guest Profiles (Google Sheets)
   Loads guest reservations and existing guest history from the source of truth.
  👤 Guest Profile Handling
   Merges data for returning guests or creates a new profile for first-time visitors.
  ⏰ Pre-Arrival Window Check
   Calculates days until check-in and filters guests arriving within 2 days only.
  🤖 AI Welcome Message Generation
   Uses OpenAI to generate short, personalized pre-arrival messages based on preferences, allergies, and special occasions.
  📬 Multi-Channel Delivery
   Sends the message via Slack (if available) or Email and logs all messages to Google Sheets.
  🗂 Profile & Message Logging
   Updates guest profiles and stores sent messages for tracking and audit.
  🚨 Error Monitoring
   Any workflow failure triggers an immediate Slack alert.

  🧩 Prerequisites
   • Google Sheets OAuth2
   • OpenAI API key
   • Slack API access
   • SMTP email credentials
   • Self-hosted n8n recommended

  💡 Key Benefits
   ✔ Personalized pre-arrival communication
   ✔ Zero manual guest follow-ups
   ✔ Unified guest profiles (new + returning)
   ✔ Timed, non-spammy outreach
   ✔ Full logging and error visibility

  👥 Perfect For
  Hotels & resorts
  Boutique hospitality brands
  Property managers
  Guest experience teams

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.function","n8n-nodes-base.function","n8n-nodes-base.function","n8n-nodes-base.if","n8n-nodes-base.openAi","n8n-nodes-base.if","n8n-nodes-base.emailSend","n8n-nodes-base.errorTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.slack","n8n-nodes-base.googleSheets","n8n-nodes-base.slack"]

workflow_json_compressed:
  [encoded data, 6348 characters]

metadata_json:
  {"categories":["Communication","Customer Service"],"complexity":"medium","use_cases":["Automate guest welcome messages","Generate personalized email content","Sync guest profiles from spreadsheets"],"estimated_setup_minutes":45,"required_services":["n8n (Self-hosted)","OpenAI (for content generation)","Slack (for notifications)","Google Sheets (for data storage and retrieval)"],"key_features":["AI-generated personalized greetings","Automated check-in detection","Unified guest profile management"],"target_audience":["hotel managers","customer service teams","operations staff"]}


name: Generate weekly AI equity research reports with Google Sheets, FMP, NewsAPI, OpenAI, and Gmail
author_name: Rahul Joshi
author_username: rahul08
categories: []
created_at: 2026-01-23T14:11:35.800Z
updated_at: 2026-01-23T14:11:35.800Z
url: https://n8n.io/workflows/12949
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  📘 Description
  This workflow automatically generates professional equity research reports for selected companies using financial data, market news, and AI analysis. It is designed for analysts, founders, and finance teams who want consistent, data-backed equity insights without manual research.
  On a weekly schedule, the workflow reads a list of companies from Google Sheets and processes only those marked as enabled. For each company, it collects five years of financial statements and recent market news, calculates key financial signals, and uses AI to generate a structured SWOT analysis, risk assessment, and growth outlook. The final report is converted into a PDF, logged for tracking, and emailed automatically.

  ⚙️ What This Workflow Does (Step-by-Step)
  ⏰ Weekly Scheduler
   Runs the workflow automatically at a fixed weekly time.
  📄 Load Company List from Google Sheets
   Uses Google Sheets as the control panel to decide which companies are analyzed.
  🔁 Iterate Enabled Companies
   Processes each enabled company one at a time for stable execution.
  📊 Fetch Financial Statements (FMP)
   Pulls income statement, balance sheet, and cash flow data for the last five years.
  📰 Fetch Recent Market News
   Retrieves the latest company-related news headlines.
  🧹 Normalize Financials & News
   Cleans and structures all data into a consistent format.
  📐 Compute Financial & Market Signals
   Calculates revenue growth, margins, leverage, cash flow strength, and buyback signals.
  🤖 AI SWOT Analysis
   Generates strengths, weaknesses, opportunities, and threats using only derived signals and news.
  📈 AI Risk & Growth Outlook
   Identifies key risks and provides a 12–24 month growth outlook.
  📝 Build Equity Research Report (HTML)
   Combines all insights into a clean, readable report layout.
  📄 Convert Report to PDF
   Automatically renders the HTML report into a downloadable PDF.
  📊 Log Report Metadata to Google Sheets
   Stores PDF URL, size, timestamp, and expiry for tracking.
  📧 Email Research Report
   Sends the PDF download link to stakeholders.

  🧩 Prerequisites
  • Google Sheets API access
   • Financial Modeling Prep (FMP) API key
   • NewsAPI key
   • OpenAI API access
   • Gmail OAuth2 credentials
   • HTML-to-PDF service credentials

  💡 Key Benefits
  ✔ Fully automated equity research reporting
   ✔ Consistent, repeatable analysis every week
   ✔ Data-backed AI insights with no assumptions
   ✔ No manual data collection or formatting
   ✔ Clean PDF reports ready for sharing
   ✔ Centralized tracking in Google Sheets
   ✔ Scales easily to multiple companies

  👥 Perfect For
  Equity analysts
  Investment research teams
  Startup founders
  Finance and strategy teams
  Advisory and consulting firms
  Anyone producing regular equity research reports

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.splitInBatches","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.merge","n8n-nodes-htmlcsstopdf.htmlcsstopdf","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 9392 characters]

metadata_json:
  {"categories":["AI/ML","Finance","Data Processing"],"complexity":"medium","use_cases":["Automated equity research","Weekly report generation","Financial data analysis"],"estimated_setup_minutes":15,"required_services":["Google Sheets","Financial Modeling Prep (FMP)","NewsAPI","OpenAI","Gmail"],"key_features":["Scheduled execution","AI-driven insights generation","Multi-source data aggregation"],"target_audience":["analysts","finance teams","founders"]}


name: Generate hotel guest upsell recommendations with OpenAI, Sheets and Slack
author_name: Rahul Joshi
author_username: rahul08
categories: []
created_at: 2026-01-23T14:12:45.011Z
updated_at: 2026-01-23T14:12:45.011Z
url: https://n8n.io/workflows/12950
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  📘 Description
  This workflow automates guest upsell discovery and recommendation for hotels by combining Google Sheets, OpenAI, and Slack. It is designed to help hospitality teams proactively identify the single best upsell opportunity for each guest—before arrival or during the stay—without manual analysis or guesswork.

  The workflow runs on a fixed daily schedule and reads guest records from Google Sheets, which acts as the operational source of truth. Guests are automatically categorized based on stay status (upcoming arrivals vs. currently checked in). For each guest, relevant context such as room type, repeat status, spend level, preferences, and special occasions is prepared and passed to an AI engine. The AI deterministically recommends one high-confidence upsell (e.g., room upgrade, airport pickup, spa, dining, or experience), returns a structured JSON response, and explains the reasoning behind the recommendation.

  The selected upsell type is written back to the spreadsheet for tracking, and a clear, actionable Slack notification is sent to the team so they can act immediately. Any workflow failure triggers a Slack alert, ensuring reliability and operational visibility.

  ⚙️ What This Workflow Does (Step-by-Step)

   ⏰ Daily Scheduled Trigger
   Runs automatically every day at a fixed time.
  📊 Read Guest Data from Google Sheets
   Fetches all guest records from the central spreadsheet.
  🔀 Split by Stay Status
   Routes guests into two paths: before arrival or during stay.
  🎯 Prepare Guest Context
   Extracts guest attributes (room type, spend level, preferences, occasion, stay phase).
  🤖 AI Upsell Recommendation
   Uses OpenAI to recommend one best upsell per guest and returns structured JSON.
  🧹 Parse AI Response
   Cleans and validates AI output to ensure reliability.
  💾 Update Guest Record
   Writes the selected upsell type back into Google Sheets.
  💬 Notify Team in Slack
   Posts a formatted upsell notification with reasoning for immediate action.
  🚨 Error Handling → Slack Alert
   Sends an instant alert if any step in the workflow fails.

  🧩 Prerequisites
   • Google Sheets OAuth2 (read/write)
   • OpenAI API key (GPT-4o-mini)
   • Slack API credentials
   • Self-hosted n8n recommended

  💡 Key Benefits
   ✔ Identifies high-value upsell opportunities automatically
   ✔ Context-aware AI recommendations (not generic offers)
   ✔ Clear before-arrival vs. during-stay logic
   ✔ Real-time team visibility via Slack
   ✔ Centralized tracking in Google Sheets
   ✔ Built-in error monitoring

  👥 Perfect For
  Hotels and resorts
  Revenue and upsell teams
  Front-desk and concierge teams
  Hospitality operators focused on guest experience and ARPU growth

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.errorTrigger","n8n-nodes-base.slack","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.slack"]

workflow_json_compressed:
  [encoded data, 6136 characters]

metadata_json:
  {"categories":["Customer Service","Marketing","Operations"],"complexity":"complex","use_cases":["auto-suggest upsells","analyze guest data","send recommendations"],"estimated_setup_minutes":45,"required_services":["OpenAI","Google Sheets","Slack","Google"],"key_features":["scheduled automation","AI-driven recommendation","multi-platform integration","error handling","conditional logic"],"target_audience":["hotel staff","hospitality managers"]}


name: Receipt Processing AI Agent (with step by step video)
author_name: Milan Vasarhelyi - SmoothWork
author_username: vasarmilan
categories: []
created_at: 2026-01-23T17:15:46.032Z
updated_at: 2026-01-23T17:15:46.032Z
url: https://n8n.io/workflows/12954
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:22
description:
  Video Introduction

  Want to automate your inbox or need a custom workflow? 📞 Book a Call | 💬 DM me on Linkedin

  What This Workflow Does

  This automation eliminates the tedious task of manually entering receipt data by automatically processing receipt images uploaded to Google Drive. When you drop a new receipt into a monitored folder, the workflow extracts vendor name, date, itemized purchases, and total amount using AI, logs everything to a Google Sheet, and sends you an email confirmation with a formatted summary.

  Key Benefits

  Save time:** No more manual data entry from receipts
  Reduce errors:** AI-powered extraction ensures accuracy
  Stay organized:** All expense data automatically tracked in one spreadsheet
  Get notified:** Instant email confirmation when receipts are processed

  Common Use Cases

  Personal expense tracking and budgeting
  Small business accounting and bookkeeping
  Reimbursement documentation
  Tax preparation record-keeping

  Setup Requirements

  Accounts needed:
  Google Drive account (for receipt storage)
  OpenAI account (for AI-powered data extraction)
  Google Sheets account (for data logging)
  Gmail account (for notifications)

  Configuration steps:

  Google Drive: Connect your account and select the folder where you'll upload receipts
  Google Sheets: Make a copy of the template spreadsheet (link in workflow notes) to your own account and update the Sheet ID in the workflow
  Email recipient: Change the notification email address to your own
  AI model: The workflow uses GPT-4-mini by default, but you can select a different OpenAI model based on your accuracy and cost preferences

  The AI Agent is configured to extract data in a strict JSON format with fields for vendor, date (converted to DD/MM/YYYY), itemized purchases, and total amount.

nodes_used:
  ["n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.googleSheets","n8n-nodes-base.html","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4444 characters]

metadata_json:
  {"categories":["Data Processing","Finance"],"complexity":"medium","use_cases":["Automate receipt scanning","Extract financial data from images","Sync expenses to spreadsheets","Generate expense reports"],"estimated_setup_minutes":15,"required_services":["Google Drive","Google Sheets","Email"],"key_features":["AI-powered image analysis","OCR text extraction","Automatic data logging","Email notifications"],"target_audience":["accountants","finance managers","small business owners"]}


name: Generate proposals with GPT-4o, Google Docs, Gmail and Slack
author_name: Hyrum Hurst
author_username: hyrum-hurst
categories: []
created_at: 2026-01-24T06:40:04.301Z
updated_at: 2026-01-24T06:40:04.301Z
url: https://n8n.io/workflows/12959
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  Who’s it for
  Consultants, agencies, freelancers, and professional service firms who need to create customized proposals and contracts quickly and efficiently.

  How it works / What it does
  This n8n workflow automates the entire proposal and contract creation process:
  Triggers when a new client is added to Google Sheets or CRM.
  Normalizes client data for processing.
  Generates personalized proposal content using OpenAI AI models based on templates, pricing, and client info.
  Creates a Google Doc proposal.
  Converts the proposal to PDF.
  Sends the proposal via Gmail or Outlook.
  Optionally routes the proposal to DocuSign or PandaDoc for e-signature collection.
  Logs the proposal and client info in Google Sheets for tracking.
  Sends Slack notifications to internal teams.
  Routes high-value clients for priority follow-up via email and Slack alerts.

  How to set up
  Connect Google Sheets or your CRM for client data.
  Configure Gmail or Outlook credentials.
  Add OpenAI credentials for proposal generation.
  Connect Slack for notifications.
  Optional: Connect DocuSign/PandaDoc.
  Customize decision nodes for priority clients or additional workflows.

  Requirements
  n8n account with Google Sheets, Gmail/Outlook, Slack integrations.
  Optional DocuSign/PandaDoc accounts for signature collection.
  OpenAI API key for AI proposal generation.

  How to customize
  Adjust templates in OpenAI prompts for company tone/style.
  Modify Sheet columns for additional client info.
  Change decision logic to define what counts as a high-value client.
  Add other integrations like CRM updates or analytics dashboards.

