# templates

name: WhatsApp AI Customer Service Bot with GPT-4o-mini and Gmail Alerts
author_name: Ghufran Ridhawi
author_username: ghufran-ridhawi
categories: []
created_at: 2025-05-28T13:33:23.084Z
updated_at: 2025-05-28T13:33:23.084Z
url: https://n8n.io/workflows/4456
scraped_at: 2025-12-24 13:02:43
description:
  Who is this for?
  This workflow is intended for WhatsApp admins, customer service, individual users or teams in businesses who want to automate their small business or medium to large businesses on WhatsApp practically by automatically replying about your business products or services using Open AI capabilities on AI Agent. Based on an automated system there is a task to answer many customers or clients on WhatsApp, in reality answering one by one is very time consuming and tiring, especially if we have to compose sentences first or click on the template and send them. This is also a form of devotion to the community at n8n and the n8n company, as well as devotion to small businesses so that the reality is no longer tiring and able to answer the problems of reality that exist.

  How does it work?
  Easy explanation:

  Whatsapp trigger here the "Input submissions" node is responsible for inputting chats from customers in the form of data. Then, it is sent to the next node, namely the if node, here there are two if nodes, namely "Signpost" and "Is text message?" responsible for forwarding customer chat input data and selecting if correct then it will be forwarded to the AI ​​Agent and if wrong then there is a "Fallback Text" node. Once correct, the AI ​​Agent will analyze with the OpenAI model capability and store it in Simple Memory. The AI ​​Agent here has been given directions and commands on what it should be like, in the parameters section, the prompt contains a special task, the knowledge base of your business, and several points and rules that must be there. After that, it will be sent via the WhatsApp reply node which is addressed to the customer. After that, the Gmail Set will process it again to be addressed to the Send Gmail Notifications Node, which contains email address parameters and also the contents of the email as a notification of success or failure. Then, there are no operations after that after the Gmail node. And enjoy this workflow that works for you.

  Setup instructions
  Complete what is in the node as stated in the notes column.
  You need a "Credential Account" on each WhatsApp node, then the OpenAI node and the Gmail Node. If you already have an account, just connect it, and if not, create it first, you can register it by following the guide from n8n, it makes it very easy.
  Because here it has been set up neatly and cleanly like in the if node. Next, you need to add your business to the AI ​​Agent node, there are parameters and a prompt section, I have made a sample here to make it easier for you. You can immediately adjust it to your business or service or product, later what communication or sentence you want to convey to customers on WhatsApp. After that, don't forget to add an email address to the Gmail node for notification of success or failure of each customer from the running of this system.
  Save and run, test the workflow and activate the workflow. This workflow is ready to use.

  Requirements
  As a reminder:

  Must be set in nodes such as your business description, also according to the conditions of your business, services, products, so that the AI ​​Agent matches your business knowledge base
  Must have (if not, make sure you have registered) in each "Credential Account" by following the guide on how to create it n8n the guide is very complete
  Don't forget to save, and make sure the workflow is active.

  How to customize this workflow to your needs

  You can immediately set up your business knowledge base in the nodes, so that the accuracy is also high when carrying out tasks and answering them.

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name: AI Telegram Bot Agent: Smart Assistant & Content Summarizer
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-28T14:19:55.730Z
updated_at: 2025-05-28T14:19:55.730Z
url: https://n8n.io/workflows/4457
scraped_at: 2025-12-24 13:02:41
description:
  Create your own intelligent Telegram bot that summarizes articles and processes commands automatically.

  This powerful workflow turns Telegram into your personal AI assistant, handling /help, /summary &lt;URL&gt;, and /img &lt;prompt&gt; commands with intelligent responses - perfect for teams, content creators, and anyone wanting smart automation in their messaging.

  🚀 What It Does

  Smart Command Processing: Automatically recognizes and routes /help, /summary, and /img commands to appropriate AI-powered responses.

  Article Summarization: Fetches any URL, extracts content, and generates professional 10-12 bullet point summaries using OpenAI.

  Image Generation: Processes image prompts and integrates with AI image generation services.

  Help System: Provides users with clear command instructions and usage examples.

  🎯 Key Benefits

  ✅ Personal AI Assistant: Get instant article summaries in Telegram  
  ✅ Team Productivity: Share quick content summaries with colleagues  
  ✅ Content Research: Rapidly digest articles and web content  
  ✅ 24/7 Availability: Bot works around the clock without maintenance  
  ✅ Easy Commands: Simple /summary &lt;link&gt; format anyone can use  
  ✅ Scalable: Handles multiple users and requests simultaneously  

  🏢 Perfect For

  Content Teams & Researchers
  Journalists quickly summarizing news articles
  Marketing teams researching competitor content
  Students processing academic papers and articles
  Analysts digesting industry reports

  Business Applications
  Team Communication**: Share article insights in group chats
  Research Assistance**: Quick content analysis for decision making
  Content Curation**: Summarize articles for newsletters or reports
  Knowledge Sharing**: Help teams stay informed efficiently

  ⚙️ What's Included

  Complete Bot Workflow: Ready-to-deploy Telegram bot with all commands
  AI Integration: OpenAI-powered content summarization and processing
  Smart Routing: Intelligent command recognition and response system
  Error Handling: Robust system handles invalid commands gracefully
  Extensible Design: Easy to add new commands and features

  🔧 Quick Setup Requirements

  n8n Platform**: Cloud or self-hosted instance
  Telegram Bot Token**: Create via @BotFather (free, 5 minutes)
  OpenAI API**: For content summarization (pay-per-use)
  Basic Configuration**: Follow 15-minute setup guide

  📱 User Experience

  Simple Commands:
  /help - Show available commands
  /summary https://example.com - Get article summary
  /img sunset over mountains - Generate image (with supported APIs)

  Sample Summary Output:
  📄 Article Summary:

  • Company reports 40% revenue growth in Q3 2024
  • New AI features driving customer acquisition
  • Expansion into European markets planned for 2025
  • Investment in R&D increased by 25% this quarter
  • Customer satisfaction scores improved to 94%
  • Three new product launches scheduled for next year
  • Remote work policy made permanent post-pandemic
  • Sustainability goals on track to meet 2025 targets
  • Partnership with major tech firm announced
  • Stock price up 15% following earnings report

  🎨 Customization Options

  Command Extensions: Add custom commands for specific workflows
  Response Formatting: Customize summary style and length
  Multi-Language: Support different languages for international teams
  Integration APIs: Connect additional AI services and tools
  User Permissions: Control who can use specific commands
  Analytics: Track usage patterns and popular content

  🏷️ Tags & Categories

  #telegram-bot #ai-automation #content-summarization #article-processing #team-productivity #openai-integration #smart-assistant #workflow-automation #messaging-bot #content-research #ai-agent #n8n-workflow #business-automation #telegram-integration #ai-powered-bot

  💡 Use Case Examples

  News Team: Quickly summarize breaking news articles for editorial meetings
  Marketing Agency: Research competitor content and industry trends efficiently  
  Sales Team: Digest industry reports and share insights with prospects
  Remote Team: Keep everyone informed with summarized company updates

  📈 Expected Results

  80% faster** content research and analysis
  50% more articles** processed per day vs manual reading
  100% team accessibility** through familiar Telegram interface
  24/7 availability** for global teams across time zones

  🛠️ Setup & Support

  Quick Start: Deploy your bot in 15 minutes with included guide
  Video Tutorial: Complete walkthrough available
  Template Commands: Pre-built responses and formatting
  Expert Support: Direct help from workflow creator

  📞 Get Help & Resources

  YouTube: https://www.youtube.com/@YaronBeen/videos

  💼 Professional Support  
  LinkedIn: https://www.linkedin.com/in/yaronbeen/

  📧 Direct Help  
  Email: Yaron@nofluff.online - Response within 24 hours

  Ready to build your intelligent Telegram assistant?

  Get this AI Telegram Bot Agent and transform your messaging app into a powerful content processing tool. Perfect for teams, researchers, and anyone who wants AI-powered assistance directly in Telegram.

  Stop manually reading long articles. Start getting instant, intelligent summaries with simple commands.

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name: Score Contact Form Leads with GPT-4 and Send Slack Notifications
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-28T14:21:41.116Z
updated_at: 2025-05-28T14:21:41.116Z
url: https://n8n.io/workflows/4458
scraped_at: 2025-12-24 13:02:44
description:
  🔥 AI Lead Scoring Agent: Smart Contact Form Triager

  Automatically score every contact form lead as Hot/Warm/Cold and alert your sales team instantly.

  This intelligent workflow captures contact form submissions, uses GPT-4 to analyze message content and score lead quality, then sends formatted alerts to Slack - ensuring your sales team always focuses on the hottest prospects first.

  🚀 What It Does

  Instant Lead Capture: Automatically receives contact form submissions via webhook endpoint

  AI-Powered Scoring: GPT-4 analyzes message content and classifies leads as Hot 🔥, Warm 🌤, or Cold ❄️

  Smart Data Extraction: Cleanly extracts name, email, and message from form submissions

  Real-Time Slack Alerts: Sends formatted notifications to your sales team with lead details and AI scoring

  🎯 Key Benefits

  ✅ Never Miss Hot Prospects: AI identifies urgent leads automatically  
  ✅ Save Sales Time: Focus effort on highest-probability leads first  
  ✅ Instant Team Alerts: Real-time notifications in Slack channels  
  ✅ Smart Prioritization: AI scoring eliminates guesswork in lead quality  
  ✅ Zero Manual Work: Complete automation from form to sales alert  
  ✅ Universal Integration: Works with any contact form or landing page  

  🏢 Perfect For

  Sales & Marketing Teams
  SaaS companies managing inbound leads
  Service businesses qualifying prospects  
  E-commerce stores identifying serious buyers
  Agencies prioritizing client inquiries

  Business Applications
  Lead Qualification**: Identify purchase-ready prospects instantly
  Sales Efficiency**: Focus team effort on highest-value opportunities  
  Response Prioritization**: Handle urgent inquiries first
  Team Coordination**: Keep entire sales team informed of new leads

  ⚙️ What's Included

  Complete Workflow: Ready-to-deploy lead scoring automation
  Webhook Endpoint: Receives submissions from any contact form
  AI Classification: GPT-4 powered lead interest analysis
  Slack Integration: Professional team notifications with emojis and formatting
  Data Processing: Clean extraction and formatting of lead information

  🔧 Quick Setup Requirements

  n8n Platform**: Cloud or self-hosted instance
  OpenAI API**: GPT-4 access for lead scoring
  Slack Workspace**: Team channel for lead notifications
  Contact Form**: Any form that can POST to webhook endpoint

  📱 Sample Slack Alert

  🔥 New Lead: Sarah Johnson (sarah@techstartup.com)

  Message: "We're looking for a project management solution for our 50-person team. Need to implement ASAP as we're scaling fast. Can we schedule a demo this week?"

  Triage: 🔥 Hot

  ❄️ New Lead: John Smith (john@email.com)

  Message: "Just browsing your website. Might be interested in learning more someday."

  Triage: ❄️ Cold

  🎨 Customization Options

  Scoring Criteria: Adjust AI prompts for industry-specific lead qualification
  Team Channels: Route different lead types to specific Slack channels  
  Additional Fields: Capture company size, budget, timeline data
  CRM Integration: Connect to Salesforce, HubSpot, or Pipedrive
  Follow-up Automation: Trigger email sequences based on lead temperature
  Analytics Tracking: Monitor lead quality trends and conversion rates

  🏷️ Tags & Categories

  #lead-scoring #sales-automation #contact-form-processing #ai-qualification #slack-integration #prospect-management #inbound-marketing #sales-productivity #lead-generation #openai-integration #webhook-automation #crm-automation #sales-alerts #lead-triage #ai-agent

  💡 Use Case Examples

  SaaS Company: Score demo requests based on company size and urgency mentions
  Consulting Firm: Identify clients ready to start projects vs those still researching  
  E-commerce Store: Spot bulk buyers and wholesale inquiries vs casual browsers
  Marketing Agency: Prioritize clients with specific budgets and timelines mentioned

  📈 Expected Results

  70% faster** lead response times through smart prioritization
  3x higher** conversion rates focusing on Hot leads first
  50% time savings** on manual lead qualification  
  100% lead coverage** - never miss or ignore a prospect again

  🛠️ Setup & Support

  5-Minute Setup: Simple webhook configuration with any contact form
  Universal Integration: Works with WordPress, Webflow, custom forms, landing pages
  Team Training: Clear Slack notification format anyone can understand
  Scalable: Handles unlimited form submissions automatically

  📞 Get Help & Resources

   
  YouTube: https://www.youtube.com/@YaronBeen/videos

  💼 Sales Automation Support  
  LinkedIn: https://www.linkedin.com/in/yaronbeen/

  📧 Direct Help  
  Email: Yaron@nofluff.online - Response within 24 hours

  Ready to never miss another hot lead?

  Get this AI Lead Scoring Agent and transform your contact forms into intelligent lead qualification systems. Your sales team will always know which prospects to call first, and you'll never waste time on cold leads again.

  Stop treating all leads equally. Start prioritizing the ones ready to buy.

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name: AI YouTube Analytics Agent: Comment Analyzer & Insights Reporter
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-28T14:26:13.676Z
updated_at: 2025-05-28T14:26:13.676Z
url: https://n8n.io/workflows/4459
scraped_at: 2025-12-24 13:02:41
description:
  Transform YouTube comments into actionable insights with automated AI analysis and professional email reports.

  This intelligent workflow monitors your Google Sheets for YouTube video IDs, fetches comments using YouTube API, performs comprehensive AI sentiment analysis, and delivers formatted email reports with viewer insights - helping content creators understand their audience and improve engagement.

  🚀 What It Does

  Smart Video Monitoring: Watches Google Sheets for new YouTube video IDs marked as "Pending" and triggers automated analysis

  Complete Comment Collection: Fetches up to 100 top comments per video using YouTube API with relevance-based ordering

  AI-Powered Analysis: Uses GPT-4 to analyze comments for sentiment, themes, questions, feedback, and actionable insights

  Professional Email Reports: Generates detailed HTML reports with statistics, sentiment breakdown, and improvement recommendations

  Automated Status Tracking: Updates spreadsheet status to prevent duplicate processing and maintain organized workflow

  🎯 Key Benefits

  ✅ Deep Audience Insights: Understand what viewers really think about your content  
  ✅ Save Hours of Manual Work: Automated comment analysis vs reading hundreds of comments  
  ✅ Improve Content Strategy: Get actionable feedback for better video performance  
  ✅ Track Sentiment Trends: Monitor positive/negative feedback patterns  
  ✅ Professional Reporting: Receive formatted analysis reports via email  
  ✅ Scalable Analysis: Process multiple videos automatically  

  🏢 Perfect For

  Content Creators & YouTubers
  Individual creators tracking audience engagement
  Educational channels analyzing learning feedback
  Entertainment creators understanding viewer preferences
  Business channels monitoring brand sentiment

  Marketing & Business Applications
  Brand Monitoring**: Track sentiment on branded content and partnerships
  Audience Research**: Understand viewer demographics and preferences  
  Content Optimization**: Identify what resonates with your audience
  Competitor Analysis**: Analyze comments on competitor videos (where allowed)

  ⚙️ What's Included

  Complete Analytics Workflow: Ready-to-deploy YouTube comment analysis system
  Google Sheets Integration: Simple spreadsheet-based video management
  YouTube API Integration: Automated comment fetching with proper authentication
  AI Analysis Engine: GPT-4 powered sentiment and insight generation
  Email Reporting System: Professional HTML-formatted reports
  Status Management: Automatic processing tracking and duplicate prevention

  🔧 Setup Requirements

  n8n Platform**: Cloud or self-hosted instance
  YouTube API Credentials**: Google Cloud Console API access
  OpenAI API**: GPT-4 access for comment analysis
  Google Sheets**: Video ID management and status tracking
  Gmail Account**: For receiving analysis reports

  📊 Required Google Sheets Structure

  | ID | Video Title | YouTube Video ID | Status |
  |----|-------------|------------------|---------|
  | 1  | My Tutorial | dQw4w9WgXcQ     | Pending |
  | 2  | Product Demo| abc123def456    | Mail Sent |
  | 3  | Weekly Vlog | xyz789uvw012    | Draft |

  Status Options: Draft → Pending → Mail Sent

  📧 Sample Analysis Report

  📺 YouTube Comments Analysis Report
  Video: "How to Build Your First Website"

  📊 Quick Statistics:
  • Total Comments Analyzed: 87
  • Average Likes per Comment: 3.2
  • Total Replies: 156
  • Sentiment Summary: Positive: 65%, Negative: 10%, Neutral: 25%

  ❓ Common Questions:
  • "What hosting service do you recommend?"
  • "Can I do this without coding experience?"
  • "How much does domain registration cost?"

