# templates

name: From Google Drive to Instagram, TikTok & YouTube with AI Descriptions & Airtable Tracking
author_name: Juan Carlos Cavero Gracia
author_username: carlosgracia
categories: []
created_at: 2025-07-08T16:46:00.998Z
updated_at: 2025-07-08T16:46:00.998Z
url: https://n8n.io/workflows/5787
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  Description



  This automation template is designed for content creators, social media managers, and influencers who want to streamline their video publishing workflow. It automatically detects new videos uploaded to a specific Google Drive folder, generates AI-powered descriptions based on video audio content, and simultaneously publishes them across Instagram, TikTok, and YouTube while tracking everything in Airtable.

  Note: This workflow uses upload-post.com API (free trial no credit card required) for multi-platform video distribution and requires API tokens for each service. The AI-generated descriptions are created using OpenAI's transcription and chat models to analyze video audio content.*

  Who Is This For?
  Content Creators & Influencers:** Automatically publish your videos across all major social platforms without manual work.
  Social Media Managers:** Maintain consistent posting schedules across multiple platforms with AI-generated, platform-optimized descriptions.
  Marketing Teams:** Scale video content distribution with automated workflows that include tracking and status monitoring.
  Video Producers:** Focus on creating content while the system handles the tedious task of multi-platform publishing and description generation.

  What Problem Does This Workflow Solve?
  Publishing the same video content across Instagram, TikTok, and YouTube is time-consuming and repetitive. You need to manually upload each video, write unique descriptions, and track publication status. This workflow addresses these challenges by:
  Automated Video Distribution:** Detects new videos in Google Drive and automatically uploads them to all three platforms simultaneously.
  AI-Powered Content Generation:** Uses OpenAI to transcribe video audio and generate engaging, platform-appropriate descriptions automatically.
  Centralized Tracking:** Maintains detailed records in Airtable including upload status, URLs, and metadata for each platform.
  Error Monitoring:** Provides real-time error notifications via Telegram to ensure you're always aware of any issues.

  How It Works
  Video Upload Detection: The workflow monitors a specific Google Drive folder for new video uploads using automated triggers.
  Content Analysis: Downloads the video, extracts audio, and uses OpenAI to transcribe and generate compelling descriptions.
  Airtable Integration: Creates and updates records to track video metadata, descriptions, and publication status.
  Multi-Platform Publishing: Simultaneously uploads the video to Instagram, TikTok, and YouTube using the upload-post.com API.
  Status Tracking: Updates Airtable records with publication status and platform-specific URLs for each successful upload.

  Setup
  Google Drive Configuration: 
     Set up the Google Drive trigger to monitor your specific folder
     Configure OAuth2 credentials for Google Drive access
  OpenAI Integration: Add your OpenAI API key to enable audio transcription and description generation
  Airtable Setup: 
     Create an Airtable base with fields for Video Name, Description, Platform Status, URLs, and Upload Date
     Add your Airtable API token and configure base/table IDs in the "Set Variables" node
  Upload-Post.com Account: 
     Create an account at upload-post.com to get your API token
     Configure the token in the HTTP request nodes for each platform
     Set your user ID in the variables section
  Platform Accounts: Ensure your Instagram, TikTok, and YouTube accounts are connected to upload-post.com
  Error Notifications: (Optional) Configure Telegram bot credentials for error notifications

  Requirements
  Accounts:** Google Drive, OpenAI, Airtable, upload-post.com, Telegram (optional)
  API Keys & Credentials:** Google Drive OAuth2, OpenAI API Key, Airtable API Token, upload-post.com API Token
  Platform Setup:** Instagram, TikTok, and YouTube accounts connected to upload-post.com

  Transform your video publishing workflow from hours of manual work to a fully automated system that handles everything from content analysis to multi-platform distribution and tracking.

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.airtable","n8n-nodes-base.errorTrigger","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.writeBinaryFile","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.airtable","n8n-nodes-base.readBinaryFile","n8n-nodes-base.readBinaryFile","n8n-nodes-base.readBinaryFile","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.airtable","n8n-nodes-base.airtable","n8n-nodes-base.airtable","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set"]

workflow_json_compressed:
  [encoded data, 5900 characters]

metadata_json:
  {"categories":["automation","integration","social media","content distribution","data tracking"],"complexity":"medium","use_cases":["Automated multi-platform video publishing","AI-powered transcription and description generation","Centralized tracking of uploads and statuses","Scaling social media distribution workflows","Error monitoring and alerting"],"estimated_setup_minutes":45,"required_services":["Google Drive (OAuth2)","OpenAI (API)","Airtable (API)","upload-post.com (API)","Instagram (connected via upload-post.com)","TikTok (connected via upload-post.com)","YouTube (connected via upload-post.com)","Telegram (optional, bot API)"],"key_features":["Detect new videos in Google Drive folder","Download video and extract/transcribe audio with OpenAI","Generate platform-optimized AI descriptions","Simultaneous uploads to Instagram, TikTok, and YouTube via upload-post.com","Create and update Airtable records with status, URLs, and metadata」「Real-time error notifications via Telegram (optional)"],"target_audience":["Content creators","Social media managers","Influencers and video producers`,`Marketing teams and agencies"]}


name: Multi-Account Email Classifier with AI, Gmail, Discord & Google Sheets
author_name: Jay Emp0
author_username: jay-emp0
categories: []
created_at: 2025-07-08T17:28:42.844Z
updated_at: 2025-07-08T17:28:42.844Z
url: https://n8n.io/workflows/5789
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  AI Email Classifier 📬  
  Automate Email Classification, Prioritization, and Spam Detection Across Multiple Accounts  

  Created by: Jayant Kumar (@jharilela)  
  🛠 Powered by: Gmail, Google Sheets, OpenAI, Discord, and n8n  

  Sample Discord labelling as Spam

  Sample Discord labelling as Legit

  Why I Built This

  Focus is Expensive. Managing multiple email inboxes every day—personal, business, partnerships, invoices. Logging into each, skimming through noise, flagging important stuff, and deleting spam started eating up hours of my week. I needed a system that helped me focus only on what matters without building an entire helpdesk dashboard.  

  I already live in Discord. It made sense to push my emails there—but in a fun, digestible, and actionable way. I built AI Email Classifier 📬 to summarize emails, detect spam, assign priority, and make everything skimmable with pictures and links.  

  And it works across multiple Gmail accounts.

  Key Features

  ✅ Works with multiple Gmail inboxes  
  🧠 Uses AI to classify spam vs legit  
  🎯 Assigns priority levels: High / Medium / Low  
  🗂 Appends everything to a central Google Sheet  
  📸 Sends visual summaries to Discord (with image + action links)  
  🛠 Powered by open-source: n8n_discord_trigger_bot

  How It Works

  Here’s the high-level flow:

  New Email in any inbox triggers the worfklow to start
  The AI Agent reads the raw content, subject, sender, Gmail labels.
  It calls a Google Sheet that acts as our feedback memory:
     Emails and domains manually marked as spam or legit.
  AI classifies the incoming email using logic:
     Spam if sender or domain is blacklisted, or content matches patterns like:  
       "promotions, phishing, ads, mass emails, cold offers"  
     Priority is assigned by:
       High: deadlines, legal, payments, clients, CEO emails  
       Medium: team updates, meetings, project notifications  
       Low: newsletters, FYIs, casual threads  
  It produces a compact JSON output with:
     Sender, recipient, subject, summary, priority, priority color, image URL, action URL  
  The message is formatted visually and posted back to Discord as an embed with:
     Summary text  
     Actionable links  
     Priority color code  
     Thumbnail (if any)  

  Google Sheet Training Table  

  The system uses this sheet as live memory to label spam and legit senders:  

  ╔════════════════════╦══════════════╦═════════════════╦══════════════╦════════════════╗
  ║       Email        ║    Domain    ║  Classification ║  Labelled By ║  Labelled Date ║
  ╠════════════════════╬══════════════╬═════════════════╬══════════════╬════════════════╣
  ║ offers@badsite.com ║  badsite.com ║  Spam           ║  Jayant      ║  08/07/2025    ║
  ║ ceo@trusted.com    ║  trusted.com ║  Legit          ║  Jayant      ║  08/07/2025    ║
  ╚════════════════════╩══════════════╩═════════════════╩══════════════╩════════════════╝



  This allows manual control to teach the AI which senders to trust or ignore. Every time I see something marked wrong, I just reply in Discord with "spam" or "legit" on that message thread. That triggers an update to the Sheet via AI parsing and n8n.

  Why Manual Input Still Matters

  AI isn’t perfect.  
  Some spam emails are cleverly disguised. And some senders are contextually important only to you.

  That’s why I kept a simple feedback loop:
  You tell the bot "spam" or "legit" on any Discord email message. Or anything along that line
  The AI agent detects the intent and updates the Sheet.
  The AI improves its judgment next time as it now remembers your preference

  Why Discord?

  Because Slack charges per seat and email feels lonely.  
  I run most of my operations inside Discord community chats, client rooms, bot alerts.  
  Instead of making a full email UI, I turned each email into a Discord card with a thumbnail, summary, and quick actions.  
  It’s fun. It’s visual. It doesn’t feel like work.  
  Email becomes more like a game feed.

  Tech Stack

  Gmail → Discord via Gmail trigger node
  Discord → n8n Webhook via n8n_discord_trigger_bot  
  OpenAI GPT-4o (classification + summarization)  
  Google Sheets (feedback memory)  
  Discord Node (embed output with JSON + images)  

  Try It Yourself

  Clone the workflow JSON, set up your Gmail integrations, and install the n8n Discord Trigger Bot.  
  I made this workaround because i couldnt find a discord trigger on n8n. 

  Now I just scroll my Discord DMs and know what to reply to, and ignore everything else.Dont let Email spam your brain. Let your AI do the thinking.

nodes_used:
  ["n8n-nodes-base.gmailTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.gmailTrigger","n8n-nodes-base.gmailTrigger","n8n-nodes-base.gmailTrigger","n8n-nodes-base.merge","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.webhook","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.discord","n8n-nodes-base.discordTool","n8n-nodes-base.googleSheetsTool","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.discord","n8n-nodes-base.if"]

workflow_json_compressed:
  [encoded data, 6896 characters]

metadata_json:
  {"categories":["automation","email management","AI classification","integrations"],"complexity":"complex","use_cases":["Multi-account email triage and prioritization","Spam detection and sender/domain blacklisting","Summarization of emails for quick review","Pushing email notifications into Discord for lightweight workflows","Maintaining a feedback-driven trust/blacklist via Google Sheets"],"estimated_setup_minutes":60,"required_services":["Gmail (Google account / Gmail API)","Google Sheets (Google Sheets API)","OpenAI (GPT-4o or compatible model)","Discord (bot or webhook + n8n_discord_trigger_bot)","n8n (self-hosted or cloud instance)"],"key_features":["Supports multiple Gmail inboxes","AI-based spam vs legit classification","Priority assignment (High / Medium / Low) with color coding","Central Google Sheet as live feedback memory (whitelist/blacklist)","Discord embeds with summary, thumbnail, and action links for each email message entry point and reply-based feedback loop to update memory"],"target_audience":["Individuals managing multiple email accounts","Productivity enthusiasts","Community managers and operators using Discord as a hub for alerts/notifications"]}


name: Extract Business Contact Leads from Google Maps with RapidAPI and Google Sheets
author_name: Javier Hita
author_username: javierhita
categories: []
created_at: 2025-07-08T19:55:29.802Z
updated_at: 2025-07-08T19:55:29.802Z
url: https://n8n.io/workflows/5794
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  Follow me on LinkedIn for more!

  Category: Lead Generation, Data Collection, Business Intelligence

  Tags: lead-generation, google-maps, rapidapi, business-data, contact-extraction, google-sheets, duplicate-prevention, automation

  Difficulty Level: Intermediate

  Estimated Setup Time: 15-20 minutes

  Template Description

  Overview

  This powerful n8n workflow automates the extraction of comprehensive business information from Google Maps using keyword-based searches via RapidAPI's Local Business Data service. Perfect for lead generation, market research, and competitive analysis, this template intelligently gathers business data including contact details, social media profiles, and location information while preventing duplicates and optimizing API usage.

  Key Features

  🔍 Keyword-Based Google Maps Scraping**: Search for any business type in any location using natural language queries
  📧 Contact Information Extraction**: Automatically extracts emails, phone numbers, and social media profiles (LinkedIn, Instagram, Facebook, etc.)
  🚫 Smart Duplicate Prevention**: Two-level duplicate detection saves 50-80% on API costs by skipping processed searches and preventing duplicate business entries
  📊 Google Sheets Integration**: Seamless data storage with automatic organization and structure
  🌍 Multi-Location Support**: Process multiple cities, regions, or countries in a single workflow execution
  ⚡ Rate Limiting & Error Handling**: Built-in delays and error handling ensure reliable, uninterrupted execution
  💰 Cost Optimization**: Intelligent batching and duplicate prevention minimize API usage and costs
  📱 Comprehensive Data Collection**: Gather business names, addresses, ratings, reviews, websites, verification status, and more

  Prerequisites

  Required Services & Accounts
  RapidAPI Account with subscription to "Local Business Data" API
  Google Account for Google Sheets integration
  n8n Instance (cloud or self-hosted)

  Required Credentials
  RapidAPI HTTP Header Authentication** for Local Business Data API
  Google Sheets OAuth2** for data storage and retrieval

  Setup Instructions

  Step 1: RapidAPI Configuration

  Create RapidAPI Account
     Sign up at RapidAPI.com
     Navigate to "Local Business Data" API
     Subscribe to a plan (Basic plan supports 1000 requests/month)

  Get API Credentials
     Copy your X-RapidAPI-Key from the API dashboard
     Note the host: local-business-data.p.rapidapi.com

  Configure n8n Credential
     In n8n: Settings → Credentials → Create New
     Type: HTTP Header Auth
     Name: RapidAPI Local Business Data
     Add headers:
       X-RapidAPI-Key: YOUR_API_KEY
       X-RapidAPI-Host: local-business-data.p.rapidapi.com

  Step 2: Google Sheets Setup

  Enable Google Sheets API
     Go to Google Cloud Console
     Enable Google Sheets API for your project
     Create OAuth2 credentials

  Configure n8n Credential
     In n8n: Settings → Credentials → Create New
     Type: Google Sheets OAuth2 API
     Follow OAuth2 setup process

  Create Google Sheet Structure

  Create a new Google Sheet with these tabs:

  keyword_searches sheet:
  | select | query | lat | lon | country_iso_code |
  |--------|-------|-----|-----|------------------|
  | X | Restaurants Madrid | 40.4168 | -3.7038 | ES |
  | X | Hair Salons Brooklyn | 40.6782 | -73.9442 | US |
  | X | Coffee Shops Paris | 48.8566 | 2.3522 | FR |

  stores_data sheet:
  The workflow will automatically create columns for business data including:
  business_id, name, phone_number, email, website, full_address, rating, 
  review_count, linkedin, instagram, query, lat, lon, and 25+ more fields

  Step 3: Workflow Configuration

  Import the Workflow
     Copy the provided JSON
     In n8n: Import from JSON

  Update Placeholder Values
     Replace YOUR_GOOGLE_SHEET_ID with your actual Google Sheet ID
     Update credential references to match your setup

  Configure Search Parameters (Optional)
     Adjust limit: 1-100 results per query (default: 100)
     Modify zoom: 10-18 search radius (default: 13)
     Change language: EN, ES, FR, etc. (default: EN)

  How It Works

  Workflow Process

  Load Search Criteria: Reads queries marked with "X" from keyword_searches sheet
  Load Existing Data: Retrieves previously processed data for duplicate detection
  Filter New Searches: Smart merge identifies only new query+location combinations
  Process Each Location: Sequential processing prevents API overload
  Configure Parameters: Prepares search parameters from sheet data
  API Request: Calls RapidAPI to extract business information
  Parse Data: Structures and cleans all business information
  Save Results: Stores new leads in stores_data sheet
  Rate Limiting: 10-second delay between requests
  Loop: Continues until all new searches are processed

  Duplicate Prevention Logic

  Search Level: Compares new queries against existing data using query+latitude combination, skipping already processed searches.

  Business Level: Each business receives a unique business_id to prevent duplicate entries even across different searches.

  Data Extracted

  Business Information
  Business name, full address, phone number
  Website URL, Google My Business rating and review count
  Business type, price level, verification status
  Geographic coordinates (latitude/longitude)
  Detailed location breakdown (street, city, state, country, zip)

  Contact Details
  Email addresses (when publicly available)
  Social media profiles: LinkedIn, Instagram, Facebook, Twitter, YouTube, TikTok, Pinterest
  Additional phone numbers
  Direct Google Maps and reviews links

  Search Metadata
  Original search query and parameters
  Extraction timestamp and geographic data
  API response details for tracking

  Use Cases

  Lead Generation
  Generate targeted prospect lists for B2B sales
  Build location-specific customer databases
  Create industry-specific contact lists
  Develop territory-based sales strategies

  Market Research
  Analyze competitor density in target markets
  Study business distribution

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleSheets","n8n-nodes-base.wait","n8n-nodes-base.googleSheets","n8n-nodes-base.merge","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, 7260 characters]

metadata_json:
  {"categories":["Lead Generation","Data Collection","Business Intelligence","Automation"],"complexity":"medium","use_cases":["Automated lead generation and prospect list building","Market research and competitor density analysis","Location-based data collection and territory planning","Contact enrichment (emails, phones, social profiles)","Centralizing business data into Google Sheets for reporting"],"estimated_setup_minutes":20,"required_services":["RapidAPI - Local Business Data API","Google Sheets API / Google Account (OAuth2)","n8n instance (cloud or self-hosted)","Google Cloud Console (to enable Sheets API / create OAuth credentials)"],"key_features":["Keyword-based Google Maps searches via RapidAPI","Comprehensive contact extraction (emails, phones, social profiles)","Two-level duplicate prevention (search-level and business-level)","Google Sheets integration for storage and incremental updates","Multi-location and batch processing support with rate limiting/delays/ error handling safeguards optimized for cost control"],"target_audience":["Sales and business development teams","Growth marketers and demand-gen specialists","Market researchers and analysts\",\"n8n users / automation engineers\",\"Data engineers and ops teams"]}


name: Find Top-Performing Instagram Reels & Save Insights to Notion with Gemini & Apify
author_name: Eugene Green
author_username: egrnkvch
categories: []
created_at: 2025-07-08T19:55:45.737Z
updated_at: 2025-07-08T19:55:45.737Z
url: https://n8n.io/workflows/5795
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

  This template helps you discover trending Instagram Reels from competitors or any public profiles you choose. 

  📺 How It Works 

  The workflow automatically monitors selected Instagram accounts using Apify, pulls recent Reels, and analyzes their performance.  

  It calculates engagement levels, detects early “hot” content, translates text if needed, and organizes all results into a structured Notion database — ready for review and production.

  I've recorded a video walkthrough to show you how the system works in detail.
  👉 https://www.youtube.com/watch?v=rdfRNHpHX8o

  @youtube

  📄 Download Notion Database Structure  
  You can download the Notion table structure (with all required columns and formats) here:  
  👉 https://drive.google.com/file/d/1FVaS_-ztp6PDAJbETUb1dkg8IqE4qHqp/view?usp=sharing

  👤 Who’s it for

  This workflow is for marketers, content creators, social media managers, and automation enthusiasts who want to stay ahead of Instagram Reels trends.  
  Whether you're building a content pipeline or studying competitors, this tool saves hours of manual tracking.

  🔧 How to set up

  Create the required databases in Notion (structure file provided).  
  Import the .json workflow into your n8n instance.  
  Set up credentials for Notion, Apify, and Gemini API.  
  Link those credentials in the workflow.  
  Adjust the Variables node with your test account list and settings.  
  Run a test with 3–5 profiles and validate the output.  
  Once working, update Variables with your full config.