  Created by Hyrum Hurst / QuarterSmart  
  Keywords: AI proposal automation, contract automation, consulting, proposal generation, n8n workflow, QuarterSmart

nodes_used:
  ["n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.set","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleDocs","n8n-nodes-base.httpRequest","n8n-nodes-base.gmail","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.slack","n8n-nodes-base.if","n8n-nodes-base.slack","n8n-nodes-base.gmail","n8n-nodes-base.errorTrigger","n8n-nodes-base.slack","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 6032 characters]

metadata_json:
  {"categories":["Marketing","Communication","Productivity","Data Processing","Business Development"],"complexity":"medium","use_cases":["Generate client proposals","Create contract documents","Automate outreach","Personalize content","Manage client data"],"estimated_setup_minutes":30,"required_services":["Google Sheets","Google Docs","Gmail","Slack","OpenAI GPT-4o","CRM systems"],"key_features":["AI-powered content generation","Multi-tool automation","Data normalization","Conditional logic","Error handling"],"target_audience":["Consultants","Agencies","Freelancers"]}


name: Search flights with Gemini via Telegram and send SerpAPI price alerts
author_name: Nguyễn Thiệu Toàn (Jay Nguyen)
author_username: nguyenthieutoan
categories: []
created_at: 2026-01-24T15:31:25.117Z
updated_at: 2026-01-24T15:31:25.117Z
url: https://n8n.io/workflows/12971
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  📖 Overview

  A comprehensive flight price monitoring and AI assistant solution built entirely in n8n. Combines automated price tracking with intelligent conversational flight search via Telegram.



  Perfect for:
  ✈️ Tracking flight prices to favorite destinations
  💰 Getting alerts when prices drop below threshold
  🗓️ Planning trips with AI-powered flight searches
  🌍 Finding best deals across airlines
  📱 Managing travel plans through Telegram chat

  Requirements: n8n v1.123.0+ or v2.0.0+  SerpAPI key (500 free/month), Google Gemini API, Telegram bot token

  ⚡ What's in the Box

  Two Powerful Workflows

  | Workflow | Function | Trigger |
  |----------|----------|---------|
  | 🔔 Automated Monitoring | Tracks specific routes, alerts on price drops | Schedule (every 7 days) |
  | 💬 AI Flight Assistant | Interactive search with natural language | Telegram messages |

  Key Capabilities:
  🎯 Set price thresholds and get instant alerts
  🤖 Ask questions in natural language (Vietnamese/English)
  🧠 AI remembers conversation context
  📊 Compares prices across airlines
  ⚡ Real-time search results from Google Flights

  🎯 Key Features

  📅 Scheduled Price Checks**: Automatic monitoring every 7 days (customizable)
  💡 Smart AI Assistant**: Understands "find cheapest flight to Bangkok next weekend"
  🔔 Instant Alerts**: Telegram notifications when prices drop
  🧠 Context-Aware**: AI remembers your preferences and previous searches
  🌐 Multi-Language**: Handles Vietnamese and English seamlessly
  📱 Mobile-Ready**: Full control via Telegram chat interface


  Technical Highlights: SerpAPI integration for real-time prices, Google Gemini Flash for AI responses, session-based conversation memory, Telegram HTML formatting, automatic date calculations (+5 days for returns)

  🏗️ How It Works

  Workflow 1: Automated Monitoring
  Schedule Trigger → Configure Route → Search Flights → Extract Best Price  
                                                              ↓  
                                          Price &lt; Threshold? → Send Alert  

  Workflow 2: AI Assistant
  Telegram Message → AI Agent → Flight Search Tools → Format Response  
                        ↓              ↓                      ↓  
                   Understand     Round-trip/One-way      Telegram HTML  
                   Context        Auto +5 days return      Send to user  

  🛠️ Setup Guide

  Step 1: API Credentials
  Get SerpAPI key (https://serpapi.com), Google Gemini API (https://aistudio.google.com/app/apikey), Telegram bot token (@BotFather)

  Step 2: Configure Monitoring
  Edit Fields node: Set departure/arrival codes, price threshold, Telegram ID

  Step 3: AI Assistant Setup
  Link Gemini model to AI Agent, connect flight search tools, activate memory

  Step 4: Activate & Test
  Enable workflow, send test message to bot, verify alerts

  💡 Usage Examples

  Automated Alert:
  ✈️ CHEAPEST TICKET
  Price: 2,450,000 VND
  Airline: Vietjet Air
  Time: 06:00 → 08:00

  AI Chat:
  "Find round-trip tickets Hanoi to Bangkok tomorrow"
  "What's the cheapest flight to Nha Trang next weekend?"
  "Search one-way Da Nang to Singapore on March 15"

  👤 About the Author

  Nguyen Thieu Toan (Nguyễn Thiệu Toàn / Jay Nguyen)

  AI Automation Specialist | n8n Workflow Expert

  Contact:
  🌐 nguyenthieutoan.com
  📘 Facebook
  💼 LinkedIn
  📧 Email: me@nguyenthieutoan.com
  More Nguyen Thieu Toan's n8n Template

  GenStaff Company: genstaff.net

  📄 License

  Free for commercial/personal use. 
  Keep author attribution when sharing.**
  Ready to never miss a flight deal again? Import this workflow and start tracking prices today! 🚀

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.set","n8n-nodes-serpapi.serpApi","n8n-nodes-base.code","n8n-nodes-base.filter","n8n-nodes-base.telegram","n8n-nodes-base.telegramTrigger","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-serpapi.serpApiTool","n8n-nodes-serpapi.serpApiTool","@n8n/n8n-nodes-langchain.memoryBufferWindow"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Travel","AI/ML","Automation"],"complexity":"medium","use_cases":["track flight prices","get price drop alerts","search flights via chatbot","monitor travel deals","plan trips through messenger"],"estimated_setup_minutes":45,"required_services":["Telegram","SerpAPI","Google Gemini API"],"key_features":["AI-powered conversational search","automated price monitoring","Telegram integration","threshold-based alerting","cross-airline deal comparison"],"target_audience":["travel planners","automation enthusiasts","chatbot developers"]}


name: Turn any website into an AI support chatbot with OpenAI and Pinecone
author_name: Dinakar Selvakumar
author_username: jamesdinakar
categories: []
created_at: 2026-01-25T09:05:45.730Z
updated_at: 2026-01-25T09:05:45.730Z
url: https://n8n.io/workflows/12981
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Complete AI support system using website data (RAG pipeline)

  This template provides a full end-to-end Retrieval-Augmented Generation (RAG) system using n8n. It includes two connected workflows:

  A data ingestion pipeline that crawls a website and stores its content in a vector database.
  A customer support chatbot that retrieves this knowledge and answers user queries in real time.

  Together, these workflows allow you to turn any public website into an intelligent AI-powered support assistant grounded in real business data.

  Use cases

  AI customer support chatbot for your website  
  Internal company knowledge assistant  
  Product FAQ automation  
  Helpdesk or IT support bot  
  AI receptionist for services  
  Semantic search over company content  

  How it works

  Ingestion workflow
  Discover all URLs from a website sitemap.
  Filter and normalize the URLs.
  Fetch each page and extract readable text.
  Clean HTML into plain text.
  Split text into overlapping chunks.
  Generate embeddings using OpenAI.
  Store vectors in Pinecone with metadata.

  Chatbot workflow
  A user sends a message via chat webhook.
  The agent queries Pinecone for relevant knowledge.
  Retrieved content is passed to OpenAI.
  OpenAI generates a grounded response.
  Short-term memory maintains conversation context.

  How to use

  Step 1 – Run ingestion
  Set your target website URL.
  Add Firecrawl, OpenAI, and Pinecone credentials.
  Create a Pinecone index.
  Execute the ingestion workflow.
  Wait until all pages are indexed.

  Step 2 – Run chatbot
  Deploy the chatbot workflow.
  Set the same Pinecone index and namespace.
  Copy the chat webhook URL.
  Connect it to a website, chat widget, or WhatsApp bot.
  Start chatting with your AI assistant.

  Requirements

  Firecrawl account  
  OpenAI API key  
  Pinecone account and index  
  Public website to crawl  
  Optional: frontend chat interface  

  Good to know

  The chatbot never answers from memory for business data.
  All company knowledge comes from Pinecone.
  If Pinecone returns nothing, the bot fails safely.
  HTML cleaning is basic and can be replaced with:
    Mozilla Readability  
    Jina Reader  
    Unstructured  
  Chunk size and overlap affect retrieval quality.
  Pinecone can be replaced with:
    Qdrant  
    Weaviate  
    Supabase Vector  
    Chroma  

  Customising this workflow

  You can extend this system by:
  Adding PDF or document loaders
  Scheduling ingestion daily or weekly
  Connecting CRM or ticketing systems
  Adding appointment booking tools
  Switching to local or open-source models
  Adding multilingual support
  Storing raw content in a database
  Adding feedback or logging

  What this n8n template demonstrates

  Real-world RAG architecture  
  Web crawling pipelines  
  Text chunking strategies  
  Vector database integration  
  AI agent orchestration  
  Memory-controlled conversations  
  Production-grade AI support systems  
  End-to-end AI infrastructure with n8n  

  Architecture overview

  This template follows a modern AI system design:

  Website → Ingestion → Embeddings → Pinecone → Retrieval → OpenAI → User

  It separates:
  Data preparation (offline)
  Knowledge storage
  Runtime inference

  This makes the system scalable, maintainable, and safe for production use.

  Need a custom setup?

  If you want a similar AI system built for your business (custom data sources, CRM integration, WhatsApp bots, booking systems, dashboards, or private deployments), feel free to reach out at dinakars2003@gmail.com.

  I help companies design and deploy production-ready AI workflows.

nodes_used:
  ["n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@mendable/n8n-nodes-firecrawl.firecrawl","n8n-nodes-base.code","n8n-nodes-base.splitInBatches","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.vectorStorePinecone","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.vectorStorePinecone","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["AI/ML","Customer Support"],"complexity":"medium","use_cases":["create AI chatbots","build RAG systems","scrape website content","deploy knowledge assistants"],"estimated_setup_minutes":20,"required_services":["OpenAI","Pinecone","Firecrawl"],"key_features":["webscraper integration","vector database storage","real-time knowledge retrieval","RAG architecture","AI-powered responses"],"target_audience":["developers","customer support teams","business owners"]}


name: Manage patient appointments and care follow-ups with OpenAI, Gmail and Twilio
author_name: Cheng Siong Chin
author_username: cschin
categories: []
created_at: 2026-01-25T14:35:07.775Z
updated_at: 2026-01-25T14:35:07.775Z
url: https://n8n.io/workflows/12985
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:22
description:
  How It Works
  This workflow automates patient care coordination in healthcare settings by intelligently processing patient information and scheduling follow-up communications through multiple channels. Designed for healthcare administrators, clinic coordinators, and medical practice managers, it solves the critical problem of manual patient follow-up management and inconsistent communication across care teams. The system receives patient intake data, uses AI-powered agents to analyze care requirements and determine appropriate notification timing, then automatically dispatches personalized messages via email and SMS. The workflow leverages OpenAI's advanced models for care coordination logic and notification content generation, ensuring contextually appropriate and timely patient communications while maintaining conversation history for continuity of care.

  Setup Steps
  Configure OpenAI credentials with API key for AI model access
  Set up EHR System Tool node with your electronic health records integration endpoint
  Configure Scheduling System Tool with your appointment management system API
  Connect Gmail account for email notifications with OAuth authentication
  Add Twilio credentials for SMS delivery with account SID and auth token
  Customize Care Coordination Agent Tool parameters for your clinical protocols

  Prerequisites
  Active OpenAI API account with credits, connected email service (Gmail recommended)
  Use Cases
  Post-appointment follow-up reminders, medication adherence check-ins, preventive care scheduling
  Customization
  Modify AI prompts in agent tools to match your clinical workflows, adjust notification timing logic
  Benefits
  Reduces administrative workload by 70%, ensures consistent patient follow-up

nodes_used:
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metadata_json:
  {"categories":["Healthcare","Medical Administration"],"complexity":"medium","use_cases":["automated patient follow-ups","care coordination","appointment scheduling","patient communication"],"estimated_setup_minutes":30,"required_services":["OpenAI","Gmail","Twilio"],"key_features":["AI-powered patient intake analysis","multi-channel communication","automated follow-up management","structured data processing"],"target_audience":["healthcare administrators","clinic coordinators","medical practice managers"]}


name: Triage emergency patients via chat with GPT-4.1 and hospital systems
author_name: Cheng Siong Chin
author_username: cschin
categories: []
created_at: 2026-01-25T14:48:45.717Z
updated_at: 2026-01-25T14:48:45.717Z
url: https://n8n.io/workflows/12986
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:22
description:
  How It Works
  This workflow automates hospital emergency department triage by intelligently processing patient intake information through multiple AI-powered assessment stages. Designed for emergency departments, urgent care centers, and hospital admission teams, it solves the critical challenge of rapid, accurate patient prioritization during high-volume periods. The system captures initial patient data through a chat interface, uses specialized AI agents to analyze medical history and current symptoms, validates business rules for priority assignment, performs stability checks, calculates priority scores, and determines required actions. It then routes patients to appropriate care pathways while sending notifications to relevant medical teams and logging all interactions for audit compliance. The workflow leverages OpenAI models and structured JSON parsing to ensure consistent, protocol-driven triage decisions.

  Setup Steps
  Configure OpenAI credentials with API key for AI agent access
  Set up Hospital Triage Agent node with your clinical triage protocols
  Configure Patient Consent and Structured JSON checkers with validation rules
  Connect notification endpoints for Execute Appointment and Send Notification nodes
  Set up audit logging system integration in Log Interactions node
  Customize business rule validation parameters for your facility's triage categories

  Prerequisites
  Active OpenAI API account, hospital system API access for appointments and notifications
  Use Cases
  Emergency department patient intake, urgent care prioritization, virtual triage for telehealth
  Customization
  Modify triage agent prompts to reflect your clinical protocols, adjust priority scoring algorithms
  Benefits
  Accelerates triage processing by 60%, ensures standardized clinical assessment

nodes_used:
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metadata_json:
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name: Evaluate automotive component compliance with OpenAI GPT-4.1 and regulatory APIs
author_name: Cheng Siong Chin
author_username: cschin
categories: []
created_at: 2026-01-25T15:38:11.315Z
updated_at: 2026-01-25T15:38:11.315Z
url: https://n8n.io/workflows/12990
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:22
description:
  How It Works
  This workflow automates automotive regulatory compliance evaluation by intelligently routing assessments through parallel evaluation paths based on component type. Designed for automotive compliance officers, quality assurance teams, and regulatory affairs managers, it solves the complex challenge of ensuring vehicle components meet diverse regulatory standards across safety, emissions, and performance requirements. The system receives compliance evaluation requests via webhook, determines whether components require split assessment or integrated regulatory database checks, then processes each path using OpenAI-powered compliance agents with specialized tools for performance simulation and structured output parsing. Results are aggregated, risk scores calculated using business rules, enriched with compliance metadata, and logged to regulatory databases while responding to the originating system with actionable compliance status and required remediation actions.

