# templates

name: Extract Invoice Data from Email to Google Sheets using GPT-4o AI Automation
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-25T06:03:38.031Z
updated_at: 2025-05-25T06:03:38.031Z
url: https://n8n.io/workflows/4376
scraped_at: 2025-12-24 13:02:41
description:
  Transform your invoice processing from manual data entry into an intelligent automation system. This powerful n8n workflow monitors Gmail for invoice attachments, extracts data using AI-powered analysis, and creates organized Google Sheets with all relevant financial information automatically structured and ready for your accounting workflows.

  🔄 How It Works

  This sophisticated 8-step automation eliminates manual invoice processing:

  Step 1: Intelligent Email Monitoring
  The workflow continuously monitors your Gmail account for emails with specific labels, checking every minute for new invoice attachments that need processing.

  Step 2: Attachment Verification
  Smart filtering ensures only emails with PDF attachments are processed, preventing unnecessary workflow triggers from text-only emails.

  Step 3: Advanced PDF Extraction
  The system automatically downloads and converts PDF invoices into readable text, handling various invoice formats and layouts with high accuracy.

  Step 4: AI-Powered Data Analysis
  GPT-4 processes the extracted text using specialized prompts designed for financial document analysis, identifying and extracting:
  Company information and contact details
  Invoice numbers, dates, and payment terms
  Detailed line items with quantities and pricing
  Tax calculations including CGST, SGST, and VAT
  Billing and shipping addresses
  Payment methods and transaction references

  Step 5: Structured Data Formatting
  The AI output is automatically formatted into clean, consistent JSON structure with 25+ standardized fields for comprehensive invoice tracking.

  Step 6: Dynamic Spreadsheet Creation
  Each processed invoice generates a new Google Sheets document with timestamp naming and organized data layout, ready for accounting review.

  Step 7: Automated File Organization
  Processed spreadsheets are automatically moved to designated Google Drive folders, maintaining organized file structure for easy retrieval and audit trails.

  Step 8: Data Population
  All extracted invoice data is populated into the spreadsheet with proper formatting, formulas, and structure for immediate use in accounting workflows.

  ⚙️ Setup Steps

  Prerequisites
  Gmail account with invoice-receiving capability
  Google Workspace access for Sheets and Drive
  OpenAI API account for data extraction
  n8n instance (cloud or self-hosted)
  PDF invoices (text-based, not scanned images)

  Gmail Configuration Requirements

  Label Setup:
  Create specific Gmail labels for invoice processing:
  📧 Labels to Create:
  "Invoice-Processing" (main processing label)
  "Invoice-Vendors" (supplier invoices)
  "Invoice-Clients" (customer invoices)  
  "Invoice-Processed" (completed items)

  Email Filter Configuration:
  Set up automatic labeling rules:
  Emails from known vendors → Auto-apply "Invoice-Processing"
  Emails with "Invoice" in subject → Auto-apply "Invoice-Processing"  
  Attachments with PDF extension → Auto-apply "Invoice-Processing"

  Configuration Steps

  1. Credential Setup
  Gmail OAuth2**: Full email access including attachments
  OpenAI API Key**: GPT-4 access for intelligent data extraction
  Google Sheets OAuth2**: Spreadsheet creation and editing permissions
  Google Drive OAuth2**: File organization and folder management

  2. Google Drive Folder Structure
  Create organized folder hierarchy:
  📁 Invoice Management/
  ├── 📁 Incoming Invoices/
  ├── 📁 Processed Invoices/
  │   ├── 📁 2024/
  │   │   ├── 📁 Q1/
  │   │   ├── 📁 Q2/
  │   │   └── 📁 Q3/
  ├── 📁 Vendor Invoices/
  └── 📁 Client Invoices/

  3. AI Extraction Customization
  The default AI prompt extracts standard invoice fields but can be customized for:
  Regional Tax Systems**: GST (India), VAT (EU), Sales Tax (US)
  Industry-Specific Fields**: Purchase orders, project codes, cost centers
  Company Standards**: Custom fields, approval workflows, coding requirements
  Multi-Currency**: Exchange rates, currency conversion, international invoices

  4. Data Validation Rules
  Implement quality control measures:
  Required Field Validation**: Ensure critical data is always extracted
  Format Standardization**: Consistent date formats, number formatting
  Duplicate Detection**: Identify potentially duplicate invoices
  Accuracy Scoring**: Confidence levels for extracted data

  5. Workflow Activation
  Import the workflow JSON into your n8n instance
  Configure all credential connections and test each step
  Process test invoices to verify accuracy
  Activate Gmail trigger for continuous monitoring

  🚀 Use Cases

  Accounting Firms & Bookkeepers
  Client Service Automation**: Process invoices for multiple clients efficiently
  Data Entry Elimination**: Convert hours of manual work into automated processing
  Accuracy Improvement**: Reduce human errors in financial data transcription
  Scalable Operations**: Handle increased client volume without proportional staff increase

  Small & Medium Businesses
  Accounts Payable Automation**: Streamline vendor invoice processing
  Cash Flow Management**: Quick access to payment due dates and amounts
  Expense Tracking**: Organized categorization of business expenses
  Audit Preparation**: Maintain organized, searchable invoice records

  Corporate Finance Teams
  Procurement Processing**: Handle purchase orders and vendor invoices at scale
  Multi-Location Operations**: Centralize invoice processing across offices
  Compliance Management**: Ensure consistent data capture for regulatory requirements
  Integration Readiness**: Prepare data for ERP and accounting system import

  Freelancers & Consultants
  Client Invoice Tracking**: Organize incoming payments and project billing
  Expense Management**: Categorize business expenses for tax preparation
  Cash Flow Monitoring**: Track outstanding invoices and payment schedules
  Professional Organization**: Maintain clean financial records for business growth

  E-commerce & Retail
  Supplier Invoice Processing**: Manage inventory purchasing and cost tracking
  Multi-Vendor Operations**: Handle invoices from numerous suppliers efficiently
  Cost Analysis**: Track product costs and supplier performance
  Inventory Reconciliation**: Match invoice data with purchase orders and receipts

  🔧 Advanced Customization Options

  Multi-Format Invoice Handling
  Extend processing capabilities:
  PDF Text-Based: Standard invoice PDFs with selectable text
  Scanned Documents: Add OCR processing for image-based invoices
  Email Body Invoices: Extract data from invoice details in email content  
  Excel Attachments: Process invoices sent as spreadsheet files
  Multi-Page Documents: Handle complex invoices with multiple pages

  Intelligent Data Validation
  Implement quality assurance features:
  Cross-Reference Validation**: Compare extracted data against purchase orders
  Vendor Database Matching**: Verify company details against known vendor lists
  Tax Calculation Verification**: Validate tax amounts and rates for accuracy
  Currency Conversion**: Handle multi-currency invoices with real-time exchange rates

  Workflow Integration Extensions
  Connect to existing business systems:
  ERP Integration**: Direct data export to SAP, Oracle, or Microsoft Dynamics
  Accounting Software**: Push data to QuickBooks, Xero, or FreshBooks
  Approval Workflows**: Add review and approval steps before final processing
  Payment Processing**: Connect to banking systems for automated payment scheduling

  Advanced Analytics & Reporting
  Generate business insights:
  Vendor Performance Analysis**: Track pricing trends and payment terms
  Expense Category Reporting**: Automated expense categorization and analysis
  Cash Flow Forecasting**: Predict payment obligations based on due dates
  Audit Trail Management**: Maintain comprehensive processing logs for compliance

  📊 Extracted Data Structure

  Standard Invoice Fields (25+ Data Points)
  The AI extraction captures comprehensive invoice information:

  Header Information:
  Billed To (Customer/Company Name)
  Invoice Number (Unique Identifier)
  Date of Issue (Invoice Creation Date)
  Due Date (Payment Deadline)

  Line Item Details:
  Item Description (Product/Service Details)
  Quantity (Number of Items/Hours)
  Rate (Unit Price)
  Amount (Line Total)

  Tax and Financial Calculations:
  CGST/SGST Rates and Amounts (Indian GST System)
  VAT Calculations (European Tax System)
  Subtotal (Pre-tax Amount)
  Total Amount (Final Invoice Value)

  Company and Contact Information:
  Vendor Company Name
  Contact Phone/Mobile
  Email Address
  Website URL
  GST Registration Number
  PAN Number (Indian Tax ID)

  Address Information:
  Billing Address
  Shipping Address  
  Place of Supply
  Place of Delivery

  Payment Details:
  Transaction IDs
  Payment Mode (Check, Bank Transfer, Card)
  Terms and Conditions
  Special Instructions

  Sample Extracted Data:
  {
    "billed_to": "Tech Solutions Inc.",
    "invoice_number": "INV-2024-0156",
    "date_of_issue": "2024-03-15",
    "due_date": "2024-04-15",
    "item_0_description": "Web Development Services",
    "item_0_quantity": 40,
    "item_0_rate": 75.00,
    "item_0_amount": 3000.00,
    "tax_0_cgst_rate": 9,
    "tax_0_cgst_amount": 270.00,
    "tax_0_sgst_rate": 9,
    "tax_0_sgst_amount": 270.00,
    "subtotal": 3000.00,
    "total": 3540.00,
    "company_name": "Digital Services LLC",
    "company_email": "billing@digitalservices.com",
    "payment_transaction_ids": "TXN123456789",
    "mode_of_payment": "Bank Transfer"
  }

  🛠️ Troubleshooting & Best Practices

  Common Issues & Solutions

  PDF Extraction Challenges
  Scanned Documents**: Original workflow handles text-based PDFs only
  Complex Layouts**: Some invoice formats may require prompt refinement
  Multi-Page Invoices**: Large invoices might need pagination handling
  Password Protection**: Encrypted PDFs require manual processing

  AI Extraction Accuracy
  Field Recognition**: Some custom invoice formats may need prompt tuning
  Currency Handling**: Multi-currency invoices may require specific configuration
  Date Formats**: International date formats might need standardization
  Vendor Variations**: Different vendor invoice styles may affect accuracy

  Gmail Integration Limitations
  Label Management**: Ensure consistent labeling for proper processing
  Attachment Size**: Large PDFs may hit Gmail API limits
  Email Volume**: High-volume processing may require rate limiting
  Security Settings**: Corporate Gmail may have additional restrictions

  Optimization Strategies

  Processing Efficiency
  Batch Processing**: Group similar invoices for more efficient processing
  Template Recognition**: Create vendor-specific extraction templates
  Quality Scoring**: Implement confidence ratings for extracted data
  Error Handling**: Add fallback processes for failed extractions

  Data Quality Assurance
  Validation Rules**: Implement business logic for data verification
  Duplicate Detection**: Prevent duplicate invoice processing
  Manual Review Queues**: Flag uncertain extractions for human review
  Audit Logging**: Maintain detailed processing logs for troubleshooting

  Business Process Integration
  Approval Workflows**: Add management approval steps for high-value invoices
  Exception Handling**: Create special processes for unusual invoice types
  Reporting Automation**: Generate regular summaries of processed invoices
  Archive Management**: Implement retention policies for processed documents

  📈 Success Metrics

  Efficiency Improvements
  Processing Time**: Reduce manual data entry from hours to minutes
  Accuracy Rates**: Achieve 95%+ data extraction accuracy
  Volume Capacity**: Process 10-50x more invoices with same resources
  Error Reduction**: Eliminate manual transcription errors

  Business Impact Measurements
  Cost Savings**: Calculate labor cost reduction from automation
  Cash Flow Management**: Faster invoice processing enables better payment scheduling
  Compliance**: Improved audit trails and data consistency
  Scalability**: Ability to handle business growth without proportional staff increase

  📞 Questions & Support

  Need help implementing or optimizing your AI Invoice Processor Agent?

  📧 Expert Technical Support
  Email**: Yaron@nofluff.online
  Response Time**: Within 24 hours on business days
  Specialization**: Invoice processing automation, AI data extraction, accounting workflow integration

  🎥 Comprehensive Training Resources
  YouTube Channel**: https://www.youtube.com/@YaronBeen/videos
    Complete setup and configuration walkthroughs
    Advanced customization for different invoice types
    Integration tutorials for popular accounting software
    Troubleshooting common extraction and processing issues
    Best practices for financial document automation

  🤝 Professional Community & Updates
  LinkedIn**: https://www.linkedin.com/in/yaronbeen/
    Connect for ongoing automation consulting and support
    Share your invoice processing success stories and ROI results
    Access exclusive workflow templates and advanced configurations
    Join discussions about financial automation trends and innovations

  💬 Support Request Guidelines
  Include in your support message:
  Your current invoice processing volume and types
  Specific vendor formats or invoice layouts you handle
  Target accounting software or systems for integration
  Any technical errors or extraction accuracy issues
  Current manual processing workflow and pain points



  Ready to eliminate manual invoice processing forever? Deploy this AI Invoice Processor Agent and transform your accounting workflow from tedious data entry into intelligent, automated financial management!

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workflow_json_compressed:
  [encoded data, 5340 characters]


name: AI Client Onboarding Agent: Auto Welcome Email Generator
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-25T06:10:41.891Z
updated_at: 2025-05-25T06:10:41.891Z
url: https://n8n.io/workflows/4377
scraped_at: 2025-12-24 13:02:45
description:
  AI Client Onboarding Agent: Auto Welcome Email Generator

  This workflow automates welcoming new clients. When someone submits a form, their details are pulled from Google Sheets, a personalized onboarding checklist is generated using Google Gemini, and an email is sent directly to the client. It also includes error handling to ensure nothing is missed.

  🟢 Section 1 – Trigger & Client Data Capture

  Nodes:

  ⏰ Trigger on New Client Form Submission → Fires when a new row is added in Google Sheets (from the client’s form).
  🧍 Extract and Structure Client Data → Collects and formats client details: name, email, company, services, extra info.

  ✅ Beginner view: This is the doorway. When a client fills the form, their info is automatically pulled into the workflow.

  📑 Section 2 – Checklist & Personalization

  Nodes:

  📋 Client Checklist → Creates a default onboarding checklist (account setup, welcome call, docs, etc.).
  🧠 Personalize Using Gemini → Sends client details + checklist to Google Gemini AI → generates a tailored onboarding email body.

  ✅ Beginner view: This is where the magic happens. Instead of a boring generic email, each client gets a customized message that feels personal.

  📤 Section 3 – Delivery & Completion

  Nodes:

  📧 Send Email to Client → Sends the personalized onboarding email directly to the client’s inbox.
  ✅ Execution Completed → Marks the workflow as successfully finished.

  ✅ Beginner view: Think of this as the final handshake with the client — they get a warm, professional onboarding email without you lifting a finger.

  🚨 Section 4 – Error Handling

  Nodes:

  ⚠️ Error Handler → Captures any failure in the workflow.
  ❌ Execution Failure → Defines fallback/alert action if something breaks.

  ✅ Beginner view: This is your safety net. If an email fails or Gemini is unavailable, the workflow won’t just stop — you can set it up to alert you.

  📊 Summary Table

  | Section           | Key Nodes                           | Purpose                                | Beginner Benefit               |
  | ----------------- | ----------------------------------- | -------------------------------------- | ------------------------------ |
  | 🟢 Trigger & Data | Google Sheets Trigger, Data Extract | Capture client info                    | Auto-collects form submissions |
  | 📑 Checklist & AI | Checklist, Gemini                   | Generate personalized onboarding email | Each client feels special      |
  | 📤 Delivery       | Gmail, Execution Completed          | Send email & close flow                | Client gets email instantly    |
  | 🚨 Error Handling | Error Trigger, Failure Node         | Catch issues                           | Ensures nothing is missed      |

  🌟 Why This Workflow Rocks

  Saves hours** → no manual onboarding emails
  Personalized at scale** → Gemini tailors messages per client
  Error-proof** → built-in error handling keeps you safe
  Scalable** → works for 10 or 10,000 clients

  👉 Example Flow in Action:

  A client named Sarah fills the onboarding form.
  Workflow captures her details → “Sarah, MarketingPro Agency, Needs Analytics Setup.”
  Gemini creates a custom email:

     &gt; Hi Sarah, welcome aboard! Here’s your onboarding plan tailored for Analytics Setup…
  Gmail sends it instantly.
  You get notified only if something fails.

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workflow_json_compressed:
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name: Extract Marketing Testimonials from Feedback with Gemini AI and Google Sheets
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-25T06:17:26.200Z
updated_at: 2025-05-25T06:17:26.200Z
url: https://n8n.io/workflows/4378
scraped_at: 2025-12-24 13:02:46
description:
  Extract Marketing Testimonials from Feedback with Gemini AI and Google Sheets

  🌍 Overview

  This workflow automatically extracts short emotional testimonials from Google Form responses. It listens for new feedback in Google Sheets, processes it with AI (Google Gemini), writes back a refined testimonial, and sends an email notification.

  Think of it as your testimonial assistant—turning raw customer feedback into marketing-ready quotes.

  🟢 Section 1: Trigger – Listen for New Feedback

  🔗 Nodes:

  Google Sheets Trigger** → Watches for new rows (new form responses).

  💡 Beginner takeaway:
  Whenever a customer submits feedback via your form, this trigger wakes up the workflow.

  📈 Advantage:
  No manual checking — feedback is instantly processed.

  🟦 Section 2: Testimonial Extraction with AI

  🔗 Nodes:

  Basic LLM Chain* → Runs a custom prompt that tells the AI: *“Extract a short, emotional testimonial quote from the feedback.”
  Google Gemini Chat Model** → The AI brain that processes and rewrites the testimonial.

  💡 Beginner takeaway:
  This part filters out neutral or boring text and produces a catchy, emotional testimonial.

  📈 Advantage:
  Saves you time editing feedback → instantly produces marketing-ready quotes.

  🟣 Section 3: Store & Notify

  🔗 Nodes:

  Google Sheets (Write Back)** → Saves the extracted testimonial into the same Google Sheet.
  Gmail** → Sends an email with the new testimonial to your chosen inbox.

  💡 Beginner takeaway:
  The testimonial is both saved for records and shared with your team via email.

  📈 Advantage:
  You get real-time alerts and maintain a growing database of testimonials.