  📋 Requirements

  An n8n instance (self-hosted or cloud)  
  A Notion account (separate workspace recommended)  
  Apify account (usage-based pricing for Instagram scraping)  
  Gemini API key for AI processing (usage-based pricing)

  🧩 How to customize the workflow

  The system is fully modular. You can:
  In the Set Prompt node, you can define your own rules for detecting content categories and video types.
  Change video filters (e.g., what counts as “hot” or “early hot”) 
  Modify Notion fields or adapt to your own database structure  
  Add more parsing logic to Variables  
  Switch translation language 
  Integrate with your content production flow

  Each part of the workflow is clearly labeled and editable — feel free to adapt it to your goals.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.notion","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.switch","n8n-nodes-base.wait","@apify/n8n-nodes-apify.apify","@apify/n8n-nodes-apify.apify","@apify/n8n-nodes-apify.apify","n8n-nodes-base.notion","n8n-nodes-base.notion","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.notion","n8n-nodes-base.notion","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.switch","n8n-nodes-base.splitInBatches","n8n-nodes-base.code","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"]

workflow_json_compressed:
  [encoded data, 9652 characters]

metadata_json:
  {"categories":["social media monitoring","automation","integration","content intelligence"],"complexity":"medium","use_cases":["Competitor Reels monitoring","Trend detection and early ‘hot’ content alerts","Building a content production pipeline","Archiving and analyzing Reels performance in Notion","Translating captions and extracting insights with AI"],"estimated_setup_minutes":45,"required_services":["n8n (self-hosted for community nodes)","Notion account","Apify account (Instagram scraping)","Gemini API (AI processing)"],"key_features":["Automated scraping of Instagram Reels via Apify","Engagement scoring and early ‘hot’ content detection","AI analysis and text translation with Gemini","Structured export of results into a Notion database","Modular and editable prompts/filters for custom rules and categories」「Supports variables for profile lists and settings"],"target_audience":["Marketers","Content creators","Social media managers」「Automation enthusiasts"]}


name: Create AI News Avatar Videos with Dumpling AI, GPT-4o and HeyGen
author_name: Yang
author_username: yang
categories: []
created_at: 2025-07-08T20:17:53.025Z
updated_at: 2025-07-08T20:17:53.025Z
url: https://n8n.io/workflows/5796
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  🧾 What this workflow does

  This workflow automatically generates avatar-style videos from the latest AI-related news using Dumpling AI and HeyGen. It runs every hour, scrapes trending articles, turns them into 30–60 second spoken scripts with GPT-4o, and produces short avatar videos with HeyGen. Finally, it logs the final video URL in a Google Sheet.

  👤 Who is this for

  Newsletters and creators who want to automate AI trend updates  
  Content marketers generating short-form video content  
  Product teams experimenting with AI-generated summaries  
  Automation enthusiasts combining LLMs + video + trending data  

  ⚙️ How to set up

  🔐 Requirements
  Dumpling AI API Key** stored securely as HTTP Header credential  
  HeyGen API Key** added as an HTTP Header credential  
  OpenAI API Key** for GPT-4o (can use GPT-4o-mini if preferred)  
  Google Sheets account** with one column: Video link  

  🛠 Step-by-step setup

  Google Sheet Setup  
     Create a Google Sheet with a single column named: Video link

  Update Credentials  
     Use n8n’s credential manager to add tokens for:  
       Dumpling AI  
       HeyGen  
       OpenAI  
       Google Sheets

  Optional Customizations
     In the "Dumpling AI: Search AI News" node, you can change "query": "AI Agent"  
       to other trending keywords (e.g., "Generative AI", "Autonomous Agents", etc.)
     Update the avatar_id and voice_id in the HeyGen request to match your preferred look/sound

  🧠 How it works

  The Schedule Trigger runs hourly.  
  Dumpling AI searches for fresh news related to "AI Agent."  
  The top 4 news links are scraped for full content.  
  Articles are merged and fed into GPT-4o via a LangChain Agent to produce a casual, conversational video script.  
  HeyGen creates a video using the script, avatar, and voice.  
  The workflow waits until the video rendering is complete.  
  Once done, the final video link is logged into Google Sheets.

  🧪 Customization Ideas

  Change the interval (e.g., every 6 hours, daily)
  Swap avatar/voice in HeyGen to fit your brand
  Expand to post the video directly to social media
  Add image background or B-roll overlays using Creatomate


  This is a fast, automated pipeline to create explainer-style AI news updates using real-time data and generative video tools.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.limit","n8n-nodes-base.httpRequest","n8n-nodes-base.aggregate","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4740 characters]

metadata_json:
  {"categories":["automation","content_creation","video_generation","news_aggregation","ai_integration"],"complexity":"medium","use_cases":["Automate short AI news video production","Create daily/hourly explainer videos for newsletters","Generate short-form social content from trending articles","Prototype LLM + generative video pipelines","Aggregate and summarize industry news"],"estimated_setup_minutes":30,"required_services":["Dumpling AI (news/search API)","HeyGen (avatar video generation)","OpenAI (GPT-4o or GPT-4o-mini)","Google Sheets"],"key_features":["Hourly scheduled workflow to fetch trending AI news","Scrapes and merges top article content","Uses a LangChain agent with GPT-4o to produce 30–60s spoken scripts","Creates avatar-style videos via HeyGen and waits for rendering","Logs final video URLs to Google Sheets for tracking/sharing"],"target_audience":["newsletter writers and editors","content marketers and creators","product teams experimenting with generative workflows (LLM + video)"]}


name: Find Quality YouTube Videos with Automated Filtering & Relevance Scoring to Google Sheets
author_name: Zach @BrightWayAI
author_username: ajenta
categories: []
created_at: 2025-07-08T20:20:26.382Z
updated_at: 2025-07-08T20:20:26.382Z
url: https://n8n.io/workflows/5797
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  Who's it for
  Content creators, researchers, educators, and digital marketers who need to discover high-quality YouTube training videos on specific topics. Perfect for building curated learning resource lists, competitive research, or content inspiration.

  What it does
  This workflow automatically searches YouTube using multiple search queries, filters for quality content, scores videos by relevance, and exports the top results to Google Sheets. It processes hundreds of videos and delivers only the most valuable educational content ranked by custom relevance criteria.

  The workflow searches for videos using 10 different AI automation-related queries (easily customizable), filters out low-quality content like shorts and clickbait, then ranks results based on title keywords, view counts, and engagement metrics.

  How it works
  Multi-query search: Searches YouTube with an array of related queries to get comprehensive coverage
  Content filtering: Removes shorts, spam, and low-quality videos using regex patterns
  Quality assessment: Filters videos based on view count, likes, and publication date
  Relevance scoring: Assigns scores based on title keywords and engagement metrics
  Result ranking: Sorts videos by relevance score and limits to top 50 results
  Export to Sheets: Delivers clean, organized data to Google Sheets with all metadata

  Requirements
  YouTube Data API v3 credentials from Google Cloud Console
  Google Sheets credentials for n8n workspace
  A Google Sheets document to receive the results

  How to set up
  Enable YouTube Data API v3 in your Google Cloud Console
  Add YouTube OAuth2 credentials to your n8n workspace
  Add Google Sheets credentials to your n8n workspace
  Create a Google Sheet and update the Google Sheets node with your document ID
  Customize search queries in the "Set Query" node for your topic
  Adjust filtering criteria in the Filter nodes based on your quality requirements

  How to customize the workflow
  Search topics: Modify the query array in the "Set Query" node to research any topic:

  [
  "Python tutorial",
  "JavaScript course", 
  "React beginner guide",
  // Add your queries here
  ]


  Quality thresholds: Adjust minimum views, likes, and date ranges in the "Filter for Quality" node

  Relevance scoring: Customize keyword weightings in the "Relevance Score" node to match your priorities

  Result limits: Change the number of final results in the "Limit" node (default: 50)

  Output format: Modify the "Set Fields" node to include additional YouTube metadata like duration, thumbnails, or category information

  The workflow is designed to be easily adaptable for any research topic while maintaining high content quality standards.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.wait","n8n-nodes-base.filter","n8n-nodes-base.stickyNote","n8n-nodes-base.splitOut","n8n-nodes-base.splitOut","n8n-nodes-base.filter","n8n-nodes-base.splitInBatches","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.removeDuplicates","n8n-nodes-base.set","n8n-nodes-base.sort","n8n-nodes-base.limit","n8n-nodes-base.googleSheets"]

workflow_json_compressed:
  [encoded data, 6772 characters]

metadata_json:
  {"categories":["automation","integration","data processing","research","content curation"],"complexity":"medium","use_cases":["Curate high-quality YouTube training resources","Competitive research on video content","Content ideation and inspiration","Building topic-specific learning libraries","Monitoring quality and trends for a topic"],"estimated_setup_minutes":20,"required_services":["YouTube Data API v3 (Google Cloud Console)","Google Sheets (Google account)","n8n workspace with OAuth2 credentials for Google"],"key_features":["Multi-query YouTube search (array-driven)","Regex-based filtering to remove shorts/clickbait/spam","Quality filtering by views, likes, and publication date","Custom relevance scoring using title keywords and engagement metrics","Sorting and limiting top results (default 50) with deduplication and batching support"],"target_audience":["Content creators","Researchers","Educators and instructional designers」「Digital marketers and SEO specialists」「Data analysts doing content research"]}


name: Turn YouTube Transcripts into Newsletter Drafts using Dumpling AI + GPT-4o
author_name: Yang
author_username: yang
categories: []
created_at: 2025-07-08T20:25:24.367Z
updated_at: 2025-07-08T20:25:24.367Z
url: https://n8n.io/workflows/5798
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  🧾 What this workflow does

  This workflow turns YouTube video links into ready-to-edit newsletter drafts using Dumpling AI and GPT-4o. It reads new video URLs from a Google Sheet, extracts their transcripts, summarizes them into email-friendly content, and logs the finished draft back into the same sheet. An email notification is also sent to alert the user once each draft is created.

  👤 Who is this for

  Newsletter writers or marketers repurposing video content  
  YouTube creators building email follow-ups from videos  
  Agencies or VAs batching social → email content  
  Automation users streamlining content workflows

  ⚙️ How to set up

  ✅ Requirements
  Google Sheet** with the following columns:  
    link — YouTube video URL  
    blog post — for saving the generated newsletter draft  
  Active accounts for:  
    Dumpling AI (API for YouTube transcripts)  
    OpenAI GPT-4 or GPT-4o  
    Google Sheets  
    Gmail (OAuth2 credential)

  🔧 Setup steps

  Connect all credentials using n8n's Credential Manager:
     Google Sheets (OAuth2)
     Dumpling AI (via HTTP Header Auth)
     OpenAI
     Gmail

  Update the sheet ID and tab name in both Google Sheets nodes.

  Customize the GPT-4o prompt (optional):
     Located in the “GPT-4o: Write Newsletter Draft from Transcript” node
     You can edit tone, structure, and audience targeting in the system message

  Verify email recipient in the Gmail node and update if needed.

  🧠 How it works

  The workflow is triggered manually or on schedule.
  It pulls YouTube links without drafts from the sheet.
  Each video’s transcript is fetched using Dumpling AI.
  GPT-4o summarizes the transcript into a clean, friendly newsletter format.
  The draft is written back to the same row in Google Sheets.
  An email is sent to notify the user that the draft is ready.

  🛠️ Customization ideas

  Send finished drafts to Notion or Airtable instead of Sheets  
  Generate social media posts from the same transcript  
  Add automatic review steps using GPT scoring or editing  
  Trigger this on new form submissions or YouTube uploads instead

  This is a fast, AI-powered way to turn long-form video content into clean, polished newsletters — ready to share or schedule with minimal editing.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.splitInBatches","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleSheets","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","content repurposing","integration","email","AI"],"complexity":"medium","use_cases":["Turn YouTube videos into newsletter drafts","Repurpose video content for email campaigns","Batch content creation for agencies or VAs","Automate follow-up emails for YouTube creators","Create editable drafts for editors or marketers"],"estimated_setup_minutes":20,"required_services":["Google Sheets (OAuth2)","Dumpling AI (YouTube transcript API)","OpenAI (GPT-4 or GPT-4o)","Gmail (OAuth2)","n8n"],"key_features":["Reads YouTube URLs from Google Sheets and skips rows with existing drafts","Fetches video transcripts via Dumpling AI","Summarizes transcripts into email-friendly newsletter drafts using GPT-4o","Writes generated drafts back to the original Google Sheet row","Sends email notifications when drafts are ready (Gmail node)"],"target_audience":["Newsletter writers","Marketers","YouTube creators building email follow-ups"]}


name: Generate Ad Image Variations Using GPT-4, Dumpling AI & Google Drive
author_name: Yang
author_username: yang
categories: []
created_at: 2025-07-08T20:31:08.872Z
updated_at: 2025-07-08T20:31:08.872Z
url: https://n8n.io/workflows/5799
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  🧾 What this workflow does

  This workflow takes a reference ad image and brand website, then uses GPT-4, LangChain, and Dumpling AI to generate 10 high-quality image variations for ad testing. These image variations are visually consistent but subtly different in background, mood, lighting, and tone — perfect for performance testing on platforms like Meta Ads or TikTok.

  👤 Who is this for

  DTC marketers and brand designers testing ad creatives  
  Creative teams automating visual experimentation  
  Content agencies using AI for fast ad mockups  
  Performance marketers running multivariate testing

  ⚙️ How to set up

  ✅ Requirements

  You’ll need the following tools set up in n8n:
  Google Drive (OAuth2 credential)
  Google Sheets (OAuth2 credential)
  OpenAI API (for GPT-4 or GPT-4o)
  Dumpling AI API (via HTTP header authentication)

  🛠️ Steps to configure

  Google Sheet Setup  
     Create a sheet with one column: Image URL  
     Update the Sheet ID and tab name in the final Google Sheets node.

  Drive Setup  
     Create a folder in Google Drive for storing the reference image.  
     Replace the folderId in the “Upload Ad Image to Google Drive” node.

  Dumpling AI API Key  
     Use n8n’s credential manager (HTTP Header Auth) — do not hardcode the key.

  OpenAI API Key  
     Required for both image description and LangChain agent prompt generation.

  Form Inputs Required
     Brand Name  
     Brand Website  
     Ad Image (upload field)

  🧠 How it works

  A user submits the brand name, website, and a reference ad image through a form.
  The image is uploaded to Google Drive.
  GPT-4o describes the image’s visual style (e.g., mood, lighting, composition).
  GPT-4 analyzes the brand’s website to define its visual aesthetic.
  A LangChain agent uses both analyses to create 10 tightly scoped variation prompts.
  Dumpling AI generates a new image for each prompt using its “FLUX.1-pro” model.
  Each new image’s link is logged into Google Sheets.

  🛠️ How to customize

  🧪 Change prompt logic to experiment with different variations (e.g., theme, season).
  🎨 Switch image model in Dumpling AI to one that supports your desired style.
  🔗 Log additional metadata (prompt, timestamp) to Google Sheets.
  📤 Connect output images to Airtable, Notion, or a review tool like Figma.
  🎯 Modify GPT system message to reflect a different tone or brand strategy.

  This workflow gives creative teams and marketers an instant, AI-powered ad image testing system — built on real brand visuals, not generic stock content.

nodes_used:
  ["n8n-nodes-base.formTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.splitOut","n8n-nodes-base.googleDrive","n8n-nodes-base.splitInBatches","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5604 characters]

metadata_json:
  {"categories":["automation","marketing","creative/design","image-generation","integration"],"complexity":"complex","use_cases":["Generate multiple ad creative variations for A/B or multivariate testing","Automate creative mockups based on real brand assets","Rapidly iterate visual styles (mood, lighting, composition) for performance ads","Log and organize generated assets for review or downstream tools"],"estimated_setup_minutes":30,"required_services":["Google Drive (OAuth2)","Google Sheets (OAuth2)","OpenAI API (GPT-4/GPT-4o)","Dumpling AI API","LangChain (agent) or n8n agent integration"],"key_features":["Uploads reference ad to Google Drive","GPT-4 analyzes image visual style","GPT-4 + LangChain generates 10 scoped variation prompts","Dumpling AI (FLUX.1-pro) creates image variations","Stores generated image links in Google Sheets for tracking/logging"],"target_audience":["DTC marketers","Brand/product designers","Creative teams and content agencies','Performance/growth marketers"]}


name: Create YouTube Shorts Scripts from Video Links with Gemini AI and Telegram
author_name: Taiki
author_username: taiki
categories: []
created_at: 2025-07-09T06:47:21.922Z
updated_at: 2025-07-09T06:47:21.922Z
url: https://n8n.io/workflows/5805
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  disclaimer: This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

  Quick Summary

  This template automates the creation of YouTube Shorts scripts. Simply send a YouTube video URL to a Telegram bot, and this workflow will use AI (Google Gemini) to generate a script optimized for Shorts and send it back to you. It streamlines your content creation process by eliminating the manual work of transcribing and scriptwriting.

  Target Audience & Problem Solved
  This template is ideal for:
  YouTube Content Creators
  Social Media Marketers
  Anyone looking to efficiently repurpose - - video content

  It solves the following problems:
  Quickly creating engaging short-form video content from existing long-form videos.
  Drastically reducing the time spent on video transcription, summarization, and scriptwriting.
  Enabling content idea generation on the go, even from a smartphone without access to a PC.

  Workflow Overview

  This workflow automatically generates a script for YouTube Shorts using AI (Google Gemini) from a YouTube video URL received via Telegram, and then sends the result back to Telegram.

  The process is as follows:

  Receive URL: A Telegram bot receives a YouTube video URL from a user.
  Get Transcript: It uses the community node n8n-nodes-supadata to retrieve the video's transcript via the Supadata service.
  Generate Script: Based on the retrieved transcript, Google Gemini creates a script (title and body) optimized for a YouTube Shorts video.
  Send Result: The generated script is sent back to the user who sent the original URL via Telegram.

  How to Use

  Prerequisites:
      Install the n8n-nodes-supadata community node as described below.
      Register your API keys for Telegram, Supadata, and Google Gemini as credentials in n8n.
      Set the appropriate credentials in each node within the workflow.
      For Telegram, create your bot with BotFarther.

  Execution:
      Activate the workflow.
      Send a YouTube video URL to your configured Telegram bot.
  Confirmation:
      After a short while, the workflow will run automatically, and you will receive the completed script from the Telegram bot.

  Customization Guide
  You can tailor this template to your specific needs:
  Modify the Prompt: Edit the prompt in the Google Gemini node to change the style of the generated script (e.g., make it more casual, use a specific tone, include emojis).
  Change the AI Model: You can switch to other AI models like OpenAI. Simply add or replace the corresponding n8n node.
  Change the Notification Channel: Replace the Telegram node with a Discord or Slack node to send the results to a different platform.

  Community Node Installation

  This workflow requires the n8n-nodes-supadata community node. Please install it using the following steps.

  Installation from the n8n UI (Recommended)

  Navigate to Settings &gt; Community Nodes in your n8n interface.
  Click on Install.
  Enter n8n-nodes-supadata in the input field and click the Install button.

nodes_used:
  ["n8n-nodes-base.telegram","n8n-nodes-base.telegramTrigger","n8n-nodes-supadata.supadata","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","content creation","social media","AI-assisted"],"complexity":"medium","use_cases":["Generate YouTube Shorts scripts from long-form videos","Repurpose existing video content into short-form scripts","Quick on-the-go content idea and script generation via Telegram","Automate transcription + summarization + scriptwriting workflow"],"estimated_setup_minutes":20,"required_services":["Telegram (bot created via BotFather)","Supadata (for video transcripts) - n8n-nodes-supadata community node","Google Gemini (AI model / API)","Self-hosted n8n (to use community nodes and install n8n-nodes-supadata)"],"key_features":["Receive YouTube URL via Telegram bot","Fetch video transcript using Supadata community node","Generate Shorts-optimized title and script using Google Gemini","Return generated script to the user in Telegram","Customizable AI prompt and easy model swap (e.g., OpenAI) within workflow nodes"],"target_audience":["YouTube content creators","Social media marketers","Content repurposing specialists / creators on-the-go"]}


name: Create Custom PDF Documents from Templates with Gemini & Google Drive
author_name: Ozgur Karateke
author_username: ozgur4864
categories: []
created_at: 2025-07-09T08:17:53.245Z
updated_at: 2025-07-09T08:17:53.245Z
url: https://n8n.io/workflows/5808
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

  1 — What Does It Do / Which Problem Does It Solve?