  💡 Key Feedback Points:
  • Tutorial pace is perfect for beginners
  • More examples of finished websites requested
  • Viewers want follow-up video on advanced features

  🎯 Actionable Insights:
  • Create hosting comparison video
  • Add timestamps for different skill levels
  • Consider beginner-friendly series expansion

  🎨 Customization Options

  Analysis Depth: Adjust AI prompts for different analysis focuses (engagement, education, entertainment)
  Comment Limits: Modify maximum comments processed (default: 100, AI analysis: 50)
  Report Recipients: Send reports to multiple team members or clients
  Custom Metrics: Add specific analysis criteria for your content niche
  Multi-Channel: Process videos from multiple YouTube channels
  Scheduling: Set up regular analysis of your latest videos

  🏷️ Tags & Categories

  #youtube-analytics #comment-analysis #content-creator-tools #ai-sentiment-analysis #video-insights #audience-research #youtube-api #content-optimization #social-media-analytics #creator-economy #video-marketing #engagement-analysis #content-strategy #ai-reporting #youtube-automation

  💡 Use Case Examples

  Educational Channel: Analyze tutorial comments to identify confusing concepts and improve teaching methods
  Product Reviews: Monitor sentiment on review videos to understand customer satisfaction trends  
  Entertainment Creator: Track audience reactions to different content formats and optimize future videos

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.limit","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.youTube","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.gmail","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheetsTrigger"]

workflow_json_compressed:
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name: Telegram Chat Summarizer with AI - using @telepilotco/n8n-nodes-telepilot
author_name: Alexey from Mingles.ai
author_username: alexx
categories: []
created_at: 2025-05-28T14:42:42.156Z
updated_at: 2025-05-28T14:42:42.156Z
url: https://n8n.io/workflows/4461
scraped_at: 2025-12-24 13:02:44
description:
  Template Description
  Automatically generate intelligent summaries of your Telegram community discussions using AI, helping you stay updated on important conversations without reading every message.
  This powerful n8n automation monitors your Telegram chats and creates periodic AI-powered summaries, highlighting key trends, new ideas, and important updates. Perfect for busy community managers, team leads, and active group participants who want to stay informed without information overload.
  Key Features
  🤖 AI-Powered Analysis

  Smart Summarization: Uses OpenRouter AI models to analyze conversation patterns
  Trend Detection: Identifies emerging topics and discussion themes
  Context Awareness: Maintains conversation history through MongoDB memory
  Intelligent Filtering: Focuses on meaningful content while skipping noise

  ⏰ Flexible Scheduling

  Automated Execution: Runs every 2 hours automatically
  Manual Triggers: Execute on-demand for instant summaries
  Time-Based Filtering: Analyzes only recent messages (last 2 hours)
  Customizable Intervals: Easy to adjust frequency based on chat activity

  📱 Advanced Telegram Integration

  TelePilot Integration: Full Telegram userbot capabilities
  Chat Access: Can monitor any public or private chat you have access to
  Message History: Retrieves up to 100 recent messages per execution
  Real-time Processing: Handles various message types and formats

  🧠 Persistent Memory System

  MongoDB Storage: Maintains conversation context across executions
  Chat-Specific Memory: Separate memory for each monitored chat
  Historical Awareness: Avoids repeating previously summarized content
  Scalable Architecture: Handles multiple chats simultaneously

  How It Works
  Chat Monitoring

  Connects to specified Telegram chat using TelePilot
  Retrieves recent message history (configurable limit)
  Filters messages from the last 2 hours

  Message Processing

  Extracts text content from various message types
  Filters out empty messages and system notifications
  Structures data for AI analysis (sender_id, text, timestamp)

  AI Analysis

  Aggregates filtered messages into conversation context
  Applies AI summarization with custom system prompts
  Identifies trends, new ideas, and important updates
  Maintains awareness of previous summaries to avoid repetition

  Summary Delivery

  Posts AI-generated summary back to the chat
  Includes conversation trends and key highlights
  Formatted for easy reading and quick understanding

  Setup Requirements
  TelePilot Plugin Installation
  Before using this template, install the TelePilot community node:

  Go to Settings → Community modules in your n8n instance
  Select "Install Community node"
  Specify the name: @telepilotco/n8n-nodes-telepilot
  Check the risk acknowledgment checkbox and click "Install"

  Required Integrations

  TelePilot Account: For Telegram userbot functionality (Full Documentation)
  OpenRouter API: For AI summarization capabilities
  MongoDB Database: For persistent conversation memory
  Target Telegram Chat: Public or private chat access

  TelePilot Authentication
  After installation, you'll need to authenticate your Telegram account:

  Click the "Chat" button at the bottom of the n8n interface
  Type /start in the chat window and follow instructions
  Keep your smartphone or desktop Telegram app ready to receive the authentication code

  📖 Complete TelePilot Setup Guide
  Configuration Options

  Chat Selection: Easily change target chat by username
  Schedule Frequency: Adjust from 2-hour default to your needs
  Message Limit: Control how many messages to analyze
  Summary Style: Customize AI prompts for different summary formats

  Perfect For

  Community Managers: Keep track of multiple active groups
  Team Leaders: Stay updated on team discussions across time zones
  Active Group Members: Catch up on missed conversations quickly
  Content Creators: Monitor audience discussions and feedback
  Research Teams: Track ongoing project conversations
  Global Teams: Bridge communication gaps across different schedules

  Key Benefits
  ✅ Never Miss Important Updates: Stay informed without constant monitoring
  ✅ Reduce Information Overload: Get concise summaries instead of hundreds of messages
  ✅ Maintain Context: AI remembers previous summaries to avoid repetition
  ✅ Flexible Scheduling: Automated or manual execution options
  ✅ Multi-Chat Support: Monitor multiple communities simultaneously
  ✅ Trend Analysis: Identify emerging topics and discussion patterns
  ✅ Time-Efficient: Spend minutes instead of hours catching up
  ✅ Scalable Solution: Works for groups of any size
  Use Cases

  Daily Team Standup Summaries: Automated updates for distributed teams
  Community Highlight Reels: Weekly summaries for large communities
  Project Status Updates: Track ongoing discussions and decisions
  Customer Feedback Analysis: Monitor support and feedback channels
  Event Planning Updates: Stay current on planning discussions
  Learning Community Insights: Track educational discussions and resources

  What's Included
  🔧 Complete Workflow: Ready to deploy with minimal configuration
  📋 Setup Instructions: Step-by-step TelePilot integration guide
  🎯 Smart Filtering: Pre-configured message processing logic
  🤖 AI Optimization: Fine-tuned prompts for quality summaries
  💾 Memory Management: MongoDB integration for context persistence
  ⚙️ Error Handling: Robust workflow with fallback mechanisms
  Transform your chat monitoring from overwhelming to insightful with this intelligent automation solution!

  Documentation: TelePilot Plugin Documentation
  Tags: #Telegram #AI #ChatSummary #CommunityManagement #TelePilot #OpenRouter #MongoDB #Automation #TeamCommunication #ContentCuration

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.splitOut","n8n-nodes-base.aggregate","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.memoryMongoDbChat","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.filter","n8n-nodes-base.set","n8n-nodes-base.filter","@telepilotco/n8n-nodes-telepilot.telePilot","@telepilotco/n8n-nodes-telepilot.telePilot","@telepilotco/n8n-nodes-telepilot.telePilot","@telepilotco/n8n-nodes-telepilot.telePilot","@telepilotco/n8n-nodes-telepilot.telePilot"]

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name: Birthday and Ephemeris Notification (Google Contact, Telegram & Home Assistant)
author_name: Thibaud
author_username: tderouze
categories: []
created_at: 2025-05-28T15:15:56.015Z
updated_at: 2025-05-28T15:15:56.015Z
url: https://n8n.io/workflows/4462
scraped_at: 2025-12-24 13:02:44
description:
  How it works:
  Schedule Trigger** on a daily basis (configured at 7.30 am)
  Connects Google Contacts** to get personal information from them
  Field Checker** on birthday date & firstnames. And see if there is any celebration for today
  Send a Telegram Notification** and display the message on a Google Home Speaker via Home Assistant if any celebration has matched

  Set up steps:
  Download* the workflow and *import** it into your n8n instance
  Configure accounts** for Google Contacts, Telegram and Home Assistant
  And you will be good to go

nodes_used:
  ["n8n-nodes-base.googleContacts","n8n-nodes-base.set","n8n-nodes-base.aggregate","n8n-nodes-base.httpRequest","n8n-nodes-base.merge","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.aggregate","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.if","n8n-nodes-base.homeAssistant","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Automated Workflow Backups to GitHub with PR Creation & Slack Notifications
author_name: Bao Duy Nguyen
author_username: duynb
categories: []
created_at: 2025-05-28T15:59:53.436Z
updated_at: 2025-05-28T15:59:53.436Z
url: https://n8n.io/workflows/4463
scraped_at: 2025-12-24 13:02:44
description:
  Who is this for?

  This template is ideal for DevOps engineers, automation specialists, and n8n users who manage multiple workflows and want a reliable version control system for backups. It’s especially useful for teams collaborating via GitHub.

  What problem is this workflow solving?

  Manually backing up n8n workflows to GitHub can be time-consuming and error-prone. This workflow solves that by automating the backup of new and updated n8n workflows, ensuring your GitHub repository always reflects the latest changes.

  What this workflow does
  Retrieves all workflows from your local n8n instance.
  Decodes their content and compares it with existing GitHub files.
  Detects newly created or updated workflows.
  Creates a new Git branch and commits changes.
  Opens a pull request (PR) to the main branch.
  Sends a Slack notification when the PR is created.

  The system uses GitHub API, n8n, Merge, Set, and Slack nodes for full automation.

  Setup
  GitHub credentials: Add your GitHub API credentials in n8n.
  Slack integration: Connect your Slack Bot token if you want PR notifications.
  Repository details: Update github_owner, repo_name, and workflow directory path in the “Define Local Variables” node.
  n8n API key - Check this doc

  How to customize this workflow to your needs
  Change the workflow directory from workflows/ to a custom path.
  Modify the Slack message or add email notification support.
  Add filters to back up only specific workflows based on naming or tags.
  Adjust branch naming conventions or use different GitHub base branches.

  This workflow provides a seamless backup and versioning pipeline, minimizing manual Git interactions and supporting collaborative automation development.

nodes_used:
  ["n8n-nodes-base.n8n","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.github","n8n-nodes-base.github","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.if","n8n-nodes-base.noOp","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.filter","n8n-nodes-base.filter","n8n-nodes-base.github","n8n-nodes-base.github","n8n-nodes-base.slack","n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4520 characters]


name: Export AI Agent Conversation Logs from Postgres to Google Sheets
author_name: Agent Studio
author_username: agentstudio
categories: []
created_at: 2025-05-28T16:04:09.907Z
updated_at: 2025-05-28T16:04:09.907Z
url: https://n8n.io/workflows/4464
scraped_at: 2025-12-24 13:02:44
description:
  Overview
  This n8n workflow retrieves AI agent chat memory logs stored in Postgres and pushes them to Google Sheets, creating one sheet per session. It’s useful for teams building chat-based products or agents and needing to review or analyze session logs in a collaborative format.

  Who is it for
  Anyone with an AI Agent in Production storing the conversation logs in Postgres (or Supabase) who wants to see transcript and have control
  Product teams building AI agents or assistants.
  Teams that want to centralize conversation history for analysis or support.
  Anyone managing AI chat memory and needing to explore it in a spreadsheet.

  Prerequisites
  A Postgres database with a n8n_chat_histories table with an AI Agent connected to it. If you need an example, you can follow this tutorial
  Once done, you need to run the Postgresql query to add the created_at column (see Setup &gt; Add a datetime column)
  Google Sheets access and OAuth credentials connected to n8n.
  A Google Sheets document set up as a template (see below).

  Google Sheets Template
  This workflow expects a Google Sheets file where each session will be stored in its own tab. 
  A basic tab layout is duplicated and renamed with the session ID.
  👉 Use this template as a starting point
  Note: You can hide the template after the first tabs have been created

  How it works
  Trigger
     The workflow can be launched manually or on a schedule (e.g. daily at noon).

  Retrieve sessions
     Runs a SQL query to get distinct session_id values from the n8n_chat_histories table.

  Loop over sessions
  For each session:
     Clears the corresponding sheet (if it exists).
     Duplicates the template tab.
     Renames it with the current session_id.

  Fetch messages
     Selects all messages linked to the session from Postgres.

  Append to sheet
     Adds each message to the Google Sheet with columns:

     Who: speaker role (user, assistant, etc.)
     Message: text content
     Date: timestamp from created_at, formatted yyyy-MM-dd hh:mm:ss

  Notes
  The sheet is cleared and rebuilt each run to ensure logs are up-to-date.
  If a sheet for a session doesn’t exist, it will be created by duplicating the first tab (template)
  You can group sessions under a persistent ID (like user_id) by overriding session_id in your memory config.
  Works perfectly with Supabase by using PG credentials from the connection pooler.

  👉 If you're looking for a solution to better visualize and analyse conversations, reach out to us!

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.postgres","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: AI-Powered Document Chat with Nextcloud Files using LangChain and OpenAI
author_name: johappel
author_username: johappel
categories: []
created_at: 2025-05-28T16:28:03.885Z
updated_at: 2025-05-28T16:28:03.885Z
url: https://n8n.io/workflows/4465
scraped_at: 2025-12-24 13:02:44
description:
  Main Workflow “AI Nextcloud”

  Entry point**: A public chat-trigger greets the user; every incoming chat message starts the flow.
  AI agent**: A LangChain agent (“AI Nextcloud”) uses the configured OpenAI model plus short-term memory to continue the dialogue in context.
  Purpose**: Answers questions about files stored in a Nextcloud folder. The user simply includes the folder path in their question.
  Tool integration**: Calls the sub-workflow “Nextcloud Tool” whenever it needs to read files and pass their text back to the AI.

  Sub-Workflow “Nextcloud Tool”

  Invocation: Triggered by other workflows with the input parameter path (folder path).
  File listing: Retrieves every file in the specified folder via the Nextcloud API.
  Filter: Allows only readable formats (PDF, Markdown, DOCX).
  Download & text extraction

     PDF → Text via Extract From File
     Markdown → Raw text
     DOCX → Text via community node word2text
  Aggregation: Combines all extracted text into a single output field and returns it.

  &gt; Outcome: Each call yields the plain content of every supported file in a Nextcloud folder—providing rich context for the AI agent to answer user questions accurately.

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.switch","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.nextCloud","n8n-nodes-base.nextCloud","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.stickyNote","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","n8n-nodes-word2text.word2text"]

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name: Generate Enhanced AI Images via Telegram with DALL-E and GPT
author_name: David Olusola
author_username: dae221
categories: []
created_at: 2025-05-28T17:41:27.309Z
updated_at: 2025-05-28T17:41:27.309Z
url: https://n8n.io/workflows/4467
scraped_at: 2025-12-24 13:02:43
description:
  PromptCraft AI – Telegram Image Generator

  🚀 How It Works

  PromptCraft AI is an n8n automation that transforms simple image ideas sent through Telegram into stunning AI-generated images using OpenAI's DALL·E (or other image models).

  🔁 Workflow Overview:

  Telegram Trigger: Listens for messages from a user on Telegram.
  Prompt Expansion: The message is transformed into a rich image description using GPT (OpenAI Chat Model).
  Image Generation: The prompt is passed to OpenAI's image API to generate a high-quality image.
  Send Image: The final image is sent back to the user on Telegram.
  (Optional) Log image titles and links to Google Drive and Google Sheets.

  ⚙️ Setup Instructions

  📋 Prerequisites

  [ ] n8n installed (Self-hosted or via n8n.cloud)
  [ ] Telegram bot token (via @BotFather)
  [ ] OpenAI API key (platform.openai.com)
  [ ] Google Sheets & Drive OAuth2 credentials (optional)

  🧠 Step-by-Step Configuration

  1. 📥 Import the Workflow

  Go to n8n → click Import → upload PromptCraft_AI_Template.json

  2. 🔐 Set Up Credentials

  In Credentials, add the following:

    Telegram API → Paste your bot token
    OpenAI API → Paste your OpenAI API key
    (Optional) Google Sheets OAuth2, Google Drive OAuth2

  3. 🔄 Replace Placeholders

  Open each node that requires credentials:

    Replace REPLACE_OPENAI_API_KEY with your actual OpenAI API key
    Replace REPLACE_TELEGRAM_API_ID and credential names as needed
    (Optional) Update Google Drive Folder ID & Sheet ID in respective nodes

  4. ✅ Activate the Workflow

  Turn on the Telegram Trigger node.
  Deploy and activate the full workflow.

  5. ✉️ Test It Out

  Send your Telegram bot a message like:

    &gt; a knight riding a robotic horse in the future

  Receive the generated image back in Telegram!

  💡 Pro Tips

  Use detailed or imaginative inputs for better outputs.
  Fine-tune the GPT prompt for specific visual styles.
  Extend with Google Vision, image upscaling, or watermarking.

  🛟 Support

  For setup assistance or custom feature requests, feel free to contact me @dimejicole21@gmail.com

  Happy Prompting! 🖼✨

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleDrive","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.telegramTrigger","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote"]

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name: Generate AI Media with ComfyUI: Images, Video, 3D & Audio Bridge
author_name: Nielo
author_username: anomali
categories: []
created_at: 2025-05-28T18:41:49.542Z
updated_at: 2025-05-28T18:41:49.542Z
url: https://n8n.io/workflows/4468
scraped_at: 2025-12-24 13:02:42
description:
  Unlock low-cost, high-control generative media workflows directly from n8n by integrating with ComfyUI. Ideal for indie creators, AI developers, or small teams seeking scalable media automation—from images to video, 3D, and even audio—this workflow makes generative content production more flexible and programmable than ever.

  How it works

  Accept a media generation request via an n8n trigger (HTTP webhook, schedule, etc.)
  Parse input and inject it into a ComfyUI payload
  Send the payload to your local or remote ComfyUI instance
  Wait for and collect the output media files (e.g., images, videos, 3D models, or audio)
  Send the result to a destination like email, Telegram, S3, or upload it back to a CMS or client app

  ✨ The format and complexity of the media are entirely dependent on the ComfyUI workflow you use, meaning this n8n integration is as powerful and creative as your ComfyUI setups.

  Set up steps

  Set up and run a local or remote ComfyUI instance with API access enabled
  Load or create a ComfyUI workflow that suits your content goals (image gen, video stitching, etc.)
  Open this n8n template and set your ComfyUI server URL, input template, and output handling preferences
  Connect additional services for input (e.g., Airtable, HTTP) and output (e.g., Notion, Slack, S3) depending on your use case

nodes_used:
  ["n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.readWriteFile","n8n-nodes-base.convertToFile","n8n-nodes-base.merge","n8n-nodes-base.aggregate","n8n-nodes-base.discord","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","n8n-nodes-base.executeWorkflow","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.crypto","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.noOp","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.readWriteFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.set","n8n-nodes-base.readWriteFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: Jobs Newsletter Automation System (N8N, Bolt.new, RapidAPI, Mails.so & ChatGPT)
author_name: Joseph
author_username: mjomba
categories: []
created_at: 2025-05-28T19:53:27.231Z
updated_at: 2025-05-28T19:53:27.231Z
url: https://n8n.io/workflows/4470
scraped_at: 2025-12-24 13:02:44
description:
  Watch on Youtube▶️

  Welcome to this complete step-by-step guide on how to build your own newsletter automation system using n8n, Bolt.new, and RapidAPI. Whether you're a solo founder, indie hacker, or community builder, this setup will allow you to collect subscribers, send them curated job updates, and manage unsubscriptions — all with full control and zero reliance on third-party newsletter tools.