  📊 Final Overview Table

  | Section           | Nodes                 | Purpose                       | Benefit                    |
  | ----------------- | --------------------- | ----------------------------- | -------------------------- |
  | 🟢 Trigger        | Google Sheets Trigger | Detect new feedback           | Automated start            |
  | 🟦 AI Extraction  | LLM Chain + Gemini    | Extract emotional testimonial | Marketing-ready quotes     |
  | 🟣 Store & Notify | Google Sheets + Gmail | Save + send testimonial       | Organized + instant alerts |

  🚀 Why This Workflow is Useful

  Automates testimonial creation** → No manual copywriting needed
  Captures emotions** → AI filters for impactful quotes
  Centralized storage** → All testimonials logged in Google Sheets
  Instant notifications** → New testimonials delivered straight to email
  Beginner-friendly** → Just connect your sheet + Gmail and it runs on its own

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  ["n8n-nodes-base.googleSheetsTrigger","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.googleSheets","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: Website Downtime Alert via LINE + Supabase Log
author_name: sayamol thiramonpaphakul
author_username: sayamol
categories: []
created_at: 2025-05-25T08:04:40.906Z
updated_at: 2025-05-25T08:04:40.906Z
url: https://n8n.io/workflows/4379
scraped_at: 2025-12-24 13:02:44
description:
  This workflow automatically checks the status of your websites using UptimeRobot API. If any site is down or unstable, it will:
  Generate a natural-language alert message using GPT-4o
  Push the message to a LINE group (with funny IT-style encouragement)
  Log all DOWN status entries into your Supabase database
  Wait 30 minutes before repeating

  🔧 How It Works
  Schedule Trigger – Runs on a fixed interval (every few minutes).
  UptimeRobot Node – Fetches website monitor data.
  Code Node (Filter) – Filters only websites with status 8 (may be down) or 9 (down).
  IF Node – If any site is down, proceed.
  LangChain LLM Node – Formats alert with a humorous message using GPT-4o.
  Line Notify (HTTP Request) – Sends the alert to your LINE group.
  Loop Over Items – Loops through all monitors.
  Filter Down (Status = 9) – Selects only “fully down” sites.
  Supabase Node – Logs these into synlora_uptime_down table.
  Wait Node – Delays next alert by 30 minutes to avoid spamming.

  ⚙️ Setup Steps

  Required:
  🔗 UptimeRobot API Key
  📲 LINE Channel Access Token and Group ID
  🧠 OpenAI Key (GPT-4o Mini)
  🗃️ Supabase Project & Table 

  Step-by-step:
  Go to UptimeRobot → Get API key and ensure monitors are set up.
  Create a Supabase table with fields: website, status, uptime_id.
  Create a LINE Messaging API bot, join it to your group, and get:
  	Access Token
  	Group ID (userId or groupId)
  Add your OpenAI API Key for GPT-4o Mini (or switch to your preferred LLM).
  Import the workflow JSON into n8n.
  Set credentials in all necessary nodes.
  Activate the workflow.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.uptimeRobot","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.splitInBatches","n8n-nodes-base.filter","n8n-nodes-base.supabase"]

workflow_json_compressed:
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name: Automated Website Change Monitoring with Bright Data, GPT-4.1 & Google Workspace
author_name: Daniel Shashko
author_username: tomax
categories: []
created_at: 2025-05-25T11:58:15.627Z
updated_at: 2025-05-25T11:58:15.627Z
url: https://n8n.io/workflows/4382
scraped_at: 2025-12-24 13:02:45
description:
  Note: This template is for self-hosted n8n instances only

  You can use this workflow to fully automate website content monitoring and change detection on a weekly basis—even when there’s no native node for scraping or structured comparison. It uses an AI-powered scraper, structured data extraction, and integrates Google Sheets, Drive, Docs, and email for seamless tracking and reporting.

  Main Use Cases

  Monitor and report changes to websites (e.g., pricing, content, headings, FAQs) over time
  Automate web audits, compliance checks, or competitive benchmarking
  Generate detailed change logs and share them automatically with stakeholders

  How it works

  The workflow operates as a scheduled process, organized into these stages:

  1. Initialization & Configuration

  Triggers weekly (or manually) and initializes key variables: Google Drive folder, spreadsheet IDs, notification emails, and test mode.

  2. Input Retrieval

  Reads the list of URLs to be monitored from a Google Sheet.

  3. Web Scraping & Structuring

  For each URL, an AI agent uses Bright Data's scrape_as_markdown tool to extract the full web page content.
  The workflow then parses this content into a well-structured JSON, capturing elements like metadata, headings, pricing, navigation, calls to action, contacts, banners, and FAQs.

  4. Saving Current Week’s Results

  The structured JSON is saved to Google Drive as the current week’s snapshot for each monitored URL.
  The Google Sheet is updated with file references for traceability.

  5. Comparison with Previous Snapshot

  If a prior week’s file exists, it is downloaded and parsed.
  The workflow compares the current and previous JSON snapshots, detecting and categorizing all substantive content changes (e.g., new/updated plans, FAQ edits, contact info modifications).
  Optionally, in test mode, mock changes are introduced for demo and validation purposes.

  6. Change Report Generation & Delivery

  A rich Markdown-formatted changelog is generated, summarizing the detected changes, and then converted to HTML.
  The changelog is uploaded to Google Docs and linked back to the tracking sheet.
  An HTML email with the full report and relevant links is sent to recipients.

  Summary Flow:

  Schedule/workflow trigger → initialize variables
  Read URL list from spreadsheet
  For each URL:
      Scrape & structure as JSON
      Save to Drive, update tracking sheet
      If previous week exists:
          Download & parse previous
          Compare, generate changelog
          Convert to HTML, save to Docs, update Sheet
          Email results

  Benefits:

  Fully automated website change tracking with end-to-end reporting
  Adaptable and extensible for any set of monitored pages and content types
  Easy integration with Google Workspace tools for collaboration and storage
  Minimal manual intervention required after initial setup

nodes_used:
  ["@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.splitInBatches","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleDrive","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.googleDrive","n8n-nodes-base.extractFromFile","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.markdown","n8n-nodes-base.googleDocs","n8n-nodes-base.googleDocs","n8n-nodes-base.googleSheets","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.scheduleTrigger","n8n-nodes-mcp.mcpClientTool","@n8n/n8n-nodes-langchain.outputParserAutofixing","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.convertToFile","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 14556 characters]


name: Remote Job Updates Pipeline with RemoteOK, Airtable, and Telegram
author_name: Puspak
author_username: dpreddy
categories: []
created_at: 2025-05-25T15:04:37.907Z
updated_at: 2025-05-25T15:04:37.907Z
url: https://n8n.io/workflows/4383
scraped_at: 2025-12-24 13:02:45
description:
  🚀 Remote Job Automation Workflow
  Automatically fetch, clean, and broadcast the latest remote job listings — powered by RemoteOK, Airtable, and Telegram.

  🔧 Key Features
  Seamless Data Fetching:
  Pulls the latest job listings from the RemoteOK API using an HTTP Request node.

  Smart Data Processing (via Code Node):

  Filters out irrelevant metadata

  Cleans and sanitizes job descriptions (e.g., HTML tags, special characters)

  Handles malformed or encoded text gracefully

  Extracts and formats salary ranges for clarity

  Airtable Integration (Upsert):

  Stores each job as a unique record using job ID

  Avoids duplication through conditional upserts using Airtable's Personal Access Token

  Telegram Bot Broadcasting:

  Automatically formats and sends job posts to a Telegram group or channel

  Keeps your community or team updated in real-time

  📦 Tech Stack
  RemoteOK API – source of curated remote job listings

  Airtable – lightweight, accessible job database

  Telegram Bot API – for real-time job notifications

  n8n – workflow automation engine to tie everything together

  🔁 Workflow Overview
  Fetch Jobs from RemoteOK API

  Clean & Normalize job descriptions and metadata

  Extract Salary ranges and standardize them

  Upsert to Airtable (avoiding duplicates)

  Format Post for visual clarity

  Send to Telegram via bot integration

  🧠 Perfect For
  Remote job boards or aggregators

  Recruitment agencies/startups

  Developers building personal job feeds

  Communities or channels sharing curated remote opportunities

  Automating newsletters or job digests

  ✅ Benefits

  Near real-time updates

  Minimal maintenance

  Full control and extensibility with n8n

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

workflow_json_compressed:
  [encoded data, 5472 characters]


name: Shopify VIP Alerts: AI Summary & Slack Notification for Big Orders
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-25T15:45:32.862Z
updated_at: 2025-05-25T15:45:32.862Z
url: https://n8n.io/workflows/4384
scraped_at: 2025-12-24 13:02:44
description:
  🧨 VIP Radar: Instantly Spot & Summarize High-Value Shopify Orders with AI + Slack Alerts

  Automatically detect when a new Shopify order exceeds $200, fetch the customer’s purchase history, generate an AI-powered summary, and alert your team in Slack—so no VIP goes unnoticed.

  🛠️ Workflow Overview

  | Feature                | Description                                                                 |
  |------------------------|-----------------------------------------------------------------------------|
  | Trigger            | Shopify “New Order” webhook                                                 |
  | Conditional Check  | Filters for orders &gt; $200                                                   |
  | Data Enrichment    | Pulls full order history for the customer from Shopify                      |
  | AI Summary         | Uses OpenAI to summarize buying behavior                                    |
  | Notification       | Sends detailed alert to Slack with name, order total, and customer insights |
  | Fallback           | Ignores low-value orders and terminates flow                                |

  📘 What This Workflow Does

  This automation monitors your Shopify store and reacts to any high-value order (over $200). When triggered:

  It fetches all past orders of that customer,
  Summarizes the history using OpenAI,
  Sends a full alert with context to your Slack channel.

  No more guessing who’s worth a closer look. Your team gets instant insights, and your VIPs get the attention they deserve.

  🧩 Node-by-Node Breakdown

  🔔 1. Trigger: New Shopify Order
  Type**: Shopify Trigger
  Event**: orders/create
  Purpose**: Starts workflow on new order
  Pulls**: Order total, customer ID, name, etc.

  🔣 2. Set: Convert Order Total to Number
  Ensures the total_price is treated as a number for comparison.

  ❓ 3. If: Is Order &gt; $200?
  Condition**: $json.total_price &gt; 200
  Yes** → Continue
  No** → End workflow

  🔗 4. HTTP: Fetch Customer Order History
  Uses the Shopify Admin API to retrieve all orders from this customer.
  Requires your Shopify access token.

  🧾 5. Set: Convert Orders Array to String
  Formats the order data so it's prompt-friendly for OpenAI.

  🧠 6. LangChain Agent: Summarize Order History
  Prompt**: "Summarize the customer's order history for Slack. Here is their order data: {{ $json.orders }}"
  Model**: GPT-4o Mini (customizable)

  📨 7. Slack: Send VIP Alert
  Sends a rich message to a Slack channel.
  Includes:
    Customer name
    Order value
    Summary of past behavior

  🧱 8. No-Op (Optional)
  Used to safely end workflow if the order is not high-value.

  🔧 How to Customize

  | What                     | How                                                                 |
  |--------------------------|----------------------------------------------------------------------|
  | Order threshold          | Change 200 in the If node                                       |
  | Slack channel            | Update channelId in the Slack node                                |
  | AI prompt style          | Edit text in LangChain Agent node                                   |
  | Shopify auth token       | Replace shpat_abc123xyz... with your actual private token         |

  🚀 Setup Instructions

  Open n8n editor.
  Go to Workflows → Import → Paste JSON.
  Paste this workflow JSON.
  Replace your Shopify token and Slack credentials.
  Save and activate.
  Place a test order in Shopify to watch it work.

  💡 Real-World Use Cases

  🎯 Notify sales team when a potential VIP buys
  🛎️ Prep support reps with customer history
  📈 Detect repeat buyers and upsell opportunities

  🔗 Resources & Support

  👨‍💻 Creator: Yaron Been
  📺 YouTube: NoFluff with Yaron Been
  🌐 Website: https://nofluff.online
  📩 Contact: Yaron@nofluff.online

  🏷️ Tags

  #shopify, #openai, #slack, #vip-customers, #automation, #n8n, #workflow, #ecommerce, #customer-insights, #ai-summaries, #gpt4o

nodes_used:
  ["n8n-nodes-base.noOp","n8n-nodes-base.shopifyTrigger","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.slack","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: AI-Powered Calendar & Meeting Digest with Gmail and GPT-4o/Claude - Daily Brief
author_name: Nick Loui
author_username: nick
categories: []
created_at: 2025-05-25T19:43:04.061Z
updated_at: 2025-05-25T19:43:04.061Z
url: https://n8n.io/workflows/4385
scraped_at: 2025-12-24 13:02:44
description:
  🛠 How It Works

  The Daily Calendar Brief is an automated n8n workflow designed to prep you each morning with a rich, executive-style email summary of your day. It pulls data from your calendar, email, and external contact sources to deliver a contextualized, prioritized briefing.

  Daily Trigger

  Runs every weekday morning at 7:00 AM using a schedule node.

  Calendar Parsing

  Grabs all Google Calendar events for the day and extracts details like:
  	•	Event title, time, and duration
  	•	Full attendee list
  	•	Meeting description

  Attendee Intelligence

  Filters for external attendees and:
  	•	Scrapes recent email threads with them
  	•	Uses Hunter and LinkedIn to enrich attendee info with roles, bios, locations, and recent activity

  Brief Assembly

  Combines:
  	•	Event metadata
  	•	Attendee research
  	•	Recent conversations


  Email Delivery

  Renders the Markdown as HTML and sends a polished email to your inbox with:
  	•	Meeting timeline & attendees
  	•	Key takeaways & extra context
  	•	Conflicts & FYIs

  Setup Steps

  Prerequisites
  	•	n8n instance (self-hosted or cloud)
  	•	Google Calendar and Gmail OAuth credentials
  	•	OpenRouter key (for GPT-4o or Claude 3.7)

  Configuration
  	Authorize Credentials
  	•	Connect Google Calendar and Gmail nodes with OAuth2
  	•	Set up OpenRouter credentials for AI processing
  	Set Your Email
  Update the Send Email node with your preferred destination address (default is you@yourcompany.com).
  	Set Your Domain Filter
  In the “Identify External Attendees” node, adjust the filter value yourcompany.com to your actual domain.
  	Customize Prompts (Optional)
  You can fine-tune tone, formatting, or limits in the two language model nodes:
  	•	Research and Develop Brief (attendee context + email summary)
  	•	Summarize Schedule (overall Markdown brief formatting)
  	Activate Workflow

  Enable the workflow and test it manually once to validate your setup. Confirm that the email lands correctly.

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.markdown","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleCalendar","n8n-nodes-base.splitOut","n8n-nodes-base.filter","n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.gmail"]

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name: Notion Status-Based Alert Messages (Slack, Telegram, WhatsApp, Discord, Email)
author_name: Matty Reed
author_username: mattyreed1
categories: []
created_at: 2025-05-25T20:54:15.469Z
updated_at: 2025-05-25T20:54:15.469Z
url: https://n8n.io/workflows/4386
scraped_at: 2025-12-24 13:02:45
description:
  Notion Status-Based Alert Template

  Who is this for?
  Teams that live in Notion and want an instant ping to the right person when a task changes state.  
  Perfect for content creators, project managers, or any small team that tracks work in a Notion database and prefers Slack / Telegram / Discord / e-mail notifications over manually checking a board.

  What problem does this solve?
  Polling Notion or checking a kanban board is slow and error-prone.  
  This workflow watches a Notion database and routes an alert to specific people based on the item’s Status. One central map decides who gets pinged for “On Deck”, “In Progress”, “Ready for Review”, or “Ready to Publish”.

  How it works
  Trigger – choose either method  
     Polling (Notion Trigger) – fires every minute.  
     Push (Webhook) – register the production URL in a Notion automation and disable polling.
  Set Notion Page Info – copies Title, Status, URL, etc. into top-level fields.
  Switch (Status router) – routes the item down a branch that matches its Status.
  Set-Mention nodes – one per Status. Each node sets a single field mention (e.g. &lt;@U123456&gt;).  
     Add or edit these nodes to map new statuses or recipients.
  Build Message – assembles a rich text block:  
  Task title
  Status: 
  &lt;@UserIDs&gt;
  &lt;Notion URL|Open in Notion&gt;
  Send nodes – Slack (active) + optional Telegram / WhatsApp / Discord / Email (disabled by default). All reuse the same {{$json.message}}.

  Setup steps
  Import this template into n8n.
  Connect credentials  
  Notion API token  
  Slack OAuth (and any other channels you enable)  
  Edit the Status → Mention map  
  Open each Set-Mention node and replace the placeholder with the real Slack ID / chat ID / phone / email.  
  Copy a node for every extra Status you use, wire it to a new Switch output, and update the value.
  Set environment variables (recommended)  
  NOTION_DB_ID, SLACK_CHANNEL, EMAIL_FROM, etc.
  Pick your trigger style  
  Keep polling enabled or disable it and enable the Webhook, then register the webhook URL in Notion.
  Test – change a task’s Status in Notion → watch Slack for the ping.

  Example output
  &gt; Title: “Draft blog post – AI productivity”  
  &gt; Status: Ready for Review  
  &gt; Slack message:  
  &gt; &gt; Draft blog post – AI productivity
  &gt; Status: Ready for Review
  &gt; &lt;@U789012&gt;
  &gt; &lt;https://www.notion.so/…|Open in Notion&gt;
  &gt; 
  Extending the flow
  Wire additional channels after Build Message—they all consume the same {{$json.message}}.
  Add richer logic (e.g. due-date reminders) in the Set Notion Page Info node.
  Verify Notion webhook signatures in a Function node if you rely on push triggers.

  This template is the leanest possible setup: one table of statuses → direct pings to the right people. Swap the IDs, flip on your favourite channels, and ship.

nodes_used:
  ["n8n-nodes-base.emailSend","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.switch","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.slack","n8n-nodes-base.telegram","n8n-nodes-base.whatsApp","n8n-nodes-base.discord","n8n-nodes-base.notionTrigger","n8n-nodes-base.webhook","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Smart Knowledge Base with Google Docs, Discord & GPT-4o-mini
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-05-25T23:06:04.917Z
updated_at: 2025-05-25T23:06:04.917Z
url: https://n8n.io/workflows/4388
scraped_at: 2025-12-24 13:02:45
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  🧠 MCP Memory Core: AI-Powered Knowledge Base
  Store, retrieve, and act on organizational memories using Google Docs + Discord. Part of the MCP ecosystem.

  Advanced toolchain with multi-platform integration

  🔍 What It Does

      📚 Save Memories: Log conversations, decisions, or code snippets to a Google Doc (timestamped).

      🔍 Retrieve Memories: Fetch past context for AI agents or workflows.

      📤 Auto-Send Updates: Push memories to Discord channels/DMs via GPT-4o-mini formatting.

      🤖 MCP-Compatible: Works with your existing GitHub/Discord MCP workflows.

  🚀 Key Features

      🌐 Multi-Trigger: Use via:

          save_memory / retrieve_memory API routes.

          Discord mentions via MCP Server integration.

      🔐 Secure Storage: Memories live in your Google Docs (no third-party DB).

      🧩 Modular Design: Swap Google Docs for Notion/Airtable with minimal changes.