  This workflow turns Google Docs-based contract & form templates into ready-to-sign PDFs in minutes—all from a single chat flow.

  Automates repetitive document creation.** Instead of copying a rental, sales, or NDA template and filling it by hand every time, the bot asks for the required values and fills them in.
  Eliminates human error.** It lists every mandatory field so nothing is missed, and removes unnecessary clauses via conditional blocks.
  Speeds up approvals.** The final draft arrives as a direct PDF link—one click to send for signing.
  One template → unlimited variations.* Every new template you drop in Drive is auto-listed with *zero workflow edits—**it scales effortlessly.
  100 % no-code.** Runs on n8n + Google Apps Script—no extra backend, self-hosted or cloud.

  2 — How It Works (Detailed Flow)

  📝 Template Discovery
      
      📂 The TemplateList node scans the Drive folder you specify via the ?mode=meta endpoint and returns an id / title / desc list. The bot shows this list in chat.
      
  🎯 Selection & Metadata Fetch
      
      The user types a template name.
      
      🔍 GetMetaData opens the chosen Doc, extracts META_JSON, placeholders, and conditional blocks, then lists mandatory & optional fields.
      
  🗣 Data-Collection Loop
      The bot asks for every placeholder value.
      For each conditional block it asks 🟢 Yes / 🔴 No.
          
          Answers are accumulated in a data JSON object.
          
  ✅ Final Confirmation
      
      The bot summarizes the inputs → when the user clicks Confirm, the DocProcess sub-workflow starts.
      
  ⚙️ DocProcess Sub-Workflow
      
      
      | 🔧 Step | Node | Task |
      | --- | --- | --- |
      | 1 | User Choice Match Check | Verifies name–ID match; throws if wrong |
      | 2 | GetMetaData (renew) | Gets the latest placeholder list |
      | 3 | Validate JSON Format | Checks for missing / unknown fields |
      | 4 | CopyTemplate | Copies the Doc via Drive API |
      | 5 | FillDocument | Apps Script fills placeholders & removes blocks |
      | 6 | Generate PDF Link | Builds an export?format=pdf URL |
  📎 Delivery
      
      The master agent sends 🔗 Download PDF & ✏️ Open Google Doc links.
      
  🚫 Error Paths
      status:"ERROR", missing:[…] → bot lists missing fields and re-asks.
      unknown:[…] → template list is outdated; rerun TemplateList.
      Any Apps Script error → the returned message is shown verbatim in chat.

  3 — 🚀 Setup Steps (Full Checklist)

  &gt; Goal: Get a flawless PDF on the first run.
  &gt; 
  &gt; 
  &gt; Mentally tick the ☑️ in front of every line as you go.
  &gt; 

  ☁️ A. Google Drive Preparation

  | Step | Do This | Watch Out For |
  | --- | --- | --- |
  | 1 | Create a Templates/ folder → put every template Doc inside | Exactly one folder; no sub-folders |
  | 2 | Placeholders in every Doc are {{UPPER_CASE}} | No Turkish chars or spaces |
  | 3 | Wrap optional clauses with [[BLOCK_NAME:START]]…[[BLOCK_NAME:END]] | The START tag must have a blank line above |
  | 4 | Add a META_JSON block at the very end | Script deletes it automatically after fill |
  | 5 | Right-click Doc &gt; Details ▸ Description = 1-line human description | Shown by the bot in the list |
  | 6 | Create a second Generated/ folder (for copies) | Keeps Drive tidy |

  &gt; 🔑 Folder ID (long alphanumerical) = &lt;TEMPLATE_PARENT_ID&gt;
  &gt; 
  &gt; 
  &gt; We’ll paste this into the TemplateList node next.
  &gt; 

  Simple sample template → Template Link

  🛠 B. Import the Workflow into n8n

  Settings ▸ Import Workflow ▸ DocAgent.json


  If nodes look Broken afterwards → no community-node problem; you only need to select credentials.

  📑 C. Customize the TemplateList Node

  Open Template List node ⚙️ → replace
      
      '%3CYOUR_PARENT_ID%3E' in parents
      
      with the real folder ID in the URL.
      
  Right-click node &gt; Execute Node.
  Copy the entire JSON response.
  In the editor paste it into:
      DocAgent → System Prompt (top)
      User Choice Match Check → System Prompt (top)
          
          Save.
          

  &gt; ⚠️ Why manual? Caching the list saves LLM tokens. Whenever you add a template, rerun the node and update the prompts.
  &gt; 

  🔗 D. Deploy the Apps Script

  | Step | Screen | Note |
  | --- | --- | --- |
  | 1 | Open Gist files GetMetaData.gs + FillDocument.gs → File ▸ Make a copy | Both files may live in one project |
  | 2 | Project Settings &gt; enable Google Docs API ✔️ & Google Drive API ✔️ | Otherwise you’ll see 403 errors |
  | 3 | Deploy ▸ New deployment ▸ Web app |  |
  | • Execute as | Me |  |
  | • Who has access | Anyone |  |
  | 4 | On the consent screen allow scopes:• …/auth/documents• …/auth/drive | Click Advanced › Go if Google warns |
  | 5 | Copy the Web App URL (e.g. https://script.google.com/macros/s/ABC123/exec) | If this URL changes, update n8n |

  Apps Script source code → Notion Link

  🔧 E. Wire the Script URL in n8n

  | Node | Field | Action |
  | --- | --- | --- |
  | GetMetaData | URL | &lt;WEB_APP_URL&gt;?mode=meta&id={{ $json["id"] }} |
  | FillDocument | URL | &lt;WEB_APP_URL&gt; |

  &gt; 💡 Prefer using an .env file? Add GAS_WEBAPP_URL=… and reference it as {{ $env.GAS_WEBAPP_URL }}.
  &gt; 

  🔐 F. Add Credentials

  Google Drive OAuth2* → *Drive API (v3) Full Access
  Google Docs OAuth2** → same account
  LLM key** (OpenAI / Gemini)
  (Optional) Postgres Chat Memory credential for the corresponding node

  🧪 G. First Run (Smoke Test)

  Switch the workflow Active.
  In the chat panel type /start.
  Bot lists templates → pick one.
  Fill mandatory fields, optionally toggle blocks → Confirm.
  🔗 Download PDF link appears → ☑️ setup complete.

  ❌ H. Common Errors & Fixes

  | 🆘 Error | Likely Cause | Remedy |
  | --- | --- | --- |
  | 403: Apps Script permission denied | Web app access set to User | Redeploy as Anyone, re-authorize scopes |
  | placeholder validation failed | Missing required field | Provide the listed values → rerun DocProcess |
  | unknown placeholders: … | Template vs. agent mismatch | Check placeholder spelling (UPPER_CASE ASCII) |
  | Template ID not found | Prompt list is old | Rerun TemplateList → update both prompts |
  | Cannot find META_JSON | No meta block / wrong tag | Add [[META_JSON_START]] … [[META_JSON_END]], retry |

  ✅ Final Checklist

  [ ]  Drive folder structure & template rules ready
  [ ]  Workflow imported, folder ID set in node
  [ ]  TemplateList output pasted into both prompts
  [ ]  Apps Script deployed, URL set in nodes
  [ ]  OAuth credentials & LLM key configured
  [ ]  /start test passes, PDF link received

  🙋‍♂️ Need Help with Customizations?

  Reach out for consulting & support on LinkedIn: Özgür Karateke

  Full Documentation → Notion

  Simple sample template → Template Link

  Apps Script source code → Notion Link

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.httpRequestTool","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.memoryPostgresChat","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","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.switch","n8n-nodes-base.googleDrive","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.set","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set"]

workflow_json_compressed:
  [encoded data, 14060 characters]

metadata_json:
  {"categories":["automation","document generation","integration","chatbot"],"complexity":"complex","use_cases":["Generate contracts, NDAs, rental/sales forms from templates","Automate repetitive document creation and reduce human error","Interactive chat-driven data collection for templates","Conditional clause inclusion/exclusion in documents","Produce ready-to-sign PDF links for approvals"],"estimated_setup_minutes":60,"required_services":["n8n (self-hosted)","Google Drive (Drive API)","Google Docs (Docs API)","Google Apps Script (web app deployment)","LLM provider (Google Gemini or OpenAI)","OAuth2 credentials for Google services","(optional) Postgres for chat memory"],"key_features":["Discovers Drive templates and lists them in chat","Extracts META_JSON, placeholders and conditional blocks from Docs","Chat-driven collection of placeholder values and boolean blocks","Validates input JSON and reports missing/unknown fields","Copies templates, fills placeholders and removes conditional blocks via Apps Script','Generates export-format=pdf download links and Google Doc edit links','Error paths surfaced back to the chat for corrections','Zero-code flow for end users; scales to new templates without workflow edits"],"target_audience":["Automation engineers and n8n power users","Small businesses and legal/HR teams creating recurring contracts/forms","Sales and property managers generating agreements quickly','Developers/IT admins deploying self-hosted document automation solutions"]}


name: Automated Product Inquiry Responder with GPT-4 and Google Sheets
author_name: Dmytro
author_username: dima-ai
categories: []
created_at: 2025-07-09T08:18:47.539Z
updated_at: 2025-07-09T08:18:47.539Z
url: https://n8n.io/workflows/5809
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  AI-Powered Product Assistant for E-commerce

  Transform your online store customer service with an intelligent AI assistant that automatically processes customer inquiries, searches your product database, and provides personalized responses about product availability, pricing, and specifications. Perfect for shoe stores, fashion retailers, and any business with extensive product catalogs - this workflow eliminates manual customer service while increasing response speed and accuracy.

  How it works
  Customer sends product inquiry via webhook (Instagram DM, website chat, or messaging app)
  AI extracts key product details (brand, model, size, color) from natural language text
  System searches your Google Sheets product database with smart filtering
  AI generates friendly, personalized response with availability, pricing, and stock information
  Automatic response sent back to customer with product details or alternatives

  Screenshots:
  Customer inquiry: "Do you have Nike Air Max 40 size?"
  AI response: "Nike Air Max 90, size 40 - in stock 3 pieces, price 120$"

  Set up steps
  Prepare your product database - Create Google Sheets with columns: Brand, Model, Size, Color, Price, Quantity
  Configure AI settings - Connect OpenAI API for natural language processing  
  Set up webhook endpoint - Configure trigger for your messaging platform (Instagram, Telegram, website chat)
  Test with sample inquiries - Verify AI correctly parses requests and finds products
  Deploy and monitor - Launch your automated assistant and track performance

  Time investment: 30-45 minutes setup, works immediately with any product catalog up to 1000+ items.

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.webhook","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.respondToWebhook"]

workflow_json_compressed:
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metadata_json:
  {"categories":["e-commerce","customer support","automation","AI/ML","integration"],"complexity":"medium","use_cases":["Automated responses to customer product inquiries","Product availability and pricing lookups","Inventory-driven sales support (size/color/stock checks)","Suggesting alternatives when items are out of stock","Reducing manual customer service workload and response time"],"estimated_setup_minutes":40,"required_services":["OpenAI API (GPT-4)","Google Sheets (Google account / Sheets API)","Messaging platform webhook (Instagram DM, Telegram, website chat or custom webhook)","n8n instance or compatible workflow runner"],"key_features":["NLP extraction of product attributes (brand, model, size, color)","Smart filtering/search of Google Sheets product database","AI-generated friendly, personalized responses","Webhook trigger and automatic reply to messaging channels","Handles catalogs of 1000+ items with low latency"],"target_audience":["E-commerce store owners and retailers","Customer support teams and contact centers","Small businesses with product catalogs (fashion, shoes, accessories)"]}


name: Find leads on Google Maps and reach out automatically (GPT-4 + Airtable + Gmail)
author_name: Baptiste Fort
author_username: baptistefort
categories: []
created_at: 2025-07-09T08:48:36.876Z
updated_at: 2025-07-09T08:48:36.876Z
url: https://n8n.io/workflows/5811
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Who is it for?  
  This workflow is perfect for marketers, sales teams, agencies, and local businesses who want to save time by automating lead generation from Google Maps.  

  It’s ideal for real estate agencies, restaurants, service providers, and any local niche that needs a clean database of fresh contacts, including emails, websites, and phone numbers.  

  ✅ Prerequisites  

  Before starting, make sure you have:  

  Apify account** → to scrape Google Maps data  
  OpenAI API key** → for GPT-4 email extraction  
  Airtable account & base** → for structured lead storage  
  Gmail account with OAuth** → to send personalized outreach emails  

  Your Airtable base should have these columns:  

  | Title                   | Street                  | Website            | Phone Number    | Email                  | URL                  |
  |-------------------------|-------------------------|--------------------|-----------------|------------------------|----------------------|
  | Paris Real Estate Agency| 10 Rue de Rivoli, Paris | https://agency.fr  | +33 1 23 45 67  | contact@agency.fr      | maps.google.com/...  |

  🏡 Example Use Case  

  To keep things clear, we’ll use real estate agencies in Paris as an example.  
  But you can replace this with restaurants, plumbers, lawyers, or even hamster trainers (you never know).  

  🔄 How the workflow works  

  Scrape Google Maps leads with Apify  
  Clean & structure the data (name, phone, website)  
  Visit each website & extract emails with GPT-4  
  Save all leads into Airtable  
  Automatically send a personalized email via Gmail  

  This works for any industry, keyword, or location.  

  Step 1 – Scraping Google Maps with Apify



  Start simply:

  Open your n8n workflow and choose the trigger: “Execute Workflow” (manual trigger).

  Add an HTTP Request node (POST method).

  Now, head over to Apify Google Maps Extractor.

  Fill in the fields according to your needs:

  Keyword: e.g., "real estate agency" (or restaurant, plumber...)

  Location: "Paris, France"

  Number of results: 50 (or more)

  Optional: filters (with/without a website, by categories…)

  Click Run to test the scraper.

  Then click API → select API endpoints tab.

  Choose “Run Actor synchronously and get dataset items”.

  Copy the URL, go back to n8n, and paste it into your HTTP Request node (URL field).



  Then enable:

  Body Content Type → JSON

  Specify Body Using JSON

  Go back to Apify, click the JSON tab, copy everything, and paste it into the JSON field of your HTTP Request.

  If you now run your workflow, you'll get a nice structured table filled with Google Maps data. Pretty magical already—but we're just getting started!

  Step 2 – Cleaning Things Up (Edit Fields)




  Raw data is cool, but messy.

  Add an Edit Fields node next, using Manual Mapping mode.

  Here’s what you keep (copy-paste friendly):

  Title → {{ $json.title }}

  Address → {{ $json.address }}

  Website → {{ $json.website }}

  Phone → {{ $json.phone }}

  URL → {{ $json.url }}

  Now, you have a clean, readable table ready to use.

  Step 3 – Handling Each Contact Individually (Loop Over Items)



  Next, we process each contact one by one.

  Add the Loop Over Items node:

  Set Batch Size to 20 or more, depending on your needs.

  This node is simple but crucial to avoid traffic jams in the automation.

  Step 4 – Isolating Websites (Edit Fields again)



  Add another Edit Fields node (Manual Mapping).
  This time, keep just:

  Website → {{ $json.website }}

  We've isolated the websites for the next step: scraping them one by one.

  Step 5 – Scraping Each Website (HTTP Request)



  Now, we send our little robot to visit each website automatically.

  Add another HTTP Request node:

  Method: GET

  URL: {{ $json.website }} (from the previous node)

  This returns the raw HTML content of each site. Yes, it's ugly, but we won't handle it manually. We'll leave the next step to AI!

  Step 6 – Extracting Emails with ChatGPT



  We now use OpenAI (Message a Model) to politely ask GPT to extract only relevant emails.

  Configure as follows:

  Model: GPT-4-1-mini or higher

  Operation: Message a Model

  Simplify Output: ON

  Prompt to copy-paste:

  Look at this website content and extract only the email I can contact this business. In your output, provide only the email and nothing else. Ideally, this email should be of the business owner, so if you have 2 or more options, try for the most authoritative one. If you don't find any email, output 'Null'.

  Exemplary output of yours:
  name@examplewebsite.com

  {{ $json.data }}

  ChatGPT will kindly return the perfect email address (or 'Null' if none is found).

  Step 7 – Neatly Store Everything in Airtable



  Almost done! Add an Airtable → Create Record node.

  Fill your Airtable fields like this:

  | Airtable Field | Content                     | n8n Variable                           |
  | ------------------ | ------------------------------- | ------------------------------------------ |
  | Title              | Business name                   | {{ $('Edit Fields').item.json.Title }}   |
  | Street             | Full address                    | {{ $('Edit Fields').item.json.Address }} |
  | Website            | Website URL                     | {{ $('Edit Fields').item.json.Website }} |
  | Phone Number       | Phone number                    | {{ $('Edit Fields').item.json.Phone }}   |
  | Email              | Email retrieved by the AI agent | {{ $json.message.content }}              |
  | URL                | Google Maps link                | {{ $('Edit Fields').item.json.URL }}     |


  Now, you have a tidy Airtable database filled with fresh leads, ready for action.

  Step 8 – Automated Email via Gmail (The Final Touch)



  To finalize the workflow, add a Gmail → Send Email node after your Airtable node.

  Here’s how to configure this node using the data pulled directly from your Airtable base (from the previous step):

  Recipient (To): Retrieve the email stored in Airtable ({{ $json.fields.Email }}).

  Subject: Use the company name stored in Airtable ({{ $json.fields.Title }}) to personalize the subject line.

  Body: You can include several fields directly from Airtable, such as:

  Company name: 
  {{ $json.fields.Title }}

  Website URL: 
  {{ $json.fields.Website }}

  Phone number: 
  {{ $json.fields["Phone Number"] }}

  Link to the Google Maps listing: 
  {{ $json.fields.URL }}

  All of this data is available in Airtable because it was automatically inserted in the previous step (Step 7). 

  This ensures that each email sent is fully personalized and based on clear, reliable, and structured information.

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.manualTrigger","n8n-nodes-base.splitInBatches","n8n-nodes-base.set","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.airtable","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.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 6848 characters]

metadata_json:
  {"categories":["automation","lead generation","integration","data enrichment","sales outreach"],"complexity":"medium","use_cases":["Automated local lead generation from Google Maps","Building and maintaining a contact database (Airtable)","Extracting contact emails from websites using AI","Personalized email outreach at scale","Prospecting for real estate, restaurants, local services, agencies"],"estimated_setup_minutes":45,"required_services":["n8n","Apify (Google Maps Extractor actor)","OpenAI API (GPT-4)","Airtable account & base","Gmail account with OAuth"],"key_features":["Scrapes Google Maps listings via Apify","Cleans and maps fields in n8n","Batches processing with Loop/ splitInBatches","Visits websites and extracts emails using GPT-4","Creates records in Airtable automatically"],"target_audience":["Marketers","Sales teams / SDRs","Agencies (digital, lead gen, recruitment, etc.)    )"]}


name: Auto-Import Contacts from Google Sheets to MailChimp Subscriber Lists
author_name: Femi Ad
author_username: hgray
categories: []
created_at: 2025-07-09T09:03:06.948Z
updated_at: 2025-07-09T09:03:06.948Z
url: https://n8n.io/workflows/5812
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  Google Sheets to MailChimp Auto-Importer

  Overview
  This n8n workflow automatically imports contacts from Google Sheets into your MailChimp mailing list. Perfect for businesses collecting leads through Google Forms, event registrations, or maintaining contact lists in spreadsheets.