  Setup Steps
  Configure webhook endpoint URL for compliance evaluation system integration
  Set up OpenAI API credentials for Automotive Compliance Agent access
  Configure Check Evaluation Type node with component classification rules
  Set up Fetch Regulatory Database node with regulatory standards API credentials
  Update Performance Simulation Tool with automotive testing parameters
  Configure Calculator node with compliance scoring algorithms
  Customize Structured Output Parser for regulatory reporting format requirements

  Prerequisites
  Active OpenAI API account, automotive compliance evaluation system with webhook capability
  Use Cases
  Pre-production component compliance validation, supplier part certification
  Customization
  Modify compliance agent prompts for region-specific regulations, adjust risk scoring thresholds
  Benefits
  Accelerates compliance evaluation by 70%, ensures systematic multi-regulation assessment

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.respondToWebhook","n8n-nodes-base.if","n8n-nodes-base.splitOut","n8n-nodes-base.aggregate","n8n-nodes-base.code","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.toolCode","@n8n/n8n-nodes-langchain.toolCalculator","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
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name: Qualify and route real estate leads with Anthropic Claude, MLS/CRM, and Google Sheets
author_name: Cheng Siong Chin
author_username: cschin
categories: []
created_at: 2026-01-25T16:48:12.712Z
updated_at: 2026-01-25T16:48:12.712Z
url: https://n8n.io/workflows/12996
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  How It Works
  This workflow automates real estate lead qualification and routing by enriching leads from multiple sources with AI-powered analysis and directing them to appropriate sales agents based on priority. Designed for real estate brokers, sales managers, and lead generation teams, it solves the critical challenge of quickly identifying high-value prospects from high-volume lead streams while ensuring timely agent follow-up. The system triggers on schedule, fetches leads simultaneously from MLS portals and CRM/email sources, aggregates all leads into unified dataset, splits leads for parallel processing, then deploys AI agents using Anthropic's Claude to analyze lead quality, buying intent, budget capacity, and urgency. Based on enrichment scores, leads are routed to best-fit agents by priority tier, with engagement tracking logged to Google Sheets for performance monitoring and optimization.

  Setup Steps
  Configure Schedule Trigger with desired lead processing frequency
  Set up MLS/portal integration API credentials in Fetch Leads from MLS/Portals node
  Configure CRM/email system API access in Fetch Leads from CRM/Email node
  Connect Anthropic API credentials for AI Lead Enrichment Agent
  Customize Structured Output Parser with your lead scoring criteria
  Update Check Lead Priority node with priority threshold rules
  Configure agent routing logic in Route to Best-Fit Agent nodes by priority tier

  Prerequisites
  Active Anthropic API account, MLS/real estate portal API access, CRM system with API integration 
  Use Cases
  Inbound lead qualification from property portals, open house inquiry processing, email campaign lead scoring 
  Customization
  Modify AI enrichment prompts for market-specific criteria, adjust priority scoring algorithms for business goals
  Benefits
  Reduces lead response time by 75%, ensures high-value prospects receive immediate attention

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.aggregate","n8n-nodes-base.splitOut","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatAnthropic","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
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name: Automated Website Monitoring & Performance Checks with Alerting System
author_name: SpaGreen Creative
author_username: spagreen
categories: []
created_at: 2026-01-26T10:57:41.132Z
updated_at: 2026-01-26T10:57:41.132Z
url: https://n8n.io/workflows/13009
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Who it's for
  This n8n workflow is designed for website administrators, digital marketers, SEO specialists, and business owners who want to continuously monitor their website performance metrics. It provides a complete end-to-end system capable of automatically testing website performance using Google PageSpeed Insights API, analyzing the results, and sending notifications when performance falls below specified thresholds.

  Features
  Automatically monitors website performance on scheduled intervals
  Tests websites on different devices (mobile/desktop) as configured
  Extracts Core Web Vitals metrics (LCP, FID, CLS)
  Generates performance scores and categorizes website status
  Provides actionable recommendations for performance improvements
  Sends alerts through multiple channels (Email, Telegram, Discord, WhatsApp)
  Updates Google Sheets with test results and maintains historical data
  Only tests websites that haven't been checked recently (configurable threshold)
  Processes multiple websites in batches to avoid API limits

  Requirements
  Google PageSpeed Insights API key
  Google Sheets API access with OAuth2 credentials
  Notification service credentials (Gmail, Telegram, Discord, WhatsApp/Rapiwa)
  A Google Sheet with website URLs, device types, and alert thresholds configured

  Important Notes
  Workflow runs on a scheduled trigger to automatically test websites
  Tests are only performed on websites that haven't been checked in the last 2 days
  Results are saved to a separate "report" sheet in the Google Sheet
  The original "data" sheet is updated with the last processed date and website status
  Alert messages include performance scores, Core Web Vitals metrics, and recommendations
  Performance categories are determined as: excellent (90+), needs improvement (50-89), or poor (&lt;50)
  The workflow processes up to 10 websites at a time to avoid overwhelming the system
  Different alert messages are generated based on performance severity levels

  Support & Help
  WhatsApp**: Chat on WhatsApp
  Discord**: SpaGreen Community
  Facebook Group**: SpaGreen Support
  Website**: https://spagreen.net
  Developer Portfolio**: Codecanyon SpaGreen

nodes_used:
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metadata_json:
  {"categories":["DevOps","Marketing"],"complexity":"medium","use_cases":["track website performance","detect speed issues","receive performance alerts","schedule routine checks"],"estimated_setup_minutes":15,"required_services":["Google PageSpeed Insights API","Discord"],"key_features":["automated performance testing","scheduled monitoring","threshold-based alerting","performance audit trail"],"target_audience":["website administrators","SEO specialists","digital marketers"]}


name: Analyze Binance Futures markets with TA indicators, OpenAI news checks, and Telegram alerts
author_name: Vadim Mubi
author_username: mubivadim
categories: []
created_at: 2026-01-26T11:23:27.922Z
updated_at: 2026-01-26T11:23:27.922Z
url: https://n8n.io/workflows/13011
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:22
description:
  This workflow acts as an automated market analyst for educational purposes. It scans Binance Futures (Testnet) for high-volume pairs, applies custom technical analysis (RSI, Bollinger Bands, EMA, ATR) using JavaScript, and uses AI to validate trends against recent news sentiment.

  It is designed for paper trading to demonstrate how to build advanced financial logic and adaptive risk management systems in n8n without risking real funds.

  💡 Why use this?
  Smart Scanning:** Automatically filters top 150 pairs by volume and excludes stablecoins to find active markets.
  Dynamic Risk Management:* Uses *ATR (Average True Range)** to calculate adaptive Stop Loss and Take Profit levels based on current market volatility.
  Custom Technical Analysis:** Demonstrates how to calculate complex indicators via a Function node, eliminating the need for paid TA APIs.
  AI Sentiment Filter:** Scrapes recent news and uses an LLM (OpenAI) to "vet" the technical signal against potential FUD or risks.
  Secure Execution:** Shows how to sign HMAC SHA256 requests manually to interact with the Binance Futures API.

  ⚙️ How it works
  Filter: Runs every 15 minutes to find liquid assets on Binance.
  Calculate: Computes indicators (EMA 200, BB, RSI) and defines Entry/Exit points using ATR logic.
  Validate: If a technical signal matches, it fetches news and asks AI: "Is there any breaking news that contradicts this trade?"
  Execute: If AI returns "CONFIRM", it posts the detailed analysis to Telegram and places a paper trade order on the Testnet.

  🛠 Setup Steps
  Binance Testnet: Create a free account on Binance Futures Testnet and generate API keys.
  Configuration: Open the 📝 MAIN CONFIG node and enter your Testnet Keys and Telegram Channel ID.
  Credentials: Add your OpenAI (or OpenRouter) credentials to the AI node.

  &gt; Disclaimer: This workflow connects to the Binance Testnet by default. It is intended for educational purposes only. The author and n8n are not responsible for financial decisions.

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.crypto","n8n-nodes-base.splitInBatches","n8n-nodes-base.noOp","n8n-nodes-base.telegram","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.splitInBatches","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code"]

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metadata_json:
  {"categories":["Finance","AI/ML","DevOps"],"complexity":"medium","use_cases":["monitor crypto markets","run TAS","send price alerts","analyze sentiment","backtest strategies"],"estimated_setup_minutes":45,"required_services":["Binance Futures","OpenAI","Telegram"],"key_features":["automated market scanning","custom technical indicators","news sentiment analysis","paper trading support","alert notifications"],"target_audience":["traders","developers","data analysts"]}


name: Generate AI case studies from Feedspace testimonials with Google Gemini and publish to WordPress
author_name: Feedspace
author_username: feedspace
categories: []
created_at: 2026-01-26T13:01:44.821Z
updated_at: 2026-01-26T13:01:44.821Z
url: https://n8n.io/workflows/13012
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:22
description:
  Who is this for?
  This template is for teams who collect customer testimonials on feedpsace (via forms) and want to automatically convert them into professional case studies using AI and publish them to WordPress.

  What this workflow does

  This workflow listens for incoming testimonial data via a webhook, extracts the relevant fields, uses an AI agent to generate a complete case study (including title, sections, and structure), and publishes the final content directly to WordPress.

  The AI is instructed to vary tone, angle, and structure across case studies to avoid repetitive content and improve SEO value.

  Requirements:
  Feedspace account with webhook integration enabled
  Access to a WordPress site with REST API enabled
  An AI API key (Google Gemini or compatible model)

  Setup steps
  Connect to Feedspace
  	Activate the workflow and copy the Production webhook URL
  	Go to Feedspace → Automations → Webhooks
  	Paste the webhook URL and activate it
  	See https://www.feedspace.io/help/automation/ for more information
  Add your AI API credentials to the AI model node
  Connect your WordPress account in the WordPress node
  Send testimonial data to the webhook in this format:
  	Reviewer name
  	Rating
  	Text feedback
  	Event or feedback type
  	Activate the workflow



  How it works

  Receives testimonial data through feedpsace webhook
  Extracts reviewer name, rating, feedback, and event type
  Filters for text-based testimonials
  Uses an AI agent to:
  Choose a unique case study angle and tone
  Generate structured HTML content
  Create an SEO-optimized title
  Parses and validates the AI output
  Publishes the generated case study to WordPress as a post

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.set","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.wordpress","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Marketing","Content Creation","Communication"],"complexity":"medium","use_cases":["automate case study creation","convert testimonials to content","publish content to CMS"],"estimated_setup_minutes":45,"required_services":["Feedspace","Google Gemini","WordPress"],"key_features":["AI-powered content generation","testimonial processing","CMS publishing automation","structured output formatting"],"target_audience":["content marketers","product managers","development teams"]}


name: Route Telegram channel posts to X, Threads, and LinkedIn using @mentions
author_name: 🦄 kai chen
author_username: c-wenlong
categories: []
created_at: 2026-01-26T13:30:50.959Z
updated_at: 2026-01-26T13:30:50.959Z
url: https://n8n.io/workflows/13013
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  This workflow listens to messages in a designated Telegram channel and automatically posts them to X (Twitter), Threads, and LinkedIn based on simple @mention tags. Write your content once, tag which platforms you want, and let automation handle the rest.

  Key Features

  Smart Channel Routing: Use @mentions to specify destinations (@x, @threads, @linkedin, or @all)
  Clean Message Parsing: Automatically removes @mentions and hashtags before posting
  Success Notifications: Get confirmation messages in Telegram when posts succeed
  Error Handling: Receive alerts for invalid channel tags or posting failures
  Multi-Platform Support: Post to X, Threads, and LinkedIn simultaneously or individually
  Bitwise Flag System: Efficient routing logic using binary flags for platform selection

nodes_used:
  ["n8n-nodes-base.twitter","n8n-nodes-base.linkedIn","n8n-nodes-base.code","n8n-nodes-base.switch","n8n-nodes-base.telegram","n8n-nodes-base.telegramTrigger","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.manualTrigger","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Communication","Social Media"],"complexity":"medium","use_cases":["multi-platform social posting","cross-channel content distribution","social media montage"],"estimated_setup_minutes":15,"required_services":["Telegram","Twitter (X)","Threads","LinkedIn"],"key_features":["Smart Channel Routing","Clean Message Parsing","Success Notifications"],"target_audience":["marketers","social media managers","community managers"]}


name: Create automated video ad clones with NanoBanana, Kling, Airtable and Blotato
author_name: Dr. Firas
author_username: drfiras
categories: []
created_at: 2026-01-26T15:27:45.586Z
updated_at: 2026-01-26T15:27:45.586Z
url: https://n8n.io/workflows/13015
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:20
description:
  💥 Clone Video Ads Factory using NanoBanana, Kling and Publish with Blotato
  📄 Documentation: Notion Guide

  Who is this for?
  This workflow is built for marketers, growth hackers, agencies, content creators, and automation builders who want to industrialize video ad production.  
  Perfect for anyone running paid ads, social media campaigns, UGC-style content, dropshipping creatives, AI ad testing, or scalable content factories.