      🤖 AI Cleanup: GPT-4o-mini reformats raw data into Discord-friendly messages.

  ⚙️ Use Cases

      Team Knowledge Base: Archive meeting notes accessible via Discord commands.

      AI Context Window: Give bots long-term memory for better issue resolution.

      Audit Trail: Track project decisions with timestamps.

  🛠️ Setup Guide

      📝 Configure Google Docs:

          In "Edit Fields", set sheet_id to your Google Doc URL.

      🤖 Discord Permissions:

          Update discord_server_id, discord_channel_id, and discord_user_id.

      🔗 Link to MCP:

          Use the MCP Server Trigger node to connect to existing workflows.

      🧠 Customize AI:

          Tweak the AI Agent prompt for different formatting styles.

  Works great with the $1 GitHub MCP Server template!

nodes_used:
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name: Collect Conference Feedback with Forms and Log to Excel OneDrive with Outlook Notifications
author_name: Akhil Varma Gadiraju
author_username: akhilv7
categories: []
created_at: 2025-05-26T03:43:21.953Z
updated_at: 2025-05-26T03:43:21.953Z
url: https://n8n.io/workflows/4389
scraped_at: 2025-12-24 13:02:44
description:
  Conference Feedback Collection and OneDrive Logging Workflow

  This n8n workflow is designed to collect feedback through a web form, log the responses into an Excel file stored in Microsoft OneDrive, and notify the support team via email.

  🧭 Overall Goal

  To collect user feedback from a web form, structure the data, log it into a OneDrive Excel file, and notify support via Outlook email.

  🔄 Workflow Breakdown

  1. Form Submission (On form submission)
  Node Type**: formTrigger
  Purpose**: Captures user feedback via a web form.
  Form Fields**:
    Full Name (Required)
    Email (Required)
    Company Name
    Job Title
    How did you hear about the conference? (Required)
    Overall experience rating (Required)
    Favorite sessions/speakers
    Relevance to interests/work (Required)
    Networking opportunities (Required)
    Suggestions for improvement
    Future topics/speakers
    Willingness to attend again (Required)
    Additional comments
    Contact permission (Required)
  Access URL**: /webhook/feedback (or /webhook-test/feedback during testing)

  2. Parse Data (Set)
  Purpose**: Renames form fields to snake_case.
  Output**: Structured JSON with renamed fields.

  3. Sample File (Convert to File)
  Purpose**: Generates a file name reference for search.
  Filename**: test-n8n-feedback-form-data.xlsx

  4. Search Document (Microsoft OneDrive)
  Purpose**: Searches OneDrive for the specified Excel file.
  Query**: test-n8n-feedback-form-data.xlsx

  5. Extract File ID (Code)
  Purpose**: Extracts the ID of the file from the search result.
  Output**: { "id": "someFileId" } or { "id": null }

  6. Check File Existence (If)
  Purpose**: Branch logic based on file existence.
  Condition**: If id exists.

  7. Build Sheet Data (Set)
  Purpose**: Prepares the data to match the Excel column headers.
  Only Runs If**: File was found.

  8. Append Data to Excel (Microsoft Excel)
  Purpose**: Appends the new feedback as a row.
  Workbook ID**: {{ $('Code').item.json.id }}
  Worksheet Name**: Sheet1
  Mode**: Auto-map from input fields

  9. Notify Support (Microsoft Outlook)
  Purpose**: Sends a notification email with key feedback details.
  To**: test@gmail.com
  Subject**: "New Feedback Submission Received"
  Body**: Includes key details from submission

  10. End Workflow (NoOp)
  Purpose**: Marks logical end of the workflow.

  📝 Sticky Notes

  ✅ Upload Target Excel File First: Ensure the Excel file exists in OneDrive.
  📝 Filename Consistency: Filename should match in "Sample File" and "Search Document" nodes.
  📧 Customize Email Content: Update "Notify Support" node with your desired message and recipient.

  🔧 Customization Guide

  🧾 Form Customization
  Change form title, description, fields, or path.

  🧪 Parsing Logic
  Update field mappings if form labels change.

  📁 Excel File Settings
  Filename must match your actual OneDrive file.
  Worksheet name and column headers must match in "Build Sheet Data".

  📬 Email Settings
  Update subject and body using variables like {{ $('Parse Data').item.json.full_name }}.

  ❗ Error Handling Tips
  Adjust email content based on file presence.
  Add an "Error Trigger" for advanced error management.

  🔁 Alternatives and Extensions
  Use Google Sheets, Airtable, or databases instead of OneDrive/Excel.
  Add Slack or SMS notifications.

  📌 Use Cases
  Post-event Feedback
  CSAT Surveys
  Employee Feedback
  Bug Reporting
  Lead Capture
  Contact Forms
  Webinar Registration

  🔐 Required Credentials

  1. Microsoft OneDrive (OAuth2)
  Used by**: "Search Document"
  Credential Name**: Microsoft Drive account

  2. Microsoft Excel (OAuth2)
  Used by**: "Append Data"
  Credential Name**: Microsoft Excel account

  3. Microsoft Outlook (OAuth2)
  Used by**: "Notify Support"
  Credential Name**: Outlook 0Auth2

  ❤️ Made with n8n by Akhil

nodes_used:
  ["n8n-nodes-base.formTrigger","n8n-nodes-base.set","n8n-nodes-base.microsoftOneDrive","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.microsoftExcel","n8n-nodes-base.noOp","n8n-nodes-base.microsoftOutlook","n8n-nodes-base.stickyNote","n8n-nodes-base.convertToFile","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: Generate & Edit Images with OpenAI GPT-Image-1 and Share via Telegram
author_name: Alexey from Mingles.ai
author_username: alexx
categories: []
created_at: 2025-05-26T08:42:12.797Z
updated_at: 2025-05-26T08:42:12.797Z
url: https://n8n.io/workflows/4391
scraped_at: 2025-12-24 13:02:43
description:
  AI Image Generator & Editor with GPT-4 Vision - Complete Workflow

  Template Description

  Transform text prompts into stunning images or edit existing visuals using OpenAI's latest GPT-4 Vision model through an intuitive web form interface.

  This comprehensive n8n automation provides three powerful image generation modes:

  🎨 Text-to-Image Generation
  Simply enter a descriptive prompt and generate high-quality images from scratch using OpenAI's gpt-image-1 model. Perfect for creating original artwork, concepts, or visual content.

  🖼️ Image-to-Image Editing 
  Upload an existing image file and transform it based on your text prompt. The AI analyzes your input image and applies modifications while maintaining the original structure and context.

  🔗 URL-Based Image Editing
  Provide a direct URL to any online image and edit it with AI. Great for quick modifications of web images or collaborative workflows.

  Key Features

  Smart Input Processing
  Flexible Form Interface**: User-friendly web form with authentication
  Multiple Input Methods**: File upload, URL input, or text-only generation
  Quality Control**: Selectable quality levels (low, medium, high)
  Format Support**: Accepts PNG, JPG, and JPEG formats

  Advanced AI Integration
  Latest GPT-4 Vision Model**: Uses gpt-image-1 for superior results
  Intelligent Switching**: Automatically detects input type and routes accordingly
  Context-Aware Editing**: Maintains image coherence during modifications
  Customizable Parameters**: Control size (1024x1024), quality, and generation settings

  Dual Storage Options
  Google Drive Integration**: Automatic upload with public sharing permissions
  ImgBB Hosting**: Alternative cloud storage for instant public URLs
  File Management**: Organized storage with timestamp-based naming

  Instant Telegram Delivery
  Real-time Notifications**: Results sent directly to your Telegram chat
  Rich Media Messages**: Includes generated image with prompt details
  Quick Access Links**: Direct links to view and download results
  Markdown Formatting**: Clean, professional message presentation

  Technical Workflow

  Form Submission → User submits prompt and optional image
  Smart Routing → System detects input type (text/file/URL)
  AI Processing → OpenAI generates or edits image based on mode
  Binary Conversion → Converts base64 response to downloadable file
  Cloud Upload → Stores in Google Drive or ImgBB with public access
  Telegram Delivery → Sends result with viewing links and metadata

  Perfect For

  Content Creators**: Generate unique visuals for social media and marketing
  Designers**: Quick concept development and image variations
  Developers**: Automated image processing for applications
  Teams**: Collaborative image editing and sharing workflows
  Personal Use**: Transform ideas into visual content effortlessly

  Setup Requirements

  OpenAI API Key**: Access to GPT-4 Vision model
  Google Drive API** (optional): For Google Drive storage
  ImgBB API Key** (optional): For alternative image hosting
  Telegram Bot**: For result delivery
  Basic Auth Credentials**: For form security

  What You Get

  ✅ Complete image generation and editing pipeline  
  ✅ Secure web form with authentication  
  ✅ Dual cloud storage options  
  ✅ Instant Telegram notifications  
  ✅ Professional result formatting  
  ✅ Flexible input methods  
  ✅ Quality control settings  
  ✅ Automated file management  

  Start creating AI-powered images in minutes with this production-ready template!

  Tags: #AI #ImageGeneration #OpenAI #GPT4 #ImageEditing #Telegram #GoogleDrive #Automation #ComputerVision #ContentCreation

nodes_used:
  ["n8n-nodes-base.googleDrive","n8n-nodes-base.httpRequest","n8n-nodes-base.convertToFile","n8n-nodes-base.convertToFile","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.telegram","n8n-nodes-base.switch"]

workflow_json_compressed:
  [encoded data, 4228 characters]


name: Command-based Telegram Bot for Article Summarization & Image Prompts with OpenAI
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-26T08:42:40.893Z
updated_at: 2025-05-26T08:42:40.893Z
url: https://n8n.io/workflows/4392
scraped_at: 2025-12-24 13:02:44
description:
  Telegram AI Assistant: Summarize Links & Generate Images On Demand

  This workflow turns any Telegram chat into a smart assistant. By typing simple commands like /summary or /img, users can trigger powerful AI actions—directly from Telegram.

  ✨ What It Does

  This automation listens for specific commands in Telegram messages:

  /help: Sends a help menu explaining available commands.
  /summary &lt;link&gt;: Fetches a webpage, extracts its content, and summarizes it using OpenAI into 10–12 bullet points.
  /img &lt;prompt&gt;: Sends the image prompt to OpenAI and replies that the request has been received (designed for future integration with image APIs).

  📦 Features

  ✅ Works instantly in Telegram  
  🧠 Uses OpenAI for text summarization and image prompt processing  
  🌐 Scrapes and cleans raw article text before summarizing  
  📤 Replies directly to the same Telegram thread  
  🔧 Easily expandable to support more commands  

  🔧 Use Cases

  Research Summaries**: Quickly condense articles or reports shared in chat.  
  Content Review**: Get team-friendly TL;DRs of long blog posts or product pages.  
  Creative Brainstorming**: Share visual ideas via /img and get quick prompts logged.  
  Customer Support**: Offer instant answers in group chats (with further extension).  
  Daily Digest Bot**: Connect to news feeds and auto-summarize updates.  

  🚀 Getting Started

  Clone this workflow and connect your Telegram Bot.  
  Insert your OpenAI credentials.  
  Deploy and test by messaging /summary https://example.com in your Telegram group or DM.  
  Expand with new commands or connect Stability.ai or other services for real image generation.  

  🔗 Author & Resources

  Built by Yaron Been  
  Follow more automations at nofluff.online

nodes_used:
  ["n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegramTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.html","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.stickyNote"]

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name: Track Expenses by Parsing Telegram Transaction Messages to Google Sheets
author_name: Mujtaba
author_username: mujtaba
categories: []
created_at: 2025-05-26T09:38:42.548Z
updated_at: 2025-05-26T09:38:42.548Z
url: https://n8n.io/workflows/4395
scraped_at: 2025-12-24 13:02:44
description:
  Overview

  This n8n workflow template automatically parses incoming Telegram transaction messages and logs structured data into a Google Sheet. It’s designed to help individuals and small businesses track and record transactions shared via Telegram without manual data entry.

  Target Audience

  This template is ideal for:

  Individuals, freelancers, and small businesses who receive transaction or payment notifications through Telegram and want to organize them in Google Sheets.

  Anyone using self-hosted n8n (required due to custom community nodes).

  Problem Solved

  Manually copying transaction details from Telegram to Google Sheets is error-prone and time-consuming.
  This workflow automates the process by:

  Monitoring a Telegram bot/chat for new messages.

  Parsing transaction details (amount, sender, date, etc.).

  Logging them in real-time into a Google Sheet for easy tracking.

  Setup Instructions

  Telegram Bot Setup
  Create a Telegram bot using BotFather.

  Add the bot to the desired group/channel and grant admin permissions if needed.

  Note down the bot token.

  Google Sheets Setup
  Create a Google Sheet with relevant columns (e.g., Date, Amount, Sender, Transaction ID).

  Set up Google Sheets credentials in n8n for access.

  n8n Workflow Configuration
  Import this template into your self-hosted n8n instance.

  Update the Telegram node: Add your bot token and specify the chat/group ID.

  Update the Google Sheets node: Link it to your created sheet and ensure column mapping matches your sheet structure.

  Adjust parsing logic if your message format varies (see next section for examples).

  Community Nodes
  This workflow uses custom community nodes. Ensure these are installed via the n8n settings or CLI:

  [List your required community nodes here, e.g., n8n-nodes-telegram, n8n-nodes-gsheet, etc.]

  Activate the Workflow
  Save and activate your workflow. Send a test transaction message to your Telegram group/chat and verify data appears in your Google Sheet.

  Troubleshooting
  If messages are not being picked up, check bot permissions and the chat ID.

  Ensure Google Sheets credentials are correct and the sheet is accessible.

  Double-check that custom nodes are properly installed and up-to-date.

  Example Telegram Message Formats

  Received: $75 from @john_doe on 2024-05-29. Transaction ID: 12345XYZ.
  Paid $120 to @vendor on 2024-05-28. Ref: 67890ABC.
  You received ₹5,000 from @amit. ID: 54321PQR. Date: 29/05/2024
  The workflow parses messages in the above formats and logs the following columns:

  Date

  Amount

  Sender/Receiver

  Transaction/Reference ID

  If your message format differs, update the regex in the parsing node.

  Disclaimer

  This n8n workflow template uses custom community nodes and is only compatible with the self-hosted version of n8n.

  Workflow Changes (For n8n Canvas)
  Rename the Nodes:

  'If' node → “Is Transaction Message?”

  'Google Sheets' node → “Log to Google Sheet”

  (Rename other generic nodes for clarity, e.g., 'Telegram' → “Listen for Telegram Messages”, 'Function' → “Parse Transaction Details”)

  Sticky Note Improvement:
  (Edit the sticky note or add one if missing)

  Workflow Steps:

  Listen for Telegram Messages: This node receives new messages from the Telegram bot.

  Is Transaction Message? Checks if the message matches known transaction patterns.

  Parse Transaction Details: Extracts amount, sender, date, and transaction ID using regex.

  Log to Google Sheet: Records the parsed transaction in the linked Google Sheet for easy tracking.

nodes_used:
  ["n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.telegramTrigger","n8n-nodes-base.code","n8n-nodes-base.stickyNote"]

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name: Smart Shopify Agent: AI-Powered Abandoned Cart Recovery
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-05-26T11:59:22.062Z
updated_at: 2025-05-26T11:59:22.062Z
url: https://n8n.io/workflows/4396
scraped_at: 2025-12-24 13:02:44
description:
  🤖 AI Cart Recovery Agent: Smart Abandoned Checkout Assistant

  Transform abandoned carts into recovered sales with intelligent automation. This sophisticated n8n workflow monitors checkout abandonment, implements smart waiting periods, and sends AI-generated personalized recovery emails only when needed - maximizing conversions while respecting customer experience.

  🔄 How It Works

  This intelligent 7-step recovery system recovers lost sales automatically:

  Step 1: Initial Abandonment Detection
  The workflow fetches current abandoned checkout data from your e-commerce platform (Shopify, WooCommerce, etc.), identifying customers who added items but didn't complete their purchase.

  Step 2: Strategic Grace Period
  Instead of immediately sending recovery emails, the system waits 1 hour (customizable), giving customers natural time to complete their purchase without pressure or interruption.

  Step 3: Smart Re-verification
  After the waiting period, the workflow rechecks the abandonment status by fetching updated checkout data, ensuring accuracy before taking action.

  Step 4: Intelligent Decision Logic
  Advanced conditional logic compares initial and updated abandonment lists, determining if customers are still abandoned or have completed their purchase during the grace period.

  Step 5: AI-Powered Email Generation
  For customers still showing abandonment, GPT generates personalized recovery emails featuring:
  Customer's actual name for personal connection
  Specific products left in their cart
  Friendly, non-pushy messaging tone
  Optional discount incentives
  Compelling call-to-action to complete purchase

  Step 6: Automated Email Delivery
  Personalized recovery emails are sent directly to abandoned customers via Gmail or your preferred email service, maintaining professional branding and deliverability.

  Step 7: Comprehensive Activity Logging
  All recovery attempts are logged in Google Sheets for tracking, including customer details, email content, and campaign performance analytics.