  Key Features
  📊 Bulk Import: Process entire Google Sheets at once
  🔄 Smart Name Parsing: Automatically splits full names into first and last names
  📱 Phone Number Support: Includes phone numbers as merge fields
  ⚡ Error Resilience: Continues processing even if individual contacts fail
  📝 Import Summary: Generates a summary of processed contacts

  Prerequisites
  Before using this workflow, ensure you have:
  An active n8n instance (self-hosted or cloud)
  A Google account with access to Google Sheets
  A MailChimp account with at least one audience/list created
  Basic understanding of n8n workflows

  Initial Setup

  Step 1: Import the Workflow
  Copy the workflow JSON
  In n8n, click "Import from File" or paste the JSON
  Save the workflow with a meaningful name

  Step 2: Configure Google Sheets Connection
  Click on the "Get Google Sheet Data" node
  Click on "Credential to connect with"
  Select "Create New" and choose "Google Sheets OAuth2"
  Follow the OAuth flow to authenticate your Google account
  Save the credentials

  Step 3: Configure MailChimp Connection
  Click on the "Add to MailChimp" node
  Click on "Credential to connect with"
  Select "Create New" and choose "MailChimp OAuth2" or "MailChimp API"
  For API method:
     Log into MailChimp
     Go to Account → Extras → API keys
     Generate a new API key
     Copy and paste it into n8n
  Save the credentials

  Step 4: Configure Your Specific Settings

  Google Sheets Settings:
  Open the "Get Google Sheet Data" node
  Replace YOUR_GOOGLE_SHEET_ID with your actual sheet ID
     Find this in your Google Sheets URL: https://docs.google.com/spreadsheets/d/[SHEET_ID]/edit
  Replace YOUR_SHEET_NAME with your worksheet name (e.g., "Sheet1" or "Form Responses 1")

  MailChimp Settings:
  Open the "Add to MailChimp" node
  Replace YOUR_MAILCHIMP_LIST_ID with your audience ID
     Find this in MailChimp: Audience → Settings → Audience name and defaults
  Verify the status is set to "subscribed"

  Google Sheets Format Requirements

  Your Google Sheet must have the following columns (exact names):
  Names**: Full name of the contact (e.g., "John Doe")
  Email address**: Valid email address
  Phone Number**: Contact phone number (optional)

  Example:
  | Names | Email address | Phone Number |
  |-------|--------------|--------------|
  | John Doe | john@example.com | +1234567890 |
  | Jane Smith | jane@example.com | +0987654321 |

  How to Use

  Manual Execution:
  Open the workflow in n8n
  Click "Execute Workflow"
  Monitor the execution progress
  Check the output of "Create Import Summary" for results

  Scheduling (Optional):
  To run this automatically:
  Replace the "Manual Trigger" node with a "Schedule Trigger" node
  Set your desired schedule (e.g., daily at 9 AM)
  Activate the workflow

  Customization Options

  Adding More Fields:
  To include additional fields like company name or address:
  Add columns to your Google Sheet
  Modify the "Edit Fields" node to include new fields
  Update the "Format Subscriber Data" code to map new fields
  Add corresponding merge fields in the MailChimp node

  Handling Duplicates:
  The workflow uses "continueRegularOutput" error handling, which means:
  Existing subscribers will be skipped
  New subscribers will be added
  The workflow continues processing

  Adding Email Notifications:
  To receive import summaries via email:
  Add a Gmail or Email node after "Create Import Summary"
  Configure with your email settings
  Use the import summary data in the email body

  Troubleshooting

  Common Issues:

  "Invalid API Key" (MailChimp)
     Verify your API key is correct
     Check that your MailChimp account is active

  "Sheet not found" (Google Sheets)
     Verify the sheet ID is correct
     Ensure the service account has access to the sheet

  "Email already exists" errors
     This is normal for existing subscribers
     The workflow will continue processing other contacts

  Missing data in MailChimp
     Check that column names match exactly (case-sensitive)
     Verify data exists in the Google Sheet

  Best Practices

  Test First: Always test with a small dataset first
  Backup Data: Export your MailChimp list before large imports
  Clean Data: Ensure email addresses are valid before importing
  Monitor Regularly: Check import summaries for any issues
  Respect Privacy: Only import contacts who have consented to receive emails

  Support
  For issues specific to:
  n8n platform: Visit n8n Community Forum
  Google Sheets API: Check Google Developers Documentation
  MailChimp API: See MailChimp API Documentation
  Need help customizing?
  Contact me for consulting and support or add me on LinkedIn - https://www.linkedin.com/in/femi-adedayo-h44/

  License
  This workflow template is provided free for personal and commercial use. Feel free to modify and share!

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.manualTrigger","n8n-nodes-base.code","n8n-nodes-base.mailchimp","n8n-nodes-base.set","n8n-nodes-base.googleSheets"]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","data processing"],"complexity":"medium","use_cases":["Import leads collected via Google Forms into MailChimp","Sync/maintain contact lists from Google Sheets to MailChimp","Process event registrations or spreadsheet-based signups","Automate scheduled mailing list imports and summaries","Handle bulk imports while skipping duplicates"],"estimated_setup_minutes":15,"required_services":["n8n instance","Google Sheets (Google account / OAuth access)","MailChimp (audience/list and API key or OAuth)"],"key_features":["Bulk import of entire Google Sheet","Smart full-name parsing into first/last name","Includes phone numbers as MailChimp merge fields","Error resilience — continues on individual failures","Creates an import summary report (optionally emailed)"],"target_audience":["Marketers","Sales teams / lead managers","Event organizers and operations staff\",\"Small business owners\",\"Automation/DevOps or integration engineers"]}


name: Automated Inventory Management with Airtable PO Creation & Supplier Emails
author_name: iamvaar
author_username: iamvaar
categories: []
created_at: 2025-07-09T09:45:50.624Z
updated_at: 2025-07-09T09:45:50.624Z
url: https://n8n.io/workflows/5815
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  In-depth description of this automation:

  This is a fully automated daily supply chain and procurement workflow that keeps product stock levels healthy and suppliers updated, by automatically generating and emailing purchase orders (POs) and syncing PO statuses in Airtable.

  📅 Daily triggers

  Two Schedule Trigger nodes run:

    One runs at midnight (00:00) to manage low stock and new purchase order creation.
    Another runs at 1:00 AM to process existing pending POs and email suppliers.

  🚦 Step-by-step breakdown

  1️⃣ Get Products with low stock

  Searches the “Products Table” in Airtable for items where {stock_level} &lt;= {reorder_threshold}.
  Detects products that need restocking.

  2️⃣ Get supplier details

  Fetches supplier data for each low-stock product using its supplier_id.

  3️⃣ Calculate Dynamic Reorder Quantity

  JS code calculates an optimal reorder quantity:

    Uses average_daily_sales × (lead_time × 1.5) × safety_margin (1.2)
    Adds extra buffer so the new order covers both immediate demand and next cycle.

  4️⃣ Search existing POs

  Looks in the “Purchase Orders” table for active POs (status Pending or Sent) matching each product.
  Prevents duplicate orders.

  5️⃣ Remove duplicate product orders

  JS node compares current low-stock products with existing POs.
  Filters out products already covered, so new POs are only created for truly uncovered products.

  6️⃣ Create new purchase orders

  For filtered products, creates new PO records in Airtable with:

    product_name
    product_id
    calculated reorder_qty
    supplier info and email
    initial status Pending

  📧 Process existing pending purchase orders and email suppliers

  7️⃣ Get Purchase Orders which are pending

  Searches Airtable for all POs with status Pending.

  8️⃣ Group products with suppliers

  JS code groups these POs by supplier_id.
  Builds a summary (total products, total quantity) and an HTML email with a styled table of items.

  9️⃣ Send PO emails to suppliers

  Uses Brevo (SendInBlue) to send emails.
  Subject and content include supplier-specific order details.

  🔄 Update PO statuses to Sent

  Extracts Airtable record IDs of the sent POs.
  Updates those POs in Airtable, changing status from Pending → Sent.

  📌 Summary

  ✅ Runs every day
  ✅ Dynamically calculates reorder needs
  ✅ Avoids duplicate purchase orders
  ✅ Automatically creates purchase orders in Airtable
  ✅ Groups & emails daily PO summaries to suppliers
  ✅ Updates PO status after sending email

  ⚙ Tables involved

  Products Table:** stores products, stock levels, reorder thresholds, average daily sales, supplier references.
  Suppliers Table:** stores supplier emails and metadata.
  Purchase Orders Table:** tracks product orders with supplier IDs, status, quantities, etc.

  This workflow makes daily procurement fully automated: detects risk of stockouts, creates POs smartly, keeps suppliers in sync by email, and updates order statuses in one closed loop — perfect for any small or mid-sized business using Airtable + N8N.

nodes_used:
  ["n8n-nodes-base.airtable","n8n-nodes-base.airtable","n8n-nodes-base.code","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.airtable","n8n-nodes-base.airtable","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.airtable","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.airtable","n8n-nodes-base.stickyNote","n8n-nodes-base.sendInBlue"]

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metadata_json:
  {"categories":["automation","integration","inventory management","procurement"],"complexity":"medium","use_cases":["Automated stock replenishment for small and mid-sized businesses","Daily purchase order creation and supplier notification","Preventing duplicate orders and reducing stockouts","Consolidating orders by supplier and sending summarized PO emails","Syncing PO lifecycle status between Airtable and suppliers"],"estimated_setup_minutes":60,"required_services":["Airtable","Brevo (SendinBlue)","n8n"],"key_features":["Daily scheduled triggers for PO creation and processing","Searches Airtable for low-stock products and existing POs","Dynamic reorder quantity calculation (avg sales × lead time × safety margin)","De-duplication logic to avoid creating redundant POs","Creates PO records in Airtable with supplier metadata and initial status 'Pending'​"],"target_audience":["Operations / Procurement managers","Inventory managers for SMBs and e-commerce","Developers / consultants implementing n8n automations for clients"]}


name: Build a Weekly AI Trend Alerter with arXiv and Weaviate
author_name: Mary Newhauser
author_username: maryn
categories: []
created_at: 2025-07-09T11:18:42.191Z
updated_at: 2025-07-09T11:18:42.191Z
url: https://n8n.io/workflows/5817
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  Build a Weekly AI Trend Alerter with arXiv and Weaviate
  Ditch the endless scroll for AI trends. Meet Archi, your personal AI research assistant that hits you up once a week with everyone you need to know. 🧑🏽‍🔬

  This workflow scrapes AI and machine learning article abstracts from arXiv, enriches them with topic categories using a LLM, and embeds them in a Weaviate vector store. The vector store is then used as a tool for agentic RAG to write a concise, easy-to-read summary of the week in AI research.

  The final output is a short, weekly email sent to the address of your choice that summarizes key AI research trends and future research directions, with links directly to the most interesting and impactful arXiv papers of the week.

  Who it's for
  This workflow is for anyone who can't keep up with all the latest AI advances. Coding skills are not required.

  How it works
  This is a contiguous workflow that can be summarized in two main parts: a data pipeline that fetches and embeds articles in Weaviate, and an agentic workflow that generates a weekly email summary.
  Part 1: Automatically fetch newly published articles on a weekly basis
  Fetch article abstracts (and metadata) from arXiv's free API
  Pre-process abstract data
  Enrich each article with a primary topic, secondary topics, and estimated potential impact of the research using a LLM
  Post-process data
  Insert data and embeddings into Weaviate
  Part 2: Use an AI Agent and Weaviate to generate a weekly summary email
  Add Weaviate as a Tool to an AI agent node
  Query Weaviate, agentically, to generate a report on the most important research trends of the week
  Post-process data
  Send the summary via email

  Prerequisites
  An existing Weaviate cluster. You can view instructions for setting up a local cluster with Docker here or a Weaviate Cloud cluster here.
  API keys to generate embeddings and power chat models. We use a combination of OpenRouter and OpenAI models. Feel free to switch out the models as you like.
  An email address with STMP privileges. This is the address the email will come from. In this demo we use a personal Gmail address. You can create a new credential to link a STMP Account using these instructions.
  Self-hosted n8n instance. See this video for how to get set up in just three minutes.

  How to run the workflow
  Go through the prerequisites, creating a Weaviate cluster (can be local or cloud), downloading self-hosted n8n, creating STMP privileges for your email account, and adding your API keys and other credentials.
  Select the embedding and chat models you'd like to use.
  Enter the email addresses you want to send the email from and to.
  Let it rip.

  Workflow output
  The output for this workflow is a weekly email that summarizes key research trends and future research directions based on AI and ML papers published on arXiv. 

  Here's an example of a summary email:

  Hey there,

  Here's a quick rundown of the key trends in Machine Learning research from the past week.

  *  Key Research Trends This Week*

  This week saw significant advancements in retrieval-augmented systems, foundation models for specialized domains, and techniques balancing efficiency with performance.

  Advanced RAG Architectures**: Researchers are developing sophisticated RAG frameworks that go beyond simple document retrieval, with  AdaPCR  introducing passage combination retrieval and  UrbanMind  proposing a framework for urban intelligence with multilevel optimization.
      
  Foundation Models for Tabular Data**: The  Real-TabPFN  shows that targeted continued pre-training on real-world datasets can significantly boost the performance of foundation models for tabular data, outperforming models trained on broader, potentially noisier datasets.
      
  Efficiency-Focused Techniques**: Researchers are developing resourceful methods that maintain performance without expensive computations, like  logit reweighting  for topic-focused summarization and  strategic querying  for privacy-preserving personalization.
      

  *  Future Research Directions*

  Based on current trends, we expect to see the following developments in the near future:

  Explainable RAG Systems**: Following the  source attribution  work in RAG systems, we can expect more research into making complex retrieval systems transparent and explainable for users.
      
  Cross-Domain and Cross-Modal Fusion**: The promising performance of vision-language and code-specialized LLMs in  retrieval tasks  points toward unified retrievers capable of handling text, code, images, and multimodal content.
      
  Data-Centric Synthetic Generation**: As shown by work on  synthetic relational tabular data, we'll likely see more sophisticated approaches to generating high-quality synthetic data for pre-training foundation models in specialized domains.
      

  This week highlights how researchers are making AI more efficient, explainable, and applicable to specialized domains. Look out for more developments in RAG systems, tabular foundation models, and privacy-preserving AI techniques in the coming weeks.

  Until next week,

  Archi  

  Want to make it better?
  Feel free to tweak, build on, or completely reconfigure this workflow. If you come up with something cool, let us know and we might just share it with our community! 💚

nodes_used:
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workflow_json_compressed:
  [encoded data, 16764 characters]

metadata_json:
  {"categories":["automation","integration","data processing","AI monitoring","knowledge management"],"complexity":"complex","use_cases":["Weekly AI research digests","Automated literature monitoring and curation","Trend detection and summarization","RAG-based agentic reporting","Email alerts and stakeholder updates"],"estimated_setup_minutes":90,"required_services":["Weaviate (self-hosted or cloud)","arXiv API","Embeddings & chat model provider (OpenAI, OpenRouter, or equivalent)","SMTP email provider (e.g., Gmail with SMTP credentials)","n8n self-hosted instance"],"key_features":["Automated weekly fetch of arXiv abstracts and metadata","LLM-based topic classification and impact estimation","Embedding generation and insertion into Weaviate vector store","Agentic RAG queries against Weaviate to synthesize trends","Automated generation and sending of concise weekly email summaries (SMTP)」「Configurable models, recipients, and scheduling"],"target_audience":["Researchers and academics","AI/ML practitioners and data scientists","Product managers and research leads tracking trends」「Non-technical users and community managers who want curated AI updates"]}


name: Automated Thai Content Creation & Publishing with Ollama, Gemini & Telegram
author_name: athipat
author_username: sirikaew
categories: []
created_at: 2025-07-09T11:34:23.019Z
updated_at: 2025-07-09T11:34:23.019Z
url: https://n8n.io/workflows/5818
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  Automated AI Content Publisher
  This n8n workflow is your all-in-one solution for automated content creation and publishing. It intelligently crafts unique articles in Thai, generates captivating AI images, and seamlessly publishes them to your website while notifying you via Telegram. Say goodbye to manual content pipelines and hello to effortless, AI-driven publishing.

  How It Works
  This workflow kicks off when new news data hits your designated Google Sheet, then it springs into action:

  Smart Image Selection: An AI analyzes your news content to decide if a general photorealistic image or a more artistic, risoprint-style AI image is the best fit.

  Article Generation: Another AI drafts a high-quality, long-form article in flawless Thai, adapting its format (listicle or analytical) to perfectly suit the topic.

  SEO & Marketing Boost: A specialized AI then optimizes your content by generating concise titles, engaging excerpts, and relevant tags in both Thai and English. It also creates the perfect prompts for image generation.

  AI Image Creation: Leveraging Google Gemini, the workflow generates stunning visuals, producing either photorealistic or artistic risoprint-style images based on the AI's prompts.

  Seamless Publishing: Your newly created article, complete with its AI-generated image and all metadata, is automatically posted to your website.

  Instant Notifications: You'll get a quick ping on Telegram with a summary of the new post, so you're always in the loop.

  Setup
  To get this workflow up and running, you'll need to configure a few things:

  Google Sheet: Link your Google Sheet and specify the sheet name and the column containing your news description.

  Ollama: Set up your Ollama API credentials to connect the workflow to your local or remote Ollama instance.

  Google Gemini API: Provide your Google Gemini API key to enable AI image generation.

  Website API: Create a credential for your website, including its posting URL, an API Key for authentication, and your desired user_id and username for posts. You can also add optional fields like bgColor, LinkAff, postType, and embeddedContent here.

  Telegram: Set up your Telegram API credential with your bot token and the chatId where you want to receive notifications.

nodes_used:
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metadata_json:
  {"categories":["automation","content_creation","ai_image_generation","publishing","seo_integration"],"complexity":"complex","use_cases":["Automated blog/article publishing","Thai-language long-form content generation","AI-driven image creation for posts","Automated SEO metadata and tags generation","Content pipeline notifications via Telegram"],"estimated_setup_minutes":60,"required_services":["Google Sheets","Ollama (local or remote)","Google Gemini API (Google Cloud)","Website/CMS HTTP API (posting endpoint and API key)","Telegram Bot API"],"key_features":["Triggers from Google Sheets","AI decides image style (photorealistic vs risoprint)","Long-form article generation in Thai","SEO optimization: titles, excerpts, tags in Thai and English","Generates image prompts and creates images via Google Gemini and Ollama where applicable (convertToFile nodes) or AI/ML nodes used for processing)"],"target_audience":["content teams and publishers (Thai market)","digital marketers and SEO specialists","bloggers and website owners who want automated publishing workflows, developers/automation engineers responsible for site integrations"]}


name: 🤖 Build an Interactive AI Agent with Chat Interface and Multiple Tools
author_name: Lucas Peyrin
author_username: lucaspeyrin
categories: []
created_at: 2025-07-09T12:12:39.907Z
updated_at: 2025-07-09T12:12:39.907Z
url: https://n8n.io/workflows/5819
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  How it works

  This template is a complete, hands-on tutorial that lets you build and interact with your very first AI Agent.

  Think of an AI Agent as a standard AI chatbot with superpowers. The agent doesn't just talk; it can use tools to perform actions and find information in real-time. This workflow is designed to show you exactly how that works.