  🚀 Goal of This Guide

  By the end of this guide, you will have a fully working system that allows you to:
  Collect user subscriptions from a modern frontend interface
  Send welcome or rejection emails (using your own SMTP)
  Automatically scrape jobs via an API and send them to subscribers weekly or daily
  Manage unsubscriptions with confirmation and webhook logic
  Customize and manage all this using n8n workflows with no-code/low-code skills

  This system is perfect for niche job boards, community newsletters, or any project that needs automated content delivery to subscribers.

  🧱 Tools You'll Be Using

  n8n** – for automation workflows and acting as your backend
  Bolt.new** – to build your newsletter landing page and subscription interface
  Google Sheets** – to act as your lightweight subscriber/job database
  RapidAPI** – to pull job listings from the Jobs Search API
  Custom SMTP Email (Optional)** – to send branded emails using your own domain

  📄 Step 1: Set Up Your Google Sheets Database

  Make a copy of this Google Sheets template that will serve as your database:

  🔗 Click here to copy the Google Sheet template](https://docs.google.com/spreadsheets/d/11vxYkjfwIrnNHN6PIdAOa_HZdTvMXI0lm_Jecac4YO0/edit?gid=0#gid=0)

  This includes:
  A Subscribers sheet to store new signups
  An Unsubscribers sheet to prevent duplicates
  A Jobs sheet to store scraped job listings

  ⚙ Step 2: Get Your API Key for Jobs Scraping

  We use this API from RapidAPI to pull job listings programmatically:

  🔗 Jobs Search API on RapidAPI

  Sign up or log into RapidAPI
  Subscribe to the Jobs Search API
  Copy your API key — you'll need this in n8n

  ⚙ Step 3: Get Your API Key for Email Validation

  We use this API from Mails.so to confirm email's validity before adding them to our database:

  🔗 Mails.so API

  Sign up or log into mails dot so
  Visit the dashboard, then click on API
  Copy the cURL command and import on http request node

  🌐 Step 4: Set Up Your Frontend with Bolt.new

  You'll be building a beautiful, modern newsletter landing page using Bolt.new.

  Use this link for prompts to generate:
  Your landing page
  Email templates (welcome, already subscribed, unsubscribe confirmation)
  Terms & Privacy Policy pages
  Unsubscribe confirmation page

  🔗 Access the Bolt.new Prompt Document

  This includes:
  A homepage form with input fields (Name, Email) and consent checkbox
  Logic to send data to n8n webhook using fetch()
  UI logic for showing webhook response (Success, Already Exists, Invalid Email)
  Unsubscribe page handling

  (Make your own copy so that you can edit it while we format the prompts)

  📤 Step 5: Set Up Email Sending With Your Custom Domain (Optional but Recommended)

  To send branded HTML emails from your own domain, follow this tutorial to configure SMTP properly on n8n with your cPanel email account:

  🔗 Guide: How to Set Up SMTP with cPanel Email on n8n

  This setup helps:
  Improve deliverability
  Avoid Gmail spam filters
  Send beautiful HTML emails you can customize fully

  🔄 Step 6: Create n8n Workflows for Subscription Management

  In n8n, you'll need to build these workflows:

  ✅ 1. Handle Subscriptions
  Receives webhook from frontend with name and email
  Validates email (using mails.so)
  Checks if already subscribed
  Sends appropriate HTML email (Welcome, Already Exists, Invalid Email)
  Adds to Google Sheet database

  ✅ 2. Scrape Jobs and Email Subscribers
  Use Cron node to run daily/weekly
  Use RapidAPI to fetch new jobs
  Format jobs into readable HTML
  Send jobs to all active subscribers via SMTP

  ✅ 3. Handle Unsubscriptions
  Expose a webhook for /unsubscribe
  Confirm email, show a button
  On confirmation, add email to Unsubscribers sheet
  Show feedback and redirect user back to homepage after 2 seconds

  🧠 What You're Learning Along the Way

  How to use n8n as a backend service (reliable, scalable, visual)
  How to use webhooks to connect frontend and backend logic
  How to scrape APIs, format JSON data, and convert it to HTML emails
  How to use Function nodes for data processing
  How to build logic with IF and Switch nodes
  How to design a minimal, clean frontend with Bolt.new
  How to control the entire newsletter system without external platforms

  Follow me on twitter @juppfy | or check out my agency website.

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.httpRequest","n8n-nodes-base.emailSend","n8n-nodes-base.if","n8n-nodes-base.merge","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.splitOut","n8n-nodes-base.merge","n8n-nodes-base.aggregate","n8n-nodes-base.aggregate","n8n-nodes-base.webhook","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.emailSend","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stopAndError","n8n-nodes-base.if","n8n-nodes-base.emailSend","n8n-nodes-base.emailSend","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: Github Webhook-Based n8n Workflow Import Template
author_name: Dave Bernier
author_username: dbern
categories: []
created_at: 2025-05-28T21:24:41.338Z
updated_at: 2025-05-28T21:24:41.338Z
url: https://n8n.io/workflows/4471
scraped_at: 2025-12-24 13:02:42
description:
  This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. 

  This template aims to ease the process of deploying workflows from github. It has a companion repository that developers might find useful{. See below for more details

  How it works

  Automatically import and deploy n8n workflows from your GitHub repository to your production n8n instance using a secured webhook-based approach. This template enables teams to maintain version control of their workflows while ensuring seamless deployment through a CI/CD pipeline.

  Receives webhook notifications from GitHub when changes are pushed to your repository
  Lists all files in the repository and filters for .json workflow files
  Downloads each workflow file and saves it locally
  Imports all workflows into n8n using the CLI import command
  Cleans up temporary files after successful import

  To trigger the deployment, send a POST request to your webhook with the set up credentials (basic auth) with the following body:
  {
    "owner": "GITHUB_REPO_OWNER_NAME",
    "repository": "GITHUB_REPOSITORY_NAME"
  }

  Set up steps
  Once importing this template in n8n :
  Setup the webhook basic auth credentials
  Setup the github credentials
  Activate the workflow !

  Companion repository
  There is a companion repository located at https://github.com/dynamicNerdsSolutions/n8n-git-flow-template that has a Github action already setup to work with this workflow.

  It provides a complete development environment with:
  Local n8n instance via Docker
  Automated workflow export and commit scripts
  Version control integration
  CI/CD pipeline setup

  This setup allows teams to maintain a clean separation between development and production environments while ensuring reliable workflow deployment.

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.noOp","n8n-nodes-base.executeCommand","n8n-nodes-base.stickyNote","n8n-nodes-base.github","n8n-nodes-base.splitInBatches","n8n-nodes-base.if","n8n-nodes-base.github","n8n-nodes-base.readWriteFile","n8n-nodes-base.executeCommand"]

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name: AI-Powered Loom Video Q&A with Gemini-2.5 and Slack Notifications
author_name: GiovanniSegar
author_username: giosegar
categories: []
created_at: 2025-05-28T21:48:31.259Z
updated_at: 2025-05-28T21:48:31.259Z
url: https://n8n.io/workflows/4472
scraped_at: 2025-12-24 13:02:44
description:
  How to use the workflow
  This workflow takes a Loom link, extracts the video ID, uses the Loom API to download the video, then sends it to Gemini along with your question. Finally, it sends the output to Slack. 

  To use it, you just need to add your own API key for Gemini and Slack connection. 

  Click the link above to get your Gemini API key, then add a generic "Query auth" type credential in n8n. The name will be "key" and the value will be your API key.

  One way to customize this workflow would be to make the trigger any received email, extract the Loom link, and run an auto-prompt like "Describe this video in detail". 

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.formTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.set","n8n-nodes-base.wait","n8n-nodes-base.splitInBatches","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.slack","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5924 characters]


name: Automate Multi-Channel Customer Support with Gmail, Telegram, and GPT AI
author_name: RedOne
author_username: redone
categories: []
created_at: 2025-05-29T05:09:06.053Z
updated_at: 2025-05-29T05:09:06.053Z
url: https://n8n.io/workflows/4474
scraped_at: 2025-12-24 13:02:42
description:
  Smart Customer Support AI Agent with Gmail and Telegram

  Who is this for?

  This workflow is perfect for:
  Small to medium businesses** looking to automate customer support
  E-commerce stores** handling order inquiries and customer questions
  SaaS companies** providing technical support to users
  Service providers** managing appointment bookings and general inquiries
  Startups** wanting to provide 24/7 customer service without hiring full-time staff
  Agencies** managing client communications across multiple channels

  What problem is this workflow solving?

  Customer support is essential but resource-intensive. Common challenges include:
  Slow response times** leading to frustrated customers
  Repetitive questions** consuming valuable staff time
  Inconsistent responses** across different support agents
  Limited availability** outside business hours
  Scaling support costs** as business grows
  Context loss** when customers switch between channels

  This workflow eliminates these pain points by providing instant, consistent, and intelligent responses 24/7.

  What this workflow does

  Core Functionality
  Multi-Channel Monitoring: Simultaneously watches Gmail and Telegram for customer inquiries
  Intelligent Processing: Uses AI to understand customer intent and context
  Knowledge Base Integration: Accesses your company's FAQ and support information
  Contextual Responses: Provides personalized, helpful replies maintaining conversation history
  Smart Escalation: Automatically escalates complex issues to human agents
  Comprehensive Logging: Tracks all interactions for analytics and improvement

  AI Agent Capabilities
  Natural Language Understanding**: Comprehends customer questions in plain English
  Context Awareness**: Remembers previous conversations with each customer
  Knowledge Retrieval**: Searches your knowledge base for accurate information
  Response Generation**: Creates professional, brand-appropriate responses
  Escalation Decision**: Identifies when human intervention is needed
  Multi-Channel Support**: Handles Gmail and Telegram with channel-specific formatting

  Automation Features
  Auto-Response**: Replies to customers within seconds
  Email Management**: Marks processed emails as read
  Conversation Threading**: Maintains context in email threads and Telegram chats
  Error Handling**: Gracefully handles failures with admin notifications
  Analytics Tracking**: Logs interactions for performance monitoring

  Setup

  Prerequisites
  Active Google Workspace or Gmail account
  Telegram account for bot creation
  OpenAI API access
  Google Sheets access
  n8n instance (cloud or self-hosted)

  Step 1: Credential Setup

  Gmail OAuth2 Configuration
  Go to Google Cloud Console
  Create new project or select existing one
  Enable Gmail API
  Create OAuth 2.0 credentials
  Add authorized redirect URIs for n8n
  In n8n: Settings → Credentials → Add Gmail OAuth2
  Enter Client ID and Client Secret
  Complete OAuth flow

  Telegram Bot Setup
  Message @BotFather on Telegram
  Create new bot with /newbot command
  Choose bot name and username
  Copy the bot token
  In n8n: Settings → Credentials → Add Telegram
  Enter bot token
  Set webhook URL in bot settings

  OpenAI API Configuration
  Sign up at OpenAI Platform
  Generate API key in API Keys section
  In n8n: Settings → Credentials → Add OpenAI
  Enter API key
  Choose appropriate model (gpt-4o-mini recommended)

  Google Sheets Setup
  Use existing Google account from Gmail setup
  In n8n: Settings → Credentials → Add Google Sheets OAuth2
  Complete authorization flow

  Step 2: Google Sheets Preparation

  Create three Google Sheets in your Google Drive:

  Knowledge Base Sheet
  Sheet Name**: "Knowledge Base"
  Columns**: ID, Category, Question/Topic, Answer/Response, Keywords, Last_Updated
  Import sample data from the Knowledge Base example
  Customize with your company's FAQs and policies

  Escalation Tracker Sheet
  Sheet Name**: "Escalations" 
  Columns**: Timestamp, Customer_Name, Customer_Contact, Inquiry_Summary, Escalation_Reason, Priority, Status, Assigned_To
  This will be auto-populated by the AI agent

  Interaction Log Sheet
  Sheet Name**: "Interaction Log"
  Columns**: Timestamp, Channel, Customer_Name, Customer_Contact, Inquiry_Subject, Customer_Message, AI_Response, Response_Time, Status
  This tracks all customer interactions for analytics

  Step 3: Workflow Configuration

  Import Template
  Copy the workflow JSON from the template
  In n8n: Import workflow from JSON
  Replace placeholder Sheet IDs with your actual Google Sheet IDs

  Update Sheet References
  Open each Google Sheets node
  Select your created sheets from the dropdown
  Verify column mappings match your sheet structure

  Customize AI Prompts
  Edit the "Customer Support AI Agent" node
  Update system message with:
     Your company name and description
     Brand voice and tone guidelines
     Specific policies and procedures
     Escalation criteria

  Configure Error Notifications (Optional)
  Set up Slack webhook or email notifications
  Update error notification node with your webhook URL
  Customize error message format

  Step 4: Testing

  Test Gmail Integration
  Send test email to your support Gmail account
  Check workflow execution in n8n
  Verify response is sent and email marked as read
  Check interaction logging in Google Sheets

  Test Telegram Integration  
  Send message to your Telegram bot
  Verify bot responds appropriately
  Test conversation memory with follow-up messages
  Check escalation functionality with complex request

  Test Knowledge Base
  Ask questions covered in your knowledge base
  Verify AI retrieves and uses correct information
  Test with variations of the same question
  Ensure responses are consistent and helpful

  How to customize this workflow to your needs

  Brand Voice Customization
  Update the AI system prompt to include:
  Your company's tone (formal, casual, friendly)
  Key phrases and terminology you use
  Brand personality traits
  Communication style preferences

  Knowledge Base Expansion
  Add industry-specific FAQs
  Include product documentation
  Add troubleshooting guides
  Create category-specific responses

  Escalation Rules
  Customize when to escalate by modifying the AI agent instructions:
  Billing disputes over $X amount
  Technical issues requiring developer help
  Angry or dissatisfied customers
  Requests outside standard services
  Legal or compliance questions

  Additional Channels
  Extend the workflow to support:
  Slack**: Add Slack triggers and response nodes
  WhatsApp**: Integrate WhatsApp Business API
  Web Chat**: Add webhook triggers for website chat
  Discord**: Connect Discord bot integration

  Analytics Enhancement
  Add sentiment analysis to customer messages
  Implement customer satisfaction scoring
  Create automated reporting dashboards
  Set up alert thresholds for escalation rates

  Integration Opportunities
  CRM Integration**: Connect to HubSpot, Salesforce, or Pipedrive
  Ticketing System**: Link to Zendesk, Freshdesk, or Jira Service Desk
  E-commerce Platform**: Integrate with Shopify, WooCommerce, or Magento
  Calendar Booking**: Connect to Calendly or Acuity for appointment scheduling

  Advanced Features
  Multi-language Support**: Add translation capabilities
  Voice Messages**: Integrate speech-to-text for Telegram voice notes
  Image Recognition**: Process customer screenshots for technical support
  Proactive Outreach**: Send follow-up messages based on customer behavior

  Workflow Maintenance

  Daily Tasks
  Review escalation queue
  Monitor error notifications
  Check response quality in interaction log

  Weekly Reviews
  Analyze customer interaction patterns
  Update knowledge base with new common questions
  Review escalation reasons and optimize AI prompts

  Monthly Optimization
  Export interaction data for detailed analysis
  Calculate key metrics (response time, resolution rate, escalation rate)
  Update AI model parameters based on performance
  Expand knowledge base with seasonal or trending topics

  Key Metrics to Track

  Response Time**: Average time from customer message to AI response
  Resolution Rate**: Percentage of inquiries resolved without escalation  
  Customer Satisfaction**: Based on follow-up surveys or sentiment analysis
  Escalation Rate**: Percentage of conversations requiring human intervention
  Channel Performance**: Effectiveness of Gmail vs Telegram vs other channels
  Knowledge Base Usage**: Which topics are accessed most frequently
  Peak Hours**: When customers contact support most often

  Troubleshooting

  Common Issues
  Gmail not triggering**: Check OAuth permissions and API quotas
  Telegram bot not responding**: Verify bot token and webhook configuration
  AI responses seem off**: Review and update system prompts
  Escalations not logging**: Check Google Sheets permissions and column mapping
  High escalation rate**: Expand knowledge base and refine AI instructions

  Performance Optimization
  Monitor OpenAI API usage and costs
  Adjust AI model temperature for response consistency
  Optimize knowledge base for faster searches
  Set appropriate conversation memory limits

  This workflow provides a solid foundation for automated customer support that can be extensively customized to match your specific business needs and grow with your company.

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name: MCP Server with AI Agent as a Tool Context Reducer
author_name: William Lettieri
author_username: fibonacci
categories: []
created_at: 2025-05-29T05:17:43.176Z
updated_at: 2025-05-29T05:17:43.176Z
url: https://n8n.io/workflows/4475
scraped_at: 2025-12-24 13:02:44
description:
  Overview

  Transform your LLM into a powerful GitHub automation specialist with this n8n workflow template. In a world where multiple MCP servers can overwhelm LLMs with context, this streamlined solution provides a dedicated GitHub Agent that handles all GitHub API operations through a single, specialized tool.

  When you need GitHub operations like creating repositories, managing issues, or handling pull requests, your LLM can make one simple call to the GitHub Agent. This agent specializes exclusively in GitHub MCP server operations, offloading all contextual complexity and providing clean, efficient GitHub automation.