  ⚙️ Setup Steps

  Prerequisites
  E-commerce platform with API access (Shopify, WooCommerce, BigCommerce)
  OpenAI API key for personalized email generation
  Gmail or SMTP email service for delivery
  Google Sheets for activity tracking and analytics
  n8n instance (cloud or self-hosted)

  E-commerce Platform Configuration

  Shopify Setup:
  API Endpoint: https://your-store.myshopify.com/admin/api/2023-10/checkouts.json
  Authentication: X-Shopify-Access-Token header
  Required Permissions: Read checkouts, Read customers
  Parameters: status=abandoned

  WooCommerce Setup:
  API Endpoint: https://your-site.com/wp-json/wc/v3/orders
  Authentication: Consumer Key/Secret or JWT
  Parameters: status=pending, status=failed
  Required Plugins: WooCommerce REST API

  Configuration Steps

  1. Credential Setup
  E-commerce API**: Store admin API access tokens or keys
  OpenAI API Key**: GPT-4 access for intelligent email generation
  Gmail OAuth2**: Professional email delivery service
  Google Sheets OAuth2**: Activity logging and performance tracking

  2. Abandonment Detection Configuration
  Monitoring Frequency**: Set workflow trigger schedule (hourly, daily)
  Grace Period Duration**: Customize wait time (default: 1 hour)
  Platform Integration**: Configure API endpoints for your specific platform
  Data Filtering**: Set criteria for what constitutes abandonment

  3. AI Email Customization
  Default email generation includes:
  Personalization Level**: Customer name, product specifics, cart value
  Tone Customization**: Friendly, urgent, helpful, or premium
  Discount Integration**: Optional percentage or fixed amount offers
  Brand Voice**: Maintain consistent company messaging and style

  4. Recovery Campaign Settings
  Email Timing**: Optimal sending times based on customer time zones
  Frequency Limits**: Prevent over-emailing with cooldown periods
  Segmentation Rules**: Different approaches for high-value vs standard carts
  Follow-up Sequences**: Multi-email recovery campaigns with escalating incentives

  5. Performance Tracking Setup
  Analytics Dashboard**: Google Sheets with recovery metrics and ROI
  Success Tracking**: Monitor completion rates and revenue recovered
  A/B Testing**: Compare different email approaches and timing
  Customer Journey**: Track from abandonment through recovery completion

  🚀 Use Cases

  E-commerce Retailers
  Fashion & Apparel**: Recover high-value clothing and accessory purchases
  Electronics**: Target abandoned tech purchases with technical support offers
  Home & Garden**: Remind customers about seasonal or home improvement items
  Beauty & Cosmetics**: Recover abandoned skincare and makeup purchases

  Subscription & SaaS Businesses
  Software Trials**: Convert abandoned trial signups into paid subscriptions
  Membership Sites**: Recover incomplete membership purchases
  Online Courses**: Re-engage learners who abandoned course purchases
  Digital Services**: Follow up on abandoned service bookings or consultations

  B2B E-commerce
  Office Supplies**: Recover bulk order abandonments with volume discounts
  Industrial Equipment**: Follow up on high-value equipment quote requests
  Professional Services**: Re-engage businesses that abandoned service bookings
  Software Licenses**: Recover enterprise software purchase abandonments

  Specialty Retailers
  Luxury Goods**: Provide white-glove service for high-value abandoned purchases
  Custom Products**: Follow up on personalized or custom order abandonments
  Seasonal Items**: Time-sensitive recovery for holiday or event-specific products
  Limited Edition**: Create urgency for exclusive or limited availability items

  Service-Based Businesses
  Travel & Hospitality**: Recover abandoned hotel, flight, or package bookings
  Event Tickets**: Re-engage customers who abandoned concert or event purchases
  Professional Services**: Follow up on abandoned consultation or service bookings
  Fitness & Wellness**: Recover abandoned membership or class package purchases

  🔧 Advanced Customization Options

  Multi-Platform Integration
  Extend beyond single platform monitoring:
  Shopify Plus: Advanced checkout analytics and customer segmentation
  WooCommerce: Custom post-purchase and abandonment tracking
  Magento: Enterprise-level cart recovery with customer journey mapping
  BigCommerce: API-driven recovery with advanced personalization
  Custom Platforms: Webhook-based abandonment detection and recovery

  Intelligent Email Sequencing
  Create sophisticated recovery campaigns:
  Progressive Incentives**: Escalating discounts over multiple touchpoints
  Behavioral Triggers**: Different emails based on cart value, customer history
  Seasonal Campaigns**: Holiday-specific recovery messaging and offers
  Win-Back Sequences**: Long-term customer re-engagement beyond immediate recovery

  Advanced Personalization
  Enhance AI-generated content with:
  Purchase History Analysis**: Reference previous purchases and preferences
  Browsing Behavior**: Include recently viewed items and categories
  Geographic Personalization**: Local offers, shipping options, or store locations
  Demographic Targeting**: Age, gender, or interest-based messaging customization

  Performance Optimization
  Implement advanced tracking and optimization:
  Revenue Attribution**: Track exact recovery amounts and ROI calculations
  Customer Lifetime Value**: Prioritize high-value customer recovery efforts
  Conversion Funnel Analysis**: Identify optimal timing and messaging strategies
  Predictive Analytics**: Use ML to predict recovery likelihood and optimize approaches

  📊 Recovery Email Examples

  Fashion Retailer Example:
  Subject: You left something stylish behind, Sarah!

  Hi Sarah,

  I noticed you were checking out those gorgeous items in your cart earlier - the Bohemian Summer Dress and Classic Leather Handbag have been waiting for you!

  I completely understand if you got busy or needed time to think it over. These pieces are still available and ready to ship to you today.

  Since you showed such great taste in selecting these items, I'd love to offer you 10% off your order to make the decision easier. Just use code WELCOME10 at checkout.

  Your cart includes:
  • Bohemian Summer Dress (Size M) - $89.99
  • Classic Leather Handbag (Brown) - $156.99

  Complete your purchase now and get free shipping to your door!

  [Complete My Purchase] 

  Best regards,
  The StyleHub Team

  P.S. These items are popular and inventory is limited - don't wait too long!

  Software/SaaS Example:
  Subject: Your ProductivityPro trial is waiting, Mike

  Hi Mike,

  You were just one step away from unlocking the full power of ProductivityPro for your team at TechStartup Inc.

  I noticed you explored our Premium Plan features - the advanced reporting and team collaboration tools that could streamline your workflow and boost productivity by up to 40%.

  Since you invested time exploring our platform, I'd like to offer you an exclusive 25% discount on your first year. This offer is valid for the next 48 hours.

  Your selected plan:
  • ProductivityPro Premium (5 users) - $99/month
  • With 25% discount: $74/month (Save $300/year!)

  Ready to transform your team's productivity?

  [Activate My Account]

  Questions? Reply to this email or schedule a quick 15-minute demo call.

  Best regards,
  David Chen
  Customer Success Manager, ProductivityPro

  High-Value B2B Example:
  Subject: Your equipment quote is ready for approval, Jennifer

  Hi Jennifer,

  Thank you for your interest in our Industrial Packaging System for ManuCorp's new facility expansion.

  I understand that equipment investments of this scale require careful consideration and stakeholder alignment. Your configured system includes:

  • Model X5000 Packaging Line - $45,000
  • Installation & Training Package - $8,000  
  • Extended 3-Year Warranty - $3,500
  Total Investment: $56,500

  Given the scope of your project, I'd like to extend our Q1 promotion pricing, which provides:
  15% discount on equipment ($6,750 savings)
  Free installation supervision ($2,000 value)
  Expedited 6-week delivery

  This brings your total to $48,750 - a savings of $7,750.

  I'm available for a brief call to address any technical questions or help facilitate internal approvals. 

  [Accept Quote & Proceed]

  Best regards,
  Robert Martinez
  Senior Sales Engineer
  Industrial Solutions Inc.
  Direct: (555) 123-4567

  🛠️ Troubleshooting & Best Practices

  Common Issues & Solutions

  API Rate Limiting
  Implement exponential backoff for API requests
  Stagger workflow execution times across different stores
  Monitor API usage and upgrade plans as needed
  Cache frequently accessed data to reduce API calls

  Email Deliverability Challenges
  Use authenticated SMTP services with proper SPF/DKIM setup
  Monitor sender reputation and email engagement metrics
  Implement opt-out mechanisms and respect unsubscribe requests
  Segment email lists and avoid over-emailing customers

  False Positive Recoveries
  Extend grace periods for complex checkout processes
  Implement more sophisticated abandonment detection logic
  Add customer behavior analysis before triggering recovery
  Create exception rules for technical checkout failures

  Optimization Strategies

  Recovery Timing Optimization
  A/B test different grace period durations (30 min, 1 hour, 3 hours)
  Analyze customer behavior patterns to optimize sending times
  Consider time zone differences for global customer bases
  Implement seasonal timing adjustments for holidays and events

  Content Personalization Enhancement
  Continuously refine AI prompts based on successful recoveries
  Implement dynamic discount strategies based on cart value
  Create customer segment-specific messaging approaches
  Add urgency elements for time-sensitive or limited inventory items

  Performance Measurement
  Track recovery rates, revenue impact, and customer satisfaction
  Implement cohort analysis for long-term customer value impact
  Monitor email engagement metrics and optimize accordingly
  Calculate true ROI including customer acquisition costs and lifetime value

  📈 Success Metrics

  Recovery Performance Indicators
  Recovery Rate**: Percentage of abandoned carts successfully recovered
  Revenue Recovery**: Total dollar amount recovered from abandoned purchases
  Email Engagement**: Open rates, click rates, and conversion rates
  Time to Recovery**: Average time from abandonment to completed purchase

  Business Impact Measurements
  ROI Calculation**: Revenue recovered vs workflow operational costs
  Customer Retention**: Impact on long-term customer relationships
  Average Order Value**: Effect on overall purchase values post-recovery
  Operational Efficiency**: Automation savings vs manual recovery efforts

  📞 Questions & Support

  Need help implementing your AI Cart Recovery Agent?

  📧 E-commerce Automation Expert Support
  Email**: Yaron@nofluff.online
  Response Time**: Within 24 hours on business days
  Specialization**: E-commerce automation, cart recovery optimization, AI email personalization

  🎥 Comprehensive Implementation Resources
  YouTube Channel**: https://www.youtube.com/@YaronBeen/videos
    Complete setup guides for major e-commerce platforms
    Advanced AI email personalization techniques
    Recovery campaign optimization strategies
    Integration tutorials for Shopify, WooCommerce, and custom platforms
    Performance tracking and analytics implementation

  🤝 E-commerce Automation Community
  LinkedIn**: https://www.linkedin.com/in/yaronbeen/
    Connect for ongoing e-commerce automation support and consulting
    Share your cart recovery success stories and ROI achievements
    Access exclusive templates for different industry verticals
    Join discussions about e-commerce automation trends and innovations

  💬 Support Request Guidelines
  Include in your support message:
  Your e-commerce platform and current cart abandonment rates
  Average order values and customer segments you serve
  Current recovery processes and conversion challenges
  Integration requirements with existing marketing tools
  Specific technical errors or workflow execution issues

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.googleSheets","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.noOp","n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: Boost posts/statuses from a specific FediVerse account on your mastodon profile
author_name: Suleman Hasib
author_username: sulemanhasib43
categories: []
created_at: 2025-05-26T12:17:56.625Z
updated_at: 2025-05-26T12:17:56.625Z
url: https://n8n.io/workflows/4397
scraped_at: 2025-12-24 13:02:46
description:
  Template Overview

  This template is designed for individuals and businesses who want to maintain a consistent presence on the Fediverse while also posting on Threads or managing multiple Fediverse profiles. By automating the process of resharing statuses or posts, this workflow saves time and ensures regular engagement across accounts.

  Use Case

  The template addresses the challenge of managing activity across Fediverse accounts by automatically boosting or resharing posts from a specific account to your own. It is especially helpful for users who want to consolidate engagement without manually reposting content across multiple platforms or profiles.

  How It Works

  The workflow runs on a scheduled trigger and retrieves recent posts from a specified Fediverse account, such as your Threads.net account. It uses a JavaScript filter to identify posts from the current day and then automatically boosts or reshares them to your selected Mastodon profile.

  Preconditions

  You need a Mastodon account with developer access.
  Identify a Threads.net or other Fediverse account which you want to boost.
  Basic familiarity with APIs and setting up credentials in n8n.

  Setup Steps

  Step 1: Create a Developer Application on Mastodon

  Log in to your Mastodon account and navigate to Preferences &gt; Development &gt; New Application.
  Fill out the required information and create your application.
  Set Scopes to atleast read, profile, write:statuses.
  Click Submit.
  Note down the access token generated for this application.

  Step 2: Get the Account ID

  Use the following command to retrieve the account ID for the profile you want to boost:

        curl -s "https://mastodon.social/api/v1/accounts/lookup?acct=&lt;ACCOUNTNAME&gt;"
     
     Alternatively, paste the URL into a GET node on n8n.
  From the returned JSON, copy the "id" field value (e.g., {"id":"110564198672505618", ...}).

  Step 3: Update the "Get Statuses" Node

  Replace &lt;ACCOUNTID&gt; in the URL field with the ID you retrieved in Step 2:

        https://mastodon.social/api/v1/accounts/&lt;ACCOUNTID&gt;/statuses
  Step 4: Configure the "Boost Statuses" Node

  Authentication type will already be set to Header Auth.

  Grab the access token from Step 1.
  In the Credential for Header Auth field, create a new credential.
  Click the pencil icon in the top-left corner to name your credential.
  In the Name field, enter Authorization.
  In the Value field, enter Bearer &lt;YOUR_MASTODON_ACCESS_TOKEN&gt;. (Note: there is a space after "Bearer.")
  Save the credential, and it should automatically be selected as your Header Auth.

  Step 5: Test the Workflow

  Run the workflow to ensure everything is set up correctly.
  Adjust filters or parameters as needed for your specific use case.

  Customization Guidance

  Replace mastodon.social with your own Mastodon domain if you're using a self-hosted instance.
  Adjust the JavaScript filter logic to meet your specific needs (e.g., filtering by hashtags or keywords).
  For enhanced security, store the access token as an n8n credential. Embedding it directly in the URL is ++not recommended++.

  Notes

  This workflow is designed to work with any Mastodon domain.
  Ensure your Mastodon account has appropriate permissions for boosting posts.

  By following these steps, you can automate your Fediverse engagement and focus on creating meaningful content while the workflow handles the rest!

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.filter","n8n-nodes-base.httpRequest"]

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name: 📸 Automate Photo Background Removal with Photoroom API and Google Drive
author_name: Samir Saci
author_username: samirsaci
categories: []
created_at: 2025-05-26T12:22:17.704Z
updated_at: 2025-05-26T12:22:17.704Z
url: https://n8n.io/workflows/4398
scraped_at: 2025-12-24 13:02:46
description:
  Tags: Marketing, Image Processing, Automation

  Context

  Hey! I’m Samir, a Data Scientist from Paris and the founder of LogiGreen Consulting.

  We use AI, automation, and data to support sustainable business practices for small, medium and large companies.

  I implemented this workflow to support an event agency to automate image processing like background removal using Photoroom API.




  &gt; Automate your photos processing with n8n!

  This n8n workflow collects all images in a Google Drive folder shared with multiple photographers.

  For each image, it calls the Photoroom API:
  A processed image w/o a background is saved in a subfolder Remove Background
  The original pictures are saved in the subfolder Original

  This workflow, triggered every morning, will process the backlog of images.




  📬 For business inquiries, feel free to connect with me on LinkedIn

  Who is this template for?

  This workflow is useful for:
  Digital Marketing** teams that use images for content creation
  Photographs* or *Event Organisers** that collect large amounts of photos that need processing
  What does it do?

  This n8n workflow:
  ⏰ Triggers automatically every morning  
  🖼️ Collects the names and IDs of all images in the folder
  🧹 HTTP POST request to Photoroom API to remove the background
  📄 Stores the processed image and the original image in two separate sub-folders  

  What do I need to get started?

  You’ll need:
  A Google Drive Account connected to your n8n instance with credentials
  A Photoroom API key that you can get for free (trial) here: Photoroom API

  Follow the Guide!

  Follow the sticky notes inside the workflow or check out my step-by-step tutorial on how to configure and deploy it.



  🎥 Watch My Tutorial



  This workflow was built using n8n version 1.93.0  
  Submitted: May 26, 2025

nodes_used:
  ["n8n-nodes-base.splitInBatches","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote"]

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name: Anthropic AI Agent: Claude Sonnet 4 and Opus 4 with Think and Web Search tool
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-05-26T12:27:34.726Z
updated_at: 2025-05-26T12:27:34.726Z
url: https://n8n.io/workflows/4399
scraped_at: 2025-12-24 13:02:41
description:
  This workflow dynamically chooses between two new powerful Anthropic models — Claude Opus 4 and Claude Sonnet 4 — to handle user queries, based on their complexity and nature, maintaining scalability and context awareness with Anthropic web search function and Think tool.

  Key Advantages

  🔁 Dynamic Model Selection

     Automatically routes each user query to either Claude Sonnet 4 (for routine tasks) or Claude Opus 4 (for complex reasoning), ensuring optimal performance and cost-efficiency.

  🧠 AI Agent with Tool Use

     The AI agent can utilize a web search tool to retrieve up-to-date information and a Think tool for complex reasoning processes — improving response quality.

  📎 Memory Integration

     Uses session-based memory to maintain conversational context, making interactions more coherent and human-like.

  🧮 Built-in Calculation Tool

     Handles numeric queries using an integrated calculator tool, reducing the need for external processing.

  📤 Structured Output Parser

     Ensures outputs are always well-structured and formatted in JSON, which improves consistency and downstream integrations.

  🌐 Web Search Capability

     Supports real-time information retrieval for current events, statistics, or details not available in the AI’s base knowledge.

  Components Overview

  Trigger**: Listens for new chat messages.
  Routing Agent**: Analyzes the message and returns the best model to use.
  AI Agent**: Handles the conversation, decides when to use tools.
  Tools**:

    web_search for internet queries
    Think for reasoning
    Calculator for math tasks
  Models Used**:

    claude-sonnet-4-20250514: Optimized for general and business logic tasks.
    claude-opus-4-20250514: Best for deep, strategic, and analytical queries.

  How It Works
  Dynamic Model Selection  
     The workflow begins when a chat message is received. The Anthropic Routing Agent analyzes the user's query to determine the most suitable model (either Claude Sonnet 4 or Claude Opus 4) based on the query's complexity and requirements.  
     The routing agent uses predefined criteria to decide:  
       Claude Sonnet 4: Best for standard tasks like real-time workflow routing, data validation, and routine business logic.  
       Claude Opus 4: Reserved for complex scenarios requiring deep reasoning, advanced analysis, or high-impact decisions.  

  Query Processing and Response Generation  
     The selected model processes the query, leveraging tools like web_search for real-time information retrieval, Think for internal reasoning, and Calculator for numerical tasks.  
     The AI Agent coordinates these tools, ensuring the response is accurate and context-aware. A Simple Memory node retains session context for coherent multi-turn conversations.  
     The final response is formatted and returned to the user without intermediate steps or metadata.  

  Set Up Steps
  Node Configuration  
     Trigger: Configure the "When chat message received" node to handle incoming user queries.  
     Routing Agent: Set up the "Anthropic Routing Agent" with the system message defining model selection logic. Ensure it outputs a JSON object with prompt and model fields.  
     AI Model Nodes: Link the "Sonnet 4 or Opus 4" node to dynamically use the selected model. The "Sonnet 3.7" node powers the routing agent itself.  

  Tool Integration  
     Attach the "web_search" HTTP tool to enable internet searches, ensuring the API endpoint and headers (e.g., anthropic-version) are correctly configured.  
     Connect auxiliary tools (Think, Calculator) to the "AI Agent" for extended functionality.  
     Add the "Simple Memory" node to maintain conversation history.  

  Credentials  
     Provide an Anthropic API key to all nodes requiring authentication (e.g., model nodes, web search).  

  Testing  
     Activate the workflow and test with sample queries to verify:  
       Correct model selection (e.g., Sonnet for simple queries, Opus for complex ones).  
       Proper tool usage (e.g., web searches trigger when needed).  
       Memory retention across chat turns.  

  Deployment  
     Once validated, set the workflow to active for live interactions.  