  The Chat Interface (Chat Trigger): This is your window to the agent. It's a fully styled, public-facing chat window where you can have a conversation.
  The Brain (AI Agent Node): This is the core of the operation. It takes your message, understands your intent, and intelligently decides which "superpower" (or tool) it needs to use to answer your request. The agent's personality and instructions are defined in its extensive system prompt.
  The Tools (Tool Nodes): These are the agent's superpowers. We've included a variety of useful and fun tools to showcase its capabilities:
      Get a random joke.
      Search Wikipedia for a summary of any topic.
      Calculate a future date.
      Generate a secure password.
      Calculate a monthly loan payment.
      Fetch the latest articles from the n8n blog.
  The Memory (Memory Node): This gives the agent a short-term memory, allowing it to remember the last few messages in your conversation for better context.


  When you send a message, the agent's brain analyzes it, picks the right tool for the job, executes it, and then formulates a helpful response based on the tool's output.

  Set up steps

  Setup time: ~3 minutes

  This template is nearly ready to go out of the box. You just need to provide the AI's "brain."

  Configure Credentials: This workflow requires an API key for an AI model. Make sure you have credentials set up in your n8n instance for either Google AI (Gemini) or OpenAI.
  Choose Your AI Brain (LLM):
      By default, the workflow uses the Google Gemini node. If you have Google AI credentials, you're all set!
      If you prefer to use OpenAI, simply disable the Gemini node and enable the OpenAI node. You only need one active LLM node. Make sure it is connected to the Agent parent node.
  Explore the Tools: Take a moment to look at the different tool nodes connected to the Your First AI Agent node. This is where the agent gets its abilities! You can add, remove, or modify these to create your own custom agent.
  Activate and Test!
      Activate the workflow.
      Open the public URL for the Example Chat Window node (you can copy it from the node's panel).
      Start chatting! Try asking it things like:
          "Tell me a joke."
          "What is n8n?"
          "Generate a 16-character password for me."
          "What are the latest posts on the n8n blog?"
          "What is the monthly payment for a $300,000 loan at 5% interest over 30 years?"

nodes_used:
  ["@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.httpRequestTool","n8n-nodes-base.dateTimeTool","@n8n/n8n-nodes-langchain.toolWikipedia","n8n-nodes-base.cryptoTool","@n8n/n8n-nodes-langchain.toolCode","n8n-nodes-base.rssFeedReadTool","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, 10952 characters]

metadata_json:
  {"categories":["automation","AI agent","chatbot","integration"],"complexity":"medium","use_cases":["Build an interactive tool-enabled AI assistant","Prototyping/customizing conversational agents","Knowledge lookup and summarization (Wikipedia, blog)","Simple task automation (date calc, password, loan payment)","Public chat demos or proof-of-concept for product teams"],"estimated_setup_minutes":300,"required_services":["n8n instance (self-hosted or cloud)","Google AI (Gemini) API key or OpenAI API key","Public HTTP access for chat window and web-based tools (Wikipedia, n8n blog)"],"key_features":["Public-facing styled chat interface (Chat Trigger)","Agent node that selects and orchestrates tool use via an LLM","Multiple tool nodes (joke, Wikipedia summary, date calculator, password generator, loan calculator, fetch n8n blog)","Short-term memory buffer to preserve recent conversation context","Easy swap between Google Gemini and OpenAI LLM nodes"],"target_audience":["Developers and no-code builders","Product teams prototyping conversational features","Support teams creating assistant workflows','Educators and demo authors"]}


name: Automatic Gmail Categorization and Labeling with AI
author_name: Matt Chong | n8n Creator
author_username: mattxchong
categories: []
created_at: 2025-07-09T12:31:25.807Z
updated_at: 2025-07-09T12:31:25.807Z
url: https://n8n.io/workflows/5820
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

  Who is this for?

  If your inbox is full of unread emails, this workflow is for you.  
  Instead of reading through them one by one, let AI do the sorting.  
  It reads your emails and flags only what needs action.

  What does it solve?

  This workflow reads your unread Gmail emails and uses AI to decide what’s important — and what’s not.
  It labels emails that need your attention, identifies receipts, and trashes everything else.
  No more manual reading. Just an inbox that uses AI to take care of itself.

  How it works

  Every hour, the workflow runs automatically.
  It searches for unread emails in your Gmail inbox.
  For each email:
     It extracts the content and sends it to OpenAI.
  The AI returns one of four labels: Action, Receipt, Informational or Spam.
  Based on the label:
     Emails are marked with the appropriate label.
     Or moved to trash it is spam.
  It marks the email as read once processed.

  How to set up?

  Connect these services in your n8n credentials:
     Gmail (OAuth2)
     OpenAI (API key)
  Create the Gmail labels:
     In your Gmail account, create these labels exactly as written:  
       Action, Receipt, and Informational  
     The workflow will apply these labels based on AI classification.

  How to customize this workflow to your needs

  Change the AI prompt to detect more types of emails like Meeting or Newsletter.
  Add more branches to the Switch node to apply custom logic.
  Change the schedule to fit your workflow.
  By default, it runs every hour, but you can update this in the Schedule Trigger node.

nodes_used:
  ["n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.gmail","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","email management","AI integration"],"complexity":"medium","use_cases":["Automated email triage and prioritization","Receipt detection and organization","Spam filtering and inbox decluttering","Applying Gmail labels based on AI classification","Reducing manual email reading for busy inboxes"],"estimated_setup_minutes":15,"required_services":["Gmail (OAuth2) account","OpenAI (API key)","Self-hosted n8n (community nodes compatible)"],"key_features":["Hourly scheduled scan of unread Gmail messages","AI classification into Action, Receipt, Informational, or Spam","Applies Gmail labels or moves spam to trash","Marks processed emails as read","Customizable AI prompt and Switch-node branching"],"target_audience":["Busy professionals and knowledge workers","Small business owners and admins","n8n self-hosted users who use community nodes or need advanced customization"]}


name: Build a Scalable AI Chatbot with GPT-4 and Pipedream: Calendly, Gmail Integration
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-07-09T13:49:54.152Z
updated_at: 2025-07-09T13:49:54.152Z
url: https://n8n.io/workflows/5821
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

  This n8n workflow integrates the powerful Pipedream MCP server with AI capabilities to create a smart, extensible assistant that can interact with over 2,700 APIs and 10,000+ tools — all within a secure and modular structure.



  This setup seamlessly integrates Pipedream's MCP server with n8n, enabling your AI assistant to leverage thousands of APIs and tools securely.

  Benefits

  Massive Tool Access**: Instantly connect 2,700+ APIs using Pipedream MCP tools — from productivity apps to custom APIs — with zero-code integration.
  Dynamic AI Agent**: The use of a LangChain agent allows for flexible tool execution and contextual conversations, powered by GPT.
  Easy Customization**: Simply copy your MCP tool URL into the respective sseEndpoint field to extend the agent’s capabilities.
  Scalable and Modular**: Add or remove tools (like Slack, Notion, Stripe, etc.) without altering the core logic.
  Secure and Revocable**: Credentials and API access can be managed directly via Pipedream’s MCP dashboard.

  How It Works  
  Chat Trigger: The workflow begins when a chat message is received via the When chat message received node, which acts as the entry point.  
  AI Agent Processing: The message is passed to the AI Agent node, which orchestrates the interaction using the connected tools and memory.  
  Language Model: The OpenAI Chat Model (GPT-4.1-mini) processes the user's input and generates responses or actions.  
  Memory: The Simple Memory node retains context from the conversation to enable coherent multi-turn interactions.  
  Tool Integration:  
     The Calendly and Gmail nodes (connected via Pipedream's MCP server) allow the AI to perform actions like scheduling events or sending emails. These tools use SSE (Server-Sent Events) endpoints provided by Pipedream.  
  Response: The AI Agent combines the model's output and tool responses to deliver a final reply to the user.  

  Set Up Steps  
  Sign Up for Pipedream:  
     Create an account on and set up your MCP server.  
  Configure MCP Tools:  
     Connect your accounts (e.g., Calendly, Gmail) in Pipedream and obtain the SSE endpoints for each tool (e.g., https://mcp.pipedream.net/xxx/calendly_v2).  
  Update n8n Nodes:  
     Replace the placeholder SSE endpoints in the Calendly and Gmail nodes with your Pipedream MCP URLs.  
  OpenAI Credentials:  
     Ensure the OpenAI Chat Model node has valid API credentials (configured under "OpenAi account").  
  Activate Workflow:  
     Enable the When chat message received node (currently disabled) and deploy the workflow.  

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

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.mcpClientTool","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.mcpClientTool","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","AI","chatbot"],"complexity":"complex","use_cases":["Build a multi-turn AI chatbot/assistant","Automate scheduling via Calendly","Send transactional or follow-up emails via Gmail","Extend assistant capabilities by connecting thousands of APIs/tools","Create modular, revocable API integrations for secure agent actions"],"estimated_setup_minutes":45,"required_services":["n8n (self-hosted with community nodes enabled)","Pipedream MCP server (MCP tools + SSE endpoints)","OpenAI (GPT-4 / GPT-4.1-mini) API credentials","Calendly account (connected via Pipedream)","Gmail account (connected via Pipedream)"],"key_features":["LangChain-style AI agent that orchestrates tool calls","Access to 2,700+ APIs and 10,000+ tools via Pipedream MCP","Server-Sent Events (SSE) endpoints for secure tool execution","Conversation memory (Simple Memory node) for coherent multi-turn chats","Prebuilt integrations for Calendly and Gmail actions (scheduling, emailing)"],"target_audience":["developers/engineers building conversational automation","automation architects and integrators","product teams prototyping AI assistants with external tooling access"]}


name: Generate Cold Emails & Sales Letters with OpenAI GPT & Google Docs via Chat
author_name: Yar Malik (Asfandyar)
author_username: yar
categories: []
created_at: 2025-07-09T19:57:09.683Z
updated_at: 2025-07-09T19:57:09.683Z
url: https://n8n.io/workflows/5828
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  How it works
  Trigger: Listens for an incoming chat message
  Copy Assistant: Feeds the message (plus memory) into an OpenAI Chat Model and exposes two “tools”

  Cold Email Writer Tool


  Sales Letter Tool• 

  Tool execution: Depending on the user’s intent, the appropriate tool generates the copy
  • Save output: Writes the generated email or sales letter into your target document via the Update a document node

  Set up steps
  • Configure your OpenAI Chat Model credentials in n8n (no hard-coded keys!)
  • Add and authenticate the Simple Memory credential (to keep context across messages)
  • Create Google Docs (or MS Word) credentials for the Update a document node
  • Ensure your Chat trigger is pointing at your incoming-message endpoint
  • Mandatory: Drop sticky-note annotations on each tool node explaining where to enter API keys and how to tweak prompts

  Once everything’s wired up, send a test chat message like “Write me a cold email for a fintech startup” and watch the workflow spin up a polished draft in your document.

  How to use

  Import the workflow JSON into n8n.

  Configure your Chat trigger (webhook or form) to receive incoming messages.

  Send a chat prompt like:

  “Write me a cold email for a B2B SaaS offering.”

  The “Copy Assistant” custom GPT picks the right tool (Cold Email or Sales Letter).

  Generated copy is written directly into your linked Google Doc or Word document.

  Requirements
  OpenAI API Key (with Chat Completions & Custom GPTs enabled)

  Custom Assistant created in your ChatGPT dashboard (Assistant ID pasted into the Chat Model node)

  n8n instance (Cloud or self-hosted) with credentials set up for:

  Simple Memory (to persist context)

  Google Docs or Microsoft Word (for document output)

  Customising this workflow
  Tweak system and user prompts inside the Copy Assistant node to fit your brand voice.

  Swap in Slack, Teams or email nodes instead of a document writer to deliver copy where you need it.

  Add or remove tools (e.g., “Follow-up Email Writer”) by duplicating the existing tool pattern.

  Use sticky-note annotations on every node to explain where to enter API keys, Assistant IDs, or prompt tweaks.

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.googleDocs","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","content generation","sales enablement","integration"],"complexity":"medium","use_cases":["Generate cold outreach emails","Draft long-form sales letters","Automate copywriting from chat prompts","Persist conversation context for iterative refinement","Save generated copy to Google Docs or Word for collaboration"],"estimated_setup_minutes":30,"required_services":["OpenAI (Chat Completions + Custom GPT / Assistant ID)","n8n (Cloud or self-hosted) with Chat trigger","Simple Memory credential in n8n","Google Docs or Microsoft Word API / credentials"],"key_features":["Custom Chat Assistant routes user intent to specific tools (Cold Email or Sales Letter)","Uses OpenAI chat model (Custom GPT) for copy generation","Persists context via Simple Memory for follow-ups","Writes output directly into Google Docs or Word via Update a document node","Configurable prompts and assistant behavior for brand voice"],"target_audience":["sales reps","marketers","founders / startups doing outreach at scale"]}


name: Qualify & Reach Out to B2B Leads with Groq AI, Apollo, Gmail & Sheets
author_name: VKAPS IT
author_username: solutions
categories: []
created_at: 2025-07-10T07:08:32.442Z
updated_at: 2025-07-10T07:08:32.442Z
url: https://n8n.io/workflows/5832
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

  🎯 How it works
  This workflow captures new lead information from a web form, enriches it with Apollo.io data, qualifies the lead using AI, and—if the lead is strong—automatically sends a personalized outreach email via Gmail and logs the result in Google Sheets.

  🛠️ Key Features
  📩 Lead form capture with validation

  🔍 Enrichment via Apollo API

  🤖 Lead scoring using AI (LangChain + Groq)

  📧 Dynamic email generation & sending via Gmail

  📊 Logging leads with job title & org into Google Sheets

  ✅ Conditional email sending (score ≥ 6 only)


  🧪 Set up steps
  Estimated time: 15–20 minutes

  Add your Apollo API Key to the HTTP Header credential (never hardcode!)

  Connect your Gmail account for sending emails

  Connect your Google Sheets account and set up the correct spreadsheet & sheet name

  Enable LangChain/Groq credentials for lead scoring and AI-generated emails

  Update the form endpoint to your live webhook if needed

  📌 Sticky Notes
  Add the following mandatory sticky notes inside your workflow:

  FormTrigger Node:
  "Collects lead info via form. Ensure your form is connected to this endpoint."

  HTTP Request Node:
  "Enrich lead using Apollo.io API. Add your API key via header-based authentication."

  AI Agent (Lead Score):
  "Scores lead from 1-10 based on job title and industry match. Only leads with score ≥ 6 proceed."

  AI Agent (Email Composer):
  "Generates a concise, polite email using lead’s job title & company. Modify tone if needed."

  Google Sheets Append:
  "Logs enriched lead with job title, org, and LinkedIn URL. Customize sheet structure if needed."

  Gmail Node:
  "Sends personalized outreach email if lead passes score threshold. Uses AI-generated content."

  💸 Free or Paid?
  Free – No paid API services are required (Apollo has a free tier).

nodes_used:
  ["n8n-nodes-base.formTrigger","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.gmailTool","@n8n/n8n-nodes-langchain.lmChatGroq","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.lmChatGroq","n8n-nodes-base.webhook","n8n-nodes-base.googleSheetsTrigger"]

workflow_json_compressed:
  [encoded data, 4552 characters]

metadata_json:
  {"categories":["automation","sales","integration","lead-generation","ai-enabled"],"complexity":"medium","use_cases":["Qualify inbound B2B leads","Automated personalized outreach","Lead enrichment with third‑party data","Logging leads into a spreadsheet/CRM","Reduce manual SDR work via AI scoring"],"estimated_setup_minutes":20,"required_services":["Apollo.io API","Gmail (Google account) for sending email","Google Sheets (Google account) for logging","Groq AI / LangChain credentials (AI scoring & email generation)","Web form provider or webhook endpoint","Self-hosted n8n (community nodes for Groq/agents)"],"key_features":["Web form capture with validation","Apollo enrichment (company/job data)","AI lead scoring (1–10) using LangChain + Groq","Conditional send: only score ≥ 6 triggers outreach","AI-generated personalized email content via Groq agent + Gmail send node"],"target_audience":["SDRs and sales teams","Growth marketers","Startup founders / small business owners doing outreach automation"]}


name: Automate Instagram Carousel Posts with Google Sheets, Drive & Cloudinary
author_name: Henry
author_username: henry
categories: []
created_at: 2025-07-10T08:29:17.367Z
updated_at: 2025-07-10T08:29:17.367Z
url: https://n8n.io/workflows/5833
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  Who is this for?

  This workflow is ideal for social media managers, content creators, marketers, and small businesses who want to automate Instagram Carousel posts using Google Sheets and Google Drive. It is also suitable for anyone looking to streamline repetitive Instagram publishing tasks with n8n, Cloudinary, and the Instagram Graph API.

  What problem is this workflow solving? / Use case

  Managing and publishing Instagram Carousel posts manually can be time-consuming, especially when handling multiple accounts or campaigns. This workflow solves that by automatically fetching scheduled posts from Google Sheets, uploading images from Google Drive to Cloudinary, and publishing them to Instagram, saving time and reducing the risk of errors.

  What this workflow does

  This n8n workflow checks a Google Sheet every 5 minutes for new Carousel posts marked as "ToDo." When found, it uploads images from a specified Google Drive folder to Cloudinary, prepares the media on Instagram using the Graph API, and publishes the Carousel post with the given caption.

  Setup

  Prepare a Google Sheet to track posts and image folder URLs.
   Example : https://docs.google.com/spreadsheets/d/1WEUHeQXFMYsWVAW3DykWwpANxxD3DxH-S6c0i06dW1g/edit?usp=sharing
  Upload post images to a dedicated Google Drive folder.
  Set up a Cloudinary account and gather API credentials.
  Obtain Instagram access_token and ig_business_id for API publishing.
  Configure the n8n workflow with required credentials and your custom intervals.

  How to customize this workflow to your needs

  Adjust the schedule trigger interval to fit your publishing frequency.
  Expand the Google Sheet with additional metadata as required.
  Modify the filter logic to support different content types or statuses.
  Add extra automation steps, such as sending notifications after publishing.

nodes_used:
  ["n8n-nodes-base.googleDrive","n8n-nodes-base.googleSheets","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.aggregate","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets"]

workflow_json_compressed:
  [encoded data, 4756 characters]

metadata_json:
  {"categories":["automation","integration","social media"],"complexity":"medium","use_cases":["Automated scheduling and publishing of Instagram Carousel posts","Batch uploading images from Google Drive and hosting on Cloudinary","Centralized content scheduling using Google Sheets","Reducing manual posting errors and saving time for social teams"],"estimated_setup_minutes":45,"required_services":["n8n","Google Sheets API / Google account","Google Drive API / Google account","Cloudinary account and API credentials","Instagram Graph API (Facebook app) — access_token and ig_business_id"],"key_features":["Polls Google Sheets on a schedule to find posts marked 'ToDo'","Uploads images from Google Drive to Cloudinary","Prepares and publishes Instagram Carousel posts via the Instagram Graph API","Configurable schedule interval and sheet-driven post metadata","Extensible filter logic and post-processing (e.g., notifications)"],"target_audience":["Social media managers","Content creators","Marketers and small business owners handling Instagram content workflows with n8n"]}


name: Create Low-Cost AI Videos with Veo3 Fast and Upload to YouTube & TikTok
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-07-10T08:53:57.003Z
updated_at: 2025-07-10T08:53:57.003Z
url: https://n8n.io/workflows/5835
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-30 08:33:37
description:
  This workflow allows users to generate AI videos using the cheaper model Google Veo3 Fast, save them to Google Drive, generate optimized titles with GPT-4o, and automatically upload them to YouTube and TikTok with Upload-Post. The entire process is triggered from a Google Sheet that acts as the central interface for input and output.

  IT automates video creation, uploading, and tracking, ensuring seamless integration between Google Sheets, Google Drive, Google Veo3 Fast, TikTok and YouTube.