  ✨ Features

  Single MCP Server Trigger** - One tool and one parameter to handle all GitHub API interactions  
  Specialized GitHub Agent** - Dedicated AI agent with direct GitHub MCP Server connection
  Self-Executing Workflow** - "When Executed by Another Workflow" trigger enables seamless workflow chaining
  Scalable Architecture** - Ready to integrate with unlimited GitHub tools and operations
  Context Optimization** - Reduces LLM token usage by delegating GitHub complexity to a specialized agent
  Flexible Request Processing** - Handles any GitHub operation through natural language requests

  🎯 Use Cases

  Repository Management** - Create, clone, and manage repositories programmatically
  Issue Tracking** - Automate issue creation, updates, and management workflows  
  Pull Request Automation - Streamline code review and merge processes
  GitHub Actions Integration** - Trigger and monitor CI/CD workflows
  Team Collaboration** - Automate notifications and team management tasks
  Documentation Updates** - Automatically update README files and documentation

  🏗️ Workflow Architecture

  Node Breakdown:
  MCP Server Trigger - Receives requests with GitHub operation parameters
  Set GitHub Username - Configures GitHub user context for API calls  
  OpenAI Chat Model - Powers the intelligent GitHub agent with contextual understanding
  Simple Memory - Maintains conversation context and operation history
  GitHub AI Agent - Specialized Tools Agent with direct GitHub MCP Server access

  [MCP Server Trigger] → [Set GitHub Username] → [GitHub AI Agent]
                                  ↓
  [OpenAI Chat Model] ← [Simple Memory] ← [GitHub API Operations]

  📋 Requirements

  Essential Prerequisites:
  ✅ OpenAI API Key - For AI Agent and Chat Model functionality
  ✅ GitHub Username Configuration - Edit the "Set GitHub Username" node with your GitHub username for API calls
  ✅ n8n Version - Compatible with n8n 2024+ releases
  ✅ MCP Server Setup - Existing GitHub MCP server configuration

  Recommended Setup:
  GitHub Personal Access Token with appropriate permissions
  Basic understanding of n8n workflow configuration
  Familiarity with GitHub API operations

  🚀 Setup Instructions

  Step 1: Import and Configure
  Import the workflow template into your n8n instance
  Navigate to the Set GitHub Username node
  Replace the placeholder with your actual GitHub username

  Step 2: API Keys Setup
  Configure your OpenAI API key in the Chat Model node
  Ensure your GitHub credentials are properly configured in n8n
  Test the connection to verify API access

  Step 3: MCP Server Integration  
  Connect your existing GitHub MCP server to the workflow
  Verify the MCP Server Trigger is properly configured
  Test with a simple GitHub operation (e.g., "List my repositories")

  Step 4: Deploy and Test
  Activate the workflow in your n8n instance
  Test with various GitHub operations to ensure functionality
  Monitor execution logs for any configuration issues

  🔧 Customization Options

  Agent Behavior
  Modify the Chat Model prompt** to adjust agent personality and response style
  Configure memory settings** to control conversation context retention
  Adjust timeout settings** for long-running GitHub operations

  GitHub Operations
  Extend supported operations** by adding new GitHub API endpoints
  Configure repository filters** to limit scope of operations
  Set up notification preferences** for important GitHub events

  Integration Points
  Webhook triggers** for real-time GitHub event processing
  Scheduled operations** for regular repository maintenance
  Cross-workflow triggers** for complex automation chains

  💡 Pro Tips

  Start Simple**: Begin with basic operations like repository listing before attempting complex workflows
  Monitor Token Usage**: The specialized agent approach significantly reduces OpenAI API costs
  Batch Operations**: Group related GitHub operations in single requests for efficiency
  Error Handling**: The agent provides detailed error messages for troubleshooting

  🤝 Support and Community

  Documentation**: Official n8n Documentation
  Community Forum**: n8n Community
  Issues & Contributions**: Feel free to suggest improvements or report issues

  📄 License

  This workflow template is provided under the MIT License. You're free to use, modify, and redistribute with attribution.

  Created by: William Lettieri
  Version: 1.0  
  Last Updated: May 28, 2025  
  Compatibility: n8n 2024+

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workflow_json_compressed:
  [encoded data, 4492 characters]


name: AI-Powered Knowledge Assistant using Google Sheets, OpenAI, and Supabase Vector Search
author_name: Alex Huy
author_username: alexhuy
categories: []
created_at: 2025-05-29T05:29:03.045Z
updated_at: 2025-05-29T05:29:03.045Z
url: https://n8n.io/workflows/4476
scraped_at: 2025-12-24 13:02:44
description:
  Description
  An intelligent conversational AI system that provides contextual responses by combining chat history, vector database knowledge retrieval, and web search capabilities.
  How it Works (High-level steps)

  Message Detection: Google Sheets trigger monitors for new user messages and filters out already-processed entries
  Context Preparation: Extracts user message, retrieves chat history, and formats conversation context with system prompt
  Knowledge Retrieval: AI agent searches vector database for relevant context using Supabase + OpenAI embeddings
  Response Generation: LangChain agent processes the request using:

  OpenAI GPT-4 language model
  Vector store tool for knowledge base queries
  SerpAPI tool for web search when needed
  Buffer memory for conversation continuity


  Response Storage: Updates Google Sheets with AI response and assigns unique timestamp ID

  Setup Steps

  Configure Google Sheets with columns: user_message, ai_respond, id
  Set up Supabase vector store with OpenAI embeddings
  Connect OpenAI API credentials (GPT-4 + embeddings)
  Configure SerpAPI for web search functionality
  Set up Google Sheets trigger and update permissions

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name: AI-Powered Knowledge Assistant using Google Sheets, OpenAI, and Supabase Vector Search
author_name: Akhil Varma Gadiraju
author_username: akhilv7
categories: []
created_at: 2025-05-29T06:47:19.887Z
updated_at: 2025-05-29T06:47:19.887Z
url: https://n8n.io/workflows/4477
scraped_at: 2025-12-24 13:02:44
description:
  AI-Powered GitHub Commit Reviewer

  Overview

  Workflow Name: AI-Powered GitHub Commit Reviewer  
  Author: Akhil  
  Purpose: This n8n workflow triggers on a GitHub push event, fetches commit diffs, formats them into HTML, runs an AI-powered code review using Groq LLM, and sends a detailed review via email.

  How It Works (Step-by-Step)

  1. GitHub Trigger
  Node Type**: n8n-nodes-base.githubTrigger
  Purpose**: Initiates the workflow on GitHub push events.
  Repo**: akhilv77/relevance
  Output**: JSON with commit and repo details.

  2. Parser
  Node Type**: n8n-nodes-base.set
  Purpose**: Extracts key info (repo ID, name, commit SHA, file changes).

  3. HTTP Request
  Node Type**: n8n-nodes-base.httpRequest
  Purpose**: Fetches commit diff details using GitHub API.
  Auth**: GitHub OAuth2 API.

  4. Code (HTML Formatter)
  Node Type**: n8n-nodes-base.code
  Purpose**: Formats commit info and diffs into styled HTML.
  Output**: HTML report of commit details.

  5. Groq Chat Model
  Node Type**: @n8n/n8n-nodes-langchain.lmChatGroq
  Purpose**: Provides the AI model (llama-3.1-8b-instant).

  6. Simple Memory
  Node Type**: @n8n/n8n-nodes-langchain.memoryBufferWindow
  Purpose**: Maintains memory context for AI agent.

  7. AI Agent
  Node Type**: @n8n/n8n-nodes-langchain.agent
  Purpose**: Executes AI-based code review.
  Prompt**: Reviews for bugs, style, grammar, and security. Outputs styled HTML.

  8. Output Parser
  Node Type**: n8n-nodes-base.code
  Purpose**: Combines commit HTML with AI review into one HTML block.

  9. Gmail
  Node Type**: n8n-nodes-base.gmail
  Purpose**: Sends review report via email.
  Recipient**: akhilgadiraju@gmail.com

  10. End Workflow
  Node Type**: n8n-nodes-base.noOp
  Purpose**: Marks the end.

  Customization Tips

  GitHub Trigger**: Change repo/owner or trigger events.
  HTTP Request**: Modify endpoint to get specific data.
  AI Agent**: Update the prompt to focus on different review aspects.
  Groq Model**: Swap for other supported LLMs if needed.
  Memory**: Use dynamic session key for per-commit reviews.
  Email**: Change recipient or email styling.

  Error Handling

  Use Error Trigger nodes to handle failures in:
  GitHub API requests
  LLM generation
  Email delivery

  Use Cases

  Instant AI-powered feedback on code pushes.
  Pre-human review suggestions.
  Security and standards enforcement.
  Developer onboarding assistance.

  Required Credentials

  | Credential | Used By | Notes |
  |-----------|---------|-------|
  | GitHub API (ID PSygiwMjdjFDImYb) | GitHub Trigger | PAT with repo and admin:repo_hook |
  | GitHub OAuth2 API | HTTP Request | OAuth2 token with repo scope |
  | Groq - Akhil (ID HJl5cdJzjhf727zW) | Groq Chat Model | API Key from GroqCloud |
  | Gmail OAuth2 - Akhil (ID wqFUFuFpF5eRAp4E) | Gmail | Gmail OAuth2 for sending email |

  Final Note

  Made with ❤️ using n8n by Akhil.

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name: Auto-Publish YouTube Videos to Facebook & Instagram with AI-Generated Captions
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-29T07:09:15.501Z
updated_at: 2025-05-29T07:09:15.501Z
url: https://n8n.io/workflows/4478
scraped_at: 2025-12-24 13:02:41
description:
  Automatically turn your YouTube videos into engaging Facebook and Instagram posts with AI-generated captions.

  This powerful workflow monitors your YouTube channel for new uploads, generates engaging social media captions using AI, and automatically publishes to both Facebook pages and Instagram business accounts - maximizing your content reach across all major platforms.

  🚀 What It Does

  YouTube Channel Monitoring: Watches your YouTube RSS feed hourly for new video uploads and triggers cross-platform publishing

  AI Caption Generation: Uses GPT-4 to create engaging, platform-optimized social media captions with emojis and calls-to-action

  Facebook Auto-Publishing: Posts directly to your Facebook page with AI-generated captions and video links

  Instagram Business Posting: Creates Instagram posts using YouTube thumbnails as images with custom captions

  Smart Error Handling: Continues workflow even if one platform fails, ensuring maximum post distribution

  🎯 Key Benefits

  ✅ 3x Content Reach: Automatically distribute YouTube content across major social platforms  
  ✅ Save 5+ Hours Weekly: Eliminate manual cross-posting and caption writing  
  ✅ AI-Optimized Captions: Professional, engaging content tailored for social media  
  ✅ Instant Publishing: New YouTube videos become social posts within 1 hour  
  ✅ Professional Thumbnails: Uses high-quality YouTube thumbnails for Instagram  
  ✅ Set & Forget: Complete automation once configured  

  🏢 Perfect For

  Content Creators & YouTubers
  Individual creators maximizing content distribution
  Educational channels expanding social reach
  Entertainment creators building multi-platform presence
  Business channels driving traffic from social media

  Business Applications
  Brand Awareness**: Increase visibility across all major social platforms
  Traffic Generation**: Drive social media traffic back to YouTube content
  Audience Growth**: Reach different demographics on each platform
  Content Amplification**: Maximize ROI from video content creation

  ⚙️ What's Included

  Complete Cross-Platform Workflow: Ready-to-deploy multi-platform publishing system
  YouTube RSS Integration: Automatic monitoring of your channel for new uploads
  AI Caption Engine: GPT-4 powered social media caption generation
  Facebook Publishing: Direct integration with Facebook Pages API
  Instagram Business Integration: Full Instagram Business account posting capability
  Error-Resistant Design: Robust system continues working even if one platform fails

  🔧 Setup Requirements

  n8n Platform**: Cloud or self-hosted instance
  YouTube Channel**: RSS feed for monitoring new uploads
  Meta Developer Account**: Facebook app with required permissions
  OpenAI API**: GPT-4 access for caption generation
  Long-lived Access Token**: For Facebook and Instagram API access

  📊 Required Meta API Permissions

  Required Permissions:
  ✅ pages_manage_posts
  ✅ pages_read_engagement  
  ✅ pages_show_list
  ✅ instagram_content_publish
  ✅ instagram_basic

  Token Type: Long-lived access token
  API Version: v22.0

  🎨 Sample AI Caption Generation

  YouTube Video: "10 Tips for Better Photography"

  Generated Social Caption:
  📸 Just dropped my latest photography tutorial! 

  Discover 10 game-changing tips that will transform your photos from amateur to professional. Whether you're just starting out or looking to level up your skills, these techniques will make a huge difference! 

  ✨ What you'll learn:
  • Composition secrets the pros use
  • Lighting techniques for any situation  
  • Camera settings that actually matter

  Which tip surprised you the most? Drop a comment below! 👇

  Watch the full tutorial: [YouTube Link]

  #Photography #Tutorial #PhotoTips #ContentCreator #Learn

  🎯 Customization Options

  Caption Personalization: Adjust AI prompts for your brand voice, hashtags, and audience
  Platform-Specific Formatting: Different caption styles for Facebook vs Instagram
  Posting Schedule: Modify monitoring frequency (hourly, daily, custom intervals)
  Multiple Channels: Monitor multiple YouTube channels with different posting strategies
  Content Filtering: Add filters for specific video types or topics
  Brand Integration: Include consistent branding elements and calls-to-action

  🏷️ Tags & Categories

  #youtube-automation #social-media-publishing #cross-platform-marketing #facebook-automation #instagram-business #content-distribution #ai-caption-generation #social-media-management #multi-platform-posting #youtube-marketing #content-amplification #social-media-automation #creator-tools #video-marketing #workflow-automation

  💡 Use Case Examples

  Educational Creator: Automatically share tutorial videos across platforms to reach students on different social networks

  Product Review Channel: Distribute review videos to Facebook and Instagram to drive traffic and affiliate sales

  Business Coach: Share valuable content across platforms to build authority and attract consulting clients

  Entertainment Channel: Maximize viral potential by instantly distributing funny videos across all major platforms

  🛠️ Setup & Support

  Quick Configuration: Complete setup in 45 minutes with Meta Developer account and API tokens
  Template Access Tokens: Instructions for generating long-lived Facebook/Instagram tokens
  Channel Integration: Simple YouTube RSS feed configuration for any channel
  Testing Protocol: Built-in error handling and testing procedures

  📞 Get Help & Resources


  YouTube: https://www.youtube.com/@YaronBeen/videos

  💼 Social Media Automation Support  
  LinkedIn: https://www.linkedin.com/in/yaronbeen/

  📧 Technical Configuration Help  
  Email: Yaron@nofluff.online - Response within 24 hours

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name: AI-Powered Candidate Screening and Evaluation Workflow using OpenAI and Airtable
author_name: Billy Christi
author_username: billy
categories: []
created_at: 2025-05-29T11:06:09.128Z
updated_at: 2025-05-29T11:06:09.128Z
url: https://n8n.io/workflows/4481
scraped_at: 2025-12-24 13:02:44
description:
  Who is this for?

  This workflow is ideal for:

  HR professionals* and *recruiters** who want to automate and enhance the hiring process
  Organizations** seeking AI-driven, consistent, and data-backed candidate evaluations
  Hiring managers** using Airtable as their recruitment database

  What problem is this workflow solving?

  Screening candidates manually is time-consuming, inconsistent, and difficult to scale. This workflow solves that by:

  Automating resume intake and AI evaluation**
  Matching candidates to job postings dynamically**
  Generating standardized suitability reports**
  Notifying HR only when candidates meet the criteria**
  Storing all applications in a structured Airtable database**

  What this workflow does

  This workflow builds an end-to-end AI-powered hiring pipeline using Airtable, OpenAI, and Google Drive. Here's how it works:

  Accept candidate applications via a public web form, including resume upload (PDF only)
  Extract text from uploaded resumes for processing
  Store resumes in Google Drive and generate shareable links
  Match the application to a job posting stored in Airtable
  Use AI to evaluate candidates (via OpenAI GPT-4) against job descriptions and requirements
  Generate suitability results including:

     Match percentage
     Screening status: Suitable, Not Suitable, Under Review
     Detailed notes
  Combine AI output and files into one data object
  Create a new candidate record in Airtable with all application data
  Automatically notify HR via Gmail if a candidate is marked “Suitable”

  Setup

  View & Copy the Airtable base here:  
  👉 Candidate Screening – Airtable Base Template  
  Set up Google Drive folder
  Connect your OpenAI API key for the AI agent model
  Connect your Gmail account for email notifications
  Deploy the public-facing form to start receiving applications
  Test the workflow using a sample job and resume

  How to customize this workflow to your needs

  Expand file support**: Allow DOC or DOCX uploads by adding format conversion nodes
  Add multi-recipient email alerts**: Extend Gmail node for multiple HR recipients
  Handle “Under Review” differently**: Add additional logic to notify or flag these candidates
  Send rejection emails automatically**: Extend the IF branch for “Not Suitable” candidates
  Schedule interviews**: Integrate with Google Calendar or Calendly APIs
  Add Slack notifications**: Send alerts to team channels for real-time updates

  Contact me for consulting and support:   
  📧 billychartanto@gmail.com

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name: LinkedIn Post Automation with AI (GPT-4o) Generation & Slack Approval
author_name: Amit Mehta
author_username: amitswba
categories: []
created_at: 2025-05-29T11:20:45.319Z
updated_at: 2025-05-29T11:20:45.319Z
url: https://n8n.io/workflows/4483
scraped_at: 2025-12-24 13:02:42
description:
  LinkedIn Post Automation with AI Generation (Gpt-4o) & Slack Approval

  How it Works

  This workflow automates the creation and publishing of LinkedIn posts with AI-generated content and human approval via Slack, using Google Sheets, OpenAI (GPT-4), Slack Interactive Messages, and the LinkedIn API.

  Whether you're a social media manager, content creator, or marketing professional, this workflow helps you maintain consistent LinkedIn presence and scale content creation while keeping human oversight — all managed from a simple spreadsheet.