  What problem is this workflow solving? / Use case
  Creating high-performing video ads is:
  Slow
  Manual
  Expensive
  Hard to scale
  Hard to test in volume

  This workflow solves:
  ❌ Manual editing
  ❌ Manual prompt writing
  ❌ Manual scene creation
  ❌ Manual video assembly
  ❌ Manual audio integration
  ❌ Manual publishing

  It turns one input video + prompt into a fully automated ad production pipeline.

  What this workflow does
  This automation system acts as a full AI video ads factory:

  Step-by-step pipeline:
  Video Analysis
     Breaks down the source video into cinematic scenes
     Extracts structure, rhythm, composition, pacing, and visual logic

  Prompt Engineering
     Generates structured prompts for:
       Images
       Videos
       Music
       Captions
       Global script
       Scene structure

  Image Generation
     Uses NanoBanana to generate consistent AI images per scene
     Keeps visual identity across scenes

  Video Generation
     Uses Kling to generate cinematic video clips
     Scene-based video creation

  Video Merging
     Automatically merges all generated scenes into one final video

  Music Generation
     Generates a full song from prompt (AI music model)

  Audio + Video Merge
     Merges generated music with the final video

  Publishing
     Automatically publishes content using Blotato
     Creates posts and media assets

  ➡️ Result: Fully automated AI video ad production system

  Setup

  Required accounts:
  Airtable
  fal.ai
  AtlasCloud** 
  Blotato**

  Initial configuration:
  Create Airtable base
  Add required fields:
     Original Video
     Avatar Image
     Product Image
     Status
     Prompts
     Scenes
     Music File
     Final Video
  Add API keys in the Setup nodes:
     AtlasCloud
     fal.ai
     Airtable
     Blotato

  Expected outcome

  You get a fully automated AI content factory that can:
  Clone ad styles
  Scale ad production
  Test creatives at scale
  Generate UGC-style ads
  Build content farms
  Automate marketing pipelines
  Create AI ad studios
  Run continuous ad experiments

  Typical use cases

  AI UGC ad factories  
  Dropshipping ad automation  
  SaaS promo videos  
  Influencer content cloning  
  Brand video scaling  
  Marketing automation  
  Ad testing labs  
  Growth hacking pipelines  
  AI content studios  

  👋 Need help or want to customize this?
  📩 Contact: LinkedIn  
  📺 YouTube: @DRFIRASS  
  🚀 Workshops: Mes Ateliers n8n

  Need help customizing?
  Contact me for consulting and support : Linkedin / Youtube / 🚀 Mes Ateliers n8n  

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.set","n8n-nodes-base.airtable","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.splitOut","n8n-nodes-base.airtable","n8n-nodes-base.airtable","@n8n/n8n-nodes-langchain.googleGemini","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.airtable","n8n-nodes-base.if","n8n-nodes-base.airtable","n8n-nodes-base.splitInBatches","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.airtable","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.set","n8n-nodes-base.airtable","n8n-nodes-base.if","n8n-nodes-base.airtable","n8n-nodes-base.code","n8n-nodes-base.splitInBatches","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.airtable","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.airtable","n8n-nodes-base.if","n8n-nodes-base.airtable","n8n-nodes-base.code","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.airtable","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.set","n8n-nodes-base.airtable","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.airtable","n8n-nodes-base.airtable","@blotato/n8n-nodes-blotato.blotato","@blotato/n8n-nodes-blotato.blotato","n8n-nodes-base.airtable","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Marketing","AI/ML","Data Processing"],"complexity":"complex","use_cases":["clone video ads","generate advertising content","scale UGC campaigns","automate ad testing","create video content"],"estimated_setup_minutes":30,"required_services":["NanoBanana","Kling","Airtable","Blotato"],"key_features":["automated video production","AI-powered ad cloning","UGC content generation","campaign scaling workflow","data synchronization"],"target_audience":["marketers","growth hackers","content creators"]}


name: Create and publish AI avatar short videos with Gemini, HeyGen and Google Sheets
author_name: giangxai
author_username: giangxai
categories: []
created_at: 2026-01-27T03:35:37.142Z
updated_at: 2026-01-27T03:35:37.142Z
url: https://n8n.io/workflows/13024
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  Automated AI Video Avatar Workflow for Shorts using n8n & HeyGen

  Automatically generate AI avatar short videos and publish them to social platforms using n8n and HeyGen.  
  This workflow turns viral ideas or prepared scripts into fully rendered AI avatar videos and handles publishing and tracking without manual editing.

  Who is this for?

  This template is ideal for:

  Content creators producing Shorts, Reels, or TikTok videos at scale  
  Marketers using AI avatars for faceless or branded content  
  Affiliate marketers running automated short-form content funnels  
  AI automation builders combining LLMs, avatars, and no-code workflows  
  Teams that want a repeatable system to generate and publish short videos  

  If you want to automate AI avatar video creation instead of manually scripting, rendering, and uploading videos, this workflow is for you.

  What problem is this workflow solving?

  Creating short-form video content with AI avatars usually involves many manual steps and tools. Common challenges include:

  Manually writing scripts for each video  
  Switching between AI tools for script generation and video rendering  
  Waiting for avatar videos to render and checking status manually  
  Uploading videos to social platforms one by one  
  Tracking which ideas have been processed or published  

  This workflow connects all steps into a single automated pipeline and removes repetitive manual work.

  What this workflow does

  This automated AI video avatar workflow:

  Triggers on a defined schedule  
  Loads viral content ideas or pending rows from Google Sheets  
  Analyzes content and generates optimized scripts using AI  
  Creates AI avatar videos automatically via HeyGen  
  Waits for video rendering and checks completion status  
  Retrieves the final video once rendering is complete  
  Publishes the video to social platforms  
  Updates Google Sheets with publishing status and results  

  The entire process runs end-to-end with minimal human intervention.

  Setup

  1. Prepare Google Sheets

  Create a Google Sheet to manage your content pipeline with columns such as:

  idea / topic – Source idea or viral reference  
  script – Generated or custom script (optional)  
  status – pending / processing / published / error  
  video_url – Final rendered video link  
  publish_result – Publishing status or notes  

  Only rows marked as pending will be processed by the workflow.

  2. Connect Google Sheets

  Authenticate your Google Sheets account in n8n  
  Select the spreadsheet in the content loading nodes  
  Ensure update nodes can write back to the same sheet for status tracking  

  3. Configure AI & HeyGen

  Add credentials for your AI model (e.g. Gemini or OpenRouter)  
  Add your HeyGen API credentials  
  Configure avatar settings such as voice, language, and style  

  Test video creation once before running the workflow at scale.

  4. Configure Publishing & Schedule

  Set up publishing credentials for your target social platforms  
  Open the Schedule trigger and define how often the workflow runs  
  The schedule controls how frequently new AI avatar videos are created and published  

  How to customize this workflow to your needs

  You can adapt this workflow without changing the core structure:

  Replace viral idea sources with your own content inputs  
  Add approval steps (Slack, Telegram, Email) before video creation  
  Customize scripts per platform or language  
  Disable publishing and use the workflow only for video generation  
  Add retry logic for failed renders or publishing steps  
  Extend the workflow with analytics or performance tracking  

  Best practices

  Start with a small batch of test rows  
  Keep status values consistent in Google Sheets  
  Use short, clear scripts optimized for AI avatars  
  Monitor render and publish status nodes regularly  
  Adjust schedule frequency based on rendering limits  

  📄 Documentation

  For a full walkthrough and advanced customization ideas, see Video Guide

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.googleSheets","n8n-nodes-base.scheduleTrigger","@apify/n8n-nodes-apify.apify","n8n-nodes-base.set","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.googleGemini","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.googleSheets","@blotato/n8n-nodes-blotato.blotato","@blotato/n8n-nodes-blotato.blotato","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
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name: Score LinkedIn leads against your ICP with Google Sheets, SourceGeek and Gemini
author_name: Niels Berkhout
author_username: sourcegeek-niels
categories: []
created_at: 2026-01-27T09:14:45.758Z
updated_at: 2026-01-27T09:14:45.758Z
url: https://n8n.io/workflows/13026
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:22
description:
  How it works
  This template is using a LinkedIn User Profile in combination with your detailed Ideal Customer Profile (ICP) to create a score, including reasoning and outreach messages.

  It is manually triggered and uses a Google Sheet as an entry point. Inside there are rows with only LinkedIn profile urls in it.

  Then the SourceGeek Node is being triggered and the complete profile info is retrieved. 

  That info is being sent to an AI Agent where a long description of the Ideal Customer Profile is written down. 

  The AI Agent will process all that data and will return with three values

  ICP rating (between 0 - 100)
  ICP reasoning. Where does the score come from
  A 1st, 2nd and 3rd outreach message which you can use later on

  After that the original Google Sheet row will be updated with the data created by the AI Agent

  How to use
  Populate a Google Sheet with LinkedIn Profile URLs which potentially can be your customers
  Let the SourceGeek fetch all their data from LinkedIn and enrich it with soft skills and much more
  Describe in detail your ICP and let the AI Agent determine the score of the profile
  Update the initial Google Sheet with the ICP Score and the reasoning how this score came to be

  Requirements
  A Google Sheet with LinkedIn profile urls
  The verified SourceGeek node

nodes_used:
  ["n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-sourcegeek.sourcegeek","n8n-nodes-base.splitInBatches","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Sales","Marketing","Data Processing"],"complexity":"medium","use_cases":["score leads","match against ICP","generate outreach"],"estimated_setup_minutes":15,"required_services":["Google Sheets","SourceGeek","Google Gemini"],"key_features":["lead scoring","ICP matching","AI reasoning","outreach message generation"],"target_audience":["sales teams"," marketers"]}


name: Create long Audiobooks 🔊📚 with custom voices using Qwen3-TTS Voice Design
author_name: Davide Boizza
author_username: n3witalia
categories: []
created_at: 2026-01-27T10:50:45.472Z
updated_at: 2026-01-27T10:50:45.472Z
url: https://n8n.io/workflows/13030
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  This workflow automates the creation of audiobooks from structured text data using AI-powered text-to-speech and audio processing services.

  Click here to listen the result of my example.

  Key Advantages

  1. ✅ Fully Automated Audiobook Production

  The entire pipeline—from text retrieval to final audio upload—is automated. This removes manual steps, reduces human error, and enables repeatable audiobook generation at scale.

  2. ✅ Advanced Voice Customization

  By using voice design prompts (voice description + style instruction), the workflow produces highly expressive and context-aware narration, ideal for audiobooks, storytelling, and branded audio content.

  3. ✅ Scalable and API-Safe Architecture

  The batch processing and looping logic respects external API limits. This makes the workflow robust even for large audiobooks with dozens or hundreds of segments.

  4. ✅ Centralized Content Management

  Google Sheets acts as a lightweight CMS:

  Easy to edit scripts and voice parameters
  Clear tracking of processed items
  Temporary URLs and merge flags ensure full visibility into the workflow state

  5. ✅ Asynchronous and Fault-Tolerant

  The use of wait nodes and status checks allows the workflow to handle long-running audio operations without blocking or failing prematurely.

  6. ✅ Seamless Cloud Storage Integration

  Final audiobooks are automatically stored in Google Drive, making them immediately accessible for distribution, review, or further processing.

  7. ✅ Modular and Extensible Design

  Each step (TTS generation, batching, merging, storage) is modular. This makes it easy to:

  Swap TTS providers
  Change storage destinations
  Add post-processing steps (e.g. metadata, chapter markers)

  How it Works

  This workflow automates the creation of audiobooks using AI-generated voice synthesis with custom voice design. The process begins by retrieving script data from a Google Sheets document containing text, speaker information, voice descriptions, and style instructions. 

  The workflow then processes each row in batches, sending the text to the Qwen3-TTS model on Replicate with specified voice parameters to generate individual audio segments. 

  Each generated audio URL is stored back in the spreadsheet. 

  Concurrently, once multiple audio segments are ready, they are merged into a single audio file using an external FFmpeg API service. 

  The system polls for merge completion, retrieves the final merged audio file, and uploads it to Google Drive as a complete audiobook with a timestamped filename.

  Set up Steps

  Data Source Configuration: Set up the Google Sheets node to connect to your spreadsheet containing the audiobook script with required columns: Text, Speaker, Voice Description, Style Instruction, Temp URL, and To Merge

  API Credentials Setup:
     Configure Replicate API credentials for Qwen3-TTS voice synthesis
     Set up Fal.run API credentials for FFmpeg audio merging operations
     Configure Google Drive OAuth2 credentials for uploading the final audiobook

  Voice Design Parameters: Ensure your spreadsheet contains appropriate voice descriptions and style instructions compatible with the Qwen3-TTS model's requirements

  Destination Settings: Verify the Google Drive folder ID in the upload node points to your desired storage location for the final audiobook

  Execution: Trigger the workflow manually to begin processing your script rows and generating the complete audiobook with custom voice design

  👉 Subscribe to my new YouTube channel. Here I’ll share videos and Shorts with practical tutorials and FREE templates for n8n.

  Need help customizing?  
  Contact me for consulting and support or add me on Linkedin.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.splitInBatches","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
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name: Send application follow-up reminders from Airtable via email and SMS
author_name: Jasurbek
author_username: jasurbeknematov
categories: []
created_at: 2026-01-28T08:44:52.241Z
updated_at: 2026-01-28T08:44:52.241Z
url: https://n8n.io/workflows/13058
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:22
description:
  How it works

  This workflow runs on a daily schedule and automatically sends follow-up reminders to candidates who have received an application link but have not yet applied. It checks Airtable for eligible records, calculates how much time has passed since outreach was sent, and decides whether to send a first reminder, second reminder, or no message.

  All decision logic is handled in a single Code node, which outputs a simple routing value. This makes the workflow easy to understand and prevents fragile conditional logic.

  Each reminder is sent only once. After a reminder is sent, the workflow updates Airtable with a corresponding “sent” flag so the same reminder cannot be sent again on future runs.

  Setup steps

  Connect your Airtable account and select the table containing candidate records.

  Ensure Airtable includes a timestamp field indicating when outreach was sent.