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

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolThink","@n8n/n8n-nodes-langchain.toolCalculator","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatAnthropic","@n8n/n8n-nodes-langchain.lmChatAnthropic","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.httpRequestTool"]

workflow_json_compressed:
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name: Build a PDF Document RAG System with Mistral OCR, Qdrant and Gemini AI
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-05-26T12:28:14.350Z
updated_at: 2025-05-26T12:28:14.350Z
url: https://n8n.io/workflows/4400
scraped_at: 2025-12-24 13:02:41
description:
  This workflow is designed to process PDF documents using Mistral's OCR capabilities, store the extracted text in a Qdrant vector database, and enable Retrieval-Augmented Generation (RAG) for answering questions. Here’s how it functions:  

  Once configured, the workflow automates document ingestion, vectorization, and intelligent querying, enabling powerful RAG applications.

  Benefits

  End-to-End Automation**
    No manual interaction is needed: documents are read, processed, and made queryable with minimal setup.

  Scalable and Modular**
    The workflow uses subflows and batching, making it easy to scale and customize.

  Multi-Model Support**
    Combines Mistral for OCR, OpenAI for embeddings, and Gemini for intelligent answering—taking advantage of the strengths of each.

  Real-Time Q\&A**
    With RAG integration, users can query document content through natural language and receive accurate responses grounded in the PDF data.

  Light or Full Mode**
    Users can choose to index full page content or only summarized text, optimizing for either performance or richness.

  How It Works 

  PDF Processing with Mistral OCR:  
     The workflow starts by uploading a PDF file to Mistral's API, which performs OCR to extract text and metadata.  
     The extracted content is split into manageable chunks (e.g., pages or sections) for further processing.  

  Vector Storage in Qdrant:  
     The extracted text is converted into embeddings using OpenAI's embedding model.  
     These embeddings are stored in a Qdrant vector database, enabling efficient similarity searches for RAG.  

  Question-Answering with RAG:  
     When a user submits a question via a chat interface, the workflow retrieves relevant text chunks from Qdrant using vector similarity.  
     A language model (Google Gemini) generates answers based on the retrieved context, providing accurate and context-aware responses.  

  Optional Summarization:  
     The workflow includes an optional summarization step using Google Gemini to condense the extracted text for faster processing or lighter RAG usage.  

  Set Up Steps  
  To deploy this workflow in n8n, follow these steps:  

  Configure Qdrant Database:  
     Replace QDRANTURL and COLLECTION in the "Create collection" and "Refresh collection" nodes with your Qdrant instance details.  
     Ensure the Qdrant collection is configured with the correct vector size (e.g., 1536 for OpenAI embeddings) and distance metric (e.g., Cosine).  

  Set Up Credentials:  
     Add credentials for:  
       Mistral Cloud API (for OCR processing).  
       OpenAI API (for embeddings).  
       Google Gemini API (for chat and summarization).  
       Google Drive (if sourcing PDFs from Drive).  
       Qdrant API (for vector storage).  

  PDF Source Configuration:  
     If using Google Drive, specify the folder ID in the "Search PDFs" node.  
     Alternatively, modify the workflow to accept PDFs from other sources (e.g., direct uploads or external APIs).  

  Customize Text Processing:  
     Adjust chunk size and overlap in the "Token Splitter" node to optimize for your document type.  
     Choose between raw text or summarized content for RAG by toggling between the "Set page" and "Summarization Chain" nodes.  

  Test the RAG:  
     Trigger the workflow manually or via a chat message to verify OCR, embedding, and Qdrant storage.  
     Use the "Question and Answer Chain" node to test query responses.  

  Optional Sub-Workflows:  
     The workflow supports execution as a sub-workflow for batch processing (e.g., handling multiple PDFs).  

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

nodes_used:
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name: AI Chatbot Agent with a Panel of Experts using InfraNodus GraphRAG Knowledge
author_name: InfraNodus
author_username: infranodus
categories: []
created_at: 2025-05-26T12:34:52.632Z
updated_at: 2025-05-26T12:34:52.632Z
url: https://n8n.io/workflows/4402
scraped_at: 2025-12-24 13:02:41
description:
  Using the knowledge graphs instead of RAG vector stores

  This workflow creates an AI 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 (no complex data import workflows needed)
  A knowledge graph has a holistic view of your knowledge base
  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 AI chatbot (n8n interface, in this case, which can be accessed via a URL or embedded to any website)
  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 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 user's chat (or a webhook endpoint)

  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

  Requirements

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

  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. 

  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:

nodes_used:
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name: Find Content Gaps in Competitors' Websites with InfraNodus GraphRAG for SEO
author_name: InfraNodus
author_username: infranodus
categories: []
created_at: 2025-05-26T12:58:02.888Z
updated_at: 2025-05-26T12:58:02.888Z
url: https://n8n.io/workflows/4403
scraped_at: 2025-12-24 13:02:41
description:
  This template can be used to find the content gaps in your competitors' discourse: identifying the topics they are not yet connecting and giving you an opportunity to fill in this gap with your content and product ideas. It will also generate research questions that will help bridge the gaps and generate new ideas.

  The template showcases the use of multiple n8n nodes and processes:
  enriching Google sheets file with the new data
  data extraction
  content enhancement using GraphRAG approach
  content gap / research question generation

  This approach can be very useful for research, marketing, and SEO applications as you can quickly get an overview of the main topics that are available online for a certain niche and understand what is missing. 

  What are Content Gaps in Marketing and SEO?

  In the context of SEO, content gaps are usually understood as the topics that your competitors rank for but you do not. 

  However, it's hard to rank for these topics because there's very high competition. So a much more effective way is to identify the gaps between the topics your competitors are talking about that are not yet bridged in their discourse.

  If you address these gaps in your content, you will increase the informational gain that your content offers and also offer a novel perspective while touching upon the topics that are relevant in your field.

  For example, if we analyze the top websites for "body and physical practices, fitness, etc." we will see that most of them are talking about the health and fitness aspects and another big topic is the community aspect. 

  However, there is a gap between the two topics: which means that most of the websites (companies) that talk about this topic don't mention the two in the same context. This might be an opportunity: bridging the gap between health, fitness but also emphasizing the community aspect that comes with a collective practice. 

  How it works
  This template consists of the two stages:

  1) Data enrichment of a Google sheet file with a list of your competitors using InfraNodus' GraphRAG to generate topical summaries and graph summaries for every URL you're analyzing. 

  2) Insight generation (using InfraNodus to identify the main topical clusters and gaps in those summaries, these insights are then added to the Google sheet file.

  Additionally, it contains a sub workflow that you can activate and launch to ask Perplexity model to conduct a market research and find the companies that operate in your field and populate the original Google sheet file.

  Here's a description step by step:

  Step 0: Populate the Google sheets file with the company data (either manually or using the sub-workflow provided or Manus AI / Deep Research)
  Steps 1-2: Triggering and Launching the workflow, extracting the company URL from the Google sheet row
  Step 3: Scraping the url content from the companies' websites and cleaning the data
  Steps 5-7: Use InfraNodus GraphRAG Content Enhancer to get a topical summary and graph summary. This is what you're going to get:



  Steps 8-10: Use InfraNodus AI to generate insight advice and research questions based on the content gaps

  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

  Requirements

  An InfraNodus account and API key
  A Google Sheet account and an authorization key

  Note: OpenAI key is not required. But you might want to get a Perplexity AI key if you'd like to use the sub-workflow that populates the Google sheet with your competitors' website addresses (if you don't have this list yet).

  Customizing this workflow

  You can use this same workflow with a Telegram bot or Slack (to be notified of the summaries and ideas). 

  You can also hook up automated social media content creation workflows in the end of this template, so you can generate posts that are relevant (covering the important topics in your niche) but also novel (because they connect them in a new way). 

  Check out our n8n templates for ideas at https://n8n.io/creators/infranodus/

  Check out the complete guide at https://support.noduslabs.com/hc/en-us/articles/20234254556828-Find-Content-Gaps-in-Websites-Market-Research-and-SEO-n8n-Workflow

  Also check the full tutorial with a conceptual explanation at https://support.noduslabs.com/hc/en-us/articles/20454382597916-Beat-Your-Competition-Target-Their-Content-Gaps-with-this-n8n-Automation-Workflow 

  Also check out the video tutorial with a demo:



  For support and help with this workflow, please, contact us at https://support.noduslabs.com

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.htmlExtract","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.splitInBatches","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDocs","n8n-nodes-base.aggregate","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","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.merge","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.formTrigger","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleSheets","n8n-nodes-base.splitOut","n8n-nodes-base.splitInBatches","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 8668 characters]


name: One-way sync between Telegram, Notion, Google Drive, and Google Sheets
author_name: Lakshit Ukani
author_username: lakshit1996
categories: []
created_at: 2025-05-26T13:36:26.445Z
updated_at: 2025-05-26T13:36:26.445Z
url: https://n8n.io/workflows/4404
scraped_at: 2025-12-24 13:02:41
description:
  One-way sync between Telegram, Notion, Google Drive, and Google Sheets

  Who is this for?

  This workflow is perfect for productivity-focused teams, remote workers, virtual assistants, and digital knowledge managers who receive documents, images, or notes through Telegram and want to automatically organize and store them in Notion, Google Drive, and Google Sheets—without any manual work.

  What problem is this workflow solving?

  Managing Telegram messages and media manually across different tools like Notion, Drive, and Sheets can be tedious. This workflow automates the classification and storage of incoming Telegram content, whether it’s a text note, an image, or a document. It saves time, reduces human error, and ensures that media is stored in the right place with metadata tracking.

  What this workflow does

  Triggers on a new Telegram message** using the Telegram Trigger node.
  Classifies the message type** using a Switch node:
    Text messages are appended to a Notion block.
    Images are converted to base64, uploaded to imgbb, and then added to Notion as toggle-image blocks.
    Documents are downloaded, uploaded to Google Drive, and the metadata is logged in Google Sheets.
  Sends a completion confirmation** back to the original Telegram chat.

  Setup

  Telegram Bot: Set up a bot and get the API token.
  Notion Integration:
     Share access to your target Notion page/block.
     Use the Notion API credentials and block ID where content should be appended.
  Google Drive & Sheets:
     Connect the relevant accounts.
     Select the destination folder and spreadsheet.
  imgbb API: Obtain a free API key from imgbb.

  Replace placeholder credential IDs and asset URLs as needed in the imported workflow.

  How to customize this workflow to your needs

  Change Storage Locations**:
    Update the Notion block ID or Google Drive folder ID.
    Switch Google Sheet to log in a different file or sheet.
  Add More Filters**:
    Use additional Switch rules to handle other Telegram message types (like videos or voice messages).
  Modify Response Message**:
    Personalize the Telegram confirmation text based on the file type or sender.
  Use a different image hosting service** if you don’t want to use imgbb.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.telegramTrigger","n8n-nodes-base.switch","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.extractFromFile","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.notion","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.googleDrive","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram"]

workflow_json_compressed:
  [encoded data, 4868 characters]


name: Generate Daily E-Commerce Order Reports with Supabase, GPT-4.1 and Gmail
author_name: Aitor | 1Node
author_username: aitoralonso
categories: []
created_at: 2025-05-26T15:45:04.864Z
updated_at: 2025-05-26T15:45:04.864Z
url: https://n8n.io/workflows/4406
scraped_at: 2025-12-24 13:02:43
description:
  This n8n workflow automates the generation and delivery of a daily order summary via email. It leverages an AI Agent to fetch and summarize e-commerce order data from the last 24 hours stored in Supabase, providing a concise overview of the daily business operations.

  How it works

  Scheduled Trigger:** The workflow is triggered every day at 8 AM.
  Sender Email Configuration:** A manual step allows you to set the sender's email address.
  AI Agent:** An AI Agent node acts as the central intelligence, interacting with various tools to gather and process data.
  Supabase Data Fetching:** The AI Agent calls "Get Orders," "Get Order Items," "Get Clients," and "Get Products" tables to retrieve relevant e-commerce data from your Supabase database.
  OpenAI Chat Model:** An OpenAI Chat Model with the 4.1 model is integrated to help the AI Agent understand and summarize the fetched data into a human-readable format.
  Gmail Summary:** Finally, the workflow sends a summarized report to your specified email address using the "Send Gmail Summary" node.

  Set up steps

  This setup will take approximately 15-20 minutes.

  Download the workflow: Download this workflow and import it into your n8n instance.
  Configure the Daily 8am trigger: Ensure the "Daily 8am" trigger is active and set to your desired timezone.
  Set Sender Email: In the "Set Sender Email" node, manually enter the email address you wish to use as the sender for the daily reports.
  Configure AI Agent:
      Chat Model: Connect your OpenAI Chat Model credential.
      Memory & Tools: Ensure all the necessary nodes ("Get Orders", "Get Order Items", "Get Clients", "Get Products", "Send Gmail Summary") are correctly linked to the AI Agent. In our workflow we call data from 4 tables in Supabase.
  Configure Supabase Database Connections:
      For each of the "Get Orders," "Get Order Items," "Get Clients," and "Get Products" nodes, you will need to configure your Supabase credentials to access your e-commerce database.
      Select the tables (e.g., orders, order_items, clients, products) that you want the AI agent to pull data from in your Supabase schema.
  Configure Gmail Credentials: In the "Send Gmail Summary" node, connect your Gmail account credentials to allow n8n to send emails on your behalf.
  Test the workflow: Run the workflow manually to ensure all connections are working correctly and the email summary is generated as expected.

  Requirements

  n8n instance:** An active n8n instance (self-hosted or cloud).
  Supabase Account:** A Supabase account with your e-commerce order data accessible.
  OpenAI API Key:** An OpenAI API key for the Chat Model.
  Gmail Account:** A Gmail account credentials to send the daily summaries.

  Need help?
  Feel free to contact us at 1 Node.
  Get instant access to a library of free resources we created.

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.supabaseTool","n8n-nodes-base.supabaseTool","n8n-nodes-base.supabaseTool","n8n-nodes-base.supabaseTool","n8n-nodes-base.gmailTool","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.set","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: n8n Workflow Error Alerts with Google Sheets, Telegram, and Gmail
author_name: Aitor | 1Node
author_username: aitoralonso
categories: []
created_at: 2025-05-26T15:51:38.558Z
updated_at: 2025-05-26T15:51:38.558Z
url: https://n8n.io/workflows/4407
scraped_at: 2025-12-24 13:02:44
description:
  This n8n workflow provides a robust error handling and notification system for your n8n workflows. When an error occurs, it automatically logs the error details to Google Sheets, sends a notification to a Telegram channel, and dispatches an email alert, ensuring you're immediately aware of any issues.

  How it works

  Error Trigger:** The workflow is activated whenever an error occurs in another n8n workflow.
  Log Error (Google Sheets):** Error details (e.g., workflow name, error message, timestamp) are appended to a specified Google Sheet, creating a centralized log for all errors.
  Edit Fields (Manual Configuration):** This node allows you to manually set the Telegram chat ID and recipient email for notifications.
  Notify in channel (Telegram):** An error notification containing relevant details is sent to your configured Telegram channel.
  Send email (Gmail):** An email alert with comprehensive error information is sent to the specified recipient.

  Set up steps

  This setup will take approximately 10-15 minutes.

  Download the workflow: Download this workflow and import it into your n8n instance.
  Configure the Error Trigger: This trigger will automatically activate when an error occurs in any workflow. Make sure you set this workflow as the "Error Workflow" inside the workflows where you want to be alerted. 
  Configure Log error (Google Sheets):
      Connect your Google Sheets account credentials.
      Specify the Google Sheet ID and the sheet name where you want to log the errors.
      Ensure the sheet has appropriate headers (e.g., "Timestamp", "Workflow Name", "Error Message", "Error Details") to receive the data.
  Configure Edit Fields:
      In the "Edit Fields" node, manually enter your Telegram chat ID. This is the ID of the chat or channel where you want to receive Telegram notifications.
      Insert the recipient's email address where you want to receive email alerts.
  Configure Notify in channel (Telegram):
      Connect your Telegram account credentials.
      Ensure the "Chat ID" field is correctly linked to the output from the "Edit Fields" node.
  Configure Send email (Gmail):
      Connect your Gmail account credentials.
      Ensure the "To" email address is correctly linked to the output from the "Edit Fields" node.
      Customize the subject and body of the email to include relevant error information from the "Error Trigger" node.
  Test the workflow: To test, you can intentionally create an error in another simple n8n workflow. This error workflow should then trigger this error handling workflow, and you can verify if the log is updated, Telegram message is sent, and email is received. Make sure that the workflow you are testing has the "Error Workflow" selected in the workflow's settings.

  Requirements

  n8n instance:** An active n8n instance (self-hosted or cloud).
  Google Account:** A Google account with access to Google Sheets.
  Telegram Account:** A Telegram account and a chat/channel ID for notifications.
  Gmail Account:** A Gmail account to send email alerts.

  Need help?
  Feel free to contact us at 1 Node.
  Get instant access to a library of free resources we created.

nodes_used:
  ["n8n-nodes-base.errorTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.set","n8n-nodes-base.telegram","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote"]

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name: Weekly AI News Digest with Perplexity AI and Gmail Newsletter
author_name: Derek Schatz
author_username: derekschatz
categories: []
created_at: 2025-05-27T01:18:31.882Z
updated_at: 2025-05-27T01:18:31.882Z
url: https://n8n.io/workflows/4412
scraped_at: 2025-12-24 13:02:42
description:
  Overview

  This automated workflow delivers a weekly digest of the most important AI news directly to your inbox. Every Monday at 9 AM, it uses Perplexity AI to research the latest developments and organizes them into four key categories: New Technology, Trending Topics, Top Stories, and AI Security. The workflow then formats this information into a beautifully designed HTML email with summaries, significance explanations, and source links.