  🎯 Use Case

  Ideal for:
  Content Marketers** managing multiple LinkedIn accounts
  Personal Brand Builders** maintaining regular posting schedule  
  Agencies** handling client social media presence
  Teams** requiring content approval workflows

  Setup Instructions

  1. Prepare the Spreadsheet

  File name: Linkedin Post
  Main sheet structure:
  | ID | Linkedin Post Title | Status | Image URL |
  Groups sheet structure:
  | GroupIds |
  Add post topics and set their Status as Pending

  2. Configure Google Sheets Nodes

  Connect your Google account to:
  Linkedin-Post-Topic (Trigger node)
  Update-Status 
  Get-Group-id

  3. Add API Credentials

  OpenAI API Key** → for GPT-4 content generation
  Slack OAuth Token** → for approval messages
  LinkedIn Access Token** → for posting content
  HTTP Header Auth** → Bearer token for LinkedIn API

  4. Configure Webhooks

  Set up Slack Interactive Components webhook
  Point Request URL to your N8N webhook endpoint
  Enable interactive messages in Slack app

  5. Activate the Workflow

  Once live, the workflow will:
  Monitor spreadsheet for new topics every minute
  Generate LinkedIn post using GPT-4
  Send to Slack for approval/editing
  Upload image to LinkedIn
  Publish to profile and groups
  Update spreadsheet status to Posted

  🔁 Workflow Logic

  Trigger: New/updated row with Pending status
  Generate: AI creates engaging LinkedIn post
  Approve: Slack message for review/edit
  Process: Handle approval response
  Upload: Register and upload image
  Publish: Post to LinkedIn profile & groups
  Update: Mark as Posted in sheet

  🧩 Node Descriptions

  | Node Name | Description |
  |-----------|-------------|
  | Linkedin-Post-Topic | Monitors spreadsheet for new post topics |
  | Validate-Status | Filters only 'Pending' items |
  | Limit | Processes one item at a time |
  | Linedin-Post-Creator | Generates post content using GPT-4 |
  | Format-Content | Prepares content for Slack display |
  | Approval-on-Slack | Sends interactive approval message |
  | Webhook | Receives Slack button responses |
  | Format-Response | Extracts edited content from Slack |
  | Set-Final-Message | Prepares approved content |
  | Linkedin-User-Detail | Fetches LinkedIn user info |
  | Register Image | Initiates LinkedIn image upload |
  | Upload Image | Uploads image to LinkedIn |
  | Linkedin-post | Publishes to personal profile |
  | Get-Group-id | Retrieves LinkedIn group IDs |
  | Post-Linkedin-Groups | Posts to multiple groups |
  | Update-Status | Marks as completed in sheet |

  🛠️ Customization Tips

  Adjust AI prompt for brand voice and hashtags
  Change Slack approver or add multiple reviewers
  Modify posting schedule with delay nodes
  Add analytics tracking with additional API calls
  Filter groups based on specific criteria
  Include URL shortening for tracking

  📒 Suggested Sticky Notes for Workflow

  | Node/Section | Sticky Note Content |
  |--------------|---------------------|
  | Linkedin-Post-Topic | "Triggers every minute for new posts in your spreadsheet" |
  | Validate-Status | "Filters to process only 'Pending' items - prevents duplicates" |
  | Linedin-Post-Creator | "Uses GPT-4 to generate LinkedIn content - customize prompt for your brand voice" |
  | Approval-on-Slack | "Sends for human review - edit the Slack user to change approver" |
  | Webhook | "Receives approval responses - ensure URL is configured in Slack app" |
  | Register Image | "Initiates LinkedIn media upload - requires valid image URL from sheet" |
  | Linkedin-post | "Publishes to your profile - update with your LinkedIn credentials" |
  | Post-Linkedin-Groups | "Posts to multiple groups - add group IDs in Groups sheet" |
  | Update-Status | "Marks as 'Posted' to prevent reprocessing" |

  💡 AI Prompt Configuration

  The workflow uses a sophisticated prompt that:
  Creates compelling hooks
  Includes 3-4 informative paragraphs
  Adds engagement questions
  Inserts relevant emojis
  Generates 4-6 hashtags
  Formats with proper spacing

  🔒 Security & Permissions

  LinkedIn App Requirements:
  r_liteprofile - Read profile data
  r_emailaddress - Access email
  w_member_social - Post content
  rw_organization_admin - Group posting

  Slack Bot Permissions:
  chat:write - Send messages
  im:write - Direct messages
  users:read - User information

  📎 Required Components

  | Component | Purpose |
  |-----------|---------|
  | Google Sheet | Store post topics and status |
  | LinkedIn App | API access for posting |
  | Slack App | Interactive approval flow |
  | OpenAI Account | GPT-4 content generation |
  | N8N Instance | Workflow execution |

  🧪 Testing Tips

  Start with one test topic marked as Pending
  Verify Slack message appears correctly
  Test both "Approve" and "Edit" buttons
  Check image upload completes
  Confirm post appears on LinkedIn
  Verify status updates to Posted

  ⚠️ Common Issues & Solutions

  LinkedIn API Errors:
  Token expiration → Refresh access token
  Rate limits → Add delays between posts
  Group restrictions → Check posting permissions

  Slack Integration:
  Missing responses → Verify webhook URL
  Button not working → Check interactive components
  User not found → Confirm Slack user ID

  Image Upload Failures:
  Invalid URL → Validate image accessibility
  Size limits → Compress images under 10MB
  Format issues → Use JPEG or PNG only

  📊 Workflow Benefits

  Time Savings**: 80% reduction in content publishing time
  Consistency**: Regular posting schedule maintained
  Quality Control**: Human review ensures brand standards
  Scalability**: Handle multiple accounts and groups
  Flexibility**: Easy to modify and extend

  📎 Required Files

  | File Name | Purpose |
  |-----------|---------|
  | Linkedin Post | Google Sheet to hold post topics and status |

  🏷 Suggested Tags & Categories

  #LinkedIn
  #AI
  #ContentAutomation
  #SocialMedia
  #Slack
  #GPT4
  #Marketing
  #WorkflowAutomation

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name: Build a Voice AI Chatbot with ElevenLabs and InfraNodus Knowledge Experts
author_name: InfraNodus
author_username: infranodus
categories: []
created_at: 2025-05-29T11:25:45.230Z
updated_at: 2025-05-29T11:25:45.230Z
url: https://n8n.io/workflows/4484
scraped_at: 2025-12-24 13:02:41
description:
  Set Up ElevenLabs Voice Chat Agent using Graph RAG Knowledge Graphs as Experts

  This workflow creates an AI voice chatbot agent that has access to several knowledge bases at the same time (used as "experts"). 

  These knowledge bases are provided using the InfraNodus GraphRAG using the knowledge graphs and providing high-quality responses without the need to set up complex RAG vector store workflows.

  We use ElevenLabs to set up a voice agent that can be embedded to any website or used via their API.

  The advantages of using GraphRAG instead of the standard vector stores for knowledge are:

  Easy and quick to set up (no complex data import workflows needed) and to update with new knowledge
  A knowledge graph has a holistic overview of your knowledge base
  Better retrieval of relations between the document chunks = higher quality responses
  Ability to reuse in other n8n workflows

  How it works
  This template uses the n8n AI agent node as an orchestrating agent that decides which tool (knowledge graph) to use based on the user's prompt. 

  The user's prompt is received from the ElevenLabs Conversational AI agent via an n8n Webhook, which also takes care of the voice interaction. 

  The response from n8n is then sent to the Webhook, which is polled by the ElevenLabs voice agent. This agent processes the response and provides the final answer.

  Here's a description step by step:

  The user submits a question using ElevenLabs voice interface
  The question is sent via the knowledge_base tool in ElevenLabs to the n8n Webhook with the POST request containing the user's prompt and sessionID for Chat Memory node in n8n.
  The n8n AI agent node checks a list of tools it has access to. Each tool has a description of the knowledge auto-generated by InfraNodus (we call each tool an "expert"). 
  The n8n AI agent decides which tool should be used to generate a response. It may reformulate user's query to be more suitable for the expert. 
  The query is then sent to the InfraNodus HTTP node endpoint, which will query the graph that corresponds to that expert. 
  Each InfraNodus GraphRAG expert provides a rich response that takes the whole context into account and provides a response from each expert (graph) along with a list of relevant statements retrieved using a combination or RAG and GraphRAG. 
  The n8n AI Agent node integrates the responses received from the experts to produce the final answer.
  The final answer is sent back to the Webhook endpoint
  ElevenLabs conversational AI agent picks up the response arriving from the knowledge_base tool via the webhook and then condenses it for conversational format and transforms text into voice.

  How to use

  You need an InfraNodus GraphRAG API account and key to use this workflow. 

  Create an InfraNodus account
  Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes.
  Create a separate knowledge graph for each expert (using PDF / content import options) in InfraNodus
  For each graph, go to the workflow, paste the name of the graph into the body name field.
  Keep other settings intact or learn more about them at the InfraNodus access points page. 
  Once you add one or more graphs as experts to your flow, add the LLM key to the OpenAI node and launch the workflow
  You will also need to set up an ElevenLabs account and to set up a conversational AI agent there. See the Post note in the n8n workflow for a complete step-by-step description or our support article on setting up ElevenLabs AI voice agent
  Once the voice AI agent is ready, you might want to combine it with a text AI chatbot workflow so your users have a choice between the text and voice interaction. In that case, you may be interested to use our free open-source website popup chat widget popupchat.dev where you can create an embed code to add to your blog or website and allow the user to choose between the text and voice interaction.

  Requirements

  An InfraNodus account and API key
  An OpenAI (or any other LLM) API key
  An ElevenLabs account

  FAQ

  1. How many "experts" should I aim for?

  We recommend to aim for the number of experts as the optimal number of people in a team, which is usually 2-7. If you add more experts, your AI orchestrating agent will have troubles choosing the most suitable "expert" tool for the user's query. You can mitigate this by specifying in the AI agent description that it can choose maximum 3-7 experts to provide a response.

  2. Why use InfraNodus GraphRAG and not standard vector store for knowledge?

  First, vector stores are complex to set up and to update. You'd need a separate workflow for that, decide on the vector dimensions, add metadata to your knowledge, etc.
  With InfraNodus, you have a complete RAG / GraphRAG solution under the hood that is easy to set up and provides high-quality responses that takes the overall structure and the relations between your ideas into account. 

  3 Why not use ElevenLabs' own knowledge?

  One of the reasons is that you want your knowledge base to be in one place so you can reuse it in other n8n workflows. Another reason is that you will not have such a good separation between the "experts" when you converse with the agent. So the answers you get will be based on top matches from all the books / articles you upload, while with the InfraNodus GraphRAG setup you can better control which graphs are consulted as experts and have an explicit way to display this data.

  Customizing this workflow

  You can use this same workflow with a Telegram bot, so you can interact with it using Telegram. There are many more customizations available on our GitHub repo for n8n workflows.

  Check out the complete setup guide for this workflow at https://support.noduslabs.com/hc/en-us/articles/20318967066396-How-to-Build-a-Text-Voice-AI-Agent-Chatbot-with-n8n-Elevenlabs-and-InfraNodus

  Also check out the video tutorial with a demo:

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  ["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/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.webhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 8008 characters]


name: Telegram AI Chatbot Agent with InfraNodus GraphRAG Knowledge Base
author_name: InfraNodus
author_username: infranodus
categories: []
created_at: 2025-05-29T11:44:34.562Z
updated_at: 2025-05-29T11:44:34.562Z
url: https://n8n.io/workflows/4485
scraped_at: 2025-12-24 13:02:43
description:
  Using the knowledge graphs instead of RAG vector stores

  This workflow creates a Telegram chatbot agent that has access to several knowledge bases at the same time (used as "experts"). 

  These knowledge bases are provided using the InfraNodus GraphRAG using the knowledge graphs and providing high-quality responses without the need to set up complex RAG vector store workflows.

  The advantages of using GraphRAG instead of the standard vector stores for knowledge are:

  Easy and quick to set up and update (no complex data import workflows or vector stores needed)
  A knowledge graph has a holistic view of your knowledge base and knows what it's about
  Better retrieval of relations between the document chunks = higher quality responses

  How it works
  This template uses the n8n AI agent node as an orchestrating agent that decides which tool (knowledge graph) to use based on the user's prompt. 

  Here's a description step by step:

  The user submits a question using the Telegram bot, which is then received in the n8n workflow via the Telegram trigger node.
  The AI agent node checks a list of tools it has access to. Each tool has a description of the knowledge it has auto-generated by InfraNodus. 
  The AI agent decides which tool should be used to generate a response. It may reformulate user's query to be more suitable for the expert. 
  The query is then sent to the official InfraNodus Graph RAG Node or directly to the InfraNodus API via the HTTP node endpoint, which will query the graph that corresponds to that expert. 
  Each InfraNodus GraphRAG expert provides a rich response that takes the whole context into account and provides a response from each expert (graph) along with a list of relevant statements retrieved using a combination or RAG and GraphRAG. 
  The n8n AI Agent node integrates the responses received from the experts to produce the final answer.
  The final answer is sent back to the Telegram bot who delivers it back to the private chat or a Telegram group.

  How to use

  You need an InfraNodus GraphRAG API account and key to use this workflow. 

  Create an InfraNodus account
  Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes.
  Create a separate knowledge graph for each expert (using PDF / content import options) in InfraNodus
  For each graph, go to the workflow, paste the name of the graph into the body name field.
  Keep other settings intact or learn more about them at the InfraNodus access points page. 
  Once you add one or more graphs as experts to your flow, add the LLM key to the OpenAI node
  Create a Telegram bot (the instructions are in the workflow Post note) — it takes 30 seconds. Get its API key and create the Telegram credentials to use in the Telegram nodes in this workflow.

  Requirements

  An InfraNodus account and API key
  An OpenAI (or any other LLM) API key
  A Telegram account

  Customizing this workflow

  You can use this same workflow with a standard AI chatbot via a URL that can also be embedded to any website. You can also use it with ElevenLabs AI voice agent. There are many more customizations available. 

  Check out the complete guide at https://support.noduslabs.com/hc/en-us/articles/20174217658396-Using-InfraNodus-Knowledge-Graphs-as-Experts-for-AI-Chatbot-Agents-in-n8n

  Also check out the video tutorial with a demo:

  Support

  If you have any questions, contact us via the support portal at https://support.noduslabs.com or via our Discord channel.

  More n8n workflows are available on our support portal: n8n x InfraNodus AI automation workflows.

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workflow_json_compressed:
  [encoded data, 8080 characters]


name: Upload Google Drive Files to an InfraNodus Graph
author_name: InfraNodus
author_username: infranodus
categories: []
created_at: 2025-05-29T12:27:25.941Z
updated_at: 2025-05-29T12:27:25.941Z
url: https://n8n.io/workflows/4486
scraped_at: 2025-12-24 13:02:44
description:
  This template can be used to upload the files in your Google drive to an InfraNodus knowledge graph. 

  The InfraNodus graph will then reveal the main topics and ideas in your collection of documents and show the content gaps in them. You can also use the built-in AI to converse with the documents.



  You can also access the InfraNodus Graphs via its GraphRAG API to re-use them in your other n8n workflows for high-quality content retrieval and knowledge base optimization.

  The template showcases the use of multiple n8n nodes and processes:
  Extracting documents from a Google Drive folder
  text extraction
  optional: high-quality PDF conversion using ConvertAPI
  InfraNodus knowledge graph generation


  Note: If you want to **Sync your Google drive to an InfraNodus graph, check out our other workflow*

  How it works

  Here's a description of this workflow step by step:

  Find all the files in a specific Google drive folder
  For each file found: reiterate the workflow and
  Identify the type of the file (TXT, PDF, Markdown)
  For TXT and Markdown files extract the text data 
  For PDF files use a special PDF to Text convertor to extract the text data. (Optional: using ConvertAPI for better quality PDF conversion)
  Forward everything to the InfraNodus graphAndStatements API endpoint with the name of the new graph, the text field with the text data, the text settings, and doNotSave=false to create a new graph
  Reiterate through another file.

  How to use

  You need an InfraNodus GraphRAG API account and key to use this workflow. 

  Create an InfraNodus account
  Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes.
  Use that API key to set up authorization for the InfraNodus tool in the workflow.
  If you want to upload the files to an existing graph, you should copy its name from InfraNodus. Otherwise you can specify any name you want.

  Requirements

  An InfraNodus account and API key
  A Google Drive account and authorization (you will need to set it up via Google Cloud using the n8n instructions provided in the Google Drive node).

  Customizing this workflow

  You can use Dropbox instead of Google Drive.

  You can also modify this workflow slightly to make it Sync with a Google Drive when the new files appear in it.

  Check out the complete guide at https://support.noduslabs.com/hc/en-us/articles/20267019838108-Upload-Sync-Your-Google-Drive-Folder-with-InfraNodus-using-n8n

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleDrive","n8n-nodes-base.switch","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","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.set","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4712 characters]


name: Automate LinkedIn Content from Twitter AI Posts with GPT-4 and Google Sheets
author_name: Archit Jain
author_username: architjn
categories: []
created_at: 2025-05-29T12:42:22.775Z
updated_at: 2025-05-29T12:42:22.775Z
url: https://n8n.io/workflows/4487
scraped_at: 2025-12-24 13:02:44
description:
  How it works
  Automates daily LinkedIn post creation from trending AI tweets.
  Fetches latest tweets, processes content, checks for duplicates, converts to LinkedIn-ready format, schedules, and posts automatically.

  Set up steps
  Setup required: Google Sheets, LinkedIn, Telegram, RapidAPI, and OpenAI/OpenRouter API credentials.
  Approximate setup time: 30-45 mins for all integrations and triggers.
  Detailed credential/config instructions are in sticky notes inside the workflow.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleSheets","n8n-nodes-base.noOp","n8n-nodes-base.googleSheets","n8n-nodes-base.noOp","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.switch","n8n-nodes-base.wait","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.limit","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.splitInBatches","n8n-nodes-base.wait","n8n-nodes-base.googleSheets","n8n-nodes-base.telegram","n8n-nodes-base.aggregate","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.filter","n8n-nodes-base.limit","n8n-nodes-base.code","n8n-nodes-base.splitInBatches","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.linkedIn","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram"]

workflow_json_compressed:
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name: Automate WooCommerce Image Product Background Removal using API and Google Sheet
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-05-29T14:02:50.912Z
updated_at: 2025-05-29T14:02:50.912Z
url: https://n8n.io/workflows/4488
scraped_at: 2025-12-24 13:02:44
description:
  This workflow automates the process of removing backgrounds from WooCommerce product images using the BackgroundCut API, and then updates the product images in both WooCommerce and a Google Sheet.