  Ensure checkbox fields exist for each reminder (for example, “Reminder 1 Sent” and “Reminder 2 Sent”).

  Connect your email provider (Brevo) and SMS provider.

  Set the Cron node to run once per day at your preferred time.

  Initial setup typically takes 10–15 minutes.

  When to use this template

  You want automated follow-ups without manual chasing

  You need to avoid sending duplicate reminders

  You want Airtable to remain the source of truth

nodes_used:
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metadata_json:
  {"categories":["Recruitment","Automation","Communication"],"complexity":"medium","use_cases":["send recruitment reminders","track candidate outreach","automate follow-ups"],"estimated_setup_minutes":15,"required_services":["Airtable","SendinBlue","Schedule"],"key_features":["scheduled execution","custom routing logic","conditional messaging"],"target_audience":["recruiters","hr professionals","hr assistants"]}


name: Extract insights from LinkedIn with Apify, Pinecone Assistant, and GPT-4.1
author_name: Pinecone
author_username: pinecone
categories: []
created_at: 2026-01-28T13:18:26.564Z
updated_at: 2026-01-28T13:18:26.564Z
url: https://n8n.io/workflows/13064
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:22
description:
  Try it out



  This n8n workflow template lets you extract insights from comments on your LinkedIn posts using Pinecone Assistant, Apify, and OpenAI. It scrapes LinkedIn comments using Apify and then retrieves relevant context from this data using Pinecone Assistant and generates insights with OpenAI, all without the need to train your own LLM.

  What is Pinecone Assistant?

  Pinecone Assistant allows you to build production-grade chat and agent-based applications quickly. It abstracts the complexities of implementing retrieval-augmented (RAG) systems by managing the chunking, embedding, storage, query planning, vector search, model orchestration, reranking for you.

  Prerequisites

  A Pinecone account
  An Open AI account and API key
  An Apify account and API token

  Setup

  Create a Pinecone Assistant in the Pinecone Console here 
  	Name your Assistant n8n-assistant
  	No need to configure a Chat model or Assistant instructions
  Use the Connect to Pinecone button to authenticate to Pinecone or if you self-host n8n, create a Pinecone credential and add your Pinecone API key directly
  Setup the Open AI and Apify credentials in n8n
  In the Set LinkedIn url node, enter your LinkedIn profile url, for a personal or company profile
  Select your Assistant Name in each of the Pinecone Assistant nodes, if it's not already
  Schedule or manually execute Step 1 and 2 to extract the LinkedIn comment data and upload to Pinecone Assistant
  Once the data is uploaded, ask a question in the chat: Summarize the comments related to [SOME TOPIC YOU TALK ABOUT] and categorize into positive, neutral, and negative.

  Ideas for customizing this workflow

  Connect to other social platforms to extract insights from Instagram, X/Twitter, etc. in addition to LinkedIn

  Need help?

  You can find help by asking in the Pinecone Discord community or filing an issue on this repo.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","@apify/n8n-nodes-apify.apify","n8n-nodes-base.convertToFile","n8n-nodes-base.filter","n8n-nodes-base.set","@pinecone-database/n8n-nodes-pinecone-assistant.pineconeAssistant","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@apify/n8n-nodes-apify.apify","n8n-nodes-base.stickyNote","n8n-nodes-base.set","@pinecone-database/n8n-nodes-pinecone-assistant.pineconeAssistantTool"]

workflow_json_compressed:
  [encoded data, 5032 characters]

metadata_json:
  {"categories":["Social Media","Communication","Data Processing"],"complexity":"medium","use_cases":["extract LinkedIn post insights","analyze social media comments","generate content summaries","retrieve context from stored data"],"estimated_setup_minutes":5,"required_services":["LinkedIn","Apify","Pinecone Assistant","OpenAI"],"key_features":["Scrapes social media comments","Uses vector retrieval for context","Generates insights with LLM","No custom model training required"],"target_audience":["social media managers","content strategists","marketing analysts"]}


name: Send personalized job application emails with Telegram, OpenAI, and Gmail
author_name: Joe V
author_username: joevenner
categories: []
created_at: 2026-01-28T22:24:07.080Z
updated_at: 2026-01-28T22:24:07.080Z
url: https://n8n.io/workflows/13077
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:22
description:
  🔧 Setup Guide - Hiring Bot Workflow

  📋 Prerequisites

  Before importing this workflow, make sure you have:

  ✅ n8n Instance (cloud or self-hosted)
  ✅ Telegram Bot Token (from @BotFather)
  ✅ OpenAI API Key (with GPT-4 Vision access)
  ✅ Gmail Account (with OAuth setup)
  ✅ Google Drive (to store your resume)
  ✅ Redis Instance (free tier available at Redis Cloud)

  🚀 Step-by-Step Setup

  1️⃣ Upload Your Resume to OpenAI

  First, you need to upload your resume to OpenAI's Files API:

  Upload your resume to OpenAI
  curl https://api.openai.com/v1/files \
    -H "Authorization: Bearer YOUR_OPENAI_API_KEY" \
    -F purpose="assistants" \
    -F file="@/path/to/your/resume.pdf"

  Important: Save the file_id from the response (looks like file-xxxxxxxxxxxxx)

  Alternative: Use OpenAI Playground or Python:
  from openai import OpenAI
  client = OpenAI(api_key="YOUR_API_KEY")

  with open("resume.pdf", "rb") as file:
      response = client.files.create(file=file, purpose="assistants")
      print(f"File ID: {response.id}")

  2️⃣ Upload Your Resume to Google Drive

  Go to Google Drive
  Upload your resume PDF
  Right-click → "Get link" → Copy the file ID from URL
     URL format: https://drive.google.com/file/d/FILE_ID_HERE/view
     Example ID: 1h79U8IFtI2dp_OBtnyhdGaarWpKb9qq9

  3️⃣ Create a Telegram Bot

  Open Telegram and message @BotFather
  Send /newbot
  Choose a name and username
  Save the Bot Token (looks like 123456789:ABCdefGHIjklMNOpqrsTUVwxyz)
  (Optional) Set bot commands:
        /start - Start the bot
     /help - Get help
  4️⃣ Set Up Redis

  Option A: Redis Cloud (Recommended - Free)
  Go to Redis Cloud
  Create a free account
  Create a database
  Note: Host, Port, Password

  Option B: Local Redis
  Docker
  docker run -d -p 6379:6379 redis:latest

  Or via package manager
  sudo apt-get install redis-server

  5️⃣ Import the Workflow to n8n

  Open n8n
  Click "+" → "Import from File"
  Select Hiring_Bot_Anonymized.json
  Workflow will import with placeholder values

  6️⃣ Configure Credentials

  A. Telegram Bot Credentials
  In n8n, go to Credentials → Create New
  Select "Telegram API"
  Enter your Bot Token from Step 3
  Test & Save

  B. OpenAI API Credentials
  Go to Credentials → Create New
  Select "OpenAI API"
  Enter your OpenAI API Key
  Test & Save

  C. Redis Credentials
  Go to Credentials → Create New
  Select "Redis"
  Enter:
     Host: Your Redis host
     Port: 6379 (default)
     Password: Your Redis password
  Test & Save

  D. Gmail Credentials
  Go to Credentials → Create New
  Select "Gmail OAuth2 API"
  Follow OAuth setup flow
  Authorize n8n to access Gmail
  Test & Save

  E. Google Drive Credentials
  Go to Credentials → Create New
  Select "Google Drive OAuth2 API"
  Follow OAuth setup flow
  Authorize n8n to access Drive
  Test & Save

  7️⃣ Update Node Values

  A. Update OpenAI File ID in "PayloadForReply" Node

  Double-click the "PayloadForReply" node
  Find this line in the code:
        const resumeFileId = "YOUR_OPENAI_FILE_ID_HERE";
     Replace with your actual OpenAI file ID from Step 1:
        const resumeFileId = "file-xxxxxxxxxxxxx";
     Save the node

  B. Update Google Drive File ID (Both "Download Resume" Nodes)

  There are TWO nodes that need updating:

  Node 1: "Download Resume"
  Double-click the node
  In the "File ID" field, click "Expression"
  Replace YOUR_GOOGLE_DRIVE_FILE_ID with your actual ID
  Update "Cached Result Name" to your resume filename
  Save

  Node 2: "Download Resume1" (same process)
  Double-click the node
  Update File ID
  Update filename
  Save

  8️⃣ Assign Credentials to Nodes

  After importing, you need to assign your credentials to each node:

  Nodes that need credentials:

  | Node Name | Credential Type |
  |-----------|----------------|
  | Telegram Trigger | Telegram API |
  | Generating Reply | OpenAI API |
  | Store AI Reply | Redis |
  | GetValues | Redis |
  | Download Resume | Google Drive OAuth2 |
  | Download Resume1 | Google Drive OAuth2 |
  | Schedule Email | Gmail OAuth2 |
  | SendConfirmation | Telegram API |
  | Send a message | Telegram API |
  | Edit a text message | Telegram API |
  | Send a text message | Telegram API |
  | Send a chat action | Telegram API |

  How to assign:
  Click on each node
  In the "Credentials" section, select your saved credential
  Save the node

  🧪 Testing the Workflow

  1️⃣ Activate the Workflow
  Click the "Active" toggle in the top-right
  Workflow should now be listening for Telegram messages

  2️⃣ Test with a Job Post
  Find a job post online (LinkedIn, Indeed, etc.)
  Take a screenshot
  Send it to your Telegram bot
  Bot should respond with:
     "Analyzing job post..." (typing indicator)
     Full email draft with confirmation button

  3️⃣ Test Email Sending
  Click "Send The Email" button
  Check Gmail to verify email was sent
  Check if resume was attached

  🐛 Troubleshooting

  Issue: "No binary image found"
  Solution:** Make sure you're sending an image file, not a document

  Issue: "Invalid resume file_id"
  Solution:** 
    Check OpenAI file_id format (starts with file-)
    Verify file was uploaded successfully
    Make sure you updated the code in PayloadForReply node

  Issue: "Failed to parse model JSON"
  Solution:** 
    Check OpenAI API quota/limits
    Verify model name is correct (gpt-5.2)
    Check if image is readable

  Issue: Gmail not sending
  Solution:**
    Re-authenticate Gmail OAuth
    Check Gmail permissions
    Verify "attachments" field is set to "Resume"

  Issue: Redis connection failed
  Solution:**
    Test Redis connection in credentials
    Check firewall rules
    Verify host/port/password

  Issue: Telegram webhook not working
  Solution:**
    Deactivate and reactivate workflow
    Check Telegram bot token is valid
    Make sure bot is not blocked

  🔐 Security Best Practices

  Never share your credentials - Keep API keys private
  Use environment variables in n8n for sensitive data
  Set up Redis password - Don't use default settings
  Limit OAuth scopes - Only grant necessary permissions
  Rotate API keys regularly
  Monitor usage - Check for unexpected API calls

  🎨 Customization Ideas

  Change AI Model
  In the PayloadForReply node, update:
  const MODEL = "gpt-5.2"; // Change to gpt-4, claude-3-opus, etc.

  Adjust Email Length
  Modify the system prompt:
  // From:
  Email body: ~120–180 words unless INSIGHTS specify otherwise.

  // To:
  Email body: ~100–150 words for concise applications.

  Add More Languages
  Update language detection logic in the system prompt to support more languages.

  Custom Job Filtering
  Edit the system prompt to target specific roles:
  // From:
  Only pick ONE job offer to process — the one most clearly related to Data roles

  // To:
  Only pick ONE job offer to process — the one most clearly related to [YOUR FIELD]

  Add Follow-up Reminders
  Add a "Wait" node after email sends to schedule a reminder after 7 days.

  📊 Workflow Structure

  Telegram Input
      ↓
  Switch (Route by type)
      ↓
  ├─ New Job Post
  │   ↓
  │   Send Chat Action (typing...)
  │   ↓
  │   PayloadForReply (Build AI request)
  │   ↓
  │   Generating Reply (Call OpenAI)
  │   ↓
  │   FormatAiReply (Parse JSON)
  │   ↓
  │   Store AI Reply (Redis cache)
  │   ↓
  │   SendConfirmation (Show preview)
  │
  └─ Callback (User clicked "Send")
      ↓
      GetValues (Fetch from Redis)
      ↓
      Format Response
      ↓
      Download Resume (from Drive)
      ↓
      ├─ Path A: Immediate Send
      │   ↓
      │   Send Confirmation Message
      │   ↓
      │   Edit Message (update status)
      │
      └─ Path B: Scheduled Send
          ↓
          Wait (10 seconds)
          ↓
          Download Resume Again
          ↓
          Schedule Email (Gmail)
          ↓
          Send Success Message

  💡 Tips for Best Results

  High-Quality Resume: Upload a well-formatted PDF resume
  Clear Screenshots: Take clear, readable job post screenshots
  Use Captions: Add instructions via Telegram captions
     Example: "make it more casual"
     Example: "send to recruiter@company.com"
  Review Before Sending: Always read the draft before clicking send
  Update Resume Regularly: Keep your Google Drive resume current
  Test First: Try with a few test jobs before mass applying

  🆘 Need Help?

  📚 n8n Documentation
  💬 n8n Community Forum
  📺 n8n YouTube Channel
  🤖 OpenAI Documentation
  📱 Telegram Bot API Docs

  📝 Checklist

  Use this checklist to verify your setup:

  [ ] OpenAI resume file uploaded (got file_id)
  [ ] Google Drive resume uploaded (got file ID)
  [ ] Telegram bot created (got bot token)
  [ ] Redis instance created (got credentials)
  [ ] All n8n credentials created and tested
  [ ] PayloadForReply node updated with OpenAI file_id
  [ ] Both Download Resume nodes updated with Drive file_id
  [ ] All nodes have credentials assigned
  [ ] Workflow activated
  [ ] Test message sent successfully
  [ ] Test email received successfully

  🎉 You're all set! Start applying to jobs in 10 seconds!