  What It Does

  Automatically searches for the latest AI news using Perplexity AI
  Categorizes content into four focused areas most relevant to AI enthusiasts and professionals
  Generates comprehensive summaries explaining why each story matters
  Creates a professional HTML email with styled sections and clickable links
  Sends weekly on Monday at 9 AM (customizable schedule)
  Includes error handling with fallback content if news parsing fails

  Setup Instructions

  Import the Workflow

  Copy the JSON code and import it into your n8n instance
  The workflow will appear as “Daily AI News Summary”

  Configure Perplexity API

  Sign up for a Perplexity API account at perplexity.ai
  Create new credentials in n8n:

    Type: “OpenAI”
    Name: “perplexity-credentials”
    API Key: Your Perplexity API key
    Base URL: https://api.perplexity.ai

  Set Up Email Credentials

  Configure SMTP credentials in n8n:

    Name: “email-credentials”
    Add your email provider’s SMTP settings
    Test the connection to ensure emails can be sent

  Customize Email Settings

  Open the “Send Email Summary” node
  Update the toEmail field with your email address
  Modify the fromEmail if needed (must match your SMTP credentials)

  Optional Customizations

  Change Schedule:** Modify the “Daily Trigger” node to run at your preferred time
  Adjust Categories:** Edit the Perplexity prompt to focus on different AI topics or change the theme altogether
  Modify Styling:** Update the HTML template in the “Format Email Content” node

  Test and Activate

  Run a test execution to ensure everything works correctly
  Activate the workflow to start receiving daily AI news summaries

  Requirements

  n8n instance (cloud or self-hosted)
  Perplexity API account and key
  SMTP email access (Gmail, Outlook, etc.)

nodes_used:
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name: Auto-Respond to Gmail Inquiries using OpenAI, Google Sheet & AI Agent
author_name: Billy Christi
author_username: billy
categories: []
created_at: 2025-05-27T02:42:11.743Z
updated_at: 2025-05-27T02:42:11.743Z
url: https://n8n.io/workflows/4413
scraped_at: 2025-12-24 13:02:44
description:
  Who is this for?

  This workflow is ideal for:

  Customer support teams looking to reduce manual response time
  SaaS companies that frequently receive product inquiries
  E-commerce stores with common customer questions about orders, shipping, and returns

  What problem is this workflow solving?

  Manually responding to repetitive customer emails is inefficient, prone to inconsistency, and time-consuming. This workflow solves the issue by:

  Automatically replying to real customer inquiries 24/7
  Ensuring every response is consistent, friendly, and based on approved knowledge
  Preventing responses to non-inquiries like newsletters or confirmations
  Logging every interaction for traceability, analysis, and compliance

  What this workflow does

  This AI-powered Gmail auto-responder intelligently handles inbound emails with the following steps:

  Monitors your Gmail inbox for new incoming emails in real time
  Classifies each email as either an “Inquiry” or “Not Inquiry” using GPT-4
  Gets context from a Google Sheets FAQ database
     The context will be used to determine the most accurate and helpful response
  Generates a professional reply only if it’s a valid inquiry (e.g., pricing, refund, product details)
  Builds a context-aware, helpful response using verified knowledge only
  Sends the reply to the original sender automatically
  Logs everything to a Google Sheet — original email, AI response, timestamp, and email address

  Example Use Case:

  An email comes in:
  "Hi, I want to know your pricing and refund policy."

  The workflow:

  Detects it’s an inquiry
  Finds the pricing and refund FAQs in your Google Sheet
  Sends back a professional response like:
    "Hi! Thanks for reaching out. Our pricing starts at \$99/month. Refunds can be requested within 30 days of purchase. Let us know if you have more questions!"
  Logs the interaction to your “Enquiry\_Log” tab

  Setup

  Copy the Google Sheet template here:
     👉 Gmail Auto-Responder – Google Sheet Template
     This contains:

     A FAQ_Context tab (your knowledge base)
     An Enquiry_Log tab (interaction logs)

  Connect your Gmail account to the Gmail Trigger and Gmail Send nodes

  Add your OpenAI API key in the classification and response generator nodes

  Link the Google Sheet in both the FAQ lookup and logging nodes

  Test with a sample email — try asking a pricing and refund question to see the complete process in action

  How to customize this workflow to your needs

  Adjust tone or brand voice** in the AI prompt for a more casual or formal reply
  Modify classification rules** if your use case includes more custom logic
  Expand the FAQ database** to include new questions and answers
  Add multilingual support** by customizing the AI prompt to detect and respond in different languages
  Integrate CRM or ticketing systems** (like HubSpot, Zendesk, or Notion) to log or escalate unanswered queries

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

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name: Automate News Publishing to LinkedIn with Gemini AI and RSS Feeds
author_name: Club de Inteligencia Artificial Politécnico CIAP
author_username: ciap
categories: []
created_at: 2025-05-27T04:13:35.056Z
updated_at: 2025-05-27T04:13:35.056Z
url: https://n8n.io/workflows/4414
scraped_at: 2025-12-24 13:02:42
description:
  📰 LinkedIn News Auto-Publisher

  Overview 📋

  This project is an automated news publisher for LinkedIn. It uses RSS feeds to fetch news, processes the content with the Gemini API to generate precise summaries, and automatically publishes to LinkedIn via its API.

  How It Works

  Architecture and Workflow ⚙️

  n8n**: Efficient orchestration of workflow with automation.
  RSS**: News sources such as TechCrunch and MIT Technology Review.
  Gemini API**: Dynamic generation of content and precise summaries.
  LinkedIn API**: Automatic publication on profiles and corporate pages.

  Content Processing 🧠

  Fetching news through RSS feeds.
  Processing and generating summaries with the Gemini API.
  Automatic publication on LinkedIn.

  Key Benefits ✅

  Complete automation of the news publishing process.
  Dynamic generation of precise and relevant content.
  Integration with reliable news sources and publication on a professional platform.

  Use Cases 💼

  Automation of news publishing for businesses and professionals.
  Keeping corporate profiles and pages updated with relevant content.
  Saving time in managing content on social networks.

  Requirements 👨‍💻

  n8n instance (self-hosted or cloud).
  Gemini API credentials.
  LinkedIn bot setup and API credentials.
  Configured RSS feeds to fetch news.

  Authors 👥

  Joel Choez
  Alan Bajaña
  Jaren Pazmiño
  David Sandoval

  Members of CIAP

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name: Form-Based X/Twitter Poster
author_name: Akhil Varma Gadiraju
author_username: akhilv7
categories: []
created_at: 2025-05-27T04:26:46.851Z
updated_at: 2025-05-27T04:26:46.851Z
url: https://n8n.io/workflows/4415
scraped_at: 2025-12-24 13:02:45
description:
  🚀 Form-Based X/Twitter Poster (v2)

  A user-friendly n8n workflow that enables users to submit tweets through a simple web form — with optional image, video, or GIF uploads — and posts them to a connected X/Twitter account. Designed for ease of use, this workflow handles both media and text-only posts, providing clear feedback upon submission.

  🧭 Overview

  Workflow Name: Form-Based X/Twitter Poster (v2)  
  Goal: Provide a web form for users to create tweets, upload optional media, and post directly to X/Twitter.

  🛠 How It Works

  1. Form Submission Trigger
  Node:** On form submission
  Type:** formTrigger
  Purpose:** Renders a web form for tweet creation.
  Fields:**
    Post Content: Required textarea for tweet text.
    Media: Optional file upload (.jpg, .png, .gif, .mp4, etc.).
  Button:** "Submit"
  Output:** JSON with text and binary media (if any).

  2. Extract Media Details
  Node:** Extract Media Details
  Type:** code
  Purpose:** Extracts tweet text, checks for media, determines media type.
  Output Example:**
  {
    "content": "My tweet!",
    "mime_type": "image/jpeg",
    "media_type": "IMAGE"
  }

  3. If Media Exists
  Node:** If Media Exists
  Type:** if
  Purpose:** Checks whether media was uploaded.
  True Path:** Media was uploaded.
  False Path:** No media uploaded.

  4. Upload Media to X/Twitter (True path only)
  Node:** Upload Media (X)
  Type:** httpRequest
  Purpose:** Uploads media to Twitter via API v1.1.
  Media Category:** TWEET_IMAGE (can be customized)
  Auth:** Twitter OAuth1 API
  Output:** Includes media_id_string

  5. Post Tweet with Media (True path)
  Node:** X
  Type:** twitter
  Purpose:** Posts tweet with uploaded media.
  Auth:** Twitter OAuth2 API

  6. Post Text-Only Tweet (False path)
  Node:** X1
  Type:** twitter
  Purpose:** Posts tweet without media.
  Auth:** Twitter OAuth2 API

  7. Show Confirmation Message
  Node:** End Form
  Type:** form
  Purpose:** Displays thank-you message post-submission.
  Title:** Thank you so much for sharing your experience on X! 🖤
  Message:** We truly appreciate your support and are so glad we could make a positive impact. Your words mean the world to us!

  🛠 How to Customize

  Form Fields:** Change form title, labels, help texts, or file formats.
  Media Logic:**
    Add logic for distinguishing GIF vs VIDEO.
    Adjust media upload URL dynamically:
          https://upload.twitter.com/1.1/media/upload.json?media_category={{ $json.media_type === 'VIDEO' ? 'TWEET_VIDEO' : ($json.media_type === 'GIF' ? 'TWEET_GIF' : 'TWEET_IMAGE') }}
      Error Handling:** Add Error Trigger nodes to catch and manage failures gracefully.
  Tweet Text:** Customize tweet text with extra formatting or default content.
  Advanced Ideas:** 
    Schedule tweets
    Post to multiple accounts
    Add content approval steps

  🔐 Required Credentials

  1. Twitter OAuth1 API
  Used by:** Upload Media (X)
  Required for:** Media upload via v1.1
  Credentials:** Consumer Key, Consumer Secret, Access Token, Access Token Secret
  Workflow Credential Name:** X OAuth - Akhil

  2. Twitter OAuth2 API
  Used by:** X, X1
  Required for:** Posting tweets
  Scopes:** tweet.read, tweet.write, users.read, offline.access
  Workflow Credential Name:** X OAuth2 - Akhil

  💡 Use Cases

  Easy Tweet Tool:** For non-technical users to share content.
  Content Approval:** Internal review system before posting.
  Announcements:** Quickly broadcast updates.
  Campaign Posting:** Streamline recurring content sharing.

  🧑‍💻 Node Naming Suggestions

  | Old Name           | Suggested Name           |
  |--------------------|--------------------------|
  | If Image Exists    | If Media Exists          |
  | X                  | Post Tweet with Media    |
  | X1                 | Post Text-Only Tweet     |

  ❤️ Made with love by Akhil using n8n

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  ["n8n-nodes-base.formTrigger","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.twitter","n8n-nodes-base.if","n8n-nodes-base.twitter","n8n-nodes-base.form","n8n-nodes-base.stickyNote"]

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name: HubSpot Contact Email Validation with Hunter.io
author_name: Akhil Varma Gadiraju
author_username: akhilv7
categories: []
created_at: 2025-05-27T04:57:19.995Z
updated_at: 2025-05-27T04:57:19.995Z
url: https://n8n.io/workflows/4416
scraped_at: 2025-12-24 13:02:45
description:
  Workflow: HubSpot Contact Email Validation with Hunter.io

  Overall Goal

  This workflow retrieves contacts from HubSpot that have an email address but haven't yet had their email validated by Hunter. It then iterates through each of these contacts, uses Hunter.io to verify their email, updates the contact record in HubSpot with the validation status and date, and finally sends a summary email notification upon completion.

  How it Works (Step-by-Step Breakdown)

  Node: "When clicking ‘Test workflow’" (Manual Trigger)
  Type:** n8n-nodes-base.manualTrigger
  Purpose:** Start the workflow manually via the n8n interface.
  Output:** Triggers workflow execution.

  Node: "HubSpot" (HubSpot)
  Type:** n8n-nodes-base.hubspot
  Purpose:** Fetch contacts from HubSpot.
  Configuration:**
    Authentication: App Token
    Operation: Search for contacts
    Return All: True
    Filter Groups:
      Contact HAS_PROPERTY email
      Contact NOT_HAS_PROPERTY hunter_email_validation_status
  Output:** List of contact objects.

  Node: "Loop Over Items" (SplitInBatches)
  Type:** n8n-nodes-base.splitInBatches
  Purpose:** Process each contact one-by-one.
  Configuration:**
    Options &gt; Reset: false
  Output:**
    Output 1 to "Hunter"
    Output 2 to "Send Email"

  Node: "Hunter" (Inside the loop)
  Type:** n8n-nodes-base.hunter
  Purpose:** Verify email with Hunter.io
  Configuration:**
    Operation: Email Verifier
    Email: {{ $json.properties.email }}

  Node: "Add Hunter Details (Contact)" (HTTP Request - Inside the loop)
  Type:** n8n-nodes-base.httpRequest
  Purpose:** Update HubSpot contact.
  Configuration:**
    Method: PATCH
    URL: https://api.hubapi.com/crm/v3/objects/contacts/{{ $('Loop Over Items').item.json.id }}
    Headers: Content-Type: application/json
    Body (JSON):
          {
        "properties": {
          "hunter_email_validation_status": "{{ $json.status }}",
          "hunter_verification_date": "{{ $now.format('yyyy-MM-dd') }}"
        }
      }
  Node: "Wait" (Inside the loop)
  Type:** n8n-nodes-base.wait
  Purpose:** Avoid API rate limits.
  Configuration:** Wait for 1 second.

  Node: "Replace Me" (NoOp - Inside the loop)
  Type:** n8n-nodes-base.noOp
  Purpose:** Junction node to complete the loop.

  Node: "Send Email" (After the loop completes)
  Type:** n8n-nodes-base.emailSend
  Purpose:** Send summary notification.
  Configuration:**
    From Email: test@gmail.com
    To Email: akhilgadiraju@gmail.com
    Subject: "Email Verification Completed for Your HubSpot Contacts"
    HTML: Formatted confirmation message

  Sticky Notes
  "HubSpot": Create custom properties (hunter_email_validation_status, hunter_verification_date).
  "Add Hunter Details": Ensure field names match HubSpot properties.
  "Wait": Prevent API rate limits.

  How to Customize It

  Trigger
  Replace Manual Trigger with Schedule Trigger (Cron) for automation.
  Optionally use HubSpot Trigger for new contact events.

  HubSpot Node
  Create matching custom properties.
  Adjust filters and returned properties as needed.

  Hunter Node
  Minimal customization needed.

  HTTP Request Node
  Update JSON property names if renaming in HubSpot.
  Customize date format as needed.

  Wait Node
  Adjust wait time to balance speed and API safety.

  Email Node
  Customize email addresses, subject, and body.
  Add dynamic contact count with a Set or Function node.

  Error Handling
  Add Error Trigger nodes.
  Use If nodes inside loop to act on certain statuses.

  Use Cases
  Clean your email list.
  Enrich CRM data.
  Prep verified lists for campaigns.
  Automate contact hygiene on a schedule.

  Required Credentials

  HubSpot App Token
  Used by: HubSpot node and HTTP Request node
  Create a Private App in HubSpot with required scopes.

  Hunter API
  Used by: Hunter node

  SMTP
  Used by: Email Send node
  Configure host, port, username, and password.

  Made with ❤️ using n8n by Akhil.

nodes_used:
  ["n8n-nodes-base.hubspot","n8n-nodes-base.manualTrigger","n8n-nodes-base.splitInBatches","n8n-nodes-base.noOp","n8n-nodes-base.hunter","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.emailSend"]

workflow_json_compressed:
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name: Auto-Cleanup of Cloudflare R2 Files Older Than 2 Weeks (+ Telegram Notifications)
author_name: Mobder
author_username: mobder
categories: []
created_at: 2025-05-27T05:38:36.173Z
updated_at: 2025-05-27T05:38:36.173Z
url: https://n8n.io/workflows/4418
scraped_at: 2025-12-24 13:02:45
description:
  This workflow automatically connects to a Cloudflare R2 bucket (via S3-compatible API), filters out files older than 14 days, deletes them, and then sends a Telegram notification for each deletion. It runs on a daily schedule.

  🕘 Schedule Trigger
  Executes the workflow once a day at a specified hour (e.g., 9 AM).

  📦 S3 Node – List Files
  Retrieves all objects from a specific folder (prefix) in a Cloudflare R2 bucket using the S3 API.

  🔎 Code Node – Filter Files Older Than 2 Weeks
  Filters the retrieved files by comparing their LastModified timestamps to the current date. Files older than 14 days (2 weeks) are selected for deletion.

  🗑️ S3 Node – Delete File
  Deletes each filtered file from the R2 bucket.

  📨 Telegram Node – Notify Deletion
  Sends a Telegram message with the name of the deleted file to a specified chat ID. The message includes:

nodes_used:
  ["n8n-nodes-base.s3","n8n-nodes-base.code","n8n-nodes-base.s3","n8n-nodes-base.telegram","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: Generate LinkedIn Posts with GPT-4, Preview on WhatsApp, and Auto-Publish
author_name: papcy
author_username: papcy
categories: []
created_at: 2025-05-27T06:33:16.319Z
updated_at: 2025-05-27T06:33:16.319Z
url: https://n8n.io/workflows/4419
scraped_at: 2025-12-24 13:02:44
description:
  # Workflow Overview
  Transform your LinkedIn presence with this powerful AI-driven automation workflow that generates and posts high-quality thought leadership content automatically. 

  Let this AI Agent, generate content for you, sends it to your whatsapp for you to review and if its ok Approve and it will post! if you don't like it, Decline and it will regenerate another and send again for preview and approval.