  Once set up, the workflow processes product images in bulk, removing backgrounds and updating WooCommerce seamlessly.

  This workflow is perfect for online stores that sell:
  Clothing and fashion items
  Jewelry and accessories
  General consumer products

  Any product that benefits from clean, background-free images for a professional storefront presentation will see improved visual appeal and potentially higher conversions.

  Benefits

  ⏱ Time-saving:** Automates what would otherwise be a manual and repetitive task of editing images and updating product listings.
  🔄 Fully Integrated:** Connects Google Sheets, BackgroundCut API, FTP server, and WooCommerce in a seamless loop.
  📦 Scalable:** Supports batch processing, making it suitable for stores with hundreds of products.
  📁 Organized Tracking:** Updates the Google Sheet with the new image and a “DONE” flag for easy monitoring.
  🔧 Customizable:** You can change the image processing API, storage server, or eCommerce platform if needed.

  How It Works  
  Data Retrieval:  
     The workflow starts by fetching product data (ID and IMAGE URL) from a Google Sheets document.  
     Only rows without a "DONE" marker are processed to avoid duplicates.  

  Background Removal:  
     Each product image URL is sent to the BackgroundCut API, which removes the background and returns the edited image.  

  File Handling:  
     The processed image is uploaded to an FTP server with the original filename preserved.  
     A new URL for the edited image is generated and assigned to the product.  

  WooCommerce Update:  
     The product in WooCommerce is updated with the new image URL.  

  Sheet Update:  
     The Google Sheet is marked as "DONE" for the processed row, and the new image URL is recorded.  

  Batch Processing:  
     The workflow loops through all rows in the sheet until all products are processed.  

  Set Up Steps  
  Prepare the Google Sheet:  
     Clone the provided Google Sheet template.  
     Fill in the ID (product ID) and IMAGE (original image URL) columns.  

  API & Credentials Setup:  
     Get an API key from BackgroundCut.co.  
     Configure the HTTP Request node ("Remove from Image URL") with:  
       Header Auth: Authorization = API_KEY.  
     Set up WooCommerce API credentials in the "Update product" node.  

  FTP Configuration:  
     Replace YOUR_FTP_URL in the "New Image Url" node with your FTP/CDN base URL.  
     Ensure FTP credentials are correctly set in the FTP node.  

  Execution:  
     Run the workflow manually via "When clicking ‘Execute workflow’".  
     The process automatically handles background removal, file upload, and WooCommerce updates.  

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

nodes_used:
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name: Learn Anything, Write a Book, Design a Curriculum
author_name: Mohammed Rifad
author_username: rifadm817
categories: []
created_at: 2025-05-29T14:42:21.363Z
updated_at: 2025-05-29T14:42:21.363Z
url: https://n8n.io/workflows/4492
scraped_at: 2025-12-24 13:02:44
description:
  Hey n8n Innovators & Knowledge Seekers! 👋


  Ever felt that spark? That "aha!" moment when you realize you need to dive deep into a new subject? Or maybe you've got a brilliant idea for a course, a comprehensive guide, or even the seeds of your next groundbreaking book, but the thought of structuring it all makes your brain do a backflip?

  What if you had an AI co-pilot, right within n8n, to help you LEARN ANYTHING profoundly, DESIGN A DETAILED CURRICULUM from scratch, or even OUTLINE YOUR NEXT BESTSELLER – and then beam it all into a beautifully organized Notion workspace?

  Well, dream no more! I'm super stoked to share a set of n8n workflows I've cooked up that does exactly this.

    
    
    
    
    
    




  Picture This: You Want To...

  🚀 Master the Unfamiliar: Finally conquer the intricacies of Decentralized Finance (DeFi), understand the core principles of Permaculture Design, or even get a solid grasp on Cognitive Bias in Decision Making. Just tell the AI your starting point!
  📚 WRITE THAT BOOK! Been mulling over a guide on Sustainable Urban Living? Or a deep dive into The History of Ancient Philosophies? Let AI generate your chapter outlines, key concepts, and foundational content.
  🎓 CREATE A WORLD-CLASS CURRICULUM: Planning a workshop on Advanced Data Visualization Techniques? Or an online course on The Fundamentals of Ethical AI Development? Get a comprehensive, Harvard-level syllabus structure in minutes.
  🧠 Personalize Your Knowledge Journey: Get content adapted not just for your current skill level, but with presentation hints based on cognitive styles (yep, we're playing with MBTI!).



  So, How Does This AI Magic Work in n8n?

  It's a dynamic duo of workflows:

  The "Learn Anything" Maestro:
      You feed it your topic, how much you know, (optionally) your MBTI, and how deep you want to go via a cool, custom-styled form.
      AI models (via OpenRouter) then get to work, sketching out a full hierarchical curriculum and brainstorming a catchy title and description.
      Then, for every single section in your new plan, our "SeniorWriter" AI crafts rich, detailed content. Think of it as your personal subject matter expert on tap!
  The "Notion Block Ninja" Sub-Workflow:
      This trusty sidekick takes all that awesome Markdown content.
      It intelligently converts it into the precise JSON that Notion loves, ensuring every heading, list, and table looks perfect.
      Then whoosh – it’s all uploaded to your Notion page, organized and ready.

  Why Share This? Because Knowledge Should Be Accessible & Creation Fun!

  I'm a firm believer that n8n isn't just for business tasks; it's an incredible platform for personal growth, learning, and creative exploration. This project is all about making it easier to dive deep, structure your thoughts, and bring big ideas to life.

  Ready to Unleash Your AI Co-Pilot?

  I'll be dropping the workflow JSONs and a setup guide (with a handy Notion database template link!) in the comments or a follow-up. You'll just need your Notion API key and an OpenRouter API key (they've got free tiers to get you started exploring!).

  Think of the Possibilities! You could be:

  Building custom learning paths for yourself or your team.
  Rapidly prototyping educational content.
  Finally writing that book** you've always talked about.
  Just satisfying your endless curiosity on any subject under the sun!

  I can't wait to hear what you think, the amazing topics you explore, and any brilliant ideas you have to make this even more powerful!

  Let the learning (and creating) begin! 🚀

nodes_used:
  ["n8n-nodes-base.formTrigger","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.splitOut","n8n-nodes-base.splitInBatches","n8n-nodes-base.notion","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.set","n8n-nodes-base.notion","n8n-nodes-base.executeWorkflow","n8n-nodes-base.notion","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.markdown","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequest","n8n-nodes-base.filter","n8n-nodes-base.merge","n8n-nodes-base.splitInBatches","n8n-nodes-base.aggregate","n8n-nodes-base.wait","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm"]

workflow_json_compressed:
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name: Airbnb Telegram Agent - AI-powered accommodation search with voice support
author_name: Friedemann Schuetz
author_username: freddy-schuetz
categories: []
created_at: 2025-05-29T16:00:00.652Z
updated_at: 2025-05-29T16:00:00.652Z
url: https://n8n.io/workflows/4494
scraped_at: 2025-12-24 13:02:41
description:
  Welcome to my Airbnb Telegram Agent Workflow!
  This workflow creates an intelligent Telegram bot that helps users search and find Airbnb accommodations using natural language queries and voice messages.

  DISCLAIMER: This workflow only works with self-hosted n8n instances! You have to install the n8n-nodes-mcp-client Community Node!

  What this workflow does
  This workflow processes incoming Telegram messages (text or voice) and provides personalized Airbnb accommodation recommendations. The AI agent understands natural language queries, searches through Airbnb data using MCP tools, and returns mobile-optimized results with clickable links, prices, and key details.

  Key Features:
  Voice message support (speech-to-text and text-to-speech)
  Conversation memory for context-aware responses
  Mobile-optimized formatting for Telegram
  Real-time Airbnb data access via MCP integration

  This workflow has the following sequence:
  Telegram Trigger - Receives incoming messages from users
  Text or Voice Switch - Routes based on message type
  Voice Processing (if applicable) - Downloads and transcribes voice messages
  Text Preparation - Formats text input for the AI agent
  Airbnb AI Agent - Core logic that:
     Lists available MCP tools for Airbnb data
     Executes searches with parsed parameters
     Formats results for mobile display
  Response Generation - Sends formatted text response
  Voice Response (optional) - Creates and sends audio summary

  Requirements:
  Telegram Bot API**: Documentation 
    Create a bot via @BotFather on Telegram
    Get bot token and configure webhook
  OpenAI API**: Documentation
    Used for speech transcription (Whisper)
    Used for chat completion (GPT-4)
    Used for text-to-speech generation
  MCP Community Client Node**: Documentation
    Custom integration for Airbnb data
    Requires MCP server setup with Airbnb/Airtable connection
    Provides tools for accommodation search and details

  Important: You need to set up an MCP server with Airbnb data access. The workflow uses MCP tools to retrieve real accommodation data, so ensure your MCP server is properly configured with the Airtable/Airbnb integration.

  Configuration Notes:
  Update the Telegram chat ID in the trigger for your specific bot
  Modify the system prompt in the Airbnb Agent for different use cases
  The workflow supports both individual users and can be extended for group chats

  Feel free to contact me via LinkedIn, if you have any questions!

nodes_used:
  ["@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.telegramTrigger","n8n-nodes-base.switch","n8n-nodes-base.telegram","n8n-nodes-base.set","n8n-nodes-base.telegram","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 7824 characters]


name: Sync Google Drive files to an InfraNodus Knowledge Graph
author_name: InfraNodus
author_username: infranodus
categories: []
created_at: 2025-05-29T16:07:41.106Z
updated_at: 2025-05-29T16:07:41.106Z
url: https://n8n.io/workflows/4495
scraped_at: 2025-12-24 13:02:45
description:
  This template can be used to sync the files in your Google drive to a new or existing InfraNodus knowledge graph. 

  The InfraNodus graph will then reveal the main topics and ideas in your collection of documents and show the content gaps in them. You can also use the built-in AI to converse with the documents.



  You can also access the InfraNodus Graphs via its GraphRAG API to re-use them in your other n8n workflows for high-quality content retrieval and knowledge base optimization.

  The template showcases the use of multiple n8n nodes and processes:
  Syncing documents from a Google Drive folder / extracting them
  text extraction from files
  optional: high-quality PDF conversion using ConvertAPI
  InfraNodus knowledge graph generation


  Note: If you want to **upload files from your Google drive to an InfraNodus graph, check out our other workflow*

  How it works

  Here's a description of this workflow step by step:

  Wait for new file(s) to appear in the Google drive folder
  Reiterate through each file
  Retrieve the new file from the Google drive
  For each file found: reiterate the workflow and
  Identify the type of the file (TXT, PDF, Markdown)
  For TXT and Markdown files extract the text data 
  For PDF files use a special PDF to Text convertor to extract the text data. (Optional: using ConvertAPI for better quality PDF conversion)
  Forward everything to the InfraNodus graphAndStatements API endpoint with the name of the new graph, the text field with the text data, the text settings, and doNotSave=false to create a new graph
  Reiterate through another file.

  How to use

  You need an InfraNodus GraphRAG API account and key to use this workflow. 

  Create an InfraNodus account
  Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes.
  Use that API key to set up authorization for the InfraNodus tool in the workflow.
  If you want to upload the files to an existing graph, you should copy its name from InfraNodus. Otherwise you can specify any name you want.

  Requirements

  An InfraNodus account and API key
  A Google Drive account and authorization (you will need to set it up via Google Cloud using the n8n instructions provided in the Google Drive node).

  Customizing this workflow

  You can use Dropbox instead of Google Drive.

  You can also modify this workflow slightly to make it Upload the files from a Google Drive when the new files appear in it.

  Check out the complete guide at https://support.noduslabs.com/hc/en-us/articles/20267019838108-Upload-Sync-Your-Google-Drive-Folder-with-InfraNodus-using-n8n

nodes_used:
  ["n8n-nodes-base.splitInBatches","n8n-nodes-base.googleDrive","n8n-nodes-base.switch","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4732 characters]


name: Wikipedia Podcast Generator - AI-Powered Voice Content Creator via Telegram
author_name: Friedemann Schuetz
author_username: freddy-schuetz
categories: []
created_at: 2025-05-29T16:56:39.662Z
updated_at: 2025-05-29T16:56:39.662Z
url: https://n8n.io/workflows/4496
scraped_at: 2025-12-24 13:02:44
description:
  This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. 

  Welcome to my Wikipedia Podcast Telegram Bot Workflow!
  This workflow creates an intelligent Telegram bot that transforms Wikipedia articles into engaging 5-minute podcast episodes using natural language queries and voice messages.

  What this workflow does
  This workflow processes incoming Telegram messages (text or voice, e.g. "Berlin") and generates professional podcast content about any Wikipedia topic (e.g. "Berlin", "Shakespeare", etc.). The AI agent researches the requested subject, creates a structured podcast script, and delivers it as high-quality audio directly through Telegram.

  Key Features:
  Voice message support (speech-to-text and text-to-speech)
  Wikipedia research integration for accurate content
  Professional podcast structure (intro, main content, outro)
  Natural-sounding AI voice synthesis
  Conversational and educational tone optimized for audio consumption

  This workflow has the following sequence:

  Telegram Trigger - Receives incoming messages (text or voice) from users via Telegram bot
  Text or Voice Switch - Routes the message based on input type (text message vs. voice message)
  Voice Message Processing (if voice input):
     Retrieval of voice file from Telegram
     Transcription of voice message to text using OpenAI Whisper
  Text Message Preparation (if text input) - Prepares the text message for the AI agent
  Wikipedia Podcast Agent - Core AI agent that:
     Researches the requested topic using Wikipedia tool
     Creates a professional 5-minute podcast script (600-750 words)
     Follows structured format: intro, main content, outro
     Uses conversational, accessible, and enthusiastic tone
  ElevenLabs Text to Speech - Converts the podcast script into natural-sounding audio using AI voice synthesis
  Send Voice Response - Delivers the generated podcast audio back to the user via Telegram

  Requirements:

  Telegram Bot API**: Documentation
    Create a bot via @BotFather on Telegram
    Get bot token and configure webhook
  Anthropic API** (Claude 4 Sonnet): Documentation
    Used for AI agent processing and podcast script generation
    Provides Wikipedia research capabilities
  OpenAI API**: Documentation
    Used for speech transcription (Whisper model)
  ElevenLabs API**: Documentation
    Used for high-quality text-to-speech generation
    Provides natural-sounding voice synthesis

  Important: The workflow uses the Wikipedia tool integrated with Claude 4 Sonnet to ensure accurate and comprehensive research. The AI agent is specifically prompted to create engaging, educational podcast content suitable for audio consumption.

  Configuration Notes:
  Update the Telegram chat ID in the trigger for your specific bot
  Modify the voice selection in ElevenLabs for different narrator styles
  The system prompt can be customized for different podcast formats or target audiences
  Supports both individual users and can be extended for group chats

  Feel free to contact me via LinkedIn, if you have any questions!

nodes_used:
  ["n8n-nodes-base.telegramTrigger","@n8n/n8n-nodes-langchain.lmChatAnthropic","@n8n/n8n-nodes-langchain.toolWikipedia","@n8n/n8n-nodes-langchain.toolThink","n8n-nodes-base.switch","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.set","@elevenlabs/n8n-nodes-elevenlabs.elevenLabs","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5548 characters]


name: Extract Structured Data from Brave Search with Bright Data MCP & Google Gemini
author_name: Ranjan Dailata
author_username: ranjancse
categories: []
created_at: 2025-05-29T17:34:51.086Z
updated_at: 2025-05-29T17:34:51.086Z
url: https://n8n.io/workflows/4497
scraped_at: 2025-12-24 13:02:45
description:
  Notice
  Community nodes can only be installed on self-hosted instances of n8n.

  Who this is for
  The Brave Search Structured Data Extractor workflow is designed for professionals and teams that need high-quality, structured insights from Brave search results in real time. Whether you're performing market research, tracking competitors, training AI models, or powering content engines, this workflow offers a robust and automated solution.

  This workflow is tailored for:

  Market Researchers - Who analyze trends across multimedia channels

  AI Developers - Who require clean, structured datasets for model fine-tuning

  SEO & Content - Analysts looking to monitor visibility across news, images, and videos

  Media Researchers - Curating timely and relevant information across formats

  Automation Engineers - Integrating search insights into downstream workflows

  What problem is this workflow solving?
  Traditional web scraping and search result parsing is fragmented, inconsistent, and prone to errors, especially when dealing with multimedia (images, videos, news) data from search engines. This workflow provides:

  Centralized Brave search data extraction across all content types. Switches the search execution based upon the type of search that is being set. ex: news, images, videos, all

  Automated structured data transformation using Google Gemini

  Unified output persistence and notification across disk, webhook, and Google Sheets

  What this workflow does

  Input Configuration

  Define your Brave search query

  Set the search type: videos, images, news, or all

  Configure your Bright Data MCP zone

  Bright Data MCP Search Execution

  Initiates a Brave search via Bright Data MCP using the correct URL pattern for each search type

  Returns raw HTML of search results

  Google Gemini LLM 

  Structured Data Extraction

  Transforms raw results into structured data (e.g., title, URL, source, snippet)

  Output Handling

  Save to disk (e.g., JSON or CSV file)

  Send Webhook notification with structured data (e.g., Slack, internal dashboards)

  Store in Google Sheets for team-wide access or dashboarding

  Pre-conditions

  Knowledge of Model Context Protocol (MCP) is highly essential. Please read this blog post - model-context-protocol
  You need to have the Bright Data account and do the necessary setup as mentioned in the Setup section below.
  You need to have the Google Gemini API Key. Visit Google AI Studio
  You need to install the Bright Data MCP Server @brightdata/mcp
  You need to install the n8n-nodes-mcp

  Setup
  Please make sure to setup n8n locally with MCP Servers by navigating to n8n-nodes-mcp
  Please make sure to install the Bright Data MCP Server @brightdata/mcp  on your local machine.
  Sign up at Bright Data.
  Create a Web Unlocker proxy zone called mcp_unlocker on Bright Data control panel.
  Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions.
  In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy).
  In n8n, configure the credentials to connect with MCP Client (STDIO) account with the Bright Data MCP Server as shown below.