  Benefits of this Workflow

  💡 No Code Interface**: Trigger and control the video production pipeline from a simple Google Sheet.
  ⚙️ Full Automation**: Once set up, the entire video generation and publishing process runs hands-free.
  🧠 AI-Powered Creativity**:

    Generates engaging YouTube and TikTok titles using GPT-4o.
    Leverages advanced generative video AI from Google Veo3.
  📁 Cloud Storage & Backup**: Stores all generated videos on Google Drive for safekeeping.
  📈 YouTube Ready**: Automatically uploads to YouTube with correct metadata, saving time and boosting visibility.
  📈 TikTok Ready**: Automatically uploads to TikTok with correct metadata, saving time and boosting visibility.
  🧪 Scalable**: Designed to process multiple video prompts by looping through new entries in Google Sheets.
  🔒 API-First**: Utilizes secure API-based communication for all services.

  How It Works  
  Trigger: The workflow can be started manually ("When clicking ‘Test workflow’") or scheduled ("Schedule Trigger") to run at regular intervals (e.g., every 5 minutes).  
  Fetch Data: The "Get new video" node retrieves unfilled video requests from a Google Sheet (rows where the "VIDEO" column is empty).  
  Video Creation:  
     The "Set data" node formats the prompt and duration from the Google Sheet.  
     The "Create Video" node sends a request to the Fal.run API (Google Veo3 Fast) to generate a video based on the prompt.  
  Status Check:  
     The "Wait 60 sec." node pauses execution for 60 seconds.  
     The "Get status" node checks the video generation status. If the status is "COMPLETED," the workflow proceeds; otherwise, it waits again.  
  Video Processing:  
     The "Get Url Video" node fetches the video URL.  
     The "Generate title" node uses OpenAI (GPT-4.1) to create an SEO-optimized YouTube and TikTok title.  
     The "Get File Video" node downloads the video file.  
  Upload & Update:  
     The "Upload Video" node saves the video to Google Drive.  
     The "HTTP Request" node uploads the video to YouTube via the Upload-Post API.  
     The "HTTP Request" node uploads the video to TikTok via the Upload-Post API.  
     The "Update Youtube URL" and "Update result" nodes update the Google Sheet with the video URL and YouTube link.  

  Set Up Steps  
  Google Sheet Setup:  
     Create a Google Sheet with columns: PROMPT, DURATION, VIDEO, and YOUTUBE_URL.  
     Share the Sheet link in the "Get new video" node.  

  API Keys:  
     Obtain a Fal.run API key (for Veo3) and set it in the "Create Video" node (Header: Authorization: Key YOURAPIKEY).  
     Get an Upload-Post API key (for YouTube uploads) and configure the "HTTP Request" node (Header: Authorization: Apikey YOUR_API_KEY).  
     Get an Upload-Post API key (for TikTok uploads) and configure the "HTTP Request" node (Header: Authorization: Apikey YOUR_API_KEY).  

  YouTube Upload Configuration:  
     Replace YOUR_USERNAME in the "HTTP Request" node with your Upload-Post profile name.  

  Schedule Trigger:  
     Configure the "Schedule Trigger" node to run periodically (e.g., every 5 minutes).  

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

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","content creation","social media","AI/ML"],"complexity":"complex","use_cases":["Low-cost AI video generation using Google Veo3 Fast","Automated upload of videos to YouTube and TikTok","Bulk content production driven from a Google Sheet","Generate SEO-optimized titles with GPT-4o","Track upload status and metadata back in Google Sheets"],"estimated_setup_minutes":60,"required_services":["n8n instance","Google Sheets","Google Drive","Google Cloud access to Veo3 Fast (Veo3) model","OpenAI GPT-4o (or equivalent LLM) for title generation","YouTube Data API / Google account with YouTube access","TikTok Upload-Post API (TikTok account)"],"key_features":["Generate videos with a low-cost Veo3 Fast model","Save and organize video files in Google Drive","Automatically generate optimized titles via GPT-4o","Automated uploads to YouTube and TikTok","Google Sheets as central trigger and status dashboard for inputs/outputs of each job(scheduled or manual triggers supported)"],"target_audience":["Content creators","Social media managers","Marketers and growth teams"]}


name: Create AI-Summarized Email Digests from Gmail Labels with OpenAI O4-Mini
author_name: German Velibekov
author_username: germanv
categories: []
created_at: 2025-07-10T12:10:09.259Z
updated_at: 2025-07-10T12:10:09.259Z
url: https://n8n.io/workflows/5839
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

  Transform email overload into actionable insights with this automated daily digest workflow that intelligently summarizes categorized emails using AI.

  Who's it for

  This workflow is perfect for busy professionals, content creators, and newsletter subscribers who need to stay informed without spending hours reading through multiple emails. Whether you're tracking industry news, monitoring competitor updates, or managing content subscriptions, this automation helps you extract key insights efficiently.

  How it works

  The workflow runs automatically each morning at 9 AM, fetching emails from a specific Gmail label received in the last 24 hours. Each email is processed through OpenAI's language model using LangChain to create concise, readable summaries that preserve important links and formatting. All summaries are then combined into a single, well-formatted digest email and sent to your inbox, replacing dozens of individual emails with one comprehensive overview.

  How to set up

  Create a Gmail label for emails you want summarized (e.g., "Tech News", "Industry Updates")
  Configure credentials for both Gmail OAuth2 and OpenAI API in their respective nodes
  Update the Gmail label ID in the "Get mails (last 24h)" node with your specific label
  Set your email address in the "Send Digested mail" node
  Adjust the schedule in the Schedule Trigger if you prefer a different time than 9 AM
  Test the workflow with a few labeled emails to ensure proper formatting

  Requirements

  Gmail account with OAuth2 authentication configured
  OpenAI API account and valid API key
  At least one Gmail label set up for email categorization
  Basic understanding of n8n workflow execution

  How to customize the workflow

  Change summarization style: Modify the prompt in the "Summarization Mails" node to adjust tone, length, or format of summaries. You can make summaries more technical, casual, or focus on specific aspects like action items.

  Adjust time range: Change the receivedAfter parameter in the Gmail node to fetch emails from different time periods (last 2 days, last week, etc.).

  Multiple labels: Duplicate the Gmail retrieval section to process multiple labels and combine them into categories within your digest.

  Add filtering: Insert additional conditions to filter emails by sender, subject keywords, or other criteria before summarization.

  Custom formatting: Modify the "Combine Subject and Body" code node to change the HTML structure, add styling, or include additional metadata like email timestamps or priority indicators.

nodes_used:
  ["n8n-nodes-base.if","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","n8n-nodes-base.noOp","n8n-nodes-base.set","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.chainSummarization","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.scheduleTrigger","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, 5936 characters]

metadata_json:
  {"categories":["automation","integration","AI","productivity","email management"],"complexity":"medium","use_cases":["Daily email digests","Monitoring industry news or competitor updates","Content curation and newsletter summarization","Inbox triage and prioritization","Generating concise summaries for research or briefing emails"],"estimated_setup_minutes":20,"required_services":["Gmail account with OAuth2 (read+send)","OpenAI API (O4-Mini)","n8n self-hosted instance (required for community nodes)","LangChain integration via n8n community nodes"],"key_features":["Scheduled daily trigger (configurable time)","Fetch emails by Gmail label and time window","AI summarization using OpenAI (via LangChain)","Combine multiple summaries into a single HTML digest","Send combined digest via Gmail node to your inbox/send list"],"target_audience":["busy professionals","content creators and curators","newsletter subscribers and marketers monitoring topics or competitors 84; analysts and researchers needing condensed email updates 84; n8n users with self-hosted setups (operators/developers)"]}


name: Automate LinkedIn Post Creation with Image using Google Gemini & DALL-E
author_name: Intuz
author_username: intuz
categories: []
created_at: 2025-07-10T12:25:46.184Z
updated_at: 2025-07-10T12:25:46.184Z
url: https://n8n.io/workflows/5840
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  This n8n template from Intuz delivers a complete AI-powered solution for automated LinkedIn posts, including unique content, custom images, and optimized hashtags.

  Use cases are many: Generate and schedule tailored LinkedIn content for different use-cases. By feeding the AI specific prompts, you can create specific post depending upon the topics and visuals to maintain a consistency yet and an online presence.

  How it works

  Maintaining a consistent and engaging presence on LinkedIn can be time-consuming, requiring constant ideation, content creation, and manual posting. This workflow takes that burden off your shoulders, delivering a fully automated solution for generating and publishing high-quality LinkedIn content.

  Scheduled Content Engine: Each day (or on your chosen schedule), the workflow kicks into gear, ensuring a fresh stream of content.

  Smart Topic & Content Generation: Using the power of Google Gemini, it intelligently crafts unique content topics and then expands them into full, engaging posts, ensuring your message is always fresh and relevant.

  Dynamic Image Creation: To make your posts stand out, the workflow leverages an AI image generator (like DALL-E) to produce a custom, eye-catching visual that perfectly complements your generated text.

  SEO-Optimized Hashtag Generation: Google Gemini then analyzes your newly created post and automatically generates a set of relevant, trending, and SEO-friendly hashtags, significantly boosting your content's reach and discoverability.

  Seamless LinkedIn Publishing: Finally, all these elements—your compelling text, unique image, and powerful hashtags—are merged and automatically published to your LinkedIn profile, establishing you as a thought leader with minimal effort.

  How to Use: Quick Start Guide
  This guide will get your AI LinkedIn Content Automation workflow up and running in n8n.

  Import Workflow Template:
  Download the template's JSON file and import it into your n8n instance via "File" &gt; "Import from JSON."

  Configure Credentials:
  Google Gemini: Set up and apply your API key credentials to all "Google Gemini Chat Model" nodes.
  AI Image Generation (e.g., OpenAI): Create and apply API key credentials for your chosen image generation service to the "Generate an Image" node.
  LinkedIn: Set up and apply OAuth credentials to the "Create a post" node for your LinkedIn account.

  Customize Schedule & AI Prompts:
  Schedule Trigger: Double-click "Schedule Trigger 1" to set how often your workflow runs (e.g., daily, weekly).

  AI Prompts: Review and edit the prompts within the "Content Topic Generator," "Content Creator," and "Hashtag Generator / SEO" nodes to guide the AI for your desired content style and topics.

  Test & Activate:
  Test Run: Click "Execute Workflow" to perform a test run and verify all steps are working as expected.

  Activate: Once satisfied, toggle the workflow "Active" switch to enable automated posting on your defined schedule.

  Requirements
  To use this workflow template, you will need:

  n8n Instance: A running n8n instance (cloud or self-hosted) to import and execute the workflow.

  Google Gemini Account: For content topic generation, content creation, and hashtag generation (requires Google Gemini API Key) from Google AI Studios.
   
  AI Image Generation Service Account: For creating images (e.g., OpenAI DALL-E API Key or similar service that the "Generate an Image" node uses).
   
  LinkedIn Account: For publishing the generated posts (requires LinkedIn OAuth Credentials for n8n connection).

  Connect with us

  Website: https://www.intuz.com/services
  Email: getstarted@intuz.com
  LinkedIn: https://www.linkedin.com/company/intuz
  Get Started: https://n8n.partnerlinks.io/intuz

  For Custom Worflow Automation
  Click here- Get Started

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.linkedIn","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","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":["automation","social media","AI content generation","integration"],"complexity":"medium","use_cases":["Automated LinkedIn post creation and scheduling","AI-generated topic and post drafting","Dynamic AI image creation for posts","SEO-optimized hashtag generation","Maintaining consistent brand presence on LinkedIn"],"estimated_setup_minutes":20,"required_services":["n8n instance (self-hosted or cloud)","Google Gemini (Google AI Studios) API key","AI image generation service (e.g., OpenAI DALL·E API key or similar)","LinkedIn account with OAuth credentials"],"key_features":["Scheduled content engine to run on a defined cadence","Topic generation using Google Gemini","Full post/content generation via Google Gemini","AI-driven image creation (DALL·E or equivalent)","SEO/trending hashtag generation from AI analysis of post text`,`Automatic publishing to LinkedIn via OAuth-enabled node`,`Customizable prompts and schedule within n8n"],"target_audience":["marketers","social media managers","content creators and strategists`,`small businesses and startups`,`digital agencies and consultants`,`developers/automation engineers"]}


name: Automate Social Media Posts with AI Content and Images across Twitter, LinkedIn & Facebook
author_name: Abrar Sami
author_username: abrarsami
categories: []
created_at: 2025-07-10T12:53:23.146Z
updated_at: 2025-07-10T12:53:23.146Z
url: https://n8n.io/workflows/5841
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  Auto-generate & post content using AI

  This workflow helps you create daily content using just a topic prompt. It writes a tweet, generates an image, and publishes across Twitter, Facebook, and LinkedIn — all on autopilot.

  How it works

  Triggers daily at 10 PM to start the flow  
  Uses OpenAI to generate a niche topic title  
  Writes a short-form post (tweet style) with hashtags  
  Generates a Japanese anime-style image for visual context  
  Saves everything in Google Sheets  
  Publishes automatically on Twitter, LinkedIn, and Facebook  

  Set up steps

  You’ll need OpenAI, Google Sheets, and social media credentials (Twitter, Facebook, LinkedIn)  
  Takes about 10–15 minutes to configure if you already have the credentials ready  
  Make sure your Sheet and API keys are properly linked before activating  

  📝 Keep detailed notes inside the workflow with sticky notes for easier handoff or collaboration.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleSheets","n8n-nodes-base.twitter","n8n-nodes-base.linkedIn","n8n-nodes-base.facebookGraphApi"]

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metadata_json:
  {"categories":["automation","social media","AI integration"],"complexity":"medium","use_cases":["Automated daily social posts","Cross-platform content distribution","AI-powered caption and hashtag generation","Visual asset generation for posts","Content logging and audit in Google Sheets"],"estimated_setup_minutes":15,"required_services":["OpenAI (text + image)","Google Sheets","Twitter API / X developer account","LinkedIn API","Facebook Graph API"],"key_features":["Scheduled daily trigger","AI-generated niche title and short-form post","Hashtag generation","Japanese anime-style image generation","Automatic posting to Twitter, LinkedIn, Facebook (Graph API)"],"target_audience":["Social media managers","Content creators","Small business owners/founders handling marketing themselves\",\"Growth marketers and agencies"]}


name: Transform Reddit Questions into SEO Blog Posts with OpenAI and Google Sheets
author_name: Abrar Sami
author_username: abrarsami
categories: []
created_at: 2025-07-10T12:56:48.385Z
updated_at: 2025-07-10T12:56:48.385Z
url: https://n8n.io/workflows/5842
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  Turn Reddit Questions into SEO Articles Automatically

  This workflow takes real user questions from Reddit and transforms them into fully structured blog posts — title, intro, steps, and conclusion — using AI.

  How it works

  Manually triggered when you want to run it
  Scrapes the latest posts from a specific subreddit (e.g. r/n8n)
  Filters only posts that are real questions (based on keywords like “how,” “what,” “why”)
  Logs relevant questions into a Google Sheet as raw input
  Enhances each question using AI (rephrases, creates a clean title and slug)
  Generates full-length blog content:
    ✏️ Intro paragraph
    ✅ Step-by-step guide
    🧠 Clear conclusion
  Saves the final blog content to a second Google Sheet for publishing

  Set up steps

  You’ll need access to:
    Reddit API (OAuth)
    OpenAI API
    Google Sheets
  Takes around 15–20 minutes to connect all the credentials and tweak prompts
  Customize the subreddit or topic focus by changing the Reddit node config

  Perfect for content teams who want to scale content output using real community pain points — without ever starting from a blank page.

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

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metadata_json:
  {"categories":["content automation","integration","SEO","data processing"],"complexity":"medium","use_cases":["Turn community questions into SEO-optimized blog posts","Scale content production from user-generated content","Content ideation and repurposing","Maintain a publishing-ready content queue"],"estimated_setup_minutes":20,"required_services":["Reddit API (OAuth)","OpenAI API","Google Sheets (Google account), Sheets API"],"key_features":["Scrapes latest posts from a specified subreddit","Filters posts to identify real questions (keyword-based)","Logs raw questions to a Google Sheet","Uses AI to rephrase questions and create titles/slugs","Generates full blog content: intro, step-by-step guide, conclusion via OpenAI nodes"],"target_audience":["Content teams","SEO specialists","Community managers and moderators`,`Growth marketers`"]}


name: Build a Restaurant Voice Assistant with VAPI and PostgreSQL for Bookings & Orders
author_name: Oneclick AI Squad
author_username: oneclick-ai
categories: []
created_at: 2025-07-10T15:10:47.642Z
updated_at: 2025-07-10T15:10:47.642Z
url: https://n8n.io/workflows/5847
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  This n8n template demonstrates how to create a comprehensive voice-powered restaurant assistant that handles table reservations, food orders, and restaurant information requests through natural language processing. The system uses VAPI for voice interaction and PostgreSQL for data management, making it perfect for restaurants looking to automate customer service with voice AI technology.

  Good to know
  Voice processing requires active VAPI subscription with per-minute billing
  Database operations are handled in real-time with immediate confirmations
  The system can handle multiple simultaneous voice requests
  All customer data is stored securely in PostgreSQL with proper indexing

  How it works

  Table Booking & Order Handling Workflow
  Voice requests are captured through VAPI triggers when customers make booking or ordering requests
  The system processes natural language commands and extracts relevant details (party size, time, food items)
  Customer data is immediately saved to the bookings and orders tables in PostgreSQL
  Voice confirmations are sent back through VAPI with booking details and estimated wait times
  All transactions are logged with timestamps for restaurant management tracking

  Restaurant Info Provider Workflow  
  Info requests trigger when customers ask about hours, menu, location, or services
  Restaurant details are retrieved from the restaurant_info table containing current information
  Wait nodes ensure proper data loading before voice response generation
  Structured restaurant information is delivered via VAPI in natural, conversational format

  Database Schema

  Bookings Table
  booking_id (PRIMARY KEY) - Unique identifier for each reservation
  customer_name - Customer's full name
  phone_number - Contact number for confirmation
  party_size - Number of guests
  booking_date - Requested reservation date
  booking_time - Requested time slot
  special_requests - Dietary restrictions or special occasions
  status - Booking status (confirmed, pending, cancelled)
  created_at - Timestamp of booking creation

  Orders Table
  order_id (PRIMARY KEY) - Unique order identifier
  customer_name - Customer's name
  phone_number - Contact for order updates
  order_items - JSON array of food items and quantities
  total_amount - Calculated order total
  order_type - Delivery, pickup, or dine-in
  special_instructions - Cooking preferences or allergies
  status - Order status (received, preparing, ready, delivered)
  created_at - Order timestamp

  Restaurant_Info Table
  info_id (PRIMARY KEY) - Information entry identifier
  category - Type of info (hours, menu, location, contact)
  title - Information title
  description - Detailed information content
  is_active - Whether info is currently valid
  updated_at - Last modification timestamp

  How to use

  The manual trigger can be replaced with webhook triggers for integration with existing restaurant systems
  Import the workflow into your n8n instance and configure VAPI credentials
  Set up PostgreSQL database with the required tables using the schema provided above
  Configure restaurant information in the restaurant_info table
  Test voice commands such as "Book a table for 4 people at 7 PM" or "What are your opening hours?"
  Customize voice responses in VAPI nodes to match your restaurant's tone and branding
  The system can handle multiple concurrent voice requests and scales with your restaurant's needs

  Requirements

  VAPI account for voice processing and natural language understanding
  PostgreSQL database for storing booking, order, and restaurant information
  n8n instance with database and VAPI integrations enabled

  Customising this workflow

  Voice AI automation can be adapted for various restaurant types - from quick service to fine dining establishments
  Try popular use-cases such as multi-location booking management, dietary restriction handling, or integration with existing POS systems
  The workflow can be extended to include payment processing, SMS notifications, and third-party delivery platform integration

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.postgres","n8n-nodes-base.respondToWebhook","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.webhook","n8n-nodes-base.postgres","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","voice assistant","integration","data processing"],"complexity":"medium","use_cases":["Voice table reservations","Voice-based food ordering","On-demand restaurant information (hours/menu/location)","Automated booking/order confirmations","Logging and analytics for restaurant operations"],"estimated_setup_minutes":60,"required_services":["VAPI (voice/NLU) account with billing","PostgreSQL database","n8n instance with VAPI and Database integrations enabled"],"key_features":["Capture voice requests via VAPI triggers","Natural language extraction of party size/time/order items","Real-time insert/update of bookings and orders in PostgreSQL","Voice confirmations and responses via VAPI","Restaurant info retrieval from restaurant_info table with wait handling for reliability\",\"Concurrent request handling and transaction logging"],"target_audience":["Restaurant operators and managers","Developers implementing voice automation","Hospitality/guest services teams integrating voice interfaces"]}


name: Generate Instagram Reels with Veo3 and GPT for AI-Powered Ad Creation
author_name: Automate With Marc
author_username: marconi
categories: []
created_at: 2025-07-10T16:13:26.519Z
updated_at: 2025-07-10T16:13:26.519Z
url: https://n8n.io/workflows/5849
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
description:
  🎬 Veo3 Instagram Reel Generator – AI-Powered Ad Creation in Minutes

  Description:
  This no-code workflow transforms your creative brief into an engaging Instagram Reel using OpenAI and Veo3 API (via Wavespeed) — fully automated in n8n. Just type a product, theme, or trend via chat, and get a short-form video plus caption delivered and logged, ready to post.