  Stage 1: Automated Content Scheduling

  Schedule Trigger runs every 6 hours (customizable)
  Topic Selection randomly chooses 3 AI-related topics from a predefined list
  Ensures fresh, varied content for each generation cycle

  Stage 2: AI Content Generation

  GPT-4 Integration creates unique LinkedIn posts using structured prompts
  Content Format: Hook → Problem/Opportunity → Insight → Strategic Takeaway → CTA
  Output: 300-word maximum posts with 3-5 relevant hashtags
  Uniqueness: Each post is completely original and industry-specific

  Stage 3: Content Processing & Formatting

  JSON Parsing extracts title, body, and hashtags from AI response
  Error Handling includes fallback mechanisms for robust operation
  LinkedIn Formatting prepares content for optimal platform display

  Stage 4: Preview & Approval System

  WhatsApp Integration sends generated content to your phone for review
  Approval Gateway waits for your decision (approve/decline)
  Quality Control ensures only approved content reaches your LinkedIn profile

  Stage 5: Automated Publishing

  LinkedIn API posts approved content automatically
  Success Notifications confirm successful publishing via WhatsApp
  Professional Formatting includes proper spacing and emoji structure

  Stage 6: Smart Restart System

  Decline Handling automatically generates new content if declined
  Continuous Operation ensures consistent content flow
  Tracking Notifications keep you informed of all workflow activities

  Prerequisites & Required Credentials
  Essential API Credentials

  OpenAI API Key (for GPT-4 content generation)
  WhatsApp Business API credentials and phone number ID
  LinkedIn Developer Account with API access
  n8n Cloud or Self-hosted instance

  Technical Requirements

  Active LinkedIn Business profile
  WhatsApp Business account
  Basic understanding of n8n workflow management

  Step-by-Step Setup Instructions
  Configure OpenAI Integration

  Add your OpenAI API key to the "OpenAI GPT-4 Model" node
  Ensure GPT-4 access is enabled on your OpenAI account
  Test connection before proceeding

  2. Setup WhatsApp Business API

  Obtain WhatsApp Business API credentials from Meta
  Configure phone number ID in all WhatsApp nodes
  Replace "YOUR_PHONE_NUMBER" with your actual number
  Test message delivery

  3. Connect LinkedIn Account

  Set up LinkedIn Developer App
  Obtain your LinkedIn Person ID
  Configure OAuth authentication
  Test posting permissions

  4. Customize Content Topics

  Edit the "Prepare Search Topics" function node
  Modify the searchTerms array for your industry
  Add relevant AI topics for your niche
  Save and test topic randomization

  5. Adjust Posting Schedule

  Modify the "Schedule Trigger" node
  Change interval from 6 hours to your preferred timing
  Consider your audience's active hours
  Enable the trigger to start automation

  Customization Options
  Content Personalization

  Industry Focus: Modify AI topics in the search terms array
  Writing Style: Adjust the system prompt in "AI Content Generator"
  Post Length: Customize maximum word count (default: 300 words)
  Hashtag Strategy: Modify hashtag generation rules

  Workflow Timing

  Posting Frequency: Adjust schedule trigger interval
  Approval Timeout: Configure WhatsApp wait duration
  Retry Logic: Customize restart behavior for declined content

  Notification Preferences

  WhatsApp Templates: Customize approval and notification messages
  Success Tracking: Modify confirmation message content
  Error Handling: Adjust failure notification settings

  **Business Benefits
  Time Savings
  **
  10+ Hours Weekly: Eliminate manual content creation and posting
  Consistent Presence: Maintain regular LinkedIn activity automatically
  Quality Control: Review and approve all content before publishing

  Lead Generation Impact

  Thought Leadership: Position yourself as an AI industry expert
  Engagement Growth: High-quality content drives more interactions
  Network Expansion: Consistent posting attracts relevant connections
  Authority Building: Regular insights establish professional credibility

  ROI Expectations

  Monthly Investment: $10-20 in API costs
  Setup Time: 15 minutes initial configuration
  Long-term Value: Increased visibility, leads, and business opportunities

  **Troubleshooting & Support
  Common Issues**

  API Rate Limits: Monitor usage and upgrade plans if needed
  Content Quality: Adjust prompts for better AI output
  Approval Delays: Check WhatsApp connectivity and permissions

  Optimization Tips

  Topic Rotation: Regularly update search terms for fresh content
  Performance Monitoring: Track engagement metrics on posted content
  Prompt Refinement: Continuously improve AI generation prompts

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.function","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.function","n8n-nodes-base.stickyNote","n8n-nodes-base.whatsApp","n8n-nodes-base.whatsApp","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.function","n8n-nodes-base.linkedIn","n8n-nodes-base.whatsApp","n8n-nodes-base.stickyNote","n8n-nodes-base.whatsApp","n8n-nodes-base.executeWorkflow","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: Automated Daily Outlook Calendar Meeting Digest
author_name: Akhil Varma Gadiraju
author_username: akhilv7
categories: []
created_at: 2025-05-27T06:47:50.602Z
updated_at: 2025-05-27T06:47:50.602Z
url: https://n8n.io/workflows/4420
scraped_at: 2025-12-24 13:02:42
description:
  Automated Daily Outlook Calendar Meeting Digest

  Overall Goal
  This workflow automatically runs at a scheduled time (daily at 8 AM by default), calculates the current day's date range, fetches all calendar events from a specified Microsoft Outlook account for that day, formats these events into a user-friendly HTML email, and then sends this digest to a designated email address.

  How it Works (Step-by-Step Breakdown):

  Node: Schedule Trigger (Schedule Trigger Node)
  Type:** n8n-nodes-base.scheduleTrigger  
  Purpose:** Automatically starts the workflow at a predefined time.  
  Configuration:**  
    Rule &gt; Interval &gt; Trigger At Hour: 8  
      (Triggers every day at 8:00 AM according to the n8n server's timezone)  
  Output:** Triggers the workflow execution at the scheduled time.

  Node: Code (Code Node)
  Type:** n8n-nodes-base.code  
  Purpose:** Dynamically calculates the start and end timestamps for "today," based on when the workflow is triggered.  
  Configuration (JS Code):**  
    Gets the current date and time (workflow runtime).  
    Sets today to beginning of current day (00:00:00).  
    Sets tomorrow to beginning of next day (00:00:00).  
    Converts these to ISO string format (e.g., 2023-10-27T00:00:00Z).  
  Output:** JSON object with today and tomorrow ISO date strings.

  Node: Microsoft Outlook (Microsoft Outlook Node)
  Type:** n8n-nodes-base.microsoftOutlook  
  Purpose:** Fetch calendar events from Outlook within the calculated date range.  
  Configuration:**  
    Resource: Event  
    Filters (Custom):  
          start/dateTime ge '{{$json.today}}' and start/dateTime lt '{{$json.tomorrow}}'
        (OData filter to fetch events starting on or after today and before tomorrow, i.e., all today's events.)  
  Output:** List of event objects from Outlook.

  Node: Edit Fields (Set Node)
  Type:** n8n-nodes-base.set  
  Purpose:** Transform and simplify the event data structure from Outlook.  
  Configuration:** Maps fields from Outlook event to new field names:  
    id  
    subject  
    description (from bodyPreview)  
    meeting_start  
    meeting_end  
    attendees  
    meeting_organizer  
    meeting_organizer_email  
    meeting_link  
  Output:** List of JSON objects with simplified meeting details.

  Node: Generate HTML (Code Node)
  Type:** n8n-nodes-base.code  
  Purpose:** Generate a single HTML email body summarizing all meetings and create the email subject line.  
  Configuration (JS Code):**  
    Processes all meeting items from "Edit Fields" node.  
    Defines generateMeetingReminderEmail function to format each meeting into an HTML "card."  
    Escapes HTML special characters, formats times, attendees, etc.  
    Concatenates all cards into a full HTML document.  
    Generates subject line (e.g., "🗓️ Your Meetings Today – Friday, Oct 27").  
  Output:** JSON object with:  
      {
      "subject": "email subject string",
      "html": "generated HTML content string"
    }
  Node: Send Email (Email Send Node)
  Type:** n8n-nodes-base.emailSend  
  Purpose:** Send the generated HTML digest email to the designated recipient.  
  Configuration:**  
    From Email: test@gmail.com  
    To Email: akhilgadiraju@gmail.com  
    Subject: {{ $json.subject }} (dynamic from Generate HTML node)  
    HTML: {{ $json.html }} (dynamic from Generate HTML node)  
  Output:** Email sending status.

  Sticky Notes
  Update Time:** Near "Schedule Trigger" node; configure trigger time as needed.  
  Update Email Details:** Near "Send Email" node; change sender and receiver email addresses.

  How to Customize It

  Schedule (Schedule Trigger node):**  
    Modify the trigger hour, minutes, or days of week to change when the workflow runs.

  Date Range (Code node):**  
    Adjust JS to change date range (e.g., next business day, upcoming week).

  Outlook Calendar (Microsoft Outlook node):**  
    Specify Calendar ID or refine OData filters for event selection.

  Event Details (Edit Fields node):**  
    Add/remove/modify event fields extracted.

  Email Appearance and Content (Generate HTML node):**  
    Change CSS styling, meeting details, or subject line logic.

  No Meetings Scenario:**  
    Use an "If" node after "Edit Fields" to handle no-meeting days (e.g., send "No meetings today!" email or skip email).

  Email Recipients (Send Email node):**  
    Update "From" and "To" emails; multiple recipients separated by commas.

  Error Handling
  Use "Error Trigger" nodes to catch and handle failures (Outlook API, SMTP errors).
  Send alerts or log errors accordingly.

  Use Cases
  Automated Daily Personal Meeting Briefing:** Get daily email summaries of your meetings.  
  Automated Team Meeting Digest:** Send daily team calendar digest emails.  
  Proactive Daily Planning:** Automatically stay informed of your day’s schedule.

  Required Credentials

  Add these credentials in your n8n instance under Credentials:

  Microsoft Outlook (OAuth2 API):**  
    Used by: "Microsoft Outlook" node  
    Credential Name in Workflow: Outlook (ID: JcYqVJwcwZIhB8oy)  
    Requires OAuth2 with Calendars.Read permission.

  SMTP:**  
    Used by: "Send Email" node  
    Credential Name in Workflow: SMTP account (ID: vCexcphurglwGBfk)  
    Requires SMTP server details (host, port, username, password).

  Ensure these credentials are configured correctly with required permissions. Activate the workflow for scheduled execution.

  Made with ❤️ using n8n by Akhil.

nodes_used:
  ["n8n-nodes-base.microsoftOutlook","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.emailSend","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Evaluations Metric: Answer Similarity
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-05-27T07:15:17.213Z
updated_at: 2025-05-27T07:15:17.213Z
url: https://n8n.io/workflows/4423
scraped_at: 2025-12-24 13:02:44
description:
  This n8n template demonstrates how to calculate the evaluation metric "Similarity" which in this scenario, measures the consistency of the agent.

  The scoring approach is adapted from the open-source evaluations project RAGAS and you can see the source here https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/_answer_similarity.py

  How it works
  This evaluation works best where questions are close-ended or about facts where the answer can have little to no deviation.
  For our scoring, we generate embeddings for both the AI's response and ground truth and calculate the cosine similarity between them.
  A high score indicates LLM consistency with expected results whereas a low score could signal model hallucination.

  Requirements
  n8n version 1.94+
  Check out this Google Sheet for a sample data https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.evaluationTrigger","n8n-nodes-base.set","n8n-nodes-base.evaluation","n8n-nodes-base.set","n8n-nodes-base.noOp","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.evaluation","n8n-nodes-base.evaluation","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequest","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.code"]

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name: Evaluate AI Agent Response Correctness with OpenAI and RAGAS Methodology
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-05-27T07:18:12.776Z
updated_at: 2025-05-27T07:18:12.776Z
url: https://n8n.io/workflows/4424
scraped_at: 2025-12-24 13:02:44
description:
  This n8n template demonstrates how to calculate the evaluation metric "Correctness" which in this scenario, measures the compares and classifies the agent's response against a set of ground truths.

  The scoring approach is adapted from the open-source evaluations project RAGAS and you can see the source here https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/_answer_correctness.py

  How it works
  This evaluation works best where the agent's response is allowed to be more verbose and conversational.
  For our scoring, we classify the agent's response into 3 buckets: True Positive (in answer and ground truth), False Positive (in answer but not ground truth) and False Negative (not in answer but in ground truth).
  We also calculate an average similarity score on the agent's response against all ground truths.
  The classification and the similarity score is then averaged to give the final score. 
  A high score indicates the agent is accurate whereas a low score could indicate the agent has incorrect training data or is not providing a comprehensive enough answer.

  Requirements
  n8n version 1.94+
  Check out this Google Sheet for a sample data https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing

nodes_used:
  ["@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.evaluationTrigger","n8n-nodes-base.set","n8n-nodes-base.evaluation","n8n-nodes-base.set","n8n-nodes-base.noOp","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.evaluation","n8n-nodes-base.evaluation","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequest","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.code"]

workflow_json_compressed:
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name: Evaluate AI Agent Response Relevance using OpenAI and Cosine Similarity
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-05-27T07:19:50.908Z
updated_at: 2025-05-27T07:19:50.908Z
url: https://n8n.io/workflows/4425
scraped_at: 2025-12-24 13:02:44
description:
  This n8n template demonstrates how to calculate the evaluation metric "Relevance" which in this scenario, measures the relevance of the agent's response to the user's question.

  The scoring approach is adapted from the open-source evaluations project RAGAS and you can see the source here 
  https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/_answer_relevance.py

  How it works
  This evaluation works best for Q&A agents.
  For our scoring, we analyse the agent's response and ask another AI to generate a question from it. This generated question is then compared to the original question using cosine similarity.
  A high score indicates relevance and the agent's successful ability to answer the question whereas a low score means agent may have added too much irrelevant info, went off script or hallucinated.

  Requirements
  n8n version 1.94+
  Check out this Google Sheet for a sample data https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.evaluationTrigger","n8n-nodes-base.set","n8n-nodes-base.evaluation","n8n-nodes-base.set","n8n-nodes-base.noOp","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.evaluation","n8n-nodes-base.evaluation","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.set"]

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name: Evaluate RAG Response Accuracy with OpenAI: Document Groundedness Metric
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-05-27T07:21:41.587Z
updated_at: 2025-05-27T07:21:41.587Z
url: https://n8n.io/workflows/4426
scraped_at: 2025-12-24 13:02:44
description:
  This n8n template demonstrates how to calculate the evaluation metric "RAG document groundedness" which in this scenario, measures the ability to provide or reference information included only in retrieved vector store documents.

  The scoring approach is adapted from https://cloud.google.com/vertex-ai/generative-ai/docs/models/metrics-templates#pointwise_groundedness

  How it works
  This evaluation works best for an agent that requires document retrieval from a vector store or similar source.
  For our scoring, we need to collect the agent's response and the documents retrieved and use an LLM to assess if the former is based off the latter.
  A key factor is to look out information in the response which is not mentioned in the documents.
  A high score indicates LLM adherence and alignment whereas a low score could signal inadequate prompt or model hallucination.

  Requirements
  n8n version 1.94+
  Check out this Google Sheet for a sample data https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.vectorStoreInMemory","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.vectorStoreInMemory","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.evaluation","n8n-nodes-base.noOp","n8n-nodes-base.set","n8n-nodes-base.evaluationTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.evaluation","n8n-nodes-base.evaluation","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Evaluation Metric: Summarization
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-05-27T08:04:21.316Z
updated_at: 2025-05-27T08:04:21.316Z
url: https://n8n.io/workflows/4428
scraped_at: 2025-12-24 13:02:44
description:
  This n8n template demonstrates how to calculate the evaluation metric "Summarization" which in this scenario, measures the LLM's accuracy and faithfulness in producing summaries which are based on an incoming Youtube transcript.

  The scoring approach is adapted from https://cloud.google.com/vertex-ai/generative-ai/docs/models/metrics-templates#pointwise_summarization_quality

  How it works
  This evaluation works best for an AI summarization workflows.
  For our scoring, we simple compare the generated response to the original transcript.
  A key factor is to look out information in the response which is not mentioned in the documents.
  A high score indicates LLM adherence and alignment whereas a low score could signal inadequate prompt or model hallucination.

  Requirements
  n8n version 1.94+
  Check out this Google Sheet for a sample data https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing

nodes_used:
  ["n8n-nodes-base.evaluation","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.evaluationTrigger","n8n-nodes-base.noOp","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.evaluation","n8n-nodes-base.evaluation","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.extractFromFile","n8n-nodes-base.webhook","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5248 characters]


name: Notion AI Summary & Tags
author_name: Parnain
author_username: parnian
categories: []
created_at: 2025-05-27T09:28:44.293Z
updated_at: 2025-05-27T09:28:44.293Z
url: https://n8n.io/workflows/4431
scraped_at: 2025-12-24 13:02:44
description:
  What This Workflow Does:

  This n8n workflow automatically generates an AI-powered summary and relevant tags whenever a new row is added to your Notion database. 

  Simply save any URL to your Notion database using the [Notion Web Clipper] Chrome extension or [Save to Notion]—on both desktop and mobile. 

  This keeps all your saved content organized in one place instead of scattered across different platforms.

  How it works:

  The workflow is triggered when a new row is added to your Notion database (it checks for updates every minute).

  It retrieves the content from the saved URL.

  An AI agent analyzes the content to generate a summary and relevant tags.

  The AI output is then formatted properly.

  Finally, the formatted summary and tags are saved into the appropriate columns in your Notion database.


  Notes:

  Make sure your Notion database includes the following columns:

  URL – Stores the content URL you want to summarize.

  AI Summary – Where the AI-generated summary will be added.

  Tags – Where the AI-generated tags will be saved.

nodes_used:
  ["n8n-nodes-base.notionTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.notion"]

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name: Generate Content Ideas with Gemini Pro and Store in Google Sheets
author_name: Dvir Sharon
author_username: dvirsharon
categories: []
created_at: 2025-05-27T09:44:11.274Z
updated_at: 2025-05-27T09:44:11.274Z
url: https://n8n.io/workflows/4432
scraped_at: 2025-12-24 13:02:42
description:
  Automated Content Idea Generation and Expansion with Google Gemini and Google Sheets

  This n8n workflow automates the process of generating content ideas based on a user-defined topic, then expands each idea into a more detailed content piece (like a blog post) using Google Gemini, and finally saves all the generated data (idea title, description, and full content) into a Google Sheet. It's a powerful tool for streamlining content creation workflows.

  This workflow includes:
  Generation of multiple content ideas from a single topic.
  Expansion of each idea into detailed content using AI.
  Storage of ideas and generated content in a structured Google Sheet.
  Sticky Notes within the workflow for inline documentation and setup guidance.

  Prerequisites

  n8n Instance: You need a running n8n instance (self-hosted or cloud).
  Google AI Account: Access to Google AI (Gemini). You will need an API key.
  Google Account: Access to Google Sheets. You will need to create or use an existing spreadsheet with specific column headers.

  Installation and Setup

  Import the Workflow:
      Copy the entire JSON code provided.
      In your n8n instance, go to "Workflows".
      Click "New" -&gt; "Import from JSON".
      Paste the JSON code and click "Import".

  Configure Credentials:
      Google AI (Gemini):
          Find the "Google Gemini Chat Model for Content Idea Generator" node and the "Google Gemini Chat Model for Content Generation" node.
          Click on the "Credentials" field in both nodes (it will likely show a placeholder name like "Google Gemini(PaLM) Api account").
          Click "Create New".
          Select "Google AI API".
          Enter your Google AI API Key.
          Save the credential. (You can reuse the same credential for both nodes).
      Google Sheets:
          Find the "Google Sheets" node.
          Click on the "Credentials" field (it will likely show a placeholder name like "Google Sheets account").
          Click "Create New".
          Select "Google Sheets OAuth2 API".
          Follow the steps to connect your Google Account and grant n8n access to Google Sheets.
          Save the credential.

  Configure Google Sheets Node:
      Open the "Google Sheets" node settings.
      Spreadsheet ID: Replace the placeholder value with the actual ID of your Google Sheet. You can find the Spreadsheet ID in the URL of your Google Sheet (it's the long string of characters between /d/ and /edit).
      Sheet Name: Select or enter the name or GID of the sheet within your spreadsheet where you want to save the data (e.g., Sheet1 or gid=0).
      Columns: Ensure your Google Sheet has columns named title, description, and content. The node is configured to map the generated data to these specific column headers.
      Save the node settings.

  Review Sticky Notes:
      Look at the Sticky Notes placed around the workflow canvas. They provide helpful context and reminders for setup, required Google Sheet columns, and the AI models used.