  Make sure to copy the Bright Data API_TOKEN within the Environments textbox above as API_TOKEN=&lt;your-token&gt;

  How to customize this workflow to your needs

  Enhance Output Analysis
  Add additional LLM prompts for topic classification, sentiment scoring, or trend forecasting.

  Output Format Options
  Choose to output CSV, Markdown, or HTML reports based on your integration target.

  Schedule Automation
  Trigger the workflow on a schedule (daily/weekly) to keep monitoring topical content.

nodes_used:
  ["n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-mcp.mcpClient","n8n-nodes-base.switch","n8n-nodes-base.set","n8n-nodes-mcp.mcpClient","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-mcp.mcpClient","n8n-nodes-mcp.mcpClient","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.function","n8n-nodes-base.readWriteFile","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5604 characters]


name: Schedule & Publish All Instagram Content Types with Facebook Graph API
author_name: Lakshit Ukani
author_username: lakshit1996
categories: []
created_at: 2025-05-29T18:35:10.370Z
updated_at: 2025-05-29T18:35:10.370Z
url: https://n8n.io/workflows/4498
scraped_at: 2025-12-24 13:02:42
description:
  Automated Instagram posting with Facebook Graph API and content routing

  Who is this for?

  This workflow is perfect for social media managers, content creators, digital marketing agencies, and small business owners who need to automate their Instagram posting process. Whether you're managing multiple client accounts or maintaining consistent personal branding, this template streamlines your social media operations.

  What problem is this workflow solving?

  Manual Instagram posting is time-inconsistent and prone to inconsistency. Content creators struggle with:
  Remembering to post at optimal times
  Managing different content types (images, videos, reels, stories, carousels)
  Maintaining posting schedules across multiple accounts
  Ensuring content is properly formatted for each post type

  This workflow eliminates manual posting, reduces human error, and ensures consistent content delivery across all Instagram format types.

  What this workflow does

  The workflow automatically publishes content to Instagram using Facebook's Graph API with intelligent routing based on content type. It handles image posts, video stories, Instagram reels, carousel posts, and story content. The system creates media containers, monitors processing status, and publishes content when ready. It supports both HTTP requests and Facebook SDK methods for maximum reliability and includes automatic retry mechanisms for failed uploads.

  Setup

  Connect Instagram Business Account to a Facebook Page
  Configure Facebook Graph API credentials with instagram_basic permissions  
  Update the "Configure Post Settings" node with your Instagram Business Account ID
  Set media URLs and captions in the configuration section
  Choose post type (http_image, fb_reel, http_carousel, etc.)
  Test workflow with sample content before going live

  How to customize this workflow to your needs

  Modify the post_type variable to control content routing:
  Use http_* prefixes for direct API calls 
  Use fb_* prefixes for Facebook SDK calls
  Use both HTTP and Facebook SDK nodes as fallback mechanisms** - if one method fails, automatically try the other for maximum success rate
  Add scheduling by connecting a Cron node trigger
  Integrate with Google Sheets or Airtable for content management
  Connect webhook triggers for automated posting from external systems
  Customize wait times based on your content file sizes
  Set up error handling** to switch between HTTP and Facebook SDK methods when API limits are reached

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.httpRequest","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.httpRequest","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.httpRequest","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","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.set","n8n-nodes-base.switch","n8n-nodes-base.manualTrigger","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote"]

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name: Sync GitHub Workflows to n8n After Pull Request Merges
author_name: Bao Duy Nguyen
author_username: duynb
categories: []
created_at: 2025-05-30T01:27:43.712Z
updated_at: 2025-05-30T01:27:43.712Z
url: https://n8n.io/workflows/4500
scraped_at: 2025-12-24 13:02:43
description:
  Who is this for?

  This template is ideal for developers, DevOps engineers, and automation managers who manage their n8n workflows using GitHub. It helps teams streamline their CI/CD automation by syncing changes from GitHub directly into n8n after a pull request (PR) is merged.

  What problem is this workflow solving?

  Manually restoring workflows after reviewing and merging code in GitHub can be tedious and error-prone. This workflow solves that by automating the restore process, ensuring that any new or updated workflow committed to your GitHub repo is automatically imported into your n8n environment.

  What this workflow does

  Triggers when a GitHub pull request is closed and merged.
  Fetches the details of the merge commit.
  Retrieves the list of added and modified workflow files.
  Downloads and decodes each workflow file.
  Creates or updates** the corresponding workflow in your n8n instance automatically.

  Setup

  Connect GitHub: Use the GitHub Trigger node and configure GitHub API credentials.
  Note: I'd recommended to use GitHub PAT (Personal Access Token) classic with repo and admin:repo_hook permission scopes enabled.
  Connect n8n API: Provide your n8n API credentials in the n8n nodes. - Check this doc
  Set repository variables: Update github_owner and repo_name in the Define Local Variables node.
  Enable webhook: Make sure your GitHub repository has a webhook for pull_request events pointing to this workflow.

  How to customize this workflow to your needs

  Modify filters to handle only certain branches or file paths.
  Add Slack or email notifications to confirm successful imports.
  Insert logging or version tagging for better traceability.
  Extend with conditional logic for workflow testing before applying changes.

  This automated flow provides a seamless CI/CD loop between GitHub and n8n, empowering teams to manage workflow versioning efficiently and securely.

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.githubTrigger","n8n-nodes-base.filter","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.filter","n8n-nodes-base.filter","n8n-nodes-base.github","n8n-nodes-base.github","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.n8n","n8n-nodes-base.n8n","n8n-nodes-base.stickyNote"]

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name: Build & Query RAG System with Google Drive, OpenAI GPT-4o-mini, and Pinecone
author_name: David Olusola
author_username: dae221
categories: []
created_at: 2025-05-30T01:35:59.082Z
updated_at: 2025-05-30T01:35:59.082Z
url: https://n8n.io/workflows/4501
scraped_at: 2025-12-24 13:02:41
description:
  🔍 What This Workflow Does

  This RAG Pipeline in n8n automates document ingestion from Google Drive, vectorizes it using OpenAI embeddings, stores it in Pinecone, and enables chat-based retrieval using LangChain agents.

  Main Functions:

  📂 Auto-detects new files uploaded to a specific Google Drive folder.
  🧠 Converts the file into embeddings using OpenAI.
  📦 Stores them in a Pinecone vector database.
  💬 Allows a user to query the knowledge base through a chat interface.
  🤖 Uses a GPT-4o-mini model with LangChain to generate intelligent responses using retrieved context.
  ⚙️ Setup Instructions

  Connect Accounts
  Ensure these services are connected in n8n:

  ✅ Google Drive (OAuth2)
  ✅ OpenAI
  ✅ Pinecone
  You can do this in n8n &gt; Credentials &gt; New and use the matching names from the file:

  Google Drive: "Google Drive account 2"
  OpenAI: "OpenAi success"
  Pinecone: "PineconeApi account 2"
  Folder Setup
  Upload your documents to this folder in Google Drive:

  📁 Power Folder

  The workflow is triggered every minute when a new file is uploaded.

  Workflow Overview
  A. File Ingestion Path

  Google Drive Trigger — detects new file.
  Google Drive (Download) — downloads the new file.
  Recursive Text Splitter — splits text into chunks.
  Default Data Loader — loads content as LangChain documents.
  OpenAI Embeddings — converts text chunks into embeddings.
  Pinecone Vector Store — stores them in "ragfile" index.
  B. Chat Retrieval Path

  When chat message received — 
  AI Agent — LangChain agent managing tools.
  OpenAI Chat Model (GPT-4o-mini) — generates replies.
  Pinecone Vector Store (retrieval) — retrieves matching content.
  Embeddings OpenAI1 — helps match queries to document chunks.

nodes_used:
  ["n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.vectorStorePinecone","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.vectorStorePinecone","@n8n/n8n-nodes-langchain.embeddingsOpenAi","n8n-nodes-base.stickyNote"]

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name: Starred Slack Messages to Notion Database with AI Auto-Tagging
author_name: Matty Reed
author_username: mattyreed1
categories: []
created_at: 2025-05-30T01:48:24.589Z
updated_at: 2025-05-30T01:48:24.589Z
url: https://n8n.io/workflows/4502
scraped_at: 2025-12-24 13:02:45
description:
  Who is this for?
  Teams that want to capture important Slack messages in Notion with smart categorization.
  Perfect for knowledge workers, community managers, or any team that needs to preserve valuable conversations from Slack and organize them automatically in a Notion database.

  What problem does this solve?
  Important Slack messages get buried in chat history and are hard to find later.
  This workflow monitors your Slack channel and automatically saves starred messages to Notion with AI-generated titles and smart tags. No more manually copying messages or losing track of important discussions.

  How it works
  Trigger - Schedule Trigger fires every 10 minutes to check for new messages.

  Get Slack Messages - fetches recent messages from your specified Slack channel within the last 10 minutes.

  Star Filter - only processes messages that have been reacted to with a ⭐ emoji (configurable to any emoji).

  Get Message Link - retrieves the permanent link to the starred Slack message.

  Choose Notion DB - connects to your target Notion database and loads available tag options.

  Set Tags - prepares the available tags from your Notion database for AI processing.

  AI Processing - uses OpenAI GPT-4o-mini to:
    Generate a concise title (under 50 characters)
    Automatically categorize the message with existing tags (90%+ confidence threshold)

  Create Notion Page - saves the message to Notion with:
    AI-generated title
    Auto-selected tags
    Original message content
    Permanent link back to Slack

  Setup steps

  1. Import and connect credentials
  Import this template into n8n
  Connect your Slack API credentials (Slack Bot Setup Guide)
  Connect your Notion API token (Notion Integration Guide)
  Connect your OpenAI API credentials

  2. Configure Slack integration
  Create a Slack bot and add it to your target channel
  Update the channelId in "Get Slack Messages" node with your channel ID
  Ensure your bot has these permissions:
    channels:history - to read channel messages
    reactions:read - to detect star reactions
    chat:write.public - to get message permalinks

  Slack Bot Setup Resources:
  Creating a Slack App
  Bot Token Scopes
  Adding Apps to Channels

  3. Set up Notion database
  Create or use existing Notion database with required properties:
    Tags (Multi-select) - add tag options with descriptions for better AI accuracy
    Link (URL) - for storing Slack permalink
    Title (Title) - will be auto-populated by AI
  Update the databaseId in "Choose Notion DB" and "Create Notion Page" nodes

  4. Customize the workflow
  Change trigger emoji**: Edit the IF condition to use a different emoji (e.g., bookmark, pushpin)
  Adjust timing**: Modify the Schedule Trigger interval (remember to update the "oldest" filter in Get Slack Messages to match)
  Improve AI prompts**: Edit the prompt in "Write Title & Tag" node for better categorization

  5. Test the setup
  Star a message in your Slack channel
  Wait for the next 10-minute trigger or manually execute the workflow
  Check your Notion database for the new entry

  Example output

  Slack message:
  &gt; "Hey team, just found this amazing tool for automating our design workflow. We should definitely consider it for next sprint: https://example.com/design-tool"

  Generated Notion page:
  Title:** "Design Tool Recommendation for Next Sprint"
  Tags:** "Tools", "Design", "Sprint Planning"
  Content:** Full message text with Slack permalink
  Link:** Direct link back to original Slack message

  Extending the flow

  Multi-channel support - duplicate the "Get Slack Messages" node for different channels and merge the outputs.

  Enhanced AI processing - modify the prompt to extract additional metadata like:
  Priority levels
  Action items
  Mentioned team members
  Due dates

  Rich content preservation - add logic to handle Slack attachments, images, or threaded replies.

  Notification system - add nodes to notify team members when important messages are archived.

  Sentiment analysis - incorporate additional AI processing to categorize message sentiment or urgency.

  This template provides a lean setup for intelligent Slack-to-Notion archiving. Star important messages, let AI handle the organization, and never lose track of valuable conversations again.

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

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name: Automate RSS Content with AI: Summarize, Notify & Archive
author_name: Victor
author_username: victoorsaad
categories: []
created_at: 2025-05-30T02:22:30.751Z
updated_at: 2025-05-30T02:22:30.751Z
url: https://n8n.io/workflows/4503
scraped_at: 2025-12-24 13:02:44
description:
  🚀 Product Overview
  This n8n workflow template automates the entire lifecycle of RSS feed monitoring—perfect for tech news aggregation, content curation, and AI-powered updates. It reads RSS links from a Google Sheets file, fetches content, summarizes it using GPT, sends digest messages to Discord, and stores clean content into a Google Sheets database for future use.



  🔄 How It Works
  ✅ 1. Scheduled RSS Fetching
  Triggers every 24 hours via Schedule Trigger.

  Reads a list of RSS feed URLs from a centralized Google Sheets file.

  Splits them for individual processing.

  🔍 2. Feed Scanning & Filtering
  Loops through each RSS link and retrieves the latest entries.

  Filters out content older than 24 hours to avoid duplicates or outdated info.

  🤖 3. AI Summarization & Messaging
  Aggregates filtered entries.

  Summarizes content using an AI Agent (OpenAI Chat Model).

  Sends beautifully formatted summaries directly to Discord as a message, keeping your community or team informed.

  🗃️ 4. Persistent Storage
  Converts each item to Markdown.

  Writes entries to a second Google Sheets file, including a rate limiter (wait step) to avoid API limits.

  💡 Why Use This Template?
  No-code setup: Drag, drop, and deploy in n8n.

  AI-powered: Smart summarization reduces content noise.

  Discord integration: Great for community managers, news bots, or internal updates.

  Database-ready: Stores everything cleanly for later analysis or republishing.

  🧩 Use Cases
  Daily tech news digest for Discord communities.

  Content curation for newsletters.

  Competitive intelligence via targeted RSS feeds.

  Auto-archiving of blog or podcast updates.

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name: Automate VIRAL Youtube Titles & Thumbnails Creation (FLUX.1 + Apify)
author_name: Nasser
author_username: nasser
categories: []
created_at: 2025-05-30T06:24:10.419Z
updated_at: 2025-05-30T06:24:10.419Z
url: https://n8n.io/workflows/4504
scraped_at: 2025-12-24 13:02:43
description:
  For Who?

  Content Creators
  Youtube Automation
  Marketing Team

  How it works?

  1 - Enter your content idea in the Edit Fields node in a "raw" format. Ex : Boil Eggs Perfectly
  2 - LLM create 3 keywords request based on the idea and Apify scrape the YTB Search
  3 - Wait until the dataset is completed in Apify
  4 - Retrieve Dataset from Apify, calculate approximation of CTR and filter top performing videos
  5 - LLM analyze patterns of best performing titles and create a prompt based on it. Another LLM create 5 titles based on these criteria
  6 - LLM analyze patterns of best performing thumbnails and create a prompt based on it. Another LLM create 1 thumbnail based on these criteria
  7 - Return titles and thumbnail in a HTML Page

  📺 YouTube Video Tutorial:

  SETUP

  Setup Input Content Idea : Enter Keyword Related to the niche you want. Trigger can be replaced with anything as long as you retrieve a content idea. For example : Form submission, Database entry, etc ...

  If you want to change the number of keywords, update the data accordingly in the "Create Keywords" LLM Chain node ➡️ Structured Output Parser AND in the "YTB Search Scrape" HTTP Request Node in Body ➡️ JSON ➡️ searchQueries.
  If you want to change the number of scraped videos for each keyword, update the data accordingly in the "Create Videos Dataset" HTTP Request Node in Body ➡️ JSON ➡️ maxResults.
  If you want to adjust the CTR Calculation feel free to update it in the Code Node ➡️ Follow the Comments (after "//") to find what you're looking for.
  If you want to adjust the level of virality of the videos kept for analaysis go to Filter Node ➡️ Value.

  Setup Output HTML Page : You can also replace this part with any type of storage. For example : Airtable Database, Google Drive/Google Sheet, Send to an email, etc ...

  APIs : For the following third-party integrations, replace ==[YOUR_API_TOKEN]== with your API Token or connect your account via Client ID / Secret to your n8n instance :
  Apify : https://docs.apify.com/api/v2/getting-started 
  OpenAI : https://platform.openai.com/docs/overview (base URL : https://api.openai.com/v1) OR OpenRouter : https://openrouter.ai/docs/quickstart (base URL : https://openrouter.ai/api/v1)
  HuggingFace (FLUX.1) : https://huggingface.co/docs

  👨‍💻 More Workflows : https://n8n.io/creators/nasser/

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workflow_json_compressed:
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name: Automate Meeting Prep & Lead Enrichment with Bright Data, Cal.com & Airtable
author_name: Zacharia Kimotho
author_username: imperolq
categories: []
created_at: 2025-05-30T06:25:28.290Z
updated_at: 2025-05-30T06:25:28.290Z
url: https://n8n.io/workflows/4505
scraped_at: 2025-12-24 13:02:45
description:
  This workflow makes it easier to prepare for meetings and calls by researching your lead right before the call and creates a high-level meeting prep that is sent to your email. This removes the extra steps needed by teams to learn their leads, research, and prepare for the upcoming calls.

  How does it work

  This workflow starts when We Capture the webhook from cal.com for new bookings.

  Ensure you have a field on the form to collect LinkedIn posts. This can be optional or mandatory depending on your preferences.

  When a new event is booked, we will add the leads to an Airtable CRM for appointments and new bookings. This table will contain all the items and items needed to enrich and maintain your CRM.

  If the lead has linkedin then we do research on LinkedIn for their content and posts and perform a lead enrichment to get as much info as we can about the leads and create a new meeting prep.