  Perfect for marketers, creators, and content teams looking to scale their ad content output without hiring editors or creative agencies.

  Watch step-by-step build video tutorial here:
  https://www.youtube.com/@Automatewithmarc

  ⚙️ How It Works:
  💬 Chat Trigger
   Start by sending a message like “Create an ad for a minimalist perfume brand using the ‘quiet luxury’ trend.”

  🧠 Prompt Engineer (ChatGPT)
   Generates a 5–8 second descriptive video prompt suitable for Veo3 based on your input — including visual tone, motion, and hook.

  📡 API Call to Veo3 via Wavespeed
   Submits the prompt to create a short video (9:16 ratio, ~8 seconds), then polls for the final video URL.

  ✍️ Caption Generator (GPT)
   Creates an Instagram-friendly caption to pair with the video, using a playful, impactful writing style.

  📄 Google Sheets Integration
   Logs each generated video prompt, final video URL, caption, and status into a Google Sheet for easy management and scheduling.

  🔌 Tools & Integrations:
  OpenAI GPT (Prompt generation & caption copywriting)

  Veo3 via Wavespeed API (Video generation)

  Google Sheets (Content tracking and publishing queue)

  Telegram / Chat UI trigger (Optional – easily swappable)

  💡 Use Cases:
  Instagram & TikTok ad generation

  Creative automation for digital agencies

  Short-form UGC testing at scale

  Trend-driven campaign ideation

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.httpRequest","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","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","content creation","social media","integration","marketing"],"complexity":"medium","use_cases":["Automated Instagram/TikTok ad creation","Scaling short-form video production for campaigns","Creative automation for digital agencies","Rapid UGC/trend testing","Content logging and scheduling workflow"],"estimated_setup_minutes":45,"required_services":["OpenAI (GPT)","Veo3 via Wavespeed API","Google Sheets","Telegram or other chat/webhook trigger","n8n"],"key_features":["Chat-triggered prompt-driven workflow","GPT-based prompt engineering for short video specs","API call to Veo3 with polling for final video URL","GPT-generated Instagram captions","Google Sheets logging for prompts, URLs, captions, and status updates (content queueing/tracking)"],"target_audience":["marketers","content creators","social media managers"]}


name: AI-Powered Multi-Platform Assistant with Google Suite, LinkedIn & Twitter
author_name: Jay Emp0
author_username: jay-emp0
categories: []
created_at: 2025-07-10T16:29:10.444Z
updated_at: 2025-07-10T16:29:10.444Z
url: https://n8n.io/workflows/5850
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  🤖 MCP Personal Assistant Workflow Description

  This workflow integrates multiple productivity tools into a single AI-powered assistant using n8n, acting as a centralized control hub to receive and execute tasks across Google Calendar, Gmail, Google Drive, LinkedIn, Twitter, and more. 

  ✅ Key Capabilities

  AI Agent + Tool Use**: Built using n8n's AI Agent and MCP system, enabling intelligent multi-step reasoning.
  Tool Integration**:
    Google Calendar: schedule, update, delete events
    Gmail: search, draft, send emails
    Google Drive: manage files and folders
    LinkedIn & Twitter: post updates, send DMs
    Utility tools: fetch date/time, search URLs
  Discord Input**: Accepts prompts via n8n_discord_trigger_bot repo link

  🛠 Setup Instructions

  Timezone Configuration:
     Go to Settings &gt; Default Timezone in n8n.
     Set to your local timezone (e.g., Asia/Jakarta).
     Ensure all Date & Time nodes explicitly use the same zone to avoid UTC-related bugs.

  Tool Authentication:
     Replace all OAuth credentials for:
       Gmail
       Google Drive
       Google Calendar
       Twitter
       LinkedIn
     Use your own accounts when copying this workflow.

  Platform Adaptability:
     While designed for Discord, you can replace the Discord trigger with any other chat or webhook service.
     Example: Telegram, Slack, WhatsApp Webhook, n8n Form Trigger, etc.

  📦 Strengths

  Great for document retrieval, email summarization, calendar scheduling, and social posting.
  Reduces the need for tab-switching across multiple platforms.
  Tested with a comprehensive checklist across categories like:
    Calendar
    Gmail
    Google Drive
    Twitter
    LinkedIn
    Utility tools
    Cross-tool actions  
    (Refer to discordGPT prompt checklist for prompt coverage.)

  ⚠️ Limitations

  ❌ Binary Uploads:
    AI agents & MCP server currently struggle with binary payloads.
    Uploading files to Gmail, Google Drive, or LinkedIn may fail due to format serialization issues.
    Binary operations (upload/post) are under development and will be fixed in future iterations.

  ❌ Date Bugs:
    If timezone settings are incorrect, event times may default to UTC, leading to misaligned calendar events.

  🔬 Testing

  Use the provided prompt checklist for full coverage of:
  ✅ Core feature flows
  ✅ Edge cases (e.g., invalid dates, nonexistent users)
  ✅ Cross-tool chains (e.g., Google Drive → Gmail → LinkedIn)

  ✅ MCP Assistant Test Prompt Checklist

  📅 Google Calendar
  [X] "Schedule a meeting with Alice tomorrow at 10am. and send an invite to alice@wonderland.com"
  [X] "Create an event called 'Project Sync' on Friday at 3pm with Bob and Charlie."
  [X] "Update the time of my call with James to next Monday at 2pm."
  [X] "Delete my meeting with Marketing next Wednesday."
  [x] "What is my schedule tommorow ? "

  📧 Gmail
  [x] "Show me unread emails from this week."
  [x] "Search for emails with subject: invoice"
  [X] "Reply to the latest email from john@company.com saying 'Thanks, noted!'"
  [X] "Draft an email to info@a16z.com with subject 'Emp0 Fundraising' and draft the body of the email with an investment opportunity in Emp0, scrape this site https://Emp0.com to get to know more about emp0.com"
  [X] "Send an email to hi@cursor.com with subject 'Feature request' and cc sales@cursor.com"
  [ ] "Send an email to recruiting@openai.com , write about how you like their product and want to apply for a job there and attach my latest CV from Google Drivce"

  🗂 Google Drive
  [ ] "Upload the PDF you just sent me to my Google Drive."
  [X] "Create a folder called 'July Reports' inside Emp0 shared drive."
  [X] "Move the file named 'Q2_Review.pdf' to 'Reports/2024/Q2'."
  [X] "Share the folder 'Investor Decks' with info@a16z.com as viewer."
  [ ] "Download the file 'Wayne_Li_CV.pdf' and attach it in Discord."
  [X] "Search for a file named 'Invoice May' in my Google Drive."

  🖼 LinkedIn
  [X] "Think of a random and inspiring quote. Post a text update on LinkedIn with the quote and end with a question so people will answer and increase engagement"
  [ ] "Post this Google Drive image to LinkedIn with the caption: 'Team offsite snapshots!'"
  [X] "Summarize the contents of this workflow and post it on linkedin with the original url https://n8n.io/workflows/5230-content-farming-ai-powered-blog-automation-for-wordpress/"

  🐦 Twitter
  [X] "Tweet: 'AI is eating operations. Fast.'"
  [X] "Send a DM to @founderguy: 'Would love to connect on what you’re building.'"
  [X] "Search Twitter for keyword: 'founder advice'"

  🌐 Utilities
  [X] "What time is it now?"
  [ ] "Download this PDF: https://ontheline.trincoll.edu/images/bookdown/sample-local-pdf.pdf"
  [X] "Search this URL and summarize important tech updates today: https://techcrunch.com/feed/"

  📎 Discord Attachments
  [ ] "Take the image I just uploaded and post it to LinkedIn."
  [ ] "Get the file from my last message and upload it to Google Drive."

  🧪 Edge Cases
  [X] "Schedule a meeting on Feb 30."
  [X] "Send a DM to @user_that_does_not_exist"
  [ ] "Download a 50MB PDF and post it to LinkedIn"
  [X] "Get the latest tweet from my timeline and email it to myself."

  🔗 Cross-tool Flows
  [ ] "Get the latest image from my Google Drive and post it on LinkedIn with the caption 'Another milestone hit!'"
  [ ] "Find the latest PDF report in Google Drive and email it to investor@vc.com."
  [ ] "Download an image from this link and upload it to my Google Drive: https://example.com/image.png"
  [ ] "Get the most recent attachment from my inbox and upload it to Google Drive."

  Run each of these in isolated test cases. For cross-tool flows, verify binary serialization integrity.

  🧠 Why Use This Workflow?

  This is an always-on personal assistant that can:
  Process natural language input
  Handle multi-step logic
  Execute commands across 6+ platforms
  Be extended with more tools and memory

  If you want to interact with all your work tools from a single prompt—this is your base to start.

  📎 Repo & Credits

  Discord bot trigger: n8n_discord_trigger_bot
  Creator: Jay (Emp₀)

nodes_used:
  ["n8n-nodes-base.webhook","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.discord","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.linkedInTool","n8n-nodes-base.gmailTool","n8n-nodes-base.twitterTool","@n8n/n8n-nodes-langchain.mcpClientTool","@n8n/n8n-nodes-langchain.mcpClientTool","@n8n/n8n-nodes-langchain.mcpClientTool","@n8n/n8n-nodes-langchain.mcpClientTool","@n8n/n8n-nodes-langchain.memoryMongoDbChat","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","@n8n/n8n-nodes-langchain.mcpTrigger","@n8n/n8n-nodes-langchain.mcpTrigger","@n8n/n8n-nodes-langchain.mcpTrigger","@n8n/n8n-nodes-langchain.mcpClientTool","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.googleDriveTool","n8n-nodes-base.twitterTool","@n8n/n8n-nodes-langchain.toolCode","n8n-nodes-base.twitterTool","n8n-nodes-base.twitterTool","n8n-nodes-base.linkedInTool","n8n-nodes-base.linkedInTool","@n8n/n8n-nodes-langchain.toolThink","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDriveTool","n8n-nodes-base.googleDriveTool","n8n-nodes-base.googleDriveTool","n8n-nodes-base.googleDriveTool","n8n-nodes-base.googleDriveTool","n8n-nodes-base.googleDriveTool","n8n-nodes-base.googleDriveTool","n8n-nodes-base.googleDriveTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","@n8n/n8n-nodes-langchain.mcpClientTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.dateTimeTool","n8n-nodes-base.dateTimeTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.discord"]

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metadata_json:
  {"categories":["automation","integration","productivity","AI assistant","social media"],"complexity":"complex","use_cases":["Natural-language personal assistant for scheduling and admin","Calendar management (create/update/delete events)","Email search, drafting and sending","File management in Google Drive (create/move/share/search)","Cross-posting and DMs on LinkedIn and Twitter (X) and social scheduling/posting from a single prompt source (Discord/webhook/etc.)"],"estimated_setup_minutes":60,"required_services":["n8n AI Agent / MCP server (AI agent runtime)","Google Calendar (OAuth)","Gmail (OAuth)","Google Drive (OAuth)","LinkedIn API (OAuth)","Twitter / X API (OAuth)","Discord (or alternate chat/webhook trigger such as Telegram/Slack/webhook)","HTTP/Webhook access (for external URL scraping/search)"],"key_features":["Unified AI-powered assistant that accepts NL prompts and executes multi-step tool chains","Tool integrations: Calendar CRUD, Gmail search/draft/send, Drive file ops, LinkedIn/Twitter posting and DMs","Cross-tool flows (e.g., Drive → Gmail → LinkedIn) and multi-step reasoning via MCP","Timezone-aware scheduling recommendations (requires n8n timezone config)","Discord trigger starter pack (replaceable with other triggers/webhooks/forms) and prompt checklist for testing/coverage"],"target_audience":["n8n users and workflow developers","Founders / operators wanting a single command assistant","Marketers and community managers (social posting / DMs automation)"]}


name: Daily Workflow Backups to GitHub with Slack Notifications
author_name: Andrew
author_username: boanse
categories: []
created_at: 2025-07-10T17:08:00.210Z
updated_at: 2025-07-10T17:08:00.210Z
url: https://n8n.io/workflows/5851
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  Who is this for?
  This workflow is ideal for n8n self-hosted users, DevOps engineers, and automation developers who want to automatically back up their n8n workflows to GitHub on a regular basis.

  What problem is this workflow solving
  Manually backing up n8n workflows can be time-consuming and prone to human error. This workflow automates the backup process, ensuring that all workflows are safely stored in a version-controlled GitHub repository every 24 hours.

  What this workflow does
  This automation runs daily to back up all workflows from your n8n instance to a specified GitHub repository. Each workflow is saved as a .json file using its unique ID, organized into a folder path defined by repo_path. The workflow is designed to manage memory usage efficiently by recursively calling itself. Once the backup is complete, it optionally sends a Slack notification to confirm success.

  Setup
  Configure the Config node in the subworkflow to set:
     GitHub Repo Owner
     GitHub Repo Name
     Main folder path (repo_path)
  Connect your GitHub and (optionally) Slack credentials.
  Set the workflow to run on a daily cron schedule.
  Test the workflow manually to confirm the GitHub integration works.

  Sign up for a free consultation and find out how n8n can help you.

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.github","n8n-nodes-base.github","n8n-nodes-base.filter","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.switch","n8n-nodes-base.n8n","n8n-nodes-base.set","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.github","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.slack","n8n-nodes-base.slack","n8n-nodes-base.splitInBatches"]

workflow_json_compressed:
  [encoded data, 4764 characters]

metadata_json:
  {"categories":["automation","backup","integration","devops"],"complexity":"medium","use_cases":["Automated daily backups of n8n workflows to a GitHub repo","Version-controlled archival of workflow JSON exports","Disaster recovery and audit trail for workflow changes","Automated notifications after backup completion"],"estimated_setup_minutes":20,"required_services":["n8n (self-hosted) instance","GitHub (repo and access token)","Slack (optional, for notifications)"],"key_features":["Runs on a daily cron schedule to export all workflows","Saves each workflow as a .json file named by workflow ID","Stores files in a configurable repo_path inside a GitHub repo","Uses recursive/self-calling pattern to manage memory usage","Optional Slack notification on successful backup completion"],"target_audience":["n8n self-hosted users","DevOps engineers","Automation developers / integrators"]}


name: WhatsApp Appointment Scheduling with Google Calendar
author_name: Andrew
author_username: boanse
categories: []
created_at: 2025-07-10T17:31:35.245Z
updated_at: 2025-07-10T17:31:35.245Z
url: https://n8n.io/workflows/5855
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  Who is this for?
  This workflow is for service-based businesses and freelancers who want to automate booking appointments via WhatsApp without relying on third-party scheduling tools. It's perfect for small teams who want full control over the reservation system and calendar integration.

  What problem is this workflow solving?
  Manually coordinating bookings through messages can be inefficient and error-prone. This workflow streamlines the entire scheduling process-from user input to calendar event creation-saving time and avoiding double-bookings. It ensures users only choose from available time slots and automatically records the meeting in your Google Calendar.

  What this workflow does
  Sends a WhatsApp message with a reservation link.
  Collects the user's name and preferred date.
  Checks availability and shows only free time slots.
  Allows the user to choose a time slot.
  Automatically creates a Google Calendar event with the selected details.
  Saves all data to a Postgres database for future reference.

  Setup
  Create Tables in Postgres DB
     Open the provided SQL script and replace "n8n" with your Postgres schema name.
     Execute the script to create the required tables.
  Add Credentials
     WhatsApp: Set up your WhatsApp Business API credentials using OAuth and API keys.
     Postgres: Connect your database where the booking data will be stored.
     Google Calendar: Authorize access to your calendar for event creation.

nodes_used:
  ["n8n-nodes-base.if","n8n-nodes-base.whatsAppTrigger","n8n-nodes-base.set","n8n-nodes-base.whatsApp","n8n-nodes-base.whatsApp","n8n-nodes-base.postgres","n8n-nodes-base.switch","n8n-nodes-base.switch","n8n-nodes-base.postgres","n8n-nodes-base.if","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.if","n8n-nodes-base.whatsApp","n8n-nodes-base.postgres","n8n-nodes-base.whatsApp","n8n-nodes-base.whatsApp","n8n-nodes-base.googleCalendar","n8n-nodes-base.postgres","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.googleCalendar","n8n-nodes-base.whatsApp","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.code","n8n-nodes-base.postgres","n8n-nodes-base.summarize","n8n-nodes-base.set","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:
  {"categories":["automation","integration","scheduling","database"],"complexity":"complex","use_cases":["Automated appointment booking via WhatsApp","Avoiding double-bookings with calendar checks","Collecting client info and storing reservations","Integrating conversation-based booking into existing workflows","Syncing bookings to Google Calendar"],"estimated_setup_minutes":45,"required_services":["WhatsApp Business API (OAuth/API keys)","Google Calendar API (OAuth)","Postgres database"],"key_features":["Send WhatsApp messages with reservation links","Collect user details (name, preferred date) via chat","Check calendar availability and show only free time slots","Allow user to select a time slot within chat","Create Google Calendar events automatically for confirmed bookings」「Persist all booking data in Postgres for record-keeping and future checks"],"target_audience":["Service-based businesses (salons, consultancies, clinics)","Freelancers and solo-preneurs","Small teams needing a self-managed booking system without third-party schedulers」「Developers or ops staff implementing/customizing messaging-based booking flows"]}


name: Generate Personalized Cold Email Openers from LinkedIn Posts with GPT-4o
author_name: Dajeel Dulal
author_username: dajeel
categories: []
created_at: 2025-07-10T17:43:21.305Z
updated_at: 2025-07-10T17:43:21.305Z
url: https://n8n.io/workflows/5856
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  Turn any LinkedIn post into a personalized cold email opener that sounds like a human wrote it in seconds.

  Whether you're in sales, partnerships, or outreach, this tool reads LinkedIn posts like a human, distills the core message, and gives you a smart, conversational opener to kick off the relationship the right way.

  How It Works:

  1.) Paste the post + author info into a short form.

  2.) AI reads the post like a B2B sales expert would.

  3.) Output = personalized opener, company name, prospect’s name, and next steps.

  4.) Copy-paste into your cold email and hit send.

  The opener isn’t generic fluff — it references real details, sounds natural, and shows you actually paid attention.

  Perfect For:

  SDRs and BDRs

  Agency outreach

  Partnership prospecting

  Any cold outreach that starts with a real conversation

  Setup Steps

  Setup time: ~2-3 mins

  1.) Add your OpenAI credentials (or use n8n’s built-in credits).

  2.) Open the form and test it with the sample post.

  3.) Tweak the AI prompt if you want to target a different niche or tone.