  How to Use

  Activate the Workflow: Toggle the workflow switch to "Active".
  Trigger the Workflow:
      Since this workflow uses a "When clicking ‘Execute workflow’" node as the trigger, you can run it directly from the n8n editor.
      Click the "Execute Workflow" button.
      The workflow will start automatically.
  Set the Topic:
      Open the "Set the input fields" node.
      Modify the topic value to the subject you want to generate content ideas about.
      Save the node settings.
  Monitor Execution: Watch the workflow execute. The nodes will light up as they process. The "Loop Over Items" node will show multiple executions as it processes each generated idea.
  Check Results:
      The generated content ideas (title, description) and the expanded content will be written as new rows in the Google Sheet you configured. Each row will correspond to one generated idea and its content.

  This workflow provides a robust starting point for AI-assisted content creation. You can customize the AI prompts in the "Content Idea Generator" and "LLM Content Generator" nodes to refine the output style and format, or integrate additional steps like sending notifications or further processing the generated content.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.splitInBatches","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatGoogleGemini"]

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name: Promote YouTube Videos on Reddit with AI-Generated Comments and Email Digest
author_name: Ari Nakos
author_username: just-aristides
categories: []
created_at: 2025-05-27T13:13:34.068Z
updated_at: 2025-05-27T13:13:34.068Z
url: https://n8n.io/workflows/4433
scraped_at: 2025-12-24 13:02:45
description:
  Motivation

  Are you a small YT channel looking to grow to 1000 subs ?
  This workflow has helped me grow to 80 subs via Reddit Marketing. 
  Check out the YT Tutorial.

  What it is

  This n8n workflow automates the process of promoting your YouTube videos on Reddit. It identifies relevant Reddit posts, generates humanized comments tailored to your video content, and delivers a weekly digest of opportunities directly to your inbox.

  How It Works

  A user submits their YouTube video URL and email through a form.

  The workflow analyzes the YouTube video's title, description, and tags to extract relevant keywords and create a custom AI classification prompt.

  It searches Reddit for posts containing those keywords and filters them based on engagement metrics

  upvotes &gt; 15
  non-empty text content
  posted within the last 14 days
  upvote ratio &gt; 0.95

  An AI agent (using OpenRouter&apos;s GPT-4.1-mini) classifies each filtered Reddit post to determine its relevance to your YouTube video.

  For relevant posts, another AI agent (using OpenRouter&apos;s Gemini-2.0-flash-lite-001) generates a humanized, authentic comment designed to subtly reference your video and add value to the Reddit discussion.

  Relevant posts and their proposed comments are stored in Google Sheets.

  A professional HTML email digest is generated, summarizing the marketing opportunities.

  The email is sent to the user's provided email address.

  Setup

  To run this workflow, you need to set up credentials in n8n for:

  YouTube: Uses OAuth 2.0. Connect by authenticating your YouTube account.
  Reddit: Uses OAuth 2.0. Requires creating an app on Reddit to get a Client ID & Secret. (YT Tutorial)
  OpenRouter: Generate API key from your OpenRouter account. (YT Tutorial)
  Google Sheets: Recommend OAuth2 - just connect by authenticating.
  Gmail: Recommend OAuth 2.0. like Google Sheets

  n8n account setup

  If you do not have a n8n account, follow the YT Tutorial to get started.

nodes_used:
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name: Automated Invoice Processing System with OCR & AI - AP Automation with Airtable
author_name: Milan Vasarhelyi - SmoothWork
author_username: vasarmilan
categories: []
created_at: 2025-05-27T13:54:23.596Z
updated_at: 2025-05-27T13:54:23.596Z
url: https://n8n.io/workflows/4434
scraped_at: 2025-12-24 13:02:43
description:
  Video Introduction

  Invoice Processing Automation

  This template is the automation behind a simple incoming invoice automation tool (AP automation) tool built in Airtable.

  Link to the Airtable base, and all other tools used, is in notes on the left of the automation.

  How it works
  See how it works on video: Full Video Walkthrough

  1) We get an email with an invoice attachment:


  2) Processes and adds the data to an Airtable interface: 

  3) Once we approved it and Due date approaches, it shows among Due invoices, where we can track if it's paid.

  Looking for customization or a custom business app? 📞 Book a Call | 💬 DM me on Linkedin

nodes_used:
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workflow_json_compressed:
  [encoded data, 7728 characters]


name: Analyze BeyondPresence Video Calls with GPT-4o-mini and Google Sheets
author_name: M Shehroz Sajjad
author_username: mshehrozsajjad
categories: []
created_at: 2025-05-27T14:28:15.263Z
updated_at: 2025-05-27T14:28:15.263Z
url: https://n8n.io/workflows/4436
scraped_at: 2025-12-24 13:02:46
description:
  Transform your BeyondPresence video agent conversations into comprehensive insights by automatically analyzing each call with AI and organizing 35+ data points in Google Sheets. This template helps customer success, support, and training teams save 30+ minutes per call on documentation while ensuring no critical action items or insights are missed.

  How it works
  Webhook receives** completed call data from BeyondPresence including full transcript
  Data validation** ensures quality and adds enriched metadata (duration, time calculations)  
  AI analysis** (GPT-4) extracts action items, sentiment, decisions, and recommendations
  Parse response** handles the AI output and structures it for sheets
  Auto-append** to Google Sheets with 35+ insights per call organized beautifully

  Set up steps
  Copy our Google Sheets template - One click! Get pre-formatted sheet: BeyondPresence Call Analytics Template
  Connect accounts - Add OpenAI API key and Google Sheets OAuth2
  Configure webhook - Copy URL from n8n to BeyondPresence Settings → Webhooks
  Customize AI prompt (optional) - Adjust analysis focus for your use case
  Test with a call - Make a test call and watch insights appear!

  Setup time: 5-10 minutes
  Requirements: BeyondPresence account, OpenAI API key, Google account

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.webhook","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-beyondpresence.beyondPresence","n8n-nodes-base.code"]

workflow_json_compressed:
  [encoded data, 7688 characters]


name: Goodreads Quote Extraction with Bright Data and Gemini
author_name: Dvir Sharon
author_username: dvirsharon
categories: []
created_at: 2025-05-27T16:36:14.875Z
updated_at: 2025-05-27T16:36:14.875Z
url: https://n8n.io/workflows/4438
scraped_at: 2025-12-24 13:02:46
description:
  Goodreads Quote Extraction with Bright Data and Gemini

  This workflow demonstrates how to fetch data specifically from Goodreads web pages using Bright Data and then extract specific information (quotes) from that data using a Google Gemini AI model.

  How it works

  The workflow is triggered manually.
  It sends a request to a Bright Data collector to scrape data from a predefined list of Goodreads URLs.
  The collected text data from Goodreads is then passed to a Google Gemini AI node.
  The AI node processes the text and extracts quotes based on a specified JSON schema output format.

  Set up steps

  Setting up this workflow should take only a few minutes.

  You will need a Bright Data API key to configure the 'Header Auth' credential.
  You will need a Google Gemini API key to configure the 'Google Gemini(PaLM) Api account' credential.
  Ensure the correct Bright Data collector ID is set in the 'Perform Bright Data Web Request' node URL.
  Make sure the full list of target Goodreads URLs is correctly added to the 'Perform Bright Data Web Request' node's body.
  Link your created credentials to the respective nodes ('Perform Bright Data Web Request' and 'Quotes Extractor').
  Keep detailed descriptions for specific node configurations in sticky notes inside your workflow canvas.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.informationExtractor","n8n-nodes-base.httpRequest"]

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name: Automated Brand Mentions Tracker With GPT-4o, Google Sheets, and Email
author_name: Daniel Shashko
author_username: tomax
categories: []
created_at: 2025-05-27T21:43:46.459Z
updated_at: 2025-05-27T21:43:46.459Z
url: https://n8n.io/workflows/4443
scraped_at: 2025-12-24 13:02:44
description:
  This workflow enables you to automate the daily monitoring of how an AI model (like ChatGPT) responds to specific queries relevant to your market. It identifies mentions of your brand and predefined competitors, logs detailed interactions in Google Sheets, and delivers a comprehensive email report.

  Main Use Cases

  Monitor how your brand is mentioned by AI in response to relevant user queries.
  Track mentions of key competitors to understand AI's comparative positioning.
  Gain insights into AI's current knowledge and portrayal of your brand and market landscape.
  Automate daily intelligence gathering on AI-driven brand perception.

  How it works

  The workflow operates as a scheduled process, organized into these stages:

  Configuration & Scheduling
      Triggers daily (or can be run manually).
      Key variables are defined within the workflow: your brand name (e.g., "YourBrandName"), a list of queries to ask the AI, and a list of competitor names to track in responses.
  AI Querying
      For each predefined query, the workflow sends a request to the OpenAI ChatGPT API (via an HTTP Request node).
  Response Analysis
      Each AI response is processed by a Code node to:
          Check if your brand name is mentioned (case-insensitive).
          Identify if any of the listed competitors are mentioned (case-insensitive).
          Extract the core AI response content (limited to 500 characters for brevity in logs/reports).
  Data Logging to Google Sheets
      Detailed results for each query—including timestamp, date, the query itself, query index, your brand name, the AI's response, whether your brand was mentioned, and any errors—are appended to a specified Google Sheet.
  Email Report Generation
      A comprehensive HTML email report is compiled. This report summarizes:
          Total queries processed, number of times your brand was mentioned, total competitor mentions, and any errors encountered.
          A summary of competitor mentions, listing each competitor and how many times they were mentioned.
          A detailed table listing each query, whether your brand was mentioned, and which competitors (if any) were mentioned in the AI's response.
  Automated Reporting
      The generated HTML email report is sent to specified recipients, providing a daily snapshot of AI interactions.

  Summary Flow:

  Schedule/Workflow Trigger → Initialize Brand, Queries, Competitors (in Code node) → For each Query: Query ChatGPT API → Process AI Response (Check for Brand & Competitor Mentions) → Log Results to Google Sheets → Generate Consolidated HTML Email Report → Send Email Notification

  Benefits:

  Fully automated daily monitoring of AI responses concerning your brand and competitors.
  Provides objective insights into how AI models are representing your brand in user interactions.
  Delivers actionable competitive intelligence by tracking competitor mentions.
  Centralized logging in Google Sheets for historical analysis and trend spotting.
  Easily customizable with your specific brand, queries, competitor list, and reporting recipients.

nodes_used:
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name: Build Production-Ready User Authentication with Airtable and JWT
author_name: NanaB
author_username: nanabrown
categories: []
created_at: 2025-05-28T03:58:04.708Z
updated_at: 2025-05-28T03:58:04.708Z
url: https://n8n.io/workflows/4444
scraped_at: 2025-12-24 13:02:45
description:
  This n8n workflow provides a comprehensive solution for user authentication and management, leveraging Airtable as the backend database. It includes flows for user sign-up and login, aswell as the sample crud operations retrieving user details, and updating user information.

  Youtube Video of me explaining the flow: https://www.youtube.com/watch?v=gKcGfyq3dPM

  How it Works

  User Sign-Up Flow
  Receives POST request: A webhook listens for POST requests containing new user details (email, first name, last name, password).
  Checks for existing email: The workflow queries Airtable to see if the submitted email already exists.
  Handles email in use: If the email is found, it responds with {"response": "email in use"}.
  Creates new user: If the email is unique, the password is SHA256 hashed (Base64 encoded), and the user's information (including the hashed password) is stored in Airtable. A successful response of {"response": "success"} is then sent.

  User Login Flow
  Receives POST request: A webhook listens for POST requests with user email and password for login.
  Verifies user existence: It checks Airtable for a user with the provided email. If no user is found, it responds with a failure message ("wrong email").
  Compares passwords: If a user is found, the submitted password is hashed (SHA256, Base64 encoded) and compared with the stored hashed password in Airtable.
  Responds with JWT or error: If passwords match, a JWT token containing the user's ID and email is issued. If they don't match, a "wrong password" response is sent.

  Flows for a Logged-In User

  These flows require a JWT-authenticated request.

  Get User Details:**
      Webhook (GET): Receives a JWT-authenticated request.
      Airtable (Read): Fetches the current user’s record using the jwtPayload.id.
      Set Node ("Specify Current Details"): Maps fields like "First Name," "Last Name," "Email," and "Date" from Airtable to a standard output format.

  Update User Details:**
      Webhook (POST): Receives updated user data (email, name, password).
      Airtable (Upsert): Updates the record matching jwtPayload.id using the submitted fields.
      Set Node ("Specify New Details"): Outputs the updated data in a standard format.

  Set Up Steps (Approx. 5 Minutes)

  Step 1: Set up your Airtable Base and Table

  You'll need an Airtable Base and a table to store your user data. Ensure your table has at least the following columns:

  Email** (Single Line Text)
  First Name** (Single Line Text)
  Last Name** (Single Line Text)
  Password** (Single Line Text - this will store the hashed password)
  Date** (Date - optional, for user sign-up date)

  Step 2: Obtain an Airtable Personal Access Token

  Go to the Airtable website and log in to your account.
  Navigate to your personal access token page (usually found under your developer settings or by searching for "personal access tokens").
  Click "Create new token."
  Give your token a name (e.g., "n8n User Management").
  Grant necessary permissions:
      Scope: data.records:read, data.records:write for the specific base you will be using.
      Base: Select the Airtable base where your user management table resides.
  Generate the token and copy it immediately. You won't be able to see it again. Store it securely.

  Step 3: Create a JWT Auth Credential in n8n

  In your n8n instance, go to "Credentials" (usually found in the left-hand sidebar).
  Click "New Credential" and search for "JWT Auth".
  Give the credential a name (e.g., "UserAuthJWT").
  For the "Signing Secret," enter a strong, random string of characters. This secret will be used to sign and verify your JWT tokens. Keep this secret highly confidential.
  Save the credential.

  Customization Options

  This workflow is designed to be highly adaptable:

  Database Integration**: Easily switch from Airtable to other databases like PostgreSQL, MySQL, MongoDB, or even Google Sheets by replacing the Airtable nodes with the appropriate database nodes in n8n.
  Authentication Methods**: Extend the authentication to include multi-factor authentication (MFA), social logins (Google, Facebook), or integrate with existing identity providers (IdP) by adding additional nodes.
  User Profile Fields**: Add or remove user profile fields (e.g., phone number, address, user roles) by adjusting the Airtable table columns and the Set nodes in the workflow.
  Notification System**: Integrate notification systems (e.g., email, SMS) for events like new user sign-ups, password resets, or account changes.
  Admin Panel**: Build an admin panel using n8n to manage users directly, including functionalities for adding, deleting, or updating user records, and resetting passwords.

  This workflow provides a solid foundation for building robust user management systems, adaptable to a wide range of applications and security requirements.

  Need Assistance or Customization?

  Do you have specific integrations in mind, or are you looking to add more user management features to this workflow?

  If you need help setting this up, or want to adapt it for a unique use case, don't hesitate to reach out! You can contact me directly at nanabrownsnr@gmail.com. I'd be glad to assist you.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.crypto","n8n-nodes-base.airtable","n8n-nodes-base.respondToWebhook","n8n-nodes-base.webhook","n8n-nodes-base.webhook","n8n-nodes-base.airtable","n8n-nodes-base.if","n8n-nodes-base.respondToWebhook","n8n-nodes-base.airtable","n8n-nodes-base.if","n8n-nodes-base.crypto","n8n-nodes-base.if","n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.webhook","n8n-nodes-base.webhook","n8n-nodes-base.airtable","n8n-nodes-base.airtable","n8n-nodes-base.stickyNote"]

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name: Generate AI Stock Images with Flux1-schnell, Metadata Tagging & Google Integration
author_name: victor Adriano
author_username: bwire
categories: []
created_at: 2025-05-28T05:38:15.887Z
updated_at: 2025-05-28T05:38:15.887Z
url: https://n8n.io/workflows/4445
scraped_at: 2025-12-24 13:02:44
description:
  📣 This template generates up to 2,000 AI-based stock images per day for under $3. It includes prompt generation, image creation, metadata enrichment, upload to Google Drive, and error logging — fully automated with minimal setup.

  📌 Who is this for?

  This workflow is designed for:

  Stock image creators** and contributors
  Agencies** managing visual content at scale
  Solo creators** or marketers automating asset production
  Anyone aiming to populate image libraries (e.g., Adobe Stock, Shutterstock)

  ❓ What problem is this workflow solving?

  Manually generating, naming, tagging, and uploading thousands of stock images is time-consuming and expensive. This automation solves that by:

  Generating photorealistic images via AI
  Auto-tagging with rich metadata
  Uploading them to structured Google Drive folders
  Logging progress and capturing errors automatically

  ⚙️ What this workflow does

  ✅ Generates text prompts from idea topics using GPT
  🎨 Converts prompts into 4 images each via the Flux Schnell model
  📐 Resizes and compresses images for preview and final use
  🧠 Uses GPT-4o-mini to generate metadata: filename, title, category, and 25 keywords
  ☁️ Uploads to Google Drive, logs metadata to Google Sheets
  🟢 Marks each prompt as completed
  📲 Sends Telegram alerts for success and errors

  🛠 Setup

  Google Sheets

     Sheet 1: Ideas — New prompt topics
     Sheet 2: Generated Pmts — Tracks generated prompts and status
     Sheet 3: Error Logs — Execution error records

  Google Drive

     A folder for image uploads
     A folder for copied daily spreadsheets

  API Access

     OpenAI GPT (gpt-4o-mini)
     PIAPI (Flux Schnell image model)

  Telegram Bot (optional but recommended)

     Real-time status notifications

  🧩 How to customize this workflow to your needs

  🔁 Change frequency of generation via trigger settings
  🧠 Swap models if using a different image API
  🧾 Adjust metadata fields or format rules
  📤 Redirect outputs to Airtable, Notion, Dropbox, etc.

  🧠 Node Naming & Notes

  ✅ All nodes are clearly renamed to reflect their purpose (e.g., Generate Image, Upload to Drive)
  🗒️ Sticky notes are used to document setup and logic
  🔗 External links to Notion setup docs or Loom videos are recommended

  🗂️ Categories

  AI**
  Marketing**
  Product**
  Building Blocks**

  🎁 Bonus Feature

  This template includes a bonus stock image renamer workflow — ideal for renaming:

  📸 Taken photos
  🗃️ Existing stock libraries
  🖼️ Downloaded image batches

  It applies SEO-friendly, consistent naming compatible with major platforms like Adobe Stock and Shutterstock.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.editImage","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.splitOut","n8n-nodes-base.editImage","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.telegram","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequest","n8n-nodes-base.merge","n8n-nodes-base.googleDrive","n8n-nodes-base.wait","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.function","n8n-nodes-base.function","n8n-nodes-base.merge","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.telegram","n8n-nodes-base.errorTrigger"]

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