  What you need
  Bright data API
  Cal.com account/calendar. Other calendars can be used too for this eg calendly, Google Calendar, etc with a few tweaks
  CRM - This can be anything not just airtable

  Setting it up
  Create/update your calendar to allow collecting users LinkedIn profiles/bios
  Add a new webhook to and subscribe to the desired events like below



  Map the fields from the webhook to match your CRM. If you have no CRM make a copy of this Airtable CRM and map the fields to your account. We will be using the Base and table ID to make the mapping easier
  Setup your Bright Data API and select the data source as linkedin for the scraping
  You can edit more data on the bio as needed 
  Update this info to the CRM under the table lead enrichment and map accordingly
  You can update the prompt on the AI models or work with them as is. 
  Update the Gmail node to send the meeting preps to you and finally update the CRM with the generated  Meeting prep

  This automated process can save your team a couple of minutes each day otherwise spent on other client fulfillment items.

  If you would like to learn more about n8n templates like this, feel free to reach out via Linkedin 

  Happy productivity!!

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name: Generate Youtube Video Metadata (Timestamps, Tags, Description, ...)
author_name: Nasser
author_username: nasser
categories: []
created_at: 2025-05-30T08:59:44.727Z
updated_at: 2025-05-30T08:59:44.727Z
url: https://n8n.io/workflows/4506
scraped_at: 2025-12-24 13:02:41
description:
  For Who?

  Content Creators
  Youtube Automation
  Marketing Team

  How it works?

  1 - Enter the ID of the YTB channel to trigger the workflow when a new video is posted
  2 - Apify scrape the last YTB video of the channel
  3 - Wait until the dataset is completed in Apify and get it
  4 - Verify if Metadata are not already generated and generate them with LLM
  5 - Format all the data created and update YTB Video

  📺 YouTube Video Tutorial: 

  SETUP

  Setup Input YTB Chanel : Go to the channel's page on YouTube, and look at the URL of the page. The channel ID is the value that comes after channel/ in the URL. Add it after "?channel_id=" You can also use free tools available to retrieve channel ID.

  Setup Output YTB Video Update : Connect your YTB account to your n8n instance thanks to the Google Cloud Console. You can find tutorials by typing "youtube api Oauth" on Google.

  APIs : For the following third-party integrations, replace ==[YOUR_API_TOKEN]== with your API Token or connect your account via Client ID / Secret to your n8n instance : 
  Apify : https://docs.apify.com/api/v2/getting-started
  Youtube : https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.youtube/?utm_source=n8n_app&utm_medium=node_settings_modal-credential_link&utm_campaign=n8n-nodes-base.youTube#templates-and-examples

  👨‍💻 More Workflows : https://n8n.io/creators/nasser/

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name: AI Email Classifier & Auto-Delete for Gmail (SPAM/OFFER Cleaner)
author_name: LukaszB
author_username: lukaszb
categories: []
created_at: 2025-05-30T09:19:19.428Z
updated_at: 2025-05-30T09:19:19.428Z
url: https://n8n.io/workflows/4507
scraped_at: 2025-12-24 13:02:43
description:
  This workflow is designed for freelancers, solopreneurs, and business owners who receive a high volume of irrelevant messages in their Gmail inbox — from cold offers to spammy promotions — and want to automatically filter and delete them using AI. Its main purpose is to scan new emails with the help of OpenAI, classify their content, and automatically delete those considered marketing (OFFER) or junk (SPAM). The result is a cleaner inbox without the need to manually sift through low-value messages.

  The classification logic uses a detailed system prompt with practical examples, so even complex or borderline messages are categorized accurately. Important emails — such as payment confirmations, shipping updates, or genuine business inquiries — remain untouched. This helps maintain a professional inbox with only valuable and relevant communication.

  The entire process runs automatically in the background and can be customized further — for example, to archive instead of delete, or log deleted emails for review.

  How it works

  When triggered (every hour), the workflow fetches new Gmail messages using the Gmail Trigger node. Each message is passed to an AI classifier powered by OpenAI, which reads the message body (email snippet) and returns one of three labels:

  SPAM: Obvious junk messages, scams, or low-effort bulk messages
  OFFER: Cold outreach, discount promotions, cart reminders, or generic advertising
  IMPORTANT: Valuable information for the user, even if commercial (e.g., invoices, order updates, personal inquiries)

  The workflow then routes the result through an IF node. If the message is marked as SPAM or OFFER, it is immediately deleted from Gmail via the Gmail Delete node. Emails marked as IMPORTANT are ignored and remain in the inbox.

  The classification is entirely AI-driven based on message content — sender address, headers, or metadata are not used.

  How to set up

  To get started, simply connect two credentials:

  A Gmail account using OAuth2 (via the Gmail Trigger and Gmail Delete nodes)
  An OpenAI API key (used by the AI classifier node)

  No advanced setup is needed beyond these two connections.

  Optionally, you can review or modify the system prompt used for classification — it’s available inside the workflow’s LangChain AI Agent node. The prompt is in English, so it’s recommended to use this workflow with English-language emails for best results.

  By default, the workflow deletes matching emails immediately. If you prefer safer testing, you can modify the Gmail node to archive, label, or log emails instead of deleting them.

  The full workflow takes around 5–10 minutes to configure and includes a sticky note with additional instructions and warnings.

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name: Multi-Platform AI Sales Agent with RAG, CRM Logging & Appointment Booking
author_name: Vansh Arora
author_username: v4nsh
categories: []
created_at: 2025-05-30T09:29:25.335Z
updated_at: 2025-05-30T09:29:25.335Z
url: https://n8n.io/workflows/4508
scraped_at: 2025-12-24 13:02:44
description:
  Multi-Platform AI Sales Agent with RAG, CRM Logging & Appointment Booking

  This workflow acts as a 24/7 sales agent, engaging leads across WhatsApp, Instagram, Facebook, Telegram, and your website. It intelligently transcribes audio messages, answers questions using a knowledge base, and uses modular sub-workflows to manage your CRM in Airtable and book appointments in Google Calendar.

  Who Is It For?

  This solution is designed for service-based businesses that require a sophisticated, multi-channel lead management and appointment booking system.
  Agencies, consultants, and clinics** looking to automate lead qualification and booking across text and voice messages.
  Sales teams** needing a robust system that separates CRM and calendar logic for easier management and scalability.
  Advanced n8n users** who want a powerful, agent-based framework that can be easily customized and extended.

  Key Features & Workflow

  This system is composed of a parent workflow that orchestrates the conversation and calls specialized sub-workflows (agents) to perform specific tasks.

  Omni-Channel Engagement:* Greets and converses with leads naturally on *Website Chat, WhatsApp, Instagram, Facebook, and Telegram**.
  Voice Message Transcription:* Automatically transcribes incoming audio/voice notes from *WhatsApp and Telegram** into text, allowing the AI to understand and respond without manual intervention.
  RAG-Powered Intelligence:* The AI agent draws answers from your dedicated *PostgreSQL Knowledge Base (RAG)**, providing accurate information about your services, pricing, and process. A built-in tool allows you to load new knowledge documents from Google Drive.
  Modular CRM Agent (Sub-Workflow):* When the conversation requires CRM actions (like creating a contact or updating an opportunity), the main agent calls a dedicated *Airtable CRM sub-workflow** to handle the task.
  Modular Calendar Agent (Sub-Workflow):* To book appointments, the main agent calls a separate *Google Calendar sub-workflow**, which manages event creation, updates, and deletions.

  What You'll Need

  This workflow framework requires credentials for the following services:
  An AI provider (OpenAI is used for the main agent, transcription, and embeddings).
  PostgreSQL** database with the pgvector extension (for RAG and chat memory).
  Airtable** account (for the CRM sub-workflow).
  Google Calendar** account (for the Calendar sub-workflow).
  Telegram Bot** credentials.
  A Meta Developer Account (for WhatsApp, Instagram & Facebook).
  (Optional) Google Drive for loading knowledge documents.
  (Optional) Google Gemini for embeddings.

  How to Set It Up

  This is a modular system. You must set up the sub-workflows first.

  Deploy Sub-Workflows: Create two new, separate workflows using the provided templates for the CRM Agent and the Calendar Agent. Configure the credentials (Airtable, Google Calendar) within those workflows, then save and activate them.
  Link Sub-Workflows in Main Workflow: Return to this main workflow. In the "CRM Agent" and "Consultation Agent" tool nodes, select the new workflows you just created from the dropdown list.
  Configure Main Credentials: Securely add the remaining credentials (OpenAI, PostgreSQL, Telegram, and your Meta App) in this main workflow.
  Personalize the AI Agent: In the "Update Agent Details" node, fill in your business name, the agent's persona name, and your key services to customize the AI's personality.
  Load Your Knowledge (Optional): To populate the RAG database, use the manual trigger path starting with "When clicking ‘Execute workflow’" to download a document from Google Drive and insert it into your PostgreSQL vector store.
  Activate: Configure your channel-specific details (e.g., Phone Number ID in WhatsApp nodes), save the workflow, and activate it.

  Demo CRM Table: View on Airtable

nodes_used:
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workflow_json_compressed:
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name: 🏛️ Daily US Congress Members Stock Trades Report via Firecrawl + OpenAI + Gmail
author_name: Automate With Marc
author_username: marconi
categories: []
created_at: 2025-05-30T10:06:06.957Z
updated_at: 2025-05-30T10:06:06.957Z
url: https://n8n.io/workflows/4509
scraped_at: 2025-12-24 13:02:42
description:
  📬 What This Workflow Does
  This workflow automatically scrapes recent high-value congressional stock trades from Quiver Quantitative, summarizes the key transactions, and delivers a neatly formatted report to your inbox — every single day.

  It combines Firecrawl's powerful content extraction, OpenAI's GPT formatting, and n8n's automation engine to turn raw HTML data into a digestible, human-readable email.

  Watch Full Tutorial on how to build this workflow here:
  https://www.youtube.com/watch?v=HChQSYsWbGo&t=947s&pp=0gcJCb4JAYcqIYzv

  🔧 How It Works
  🕒 Schedule Trigger
  Fires daily at a set hour (e.g., 6 PM) to begin the data pipeline.

  🔥 Firecrawl Extract API (POST)
  Targets the Quiver Quantitative “Congress Trading” page and sends a structured prompt asking for all trades over $50K in the past month.

  ⏳ Wait Node
  Allows time for Firecrawl to finish processing before retrieving results.

  📥 Firecrawl Get Result API (GET)
  Retrieves the extracted and structured data.

  🧠 OpenAI Chat Model (GPT-4o)
  Formats the raw trading data into a readable summary that includes:

  Date of Transaction

  Stock/Asset traded

  Amount

  Congress member’s name and political party

  📧 Gmail Node
  Sends the summary to your inbox with the subject “Congress Trade Updates - QQ”.

  🧠 Why This is Useful
  Congressional trading activity often reveals valuable signals — especially when high-value trades are made.
  This workflow:

  Saves time manually tracking Quiver Quant updates

  Converts complex tables into a daily, readable email

  Keeps investors, researchers, and newsrooms in the loop — hands-free

  🛠 Requirements
  Firecrawl API Key (with extract access)

  OpenAI API Key

  Gmail OAuth2 credentials

  n8n (self-hosted or cloud)

  💬 Sample Output:
  Congress Trade Summary – May 21

  Nancy Pelosi (D) sold TSLA for $85,000 on April 28

  John Raynor (R) purchased AAPL worth $120,000 on May 2
  ... and more

  🪜 Setup Steps
  Add your Firecrawl, OpenAI, and Gmail credentials in n8n.

  Adjust the schedule node to your desired time.

  Customize the OpenAI system prompt if you want a different summary style.

  Deploy the workflow — and enjoy your daily edge.

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

workflow_json_compressed:
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name: Sprint Cycle Announcements with Form Input, GPT-4 and Slack
author_name: Nikhil Kuriakose
author_username: nikhilkuriakose
categories: []
created_at: 2025-05-30T11:14:45.141Z
updated_at: 2025-05-30T11:14:45.141Z
url: https://n8n.io/workflows/4510
scraped_at: 2025-12-24 13:02:46
description:
  How it works
  Triggers on submitting an n8n form
  Uses the form details to prepare a message
  Sends the message to Slack

  Set up Steps
  Add in your team name
  Add in message tone
  Set up Open AI
  Set up Slack

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.slack","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set"]

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name: Automate Microsoft Teams Meeting Analysis with GPT-4.1, Outlook & Mem.ai
author_name: Wayne Simpson
author_username: nocodecreative
categories: []
created_at: 2025-05-30T12:43:51.349Z
updated_at: 2025-05-30T12:43:51.349Z
url: https://n8n.io/workflows/4512
scraped_at: 2025-12-24 13:02:43
description:
  Automate Microsoft Teams Meeting Analysis with GPT-4.1, Outlook & Mem.ai
      
  Watch the YouTube video to get started
  Follow along with the blog post

  Template Overview

  This advanced n8n template automates Microsoft Teams meeting analysis, knowledge base creation, and email drafting directly from meeting recordings and transcripts.

  It provides end-to-end automation for the following use cases:

  Meeting Analysis

  Connects to Microsoft Graph to retrieve meeting recordings, chat messages, and transcripts.
  Analyses meeting content using AI models.
  Extracts key points, action items, questions, and themes from meetings automatically.

  AI-Powered Web App

  Automatically creates a detailed report from past meetings.
  Stores meeting summaries, metadata, and insights into an easy-to-browse frontend.
  New meetings are added dynamically without manual work.
  **
  Knowledge Base Indexing (via Mem.ai)**

  Uploads extracted meeting data into a structured knowledge base.
  Supports categorisation, search and chat functionality across meetings.
  Draft Follow-Up Emails**

  Draft personalised follow-up emails for meeting participants.
  Email drafts include:
      Meeting summary
      Key decisions
      Action items
  Emails can be sent manually with a human in the loop context via Microsoft Outlook integration.

  Core Components

  Microsoft Graph API for accessing meetings, chats, files, and user profiles.
  SharePoint API for file storage and search.
  n8n Webhooks to trigger processes dynamically.
  Generic OAuth2 authentication for seamless Microsoft access.
  JavaScript Code Nodes for flexible, intelligent parsing and structuring of meeting data.
  AI/LLM nodes for summarisation and content creation.

  Designed to be scalable, modular, and easily customisable for different organisation sizes and industries.

  🛡️ Note

  Failure to correctly configure Azure permissions will prevent the template from functioning. Ensure admin approval is fully completed during setup.

  Important Prerequisites

  ⚠️ Administrator consent is required

  This template requires a Microsoft 365 Global Administrator or Application Administrator to grant admin consent to a set of Microsoft Graph and SharePoint API scopes.

  Basic Azure App Registration knowledge is required:

  You need to set up an Azure App Registration manually, configure OAuth2 authentication, and assign specific API permissions.

  A setup guide is included, but familiarity with:

  App registrations
  API permissions
  Client secrets
  OAuth2 flows

  is highly recommended.

  Knowledge of Postgres is required
  The template includes a SQL script to create the required Postgres table (see blog post).

  You are responsible for hosting your own database (You can use Supabase with the Postgres connection string).

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.postgres","n8n-nodes-base.code","n8n-nodes-base.filter","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequest","n8n-nodes-base.postgres","n8n-nodes-base.respondToWebhook","n8n-nodes-base.html","n8n-nodes-base.html","n8n-nodes-base.webhook","n8n-nodes-base.webhook","n8n-nodes-base.switch","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.markdown","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.set","n8n-nodes-base.filter","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.merge","n8n-nodes-base.splitInBatches","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.sort","n8n-nodes-base.stickyNote","n8n-nodes-base.removeDuplicates","n8n-nodes-base.formTrigger","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.if","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/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.microsoftOutlook","n8n-nodes-base.httpRequest","n8n-nodes-base.respondToWebhook","n8n-nodes-base.microsoftOutlook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Generate Azure VM Timeline Reports with Google Gemini AI Chat Assistant
author_name: Adam Bertram
author_username: adbertram
categories: []
created_at: 2025-05-30T13:38:24.059Z
updated_at: 2025-05-30T13:38:24.059Z
url: https://n8n.io/workflows/4513
scraped_at: 2025-12-24 13:02:44
description:
  An AI-powered chat assistant that analyzes Azure virtual machine activity and generates detailed timeline reports showing VM state changes, performance metrics, and operational events over time.

  How It Works

  The workflow starts with a chat trigger that accepts user queries about Azure VM analysis. A Google Gemini AI agent processes these requests and uses six specialized tools to gather comprehensive VM data from Azure APIs. The agent queries resource groups, retrieves VM configurations and instance views, pulls performance metrics (CPU, network, disk I/O), and collects activity log events. It then analyzes this data to create timeline reports showing what happened to VMs during specified periods, defaulting to the last 90 days unless the user specifies otherwise.

  Prerequisites

  To use this template, you'll need:

  n8n instance (cloud or self-hosted)
  Azure subscription with virtual machines
  Microsoft Azure Monitor OAuth2 API credentials
  Google Gemini API credentials
  Proper Azure permissions to read VM data and activity logs

  Setup Instructions

  Import the template into n8n.
  Configure credentials:  
     Add Microsoft Azure Monitor OAuth2 API credentials with read permissions for VMs and activity logs
     Add Google Gemini API credentials
  Update workflow parameters:  
     Open the "Set Common Variables" node  
     Replace &lt;your azure subscription id here&gt; with your actual Azure subscription ID
  Configure triggers:  
     The chat trigger will automatically generate a webhook URL for receiving chat messages
     No additional trigger configuration needed
  Test the setup to ensure it works.

  Security Considerations

  Use minimum required Azure permissions (Reader role on subscription or resource groups). Store API credentials securely in n8n credential store. The Azure Monitor API has rate limits, so avoid excessive concurrent requests. Chat sessions use session-based memory that persists during conversations but doesn't retain data between separate chat sessions.

  Extending the Template

  You can add more Azure monitoring tools like disk metrics, network security group logs, or Application Insights data. The AI agent can be enhanced with additional tools for Azure cost analysis, security recommendations, or automated remediation actions. You could also integrate with alerting systems or export reports to external storage or reporting platforms.

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