  (Optional) Connect to Google Sheets, a CRM, or your email tool.

  You're live.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.formTrigger","n8n-nodes-base.code"]

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  {"categories":["automation","sales_outreach","AI_content_generation","productivity"],"complexity":"simple","use_cases":["Cold email personalization","SDR/BDR outreach","Partnership prospecting","Agency client outreach","Manual-to-automated message drafting"],"estimated_setup_minutes":30,"required_services":["OpenAI (GPT-4o) or n8n built-in OpenAI credits","Optional: Google Sheets","Optional: CRM (HubSpot, Salesforce, etc.)","Optional: Email provider (Gmail, SMTP, etc.)","Source input: LinkedIn post (pasted manually)"],"key_features":["Converts LinkedIn post + author info into a human-sounding cold email opener","Outputs structured fields: opener, company name, prospect name, next steps","Editable AI prompt to change tone or niche","Fast, form-based input and instant AI-generated output","Optional integration points to store or send results (Sheets/CRM/email)"],"target_audience":["Sales reps (SDRs, BDRs)","Partnership and biz dev teams","Agency outreach teams and account execs"]}


name: Multimodal Chat Assistant with GPT-4o for Text, Images, and PDFs
author_name: Cooper
author_username: cooper
categories: []
created_at: 2025-07-10T19:57:54.523Z
updated_at: 2025-07-10T19:57:54.523Z
url: https://n8n.io/workflows/5857
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  Chat with thing

  This n8n template lets you build a smart AI chat assistant that can handle text, images, and PDFs — using OpenAI's GPT-4o multimodal model. It supports dynamic conversations and file analysis, making it great for AI-driven support bots, personal assistants, or embedded chat widgets.

  🔍 How it Works

  The chat trigger node kicks off a session using n8n's hosted chat UI.
  Users can send text or upload images or PDFs — the workflow checks if a file was included.
  If an image is uploaded, the file is converted to base64 and analyzed using GPT-4o's vision capabilities.
  GPT-4o generates a natural language description of the image and responds to the user's question in context.
  A memory buffer keeps track of the conversation thread, so follow-up questions are handled intelligently.
  OpenAI’s chat model handles both text-only and mixed media input seamlessly.

  🧪 How to Use

  You can embed this in a website or use it with your own webhook/chat interface.
  The logic is modular — just swap out the chatTrigger node for another input (e.g. form or API).
  To use with documents, you can modify the logic to pass PDF content to GPT-4 directly.
  You can extend it with action nodes, e.g. saving results to Notion, Airtable, or sending replies via email or Slack.

  🔐 Requirements

  Your OpenAI GPT-4o API key
  Set File Upload on the chat

  🚀 Use Cases

  PDF explainer bot
  Internal knowledge chat with media support
  Personal assistant for mixed content

nodes_used:
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metadata_json:
  {"categories":["automation","AI/ML","chatbot","document-processing","multimodal"],"complexity":"medium","use_cases":["PDF explainer bot","Internal knowledge chat with media support","Embedded chat widget for websites","Personal assistant for mixed content","Customer support with image/PDF analysis"],"estimated_setup_minutes":30,"required_services":["OpenAI (GPT-4o API)","n8n (hosted chat UI or webhook)"],"key_features":["Multimodal input handling (text, images, PDFs)","Base64 conversion and file preprocessing for uploads","Vision-enabled analysis and natural language responses","Conversation memory buffer for context-aware follow-ups","Modular trigger allowing easy embedding or replacement of input source"],"target_audience":["Developers building chatbots or assistants","Support and customer success teams","Knowledge managers and internal IT teams"]}


name: Summarize Documents, Images & Spreadsheets with Gemma 3 on Ollama
author_name: Rish
author_username: b2brish
categories: []
created_at: 2025-07-10T20:16:42.077Z
updated_at: 2025-07-10T20:16:42.077Z
url: https://n8n.io/workflows/5858
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
description:
  Tutorial Video

  🚀 Overview
  Transform your file management with this intelligent workflow that automatically processes and summarizes any file dropped into a monitored folder. Using local AI powered by Ollama, this workflow provides instant insights for images, documents, and data files.
  ✨ Key Features

  🔄 Automatic Processing: Monitors a folder and processes files instantly upon detection
  🎯 Multi-Format Support: Handles images (JPG, PNG), documents (PDF), and data files (CSV, XLS)
  🤖 AI-Powered Analysis: Uses Ollama's Gemma 3 model for intelligent content understanding
  📝 Smart Summaries: Generates concise, informative summaries tailored to each file type
  💾 Organized Output: Saves all summaries as text files with descriptive naming

  🛠️ What It Does

  Image Analysis: Describes visual content and identifies key elements in photos and graphics
  Document Summarization: Extracts and summarizes text from PDF documents
  Data Insights: Analyzes spreadsheet data and provides structural insights

  📋 Prerequisites

  Ollama Installation: Download and install Ollama on your system
  Model Setup: Pull the Gemma 3 model with ollama pull gemma3:4b
  Service Running: Ensure Ollama is running with ollama serve
  Credentials: Configure Ollama API credentials in n8n

  🔧 Setup Instructions

  Clone this workflow to your n8n instance
  Update the folder path in the "Local File Trigger" node to your desired monitoring directory
  Configure Ollama credentials for all three AI model nodes
  Test the workflow by dropping a sample file into your monitored folder

  📊 Supported File Types
  TypeExtensionsProcessingImages.jpg, .pngAI vision analysis and descriptionDocuments.pdfText extraction and summarizationData Files.csv, .xlsData structure analysis and insights
  🎯 Perfect For

  Content Creators: Quickly understand and catalog image collections
  Researchers: Summarize academic papers and research documents
  Data Analysts: Get instant insights into dataset structures
  Knowledge Workers: Organize and understand file collections efficiently

  🔒 Privacy & Security

  100% Local Processing: All AI processing happens on your machine
  No Cloud Dependencies: Files never leave your system
  Private & Secure: Complete control over your data and processing

  🚦 Getting Started
  Simply drop any supported file into your monitored folder and watch as the workflow automatically:

  Detects the file type
  Processes the content appropriately
  Generates an intelligent summary
  Saves the result as a text file

  Your intelligent file assistant is ready to help you understand and organize your digital content!

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.readWriteFile","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOllama","n8n-nodes-base.localFileTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.switch","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOllama","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOllama","n8n-nodes-base.stickyNote","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.convertToFile","n8n-nodes-base.readWriteFile","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","data processing","AI","file management"],"complexity":"medium","use_cases":["Automatic summarization of dropped files","Image description and visual element extraction","PDF/document text extraction and summarization","Spreadsheet structure analysis and data insights","Local, private file cataloging and indexing"],"estimated_setup_minutes":20,"required_services":["n8n instance","Ollama (local)","Gemma 3 model (ollama pull gemma3:4b)","Local filesystem access (monitored folder)"],"key_features":["Folder monitoring with automatic processing","Multi-format support: JPG, PNG, PDF, CSV, XLS","AI-powered analysis using Gemma 3 (Ollama)","Tailored summaries per file type (images, docs, spreadsheets)","Saves generated summaries as descriptive text files locally"],"target_audience":["Content creators","Researchers","Data analysts"]}


name: Dynamic AI Model Selector with GDPR Compliance via Requesty and Google Sheets
author_name: Stefan
author_username: stefan
categories: []
created_at: 2025-07-10T23:26:33.951Z
updated_at: 2025-07-10T23:26:33.951Z
url: https://n8n.io/workflows/5862
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
description:
  Overview
  This comprehensive n8n workflow provides a sophisticated solution for dynamically selecting and using AI models while maintaining GDPR compliance. It leverages Requesty's European-based AI routing service to ensure data privacy and automatically updates available model options based on real-time API availability.

  Choose Your Integration Approach

  Before diving into the setup, it's crucial to understand that this workflow offers two completely independent AI integration approaches:

  Approach 1: Dynamic HTTP Request Workflow (Advanced)
  Complete infrastructure with dynamic model selection

  What it includes:
  Automatic model discovery from Requesty's API
  Dynamic dropdown updates in web forms
  Model selection persistence in Google Sheets
  Complex workflow orchestration with multiple phases
  Full control over API parameters and response handling

  Best for:
  Teams needing multiple AI models for different tasks
  Organizations requiring model usage auditing
  Users who want maximum flexibility and control
  Advanced n8n users comfortable with complex workflows

  Setup complexity: High (requires multiple components and configurations)

  Approach 2: Standalone AI Agent (Simple)
  Plug-and-play solution without complexity

  What it includes:
  Direct use of n8n's native OpenAI Chat Model node
  Simple configuration: just set base URL to https://router.requesty.ai/v1
  Immediate GDPR compliance through European infrastructure
  No model discovery or selection infrastructure needed

  Best for:
  Users wanting quick GDPR-compliant AI integration
  Single-model use cases
  Simple chat interfaces
  Users preferring minimal configuration

  Setup complexity: Low (5-minute setup)

  Quick Start: Approach 2 (Simple AI Agent)

  If you want to get started quickly with GDPR-compliant AI, follow these steps:

  Step 1: Register with Requesty
  Visit https://www.requesty.ai
  Complete the registration process
  Choose "OpenAI-compatible" integration
  Note your API endpoint: https://router.requesty.ai/v1
  Create an API key (name it "n8n Integration")

  Step 2: Configure n8n
  Add a new OpenAI credential in n8n
  Set the base URL to: https://router.requesty.ai/v1
  Enter your Requesty API key
  Add an OpenAI Chat Model node to your workflow
  Select your Requesty credential

  Step 3: Test
  Your AI agent is now ready and GDPR-compliant! All requests will be routed through Requesty's European infrastructure.

  Advanced Setup: Approach 1 (Dynamic HTTP Workflow)

  For users who need dynamic model selection and advanced features, follow this comprehensive setup:

  Prerequisites
  n8n instance (self-hosted or cloud)
  Requesty API credentials
  Google Sheets integration
  Basic understanding of n8n workflows

  Phase 1: Requesty Account Setup

  1.1 Registration Process
  Navigate to https://www.requesty.ai
  Sign up with your email address
  Complete the welcome process

  1.2 Integration Configuration
  Choose Integration Type: Select "OpenAI-compatible"
  Note API Endpoint: https://router.requesty.ai/v1
  Create API Key:
     Provide a descriptive name (e.g., "n8n Dynamic Workflow")
     Click "Create API Key"
     Important: Save this key securely - you'll need it for n8n configuration

  Phase 2: Google Sheets Preparation

  2.1 Create Storage Sheet
  Create a new Google Sheet named "AI Model Selections"
  Add the following column:
     A1: "Selected Model"
  Note the Google Sheet ID from the URL

  2.2 Configure Google Sheets API
  Enable Google Sheets API in Google Cloud Console
  Create service account credentials
  Share your sheet with the service account email
  Download the credentials JSON file

  Phase 3: n8n Workflow Configuration

  3.1 Import Workflow
  Download the workflow JSON file
  Import into your n8n instance
  Review all nodes and connections

  3.2 Configure Credentials

  Requesty API Credentials:
  Go to n8n Credentials section
  Create new HTTP Request credential
  Set authentication type to "Header Auth"
  Header name: "Authorization"
  Header value: "Bearer YOUR_REQUESTY_API_KEY"

  Google Sheets Credentials:
  Create new Google Sheets credential
  Upload your service account JSON file
  Test the connection

  Google Sheets Nodes:
  Update sheet ID in all Google Sheets nodes
  Verify column mappings match your sheet structure

  Phase 4: Troubleshooting Guide

  Common Issues and Solutions

  Models Not Loading:
  Verify Requesty API credentials
  Check network connectivity and API endpoint URL

  Selection Not Persisting:
  Verify Google Sheets credentials and write permissions
  Check sheet ID configuration

  Chat Not Responding:
  Verify selected model availability
  Check API request formatting and response processing

  Debug Procedures
  Enable debug mode and detailed logging
  Check node outputs and data flow
  Validate API calls with external tools
  Review n8n execution logs

  Conclusion

  The choice between approaches depends on your specific requirements:
  Simple AI Agent**: Perfect for straightforward AI integration with minimal setup
  Dynamic HTTP Workflow**: Ideal for complex requirements with multiple models and advanced features

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.set","n8n-nodes-base.n8n","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.n8n","n8n-nodes-base.formTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.code"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data processing","ai/ml","compliance"],"complexity":"complex","use_cases":["GDPR-compliant AI/chat integration","Dynamic multi‑model routing and selection","Populating dynamic dropdowns in forms","Model usage auditing and persistence","Quick standalone AI agent (chat) for simple use cases"],"estimated_setup_minutes":30,"required_services":["Requesty (https://router.requesty.ai)","Google Sheets (Google Sheets API / Google Cloud service account)","n8n instance (self‑hosted or cloud)","OpenAI‑compatible API (via Requesty)"],"key_features":["Two integration approaches: simple OpenAI Chat node (plug‑and‑play) and advanced dynamic HTTP workflow","Automatic model discovery from Requesty API","Real‑time dropdown updates and model selection persistence to Google Sheets","GDPR compliance by routing through Requesty’s European infrastructure","Full control of API parameters and response handling in advanced flow','Prebuilt troubleshooting guidance and logging tips"],"target_audience":["Developers and n8n power users","Automation / integration engineers","Data engineers and MLOps teams needing multi‑model orchestration and auditing teams concerned with compliance and data residency"]}


name: Convert CAD & BIM (Revit, IFC, AutoCAD) in DataBase (DataFrame)
author_name: Artem Boiko
author_username: datadrivenconstruction
categories: []
created_at: 2025-07-11T05:50:35.160Z
updated_at: 2025-07-11T05:50:35.160Z
url: https://n8n.io/workflows/5867
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  A minimal workflow to convert a Revit/IFC/DWG project into analysis-ready XLSX (and optional DAE) with a single run. Set two variables, execute, and the converter does the rest.

  What it does
  Inputs:** path_to_converter and path_project_file (RVT/IFC/DWG).
  Runs:** RvtExporter.exe "&lt;converter&gt;" "&lt;project_file&gt;".
  Outputs:* writes &lt;ProjectName&gt;_rvt.xlsx (and _rvt.dae if enabled by your converter).

  Prerequisites
  Windows** host (local executable + filesystem).
  DDC Revit toolkit installed: C:\\DDC_Converter_Revit\\datadrivenlibs\\RvtExporter.exe.
  A local project file you can read.

  How to use
  Import this JSON into n8n.
  Open “Set path to file and converter” and set:
     path_to_converter: C:\\DDC_Converter_Revit\\datadrivenlibs\\RvtExporter.exe
     path_project_file: e.g., C:\\Sample_Projects\\your_project.rvt
  Run Manual Trigger → the command node executes the converter.

  Notes & tips
  Ensure the path points to the executable inside datadrivenlibs.
  Use ASCII-safe paths; ensure write permissions next to the project file.
  This is intentionally simple: chain it with your own Parse/Transform/Load steps as needed.

  Categories
  Data Extraction · Files & Storage · ETL · CAD/BIM

  Tags
  cad-bim, revit, ifc, dwg, converter, xlsx, dae

  Author
   DataDrivenConstruction.io 
   info@datadrivenconstruction.io

  Consulting and Training
  We work with leading construction, engineering, consulting agencies and technology firms around the world to help them implement open data principles, automate CAD/BIM processing and build robust ETL pipelines.

  If you would like to test this solution with your own data, or are interested in adapting the workflow to real project tasks, feel free to contact us.


  Docs & Issues:  
    Full Readme on GitHub

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","n8n-nodes-base.set","n8n-nodes-base.executeCommand","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Data Extraction","Files & Storage","ETL","CAD/BIM"],"complexity":"simple","use_cases":["Convert Revit/IFC/DWG projects to analysis-ready XLSX","Generate optional DAE exports from CAD/BIM files","Automate local CAD/BIM preprocessing in ETL pipelines","Quickly integrate converter into larger parsing/transform workflows"],"estimated_setup_minutes":10,"required_services":["Windows host with local filesystem access","DDC Revit toolkit (RvtExporter.exe) installed at C:\\DDC_Converter_Revit\\datadrivenlibs\\RvtExporter.exe","n8n instance (with ability to run local executeCommand node)","Local readable CAD/BIM project file (RVT/IFC/DWG)"],"key_features":["Runs local RvtExporter.exe with specified converter and project file","Produces <ProjectName>_rvt.xlsx and optional _rvt.dae","Minimal configuration — set two path variables and run","Designed to be chained into further Parse/Transform/Load steps"],"target_audience":["BIM/CAD engineers","Construction data engineers","Architects and consultants handling BIM exports and analysis data preparation"]}


name: Validate CAD and BIM Files Against Excel Standards (Revit, IFC, AutoCAD, DGN)
author_name: Artem Boiko
author_username: datadrivenconstruction
categories: []
created_at: 2025-07-11T05:55:45.745Z
updated_at: 2025-07-11T05:55:45.745Z
url: https://n8n.io/workflows/5868
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

  CAD-BIM Multi-Format Validation Pipeline

  This workflow enables automated validation of CAD and BIM files in multiple formats (Revit, IFC, DWG, DGN) for compliance with project standards and requirements.

  Key Features

  Converts Revit, IFC, DWG, and DGN models into open data tables
  Runs automated validation checks on model naming, structure, attributes, and completeness
  Generates error reports and QTO (Quantity Take-Off) tables for all processed files

  How it works

  Upload one or more project files in Revit (.rvt), IFC (.ifc), DWG, or DGN formats
  The pipeline automatically processes each file and validates against configurable rules in Excel form
  Error summaries and QTO tables are generated 
  All outputs are available for download as Excel 


  Converter Path:**  
    Make sure the converter executable (e.g. RvtExporter.exe) is placed in DDC Exporter\datadrivenlibs\.  
    Specify the full path in the workflow settings if required.



  Troubleshooting:**  
    If conversion fails, double-check the path to the executable.
    Only supported formats can be processed (see GitHub Readme).
    Review logs in /output for error details.

  Docs & Issues:**  
    Full Readme on GitHub

  Consulting and Training
  We work with leading construction, engineering, consulting agencies and technology firms around the world to help them implement open data principles, automate CAD/BIM processing and build robust ETL pipelines.

  If you would like to test this solution with your own data, or are interested in adapting the workflow to real project tasks, feel free to contact us.

  Author
   DataDrivenConstruction.io 
   info@datadrivenconstruction.io

  Docs & Issues:  
    Full Readme on GitHub

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.readBinaryFile","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.readBinaryFile","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.writeBinaryFile","n8n-nodes-base.executeCommand","n8n-nodes-base.set","n8n-nodes-base.readBinaryFile","n8n-nodes-base.if","n8n-nodes-base.executeCommand","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.merge","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:
  {"categories":["automation","data processing","integration","BIM/CAD"],"complexity":"complex","use_cases":["Batch validation of Revit, IFC, DWG, and DGN files against project standards defined in Excel","Generate error reports and QTO (Quantity Take-Off) tables for model compliance and QA/QC","Convert proprietary BIM/CAD formats into open data tables for downstream ETL and analytics","Automate model naming, structure and attribute checks as part of project handover or CI processes"],"estimated_setup_minutes":60,"required_services":["Self-hosted n8n (community nodes required)","Converter executable(s) such as RvtExporter.exe placed in DDC Exporter/datadrivenlibs","Local file system or network storage for input/output and logs","Access to the workflow's GitHub repo/README for configuration details"],"key_features":["Multi-format conversion (Revit .rvt, IFC .ifc, DWG, DGN) to open data tables","Configurable Excel-based validation rules","Automated checks for naming, structure, attributes and completeness","Generates downloadable Excel error summaries and QTO tables","Batch processing with per-file logs and troubleshooting guidance"],"target_audience":["BIM managers and coordinators","CAD/BIM engineers and model authors","Construction and engineering firms (QA/QC teams)」「Data engineers and automation specialists working with AEC data"]}