  Made with ❤️ and n8n

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metadata_json:
  {"categories":["AI/ML","Communication","Job Hunting"],"complexity":"medium","use_cases":["Applying for jobs","Personalizing cover letters","Storing resumes in cloud storage","Sending automated Telegram messages","Automating job applications"],"estimated_setup_minutes":15,"required_services":["Telegram Bot API","OpenAI API","Gmail API","Google Drive API","Redis API"],"key_features":["Multi-service integration","Resume analysis with AI","Automated email communication","Document storage","Personalized messaging"],"target_audience":["recruiters","job seekers","automation developers"]}


name: Build a Facebook Messenger customer service AI chatbot with Google Gemini
author_name: Nguyễn Thiệu Toàn (Jay Nguyen)
author_username: nguyenthieutoan
categories: []
created_at: 2026-01-28T22:46:49.541Z
updated_at: 2026-01-28T22:46:49.541Z
url: https://n8n.io/workflows/13080
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  🤖 Build a customer service AI chatbot for Facebook Messenger with Google Gemini

  📌 Overview
  A streamlined Facebook Messenger chatbot powered by AI with conversation memory.  
  This is a simplified version designed for quick deployment, learning, and testing — not suitable for production environments.

  Base workflows:
  Smart message batching AI-powered Facebook Messenger chatbot use Data Table  
  Smart human takeover & auto pause AI-powered Facebook Messenger chatbot  

  🎯 What This Workflow Does

  ✅ Core Features:
  Receives messages from Facebook Messenger via webhook  
  Processes user messages with Google Gemini AI  
  Maintains conversation context using Simple Memory node  
  Automatically responds with AI-generated replies  
  Handles webhook verification for Facebook setup  
  Send image or video to customer through Facebook Messenger

  🔹 Simplified Approach:
  Memory**: Simple Memory node (10-message window)  
  Format**: Cleans text, strips markdown, truncates &gt;1900 chars  
  Response**: Single message delivery  

  ⚠️ Limitations & Trade-offs:
  No Smart Batching → fragmented user messages cause spam-like replies  
  No Human Takeover Detection → bot continues even when admin joins  
  Basic Memory Management → no persistence, not reliable in production  
  Basic Text Formatting → strips markdown, truncates brutally, no smart splitting  

  🚀 When to Upgrade
  Upgrade to full workflows when you need:  
  Production deployment with reliability & persistence  
  Analytics & tracking (query history, reports)  
  Professional formatting (bold, italic, lists, code blocks)  
  Handling long messages (&gt;2000 chars)  
  Smart batching for fragmented inputs  
  Human handoff detection  
  Full conversation persistence  

  Key upgrades available:
  Smart message batching workflow  
  Smart human takeover workflow  

  ⚙️ Setup Requirements

  Facebook Setup
  Create Facebook App at developers.facebook.com  
  Add Messenger product  
  Configure webhook:  
     URL: https://your-domain.com/webhook/your-path  
     Verify token: secure string  
     Subscribe to: messages, messaging_postbacks  
  Generate Page Access Token  
  Copy token to "Set Context" node  

  n8n Setup
  Import workflow  
  Edit "Set Context" node → update page_access_token  
  Configure "Gemini Flash" node credentials  
  Deploy workflow (must be publicly accessible)  

  🔄 How It Works
  User Message → Facebook Webhook → Validation
      ↓
  Set Context (extract user_id, message, token)
      ↓
  Mark Seen → Show Typing
      ↓
  AI Agent (Gemini + 10-message memory)
      ↓
  Format Output (remove markdown, truncate)
      ↓
  Send Response via Facebook API

  🏗️ Architecture Overview

  Section 1: Webhook & Initial Processing
  Facebook Webhook: handles GET (verification) & POST (messages)  
  Confirm Webhook: returns challenge / acknowledges receipt  
  Filters text messages only  
  Blocks echo messages from bot itself  

  Section 2: AI Processing with Memory
  Set Context: extracts user_id, message, token  
  Seen & Typing: user feedback  
  Conversation Memory: 10-message window, per-user isolation  
  Process Merged Message: AI Agent with Jenix persona  
  Gemini Flash: Google’s AI model for response generation  

  Section 3: Format & Delivery
  Cuts replies &gt;2000 chars, strips markdown  
  Sends text via Facebook Graph API  

  🎨 Customisation Guide
  Bot Personality**: edit system prompt in "Process Merged Message" node  
  Memory**: adjust contextWindowLength (default 10), change sessionKey if needed  
  AI Model**: replace Gemini Flash with OpenAI, Anthropic Claude, or other LLMs  

  📌 Important Notes
  ⚠️ Production Warning: testing only, memory lost on n8n restart in queue mode  
  📊 No Analytics: no history storage, no reporting  
  🔧 Format Limitations: responses ≤1800 chars, markdown stripped, no complex formatting  

  🛠️ Troubleshooting
  Bot not responding** → check token, webhook accessibility, event subscriptions  
  Memory not working** → verify session key, ensure not in queue mode, restart workflow  
  Messages truncated** → adjust system prompt for conciseness, reduce response length  

  📜 License & Credits
  Created by: Nguyễn Thiệu Toàn (Jay Nguyen)  
  Email: me@nguyenthieutoan.com
  Website: nguyenthieutoan.com  
  n8n Creator: n8n.io/creators/nguyenthieutoan  
  Company: GenStaff  

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name: Create and publish AI videos with Sora 2 Cameos, Gemini, and Blotato
author_name: giangxai
author_username: giangxai
categories: []
created_at: 2026-01-29T03:22:56.241Z
updated_at: 2026-01-29T03:22:56.241Z
url: https://n8n.io/workflows/13085
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  Overview

  This workflow automatically creates short-form AI videos using Sora 2 Cameos, powered by n8n and AI agents.

  It connects viral content collection, AI script and prompt generation, video rendering, video merging, and multi-platform publishing into a single fully automated system. Once configured, the workflow runs end to end without manual editing or intervention.

  The workflow is designed for creators, marketers, and affiliate builders who want to scale faceless or avatar-style AI videos consistently using viral ideas and automated publishing.

  What can this workflow do?

  Automatically collect viral content ideas from external sources  
  Analyze viral ideas and generate structured Sora 2–ready prompts  
  Create AI videos using pre-selected Sora 2 Cameos characters  
  Merge multiple AI video clips into a single final video  
  Publish videos automatically to TikTok, Facebook, and Instagram  
  Track publishing status, success, and errors in Google Sheets  

  This workflow reduces manual video production work while keeping the process structured, scalable, and repeatable.

  How it works

  The workflow starts by automatically collecting viral content ideas on a schedule and storing them in Google Sheets as a content backlog.

  Before prompt generation, a Cameos character is selected and configured manually on Sora2.com. This selected avatar is used consistently across all generated videos.

  Each viral idea is then analyzed to extract hooks, themes, and video direction. An AI Agent generates structured scripts and Sora 2–ready prompts based on both the viral content and the selected Cameos character.

  These prompts are sent to the Sora 2 Cameos video generation API to render short video clips. The workflow monitors rendering status and retries if needed.

  Once all clips are ready, they are automatically merged into a single final video. The finished video is published to social platforms such as TikTok, Facebook, and Instagram. Publishing results and errors are logged back to Google Sheets for monitoring and optimization.

  Setup steps

  Connect an AI model (Gemini or compatible LLM) for script and prompt generation  
  Select and configure a Cameos character on Sora2.com  
  Add Sora 2 Cameos API credentials for AI video generation  
  Configure the video merge step to combine multiple clips into one final video  
  Connect social publishing APIs (TikTok, Facebook, Instagram)  
  Connect Google Sheets for content intake and status tracking  

  Once configured, the workflow runs automatically on a schedule without manual input.

  Documentation

  For a full walkthrough, optimization tips, and scaling strategies, watch the detailed tutorial on YouTube.

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metadata_json:
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name: Create hours-long wave music videos with Suno, ffmpeg-api and YouTube
author_name: giangxai
author_username: giangxai
categories: []
created_at: 2026-01-29T06:17:30.046Z
updated_at: 2026-01-29T06:17:30.046Z
url: https://n8n.io/workflows/13088
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  Overview

  This workflow automatically creates hours-long wave music videos by combining AI-generated music from Suno with a background video, fully automated using n8n and ffmpeg-api.

  It connects music prompt generation, AI song creation, audio aggregation, video merging, and YouTube publishing into a single end-to-end automation. Once configured, the workflow runs continuously with no manual editing required.

  This workflow is built for creators producing lo-fi, wave, ambient, or long-play music content who want a reliable and scalable way to generate long-form videos automatically.

  What can this workflow do?

  Collect music themes, background video URLs, and track counts via an input form  
  Generate multiple AI music tracks using Suno  
  Automatically check rendering status and retrieve completed songs  
  Concatenate multiple tracks into a single long-form audio file  
  Merge the final audio with a background video using ffmpeg-api  
  Upload the completed video to YouTube automatically  
  Generate SEO-optimized titles and descriptions using an AI model  

  This workflow reduces manual work while keeping the entire music video production process structured and repeatable.

  How it works

  You start by submitting a music theme, a background video URL, and the number of music tracks through an n8n form. The workflow initializes a working directory using ffmpeg-api to manage all audio and video assets.

  An AI agent converts the music theme into structured Suno prompts. Suno then generates multiple music tracks, and the workflow continuously checks their rendering status until all songs are ready.

  Once completed, the songs are downloaded, uploaded to ffmpeg-api storage, and concatenated into a single long-form audio track. This audio is merged with the background video to create the final hours-long wave music video.

  Finally, the completed video is uploaded to YouTube. An AI model generates SEO-friendly metadata, and the video is published automatically without manual intervention.

  Setup steps

  Connect an AI model (Gemini) for music prompt generation and YouTube metadata creation  
  Configure Suno API access for AI music generation  
  Set up ffmpeg-api for directory creation, file uploads, audio concatenation, and video merging  
  Connect your YouTube account for automated uploads  
  Review and customize the input form fields if needed  

  After setup, the workflow runs end to end automatically.

  Documentation

  For a full walkthrough and advanced customization ideas, watch the detailed tutorial on YouTube.

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name: Generate AI short-form health videos with Gemini, Veo 3 and Google Sheets
author_name: giangxai
author_username: giangxai
categories: []
created_at: 2026-01-29T06:56:47.268Z
updated_at: 2026-01-29T06:56:47.268Z
url: https://n8n.io/workflows/13089
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  Overview

  Automatically generate viral short-form health videos using AI and publish them to social platforms with n8n and Veo 3.  
  This workflow collects viral ideas, analyzes engagement patterns, generates AI video scripts, renders videos with Veo 3, and handles publishing and tracking fully automated, with no manual editing.

  Who is this for?

  This template is ideal for:

  Content creators building faceless health channels (Shorts, Reels, TikTok)
  Affiliate marketers promoting health products with video content
  AI marketers running high-volume short-form content funnels
  Automation builders combining LLMs, video AI, and n8n
  Teams that want a scalable, repeatable system for viral AI video production

  If you want to create health niche videos at scale without manually scripting, rendering, and uploading each video, this workflow is for you.

  What problem is this workflow solving?

  Creating viral short-form health videos usually involves many manual steps and disconnected tools, such as:

  Manually collecting and validating viral content ideas
  Writing hooks and scripts for each video
  Switching between AI tools for analysis and video generation
  Waiting for videos to render and checking status manually
  Uploading videos and tracking what has been published

  This workflow connects all these steps into a single automated pipeline and removes repetitive manual work.

  What this workflow does

  This automated AI health video workflow:

  Runs on a defined schedule
  Collects viral health content ideas from external sources
  Normalizes and stores ideas in Google Sheets
  Loads pending viral ideas for processing
  Analyzes each idea and generates AI-optimized video scripts
  Creates AI videos automatically using the Veo 3 API
  Waits for video rendering and checks completion status
  Retrieves the final rendered videos
  Optionally aggregates or merges video assets
  Publishes videos to social platforms
  Updates Google Sheets with processing and publishing results

  The entire process runs end-to-end with minimal human intervention.

  Setup

  1. Prepare Google Sheets

  Create a Google Sheet to manage your content pipeline with columns such as:

  idea / topic – Viral idea or source content
  analysis – AI analysis or hook summary
  script – Generated video script
  status – pending / processing / completed / failed
  video_url – Final rendered video link
  publish_result – Publishing status or notes

  Only rows marked as pending will be processed by the workflow.

  2. Connect Google Sheets

  Authenticate your Google Sheets account in n8n
  Select the spreadsheet in the load and update nodes
  Ensure the workflow can write status updates back to the same sheet

  3. Configure AI & Veo 3

  Add credentials for your AI model (e.g. Gemini or similar)
  Configure prompt logic for health niche content
  Add your Veo 3 API credentials
  Test video creation with a small number of ideas before scaling

  4. Configure Publishing & Schedule

  Set up publishing credentials for your target social platforms
  Open the Schedule triggers and define how often the workflow runs
  The schedule controls how frequently new AI health videos are created and published

  How to customize this workflow to your needs

  You can adapt this workflow without changing the core structure:

  Replace viral idea sources with your own research or internal data
  Adjust AI prompts for different health sub-niches
  Add manual approval steps before video creation
  Disable publishing and use the workflow only for video generation
  Add retry logic for failed renders or API errors
  Extend the workflow with analytics or performance tracking

  Best practices

  Start with a small batch of test ideas
  Keep status values consistent in Google Sheets
  Focus on strong hooks for health-related content
  Monitor rendering and publishing nodes during early runs
  Adjust schedule frequency based on API limits

  Documentation

  For a full walkthrough and advanced customization ideas, see the Video Guide.

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name: Create TikTok videos with GPT-4o, Digital Twins, Veo 3 and Telegram
author_name: Vedad Sose
author_username: vedad27
categories: []
created_at: 2026-01-29T14:54:29.586Z
updated_at: 2026-01-29T14:54:29.586Z
url: https://n8n.io/workflows/13097
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Create TikTok videos grounded in real human insight. One agent researches viral trends, gathers authentic audience feedback on your product to inform script creation, tests script variations with target audiences to identify the most resonant script option, generates the video, and sends it back to you on Telegram.

  Description

  Most AI video tools generate content based on assumptions and AI guesswork. That's why content often looks and feels the same. This workflow grounds every creative decision in an authentic human perspective.

  The process:
  Research trends — Apify scrapes what's actually viral on TikTok
  Understand your audience — Digital Twins provide real feedback on your product/concept to inform creative direction
  Generate informed scripts — The agent writes variations based on actual human insights, not AI assumptions
  Test for resonance — Digital Twins evaluate which script will genuinely connect with your target audience
  Produce the winner — Veo 3 generates video from the most resonant script

  By anchoring both the script development and selection in real human perspectives, you can create TikTok videos that actually resonate with your target audience.

  Triggers

  Telegram message** — send your product/concept to your bot to start the workflow

  Nodes Used

  Set** (Workflow Configuration) — target audience demographics
  Telegram Trigger** — starts the workflow with product/concept input
  AI Agent** — orchestrates the entire research → insight → creation → resonance testing flow
  OpenAI Chat Model** (GPT-4o) — powers the agent
  MCP Client Tool** (Apify) — scrapes trending TikTok content
  MCP Client Tool** (OriginalVoices) — queries Digital Twins for:
    Initial product/concept feedback to inform scripts
    Resonance testing to select the most compelling script version
  Code** (Parse JSON) — extracts structured output from the agent
  HTTP Request** (Veo 3) — generates 9:16 video via fal.ai
  Wait** — pauses for video generation
  HTTP Request** (Poll) — checks video status
  Telegram** — sends the finished video URL back to you

  Required Credentials

  Telegram Bot — create via @BotFather
  OpenAI API — for GPT-4o
  Apify API — for TikTok trend scraping (apify.com)
  OriginalVoices API — for real-time audience insights and feedback (originalvoices.ai)
  FAL.ai API — for Veo 3 video generation (fal.ai)

  Configuration

  Import workflow.json into n8n
  Edit the Workflow Configuration node:
     productName — your product/brand name
     productDescription — what your product does
     targetAudience — e.g., "US women, 25-40, interested in wellness and productivity" (defines which Digital Twins provide insights and resonance feedback)
     tone — e.g., "casual, energetic, Gen-Z friendly"
  Connect Telegram Bot credentials on both Telegram nodes
  Connect OpenAI API credentials on the Chat Model node
  Connect Header Auth on Apify MCP node:
     Header: Authorization, Value: Bearer YOUR_APIFY_TOKEN
  Connect Header Auth on OriginalVoices node:
     Header: X-Api-Key, Value: YOUR_API_KEY
  Connect Header Auth on Veo 3 and Poll Video Status nodes:
     Header: Authorization, Value: Key YOUR_FAL_API_KEY
  Activate the workflow

  Usage

  Send a message to your Telegram bot describing your product/concept (e.g., "meditation app that uses AI-generated soundscapes")
  The agent:
     Researches current TikTok trends
     Gathers authentic audience feedback on your concept from Digital Twins
     Writes script variations informed by real human perspectives
     Tests all scripts with Digital Twins of target audience to identify which one resonates most
  The most resonant script is sent to Veo 3 for video generation
  You receive the video URL, audience-informed caption, and hashtags back on Telegram

  Why this matters: Every creative decision — from initial direction to final script selection — is grounded in how real humans in your target demographic actually think, feel, and respond. Not AI assumptions or guesswork. Real human intelligence that ensures your content actually resonates.

  Customize:
  Audience targeting** — refine the targetAudience parameter to query specific Digital Twin demographics
  Trend niche** — modify the agent prompt to focus on specific hashtags or content types
  Script count** — adjust the prompt to generate more or fewer variations for testing
  Video style** — update the Veo 3 prompt for different aesthetics (cinematic, UGC, etc.)
  Resonance criteria** — specify what makes a script "compelling" for your use case

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name: Track job applications and prep interviews with Notion and GPT-5-mini
author_name: Diego Alejandro Parrás
author_username: diegoalejandroparras
categories: []
created_at: 2026-01-29T18:40:47.280Z
updated_at: 2026-01-29T18:40:47.280Z
url: https://n8n.io/workflows/13104
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  AI job application tracker and interview prep assistant

  Categories: AI, Productivity, Career

  Transform your job search from chaos to clarity. This workflow automatically tracks every application, researches companies, and prepares you for interviews with AI-generated materials — all saved to a visual Notion pipeline.

  Benefits

  Never lose track of applications** — Every job gets logged automatically with status tracking
  Walk into interviews prepared** — AI generates likely questions, talking points, and company insights
  Save 2-3 hours per application** — Research and prep that took hours now happens in seconds
  Automated follow-up reminders** — Get notified when it's time to send that follow-up email

  How It Works

  Submit application via form (paste job URL) or forward your confirmation email
  AI extracts job details — company, role, requirements, salary, location
  Interview prep generates — likely questions, suggested talking points, questions to ask
  Everything saves to Notion — visual pipeline with follow-up dates
  Daily reminders — Slack notification for applications needing follow-up

  Required Setup

  Notion Database Structure

  Create a Notion database with these properties:

  | Property Name | Type | Purpose |
  |---------------|------|---------|
  | Company | Title | Company name |
  | Role | Text | Job title |
  | Status | Select | Applied, Interviewing, Offer, Rejected, Ghosted |
  | Applied Date | Date | When you applied |
  | Salary Range | Text | Compensation info |
  | Job URL | URL | Link to posting |
  | Location | Text | City/Remote |
  | Interview Prep | Text | AI-generated prep materials |
  | Follow Up Date | Date | When to follow up |
  | Requirements | Text | Key job requirements |
  | Notes | Text | Your personal notes |

  Credentials Needed

  OpenAI API** — For job extraction and interview prep generation
  Notion** — Connected to your job tracker database
  Gmail** (optional) — For email forwarding and confirmations
  Slack** (optional) — For follow-up reminders

  Use Cases

  Active job seekers** — Track 20+ applications without spreadsheet chaos
  Career changers** — Get AI help understanding new industry requirements
  Recent graduates** — Build interview confidence with generated prep materials
  Passive searchers** — Keep a running list with minimal effort

  Set Up Steps

  Import the workflow into your n8n instance
  Create Notion database with the structure above (or duplicate template)
  Connect OpenAI credentials — API key with GPT-5 access recommended
  Connect Notion credentials — Select your job tracker database
  Configure Gmail trigger (optional) — Set filter for forwarded job emails
  Set up Slack webhook (optional) — Choose channel for reminders
  Test with a sample job posting — Paste a LinkedIn or company careers page URL

  Customization Tips

  Edit the interview prep prompt to mention your background/experience
  Adjust the follow-up reminder interval (default: 7 days)
  Add additional research sources (LinkedIn, Crunchbase) for richer company data
  Connect to calendar to block interview prep time automatically

  Technical Notes

  Uses Jina AI Reader for web scraping (free tier available)
  GPT-5-mini recommended for cost efficiency
  Notion text fields limited to 2000 characters (full prep saved)
  Daily check runs at 9 AM (configurable)

  Difficulty Level: Intermediate  
  Estimated Setup Time: 30-45 minutes  
  Monthly Operating Cost: ~$2-5 (based on 50 applications/month with GPT-5-mini)

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name: Generate daily AI reels from Google Drive images with GPT‑5.1, Wavespeed and Submagic
author_name: Automate With Marc
author_username: marconi
categories: []
created_at: 2026-01-30T08:26:00.910Z
updated_at: 2026-01-30T08:26:00.910Z
url: https://n8n.io/workflows/13110
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  Image to Video Social Media Reel Generator + Autopost Without AI Slop

  Google Drive → AI Video Generation → Captions → Approval → Instagram & TikTok

  Watch Step-By-Step Video: https://www.youtube.com/watch?v=jPOYxQF25ws

  Turn a folder of images into fully-produced short-form social media reels—automatically.
  This workflow picks a random image, generates a cinematic AI video from it, adds text overlays and captions, waits for your approval, and then posts to Instagram and TikTok.

  What this template does

  On a scheduled basis (default: daily at 9:00 AM), this workflow:
  Selects a random image from a Google Drive folder
  Uploads the image for processing
  Generates a cinematic image-to-video prompt using AI
  Creates an 8-second vertical video using an image-to-video model (via Wavespeed)
  Applies captions and text overlays using Submagic
  Waits for human approval via email
  Automatically posts the approved reel to:
  Instagram
  TikTok
  If the video is not approved, the workflow loops and tries again on the next run.

  Why this workflow is useful
  Converts static images into high-engagement video content
  Removes repetitive manual work in short-form content creation
  Keeps a human-in-the-loop before anything is published

  Perfect for:
  Creators & solopreneurs
  Social media managers
  Small businesses & local brands
  AI-first content pipelines
  High-level flow
  Schedule → Pick Image → Generate Video → Add Captions → Approve → Post

  Node overview
  Schedule Trigger
  Runs the workflow automatically at a fixed time (default: daily at 9 AM).
  Google Drive – Search Files
  Fetches all images from a selected Drive folder.
  Randomizer (Code Node)
  Selects one random image to avoid repetitive posting.
  Upload Media
  Uploads the selected image so it can be used by downstream tools.
  Prompt Generator (AI)
  Generates a high-quality cinematic prompt optimized for image-to-video models
  Wavespeed – Image to Video
  Creates an 8-second, 9:16 video from the image + prompt.
  Wait & Polling (IF Nodes)
  Waits and checks until video generation is completed.
  Submagic – Text Overlay & Captioning
  Adds captions and overlays in a short-form style optimized for social platforms.
  Gmail – Send for Approval
  Sends a preview link and caption to your inbox and waits for approval.
  IF (Approved?)
  Yes: posts the reel automatically
  No: skips posting and retries in the next run
  Blotato – Social Posting
  Publishes the approved reel to:
  Instagram
  TikTok

  Requirements

  Before running this template, you’ll need to configure:
  Google Drive OAuth (image source folder)
  OpenAI API key (prompt generation)
  Wavespeed API key (image-to-video generation)
  Submagic API key (captions & overlays)
  Gmail OAuth (approval workflow)
  Blotato account (Instagram & TikTok posting)
  All credentials must be added manually after importing.

  Setup instructions

  Import the template into your n8n workspace
  Connect your Google Drive account and set your image folder
  Add credentials for:
  OpenAI
  Wavespeed
  Submagic
  Gmail
  Blotato

  Adjust the Schedule Trigger if needed
  Run the workflow once to test the full flow
  Enable the workflow to start daily automated posting

  Customization ideas

  Change video duration, aspect ratio, or style
  Modify the AI prompt to match your brand voice
  Post only after manual approval (already built-in)
  Add a Slack or Telegram approval step
  Duplicate posting logic for YouTube Shorts or Facebook Reels
  Store generated videos in cloud storage or a content database

  Troubleshooting

  No images found: check Drive folder ID and permissions
  Video stuck generating: increase wait time or polling interval
  Approval email not received: verify Gmail OAuth and inbox filters
  Posting fails: confirm Blotato account and platform permissions

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name: Publish SEO blogs to WordPress with GPT-4.1, DALL-E, Gemini, and Google Sheets
author_name: isaWOW
author_username: isawow
categories: []
created_at: 2026-01-30T11:22:52.888Z
updated_at: 2026-01-30T11:22:52.888Z
url: https://n8n.io/workflows/13113
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:22
description:
  Automatically publish blog content to WordPress with AI-generated branded images, internal linking, and client reporting using Google Sheets, OpenAI, and Gemini

  What this workflow does

  This workflow receives written blog content from your content creation automation and handles the complete WordPress publishing process. It adds internal links to your content based on target keywords, generates 3 AI-powered branded images (thumbnail + 2 content images), uploads them to WordPress, inserts them into your article, publishes the complete blog with proper categories, updates tracking sheets, and notifies clients automatically.

  Perfect for agencies managing multiple client blogs who want to eliminate manual publishing tasks while maintaining brand consistency and SEO optimization.

  Key features

  Intelligent internal linking: Automatically analyzes your target keywords and adds up to 3 natural anchor links within the content to improve site SEO and user navigation

  AI image generation: Creates 3 professional branded images using DALL-E based on your blog topic and brand colors - one thumbnail with overlay text and two supporting content images

  Automated WordPress publishing: Publishes blogs with proper categories, sets featured images, and handles all WordPress REST API interactions without manual intervention

  Multi-client management: Processes different projects based on individual client settings including image preferences, brand colors, and reporting requirements

  Tracking and reporting: Updates Google Sheets with live URLs and publish dates, sends Discord notifications to project managers, and triggers client reporting workflows

  How it works

  Receives content from writing automation: Triggered by your blog content creation workflow with title, body content, focus keyword, and client details

  Fetches project configuration: Loads client-specific settings from Google Sheets including website URL, WordPress API credentials, image creation preferences, and brand guidelines

  Adds internal links: Retrieves target keywords and URLs from project sheets, filters valid links, and uses Gemini AI to intelligently insert 3 contextual anchor links

  Generates branded images (if enabled): Uses OpenAI GPT to create detailed image prompts based on blog topic and brand colors, then generates 3 images with DALL-E (thumbnail with text overlay + 2 content images)

  Uploads to WordPress media library: Processes each image through a loop, uploads to WordPress, stores metadata including URLs and alt text

  Inserts images into content: Uses Gemini AI to intelligently place images at strategic positions within the article while preserving existing HTML structure and anchor links

  Publishes to WordPress: Creates the blog post with proper title, content, categories, and sets the thumbnail as featured image via REST API

  Updates tracking sheets: Records the live blog URL and publish date in Google Sheets for project management

  Sends notifications: Triggers Discord alerts for project managers and executes the Reporting Manager workflow for client communication via email, Slack, or WhatsApp

  Setup requirements

  Tools you'll need:
  Active n8n instance (self-hosted or n8n Cloud)
  Google Sheets with OAuth access for project management
  WordPress site with REST API enabled and proper authentication
  OpenAI API key (for DALL-E image generation)
  Google Gemini API key (for content processing)
  Discord bot (optional, for team notifications)
  Blog Content Creation workflow (Part 1 - sold separately or built independently)

  Estimated setup time: 30-40 minutes

  Configuration steps

  Add credentials in n8n:
     Google Sheets OAuth API
     OpenAI API (for DALL-E image generation)
     Google Gemini API (for AI content processing)
     Discord Bot API (for notifications)
     WordPress credentials (API tokens)

  Set up Project Central Sheet:
     Create a master Google Sheet with these columns:
     Client ID
     Website URL
     Blog API (WordPress auth token)
     GMB Name (business name)
     Image Creation (Yes/No)
     Image Instructions (specific image guidelines)
     Color and Font (brand colors in hex format)
     Discord Channel ID
     Project Manager Discord ID
     On Page Sheet (URL to client's tracking sheet)
     Project Information Sheet (URL to internal linking keywords sheet)
     Categories (WordPress category IDs)
     
     Update the sheet URL in the "Fetch Project Configuration" node

  Create client-specific sheets:
     For each client, maintain two sheets:
     
     Sheet 1: TGT Keywords (for internal linking)
     Keywords column: Target keywords to link
     Target Pages column: Full URLs to link to
     
     Sheet 2: Content Requirement & Posting (for tracking)
     row_number: Unique identifier
     Focus Keyword: Target SEO keyword
     Content Topic: Blog title
     Publish URLs: Live blog URL (auto-filled)
     Published Date: Publish date (auto-filled)

  Configure WordPress authentication:
     Enable REST API on your WordPress site
     Generate API authentication tokens
     Update authorization values in these nodes:
       "Upload to WordPress Media"
       "Publish Blog with Featured Image"
       "Set Thumbnail as Featured Image"
       "Publish Blog without Images"

  Connect to Blog Creation workflow:
     Ensure your Blog Content Creation workflow (Part 1) triggers this workflow
     The trigger should pass these workflow inputs:
       Client ID
       Blog S.NO. (row number)
       Blog Title
       Content (HTML formatted)
       OnPage SEO (tracking sheet URL)
       Focus Keyword

  Set up Reporting Manager (optional):
     Create or connect your client reporting workflow
     Update the workflow ID in "Trigger Client Reporting Workflow" node
     This sends automated reports to clients via email, Slack, or WhatsApp

  Test the workflow:
     Run your Blog Creation workflow manually with test data
     Verify images generate correctly with brand colors
     Check WordPress post publishes with featured image
     Confirm tracking sheet updates
     Test Discord notification delivery

  Use cases

  Marketing agencies: Manage blog publishing for 10+ clients with different brand guidelines and WordPress sites from a single automation

  Content teams: Eliminate 2-3 hours of manual work per blog by automating image creation, internal linking, and WordPress publishing

  SEO specialists: Ensure consistent internal linking and proper category assignment across all published content

  Freelance writers: Offer end-to-end blog services including branded image creation and WordPress publishing without manual intervention

  SaaS companies: Maintain consistent blog publishing schedule across multiple product blogs with automated tracking and reporting

  Customization options

  Modify image generation:
  Edit the "Generate Image Prompts with AI" node to change image style, dimensions, or prompt instructions
  Change DALL-E model or image size in "Generate Image with DALL-E" node

  Adjust internal linking:
  Modify the "Add Internal Links to Content" agent prompt to change linking strategy (more/fewer links, different placement rules)

  Change notification channels:
  Replace Discord with Slack, email, or webhook notifications
  Add multiple notification channels in parallel

  WordPress customization:
  Add custom fields, tags, or metadata to published posts
  Integrate with WordPress plugins via REST API extensions

  Troubleshooting

  Images not generating: Check OpenAI API key validity and account credits. Verify image prompt node receives content properly.

  WordPress publish fails: Confirm REST API is enabled, authentication tokens are correct, and site URL is properly formatted with trailing slash.

  Internal links not appearing: Ensure "TGT Keywords" sheet has valid URLs starting with "http" and filter node is working correctly.

  Tracking sheet not updating: Verify Google Sheets OAuth connection and that row_number matches between sheets.

  Discord notification fails: Check Discord bot permissions and channel ID accuracy.

  Resources

  n8n documentation
  WordPress REST API guide
  OpenAI DALL-E API
  Google Gemini API
  Google Sheets API

  Important notes

  This workflow is specifically for blog publishing. To use it correctly, you must first have a Blog Content Creation workflow that generates the blog title, content, and required metadata.
  I have already shared a Blog Writing Automation workflow, which you can use directly for content creation before running this publishing workflow.
  Make sure the content creation workflow runs before this publishing workflow, as this setup depends on the generated output.

  Support

  Need help or custom development?

  📧 Email: info@isawow.com  
  🌐 Website: https://isawow.com/

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name: Score and route qualified leads to Notion and Matrix
author_name: vinci-king-01
author_username: vinci-king-01
categories: []
created_at: 2026-01-30T13:00:32.284Z
updated_at: 2026-01-30T13:00:32.284Z
url: https://n8n.io/workflows/13116
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:22
description:
  Lead Scoring Pipeline – Matrix + Notion

  This workflow automatically enriches incoming form leads, applies a customizable scoring model, then routes high-value prospects to a Notion CRM database and a Matrix channel for instant sales notification. It streamlines lead qualification by combining third-party enrichment APIs, conditional logic, and asynchronous batching—eliminating manual research and ensuring your sales team focuses on the best opportunities.

  Pre-conditions/Requirements

  Prerequisites
  n8n instance (self-hosted or n8n cloud)
  ScrapeGraphAI community node installed
  Matrix community node installed
  Notion Integration (internal integration or Notion OAuth)
  Active third-party enrichment/validation APIs (e.g., Clearbit, Hunter, Kickbox) for scoring data
  A Notion database set up as your “Leads” table with fields: Name, Email, Company, Score, Status, Enrichment

  Required Credentials
  ScrapeGraphAI API Key** – For optional web-scraping based enrichment  
  Notion OAuth2 / Integration Token** – To create & update pages in your CRM database  
  Matrix Username & Password** – For sending room messages  
  (Optional) Third-party API Keys** – Clearbit, Hunter, etc.

  Additional Setup Requirements
  | Setting                         | Example / Notes                                          |
  |---------------------------------|----------------------------------------------------------|
  | Notion Database ID              | 8f3d49e8c8f74e6f9d32e8e2bf7c1c46                      |
  | Matrix Room ID                  | !aBcDeFgHiJ:matrix.org                                |
  | Scoring Threshold (env var)     | LEAD_SCORE_MIN=70                                     |
  | Batch Size                      | SPLIT_IN_BATCHES=10 (controls parallel requests)       |
  | Webhook URL for form submission | https://your-n8n-instance/webhook/leads                |

  How it works

  This workflow automatically enriches incoming form leads, applies a customizable scoring model, then routes high-value prospects to a Notion CRM database and a Matrix channel for instant sales notification. It streamlines lead qualification by combining third-party enrichment APIs, conditional logic, and asynchronous batching—eliminating manual research and ensuring your sales team focuses on the best opportunities.

  Key Steps:
  Schedule / Webhook Trigger**: Starts on a schedule (daily) or via a form-submission webhook.
  Split in Batches**: Processes leads in manageable chunks to avoid rate limits.
  HTTP Requests**: Calls enrichment APIs (Clearbit, Hunter, etc.) to retrieve firmographic & technographic data.
  Code (Scoring Logic)**: Calculates a numeric lead score using weighted criteria (industry, employee count, email validity, etc.).
  If Node (Qualification)**: Checks if the computed score meets or exceeds the defined threshold.
  Notion Node**: Inserts or updates the qualified lead record in your Notion CRM database.
  Matrix Node**: Sends a rich-text message to the sales room with lead details and score.
  Wait + Merge**: Handles asynchronous API limits and merges enrichment data back into the main flow.

  Set up steps

  Setup Time: 15-25 minutes

  Clone the template in your n8n instance or import the JSON.
  Set environment variables (LEAD_SCORE_MIN, SPLIT_IN_BATCHES, API keys) in n8n Settings → Variables.
  Configure the Webhook/Schedule Trigger  
     Webhook: copy the URL to your form provider  
     Schedule: set cron (e.g., every hour).
  Update HTTP Request nodes with your enrichment API endpoints & headers.
  Map Notion fields: open the Notion node → choose your connection → select your Leads database → map data pins (Name, Email, etc.).
  Enter Matrix credentials & Room ID in the Matrix node.
  Adjust scoring weights in the Code node (weights object) to match your ICP (Ideal Customer Profile).
  Execute the workflow once with test data, verify Notion rows and Matrix messages.
  Activate the workflow and monitor via n8n’s execution list.

  Node Descriptions

  Core Workflow Nodes:
  Schedule Trigger / Webhook** – Initiates the workflow on time-based interval or form submission.
  SplitInBatches** – Limits API calls to avoid hitting rate caps.
  HTTP Request (Enrichment)** – Queries external services for company, domain, and email data.
  Set (Normalize)** – Formats API responses for scoring.
  Code (Score Calculator)** – JavaScript that assigns points based on business rules.
  If (Score ≥ Threshold?)** – Branches leads into “Qualified” or “Discard” paths.
  Notion (Create/Update Page)** – Inserts the qualified lead into Notion database.
  Matrix (Send Message)** – Notifies the sales team with lead context.
  Merge (Rejoin Streams)** – Consolidates asynchronous branches before completion.
  Sticky Note** – Documentation & config hints embedded directly in the canvas.

  Data Flow:
  Schedule/Webhook → SplitInBatches → HTTP Request (Enrichment) → Set → Code (Score) → If (Qualified?) →  
     a. (Yes) Notion → Matrix  
     b. (No) Wait (Cooldown) → Merge

  Customization Examples

  1. Change Scoring Weights
  // Code node snippet
  const weights = {
    employeeCount: 0.4, // increase influence of company size
    emailDeliverability: 0.2,
    industryMatch: 0.25,
    techStack: 0.15,
  };

  2. Notify Different Matrix Rooms Based on Territory
  // If node expression
  {{ $json.country === 'US' ? '!usSales:matrix.org' : '!intlSales:matrix.org' }}

  Data Output Format

  The workflow outputs structured JSON data:

  {
    "name": "Jane Doe",
    "email": "jane@acme.co",
    "company": "Acme Co.",
    "enrichment": {
      "employeeCount": 120,
      "industry": "SaaS",
      "techStack": ["AWS", "React"]
    },
    "score": 83,
    "qualified": true,
    "notionPageId": "9b2a4c09-0bf4-4b58-988a-1f361b0a2c20",
    "matrixEventId": "$15163622445EBvZJ:matrix.org"
  }

  Troubleshooting

  Common Issues
  Low or zero scores for valid leads – Review weighting logic and API response mapping in the Code node.  
  Notion “Missing required property” error – Ensure all mandatory database fields are mapped and Notion token has write access.  
  Matrix authentication failure – Double-check username/password or switch to an access token login method.  

  Performance Tips
  Reduce SPLIT_IN_BATCHES size if you’re hitting API rate limits.
  Enable “Execute Once” during testing to prevent excess API usage.

  Pro Tips:
  Store enrichment API keys as n8n credentials, not hard-coded strings.
  Add a second If node to flag “Priority” leads (score &gt; 90) for immediate follow-up.
  Use n8n’s built-in logging to create an audit trail by writing each execution to a Loggly/Datadog endpoint.

  This is a community template provided “as is.” Always test thoroughly in a non-production environment before activating in production.

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metadata_json:
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name: Generate consistent styled images from references with Google Gemini and Sheets
author_name: Adem Tasin
author_username: ademtasin
categories: []
created_at: 2026-01-30T13:41:32.071Z
updated_at: 2026-01-30T13:41:32.071Z
url: https://n8n.io/workflows/13117
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Who’s it for

  This workflow is designed for creators, designers, and automation builders who need to generate visually consistent images at scale.  
  It is ideal for teams producing branded visuals, social media assets, or AI-generated images where preserving a recognizable visual style is important.

  If you already manage prompts and image references in Google Sheets and want a repeatable, automated image generation pipeline, this template is a good fit.

  How it works / What it does

  The workflow is triggered via a webhook and reads pending image generation tasks from a Google Sheet.  
  For each row, it downloads a reference image and analyzes its visual characteristics using Google Gemini, including color palette, composition, and overall artistic style.

  Using this analysis, Gemini generates a new image that follows the same visual style while applying your provided prompt.  
  The generated image is uploaded to Google Drive, and the original Google Sheet is updated with the result or an error message.

  Real-time status updates are sent during execution using ntfy.sh notifications.

  How to set up

  Create a Google Sheet with columns such as gorsel_id, ana_prompt, stil_prompt, referans_url, and durum.
  Connect credentials for Google Sheets, Google Drive, and Google Gemini.
  Replace the Document ID and Folder ID values in the corresponding nodes.
  Update the ntfy topic name with your own unique topic.
  Activate the workflow and trigger it using the webhook URL.

  Requirements

  Google Sheets account  
  Google Drive account  
  Google Gemini (PaLM) API credentials  
  Self-hosted n8n instance  

  &gt; This workflow uses community nodes and is supported on self-hosted n8n instances only.

  How to customize the workflow

  You can adjust the Wait nodes to better align with your API rate limits.  
  To control how closely the generated image matches the reference style, modify the instructions in the Analyze – Gemini – Visual Style node.

  You can also extend the workflow with additional approval steps, storage locations, or notification channels without changing the core logic.

  🧑‍💻 Creator Information
  Developed by: Adem Tasin
  🌐 Website: ademtasin.com
  💼 LinkedIn: ademtasin

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