Manage contacts in Google Contacts
No description available.
By Harshil AgrawalDoctor appointment management system with Gemini AI, WhatsApp, Stripe & Google Sheets
WhatsApp AI Assistant for Clinic Appointment Booking Automate your entire appointment lifecycle with an intelligent AI assistant that lives on WhatsApp. This workflow empowers any clinic or independent practitioner to manage bookings, take payments, and send reminders without manual intervention, using Google Sheets as a simple database. This template handles everything from the initial booking conversation to sending the final reminder, allowing you to focus on your patients, not your schedule. Features ๐ค Conversational AI Booking: A Google Gemini-powered agent guides patients through booking, rescheduling, and canceling appointments in a natural, friendly chat. ๐๏ธ Smart Scheduling: The AI checks for available slots based on your working hours and existing appointments in Google Sheets, preventing double-bookings. ๐ Automated Reminders: A daily trigger automatically sends WhatsApp reminders to patients for their appointments on that day, reducing no-shows. ๐ณ Seamless Payments: Integrated with Stripe to handle online payments. The workflow sends a confirmation message upon successful payment. ๐ Centralized Management: Uses a single Google Sheet with separate tabs for Patients, Appointments, and Configuration, making it easy to view and manage all your data. ๐ Easy Rescheduling & Cancellations: Patients can manage their own bookings through the WhatsApp chat, and all changes are instantly reflected in your Google Sheet. Prerequisites Before you begin, you will need the following accounts and credentials: n8n Account: A running n8n instance (cloud or self-hosted). WhatsApp Business Account: Access to the WhatsApp Cloud API. Google Account: For using Google Sheets and the Google Gemini (AI) API. Stripe Account: To process online payments. n8n Credentials: You must configure credentials in your n8n instance for: WhatsApp Cloud API Google Sheets (OAuth2) Google Gemini API Stripe Setup Instructions Follow these steps carefully to get your automated assistant up and running. Step 1: Set Up Your Google Sheet This workflow relies on a specific Google Sheet structure. Create a new Google Sheet. Rename the sheet to something memorable, like "Clinic Appointments". Create three tabs at the bottom with the exact names: Patients, Appointments, and Config. Set up the columns for each tab as follows (the header names must be an exact match): Patients tab: patientid, whatsappnumber, name, age, gender Appointments tab: appointmentid, patientid, whatsappnumber, date, time, paymentmethod, paymentstatus, status, stripepayment_intent Config tab: key, value (Add a row with working_hours as the key and a value like 10:00-18:00) Step 2: Configure the Workflow Nodes Now, you'll link the workflow to your accounts and your new Google Sheet. Update All Google Sheets Nodes: Go through every Google Sheets node in the workflow (e.g., "Get Appointment sheet", "Add Patient", "Google Sheets Trigger") and do the following: Select your Google Sheets credential from the dropdown. In the Document ID field, paste the ID of your Google Sheet. Select the correct sheet (Appointments, Patients, etc.) from the Sheet Name dropdown. Update All WhatsApp Nodes: Go through every WhatsApp node (e.g., "Send message", "WhatsApp Trigger", "Send Payment Confirmation"): Select your WhatsApp credential. Enter your Phone Number ID from your Meta for Developers account. Update AI & Stripe Nodes: In the Google Gemini Chat Model nodes, select your Google Gemini credential. In the Stripe Trigger node, select your Stripe credential. Step 3: Activate the Workflow Click Save to apply your changes. Click the Activate toggle in the top-right corner to turn the workflow on. Your AI appointment assistant is now live! Send a message to your WhatsApp number to begin testing. Customization Change Reminder Time: To change the daily reminder time, open the Schedule Trigger node and adjust the hour from the default of 8 AM. Edit AI Personality: To modify how the AI communicates, edit the system message in the AI Agent node (the one connected to the WhatsApp Trigger). You can change its tone, instructions, or language.
By GreatStackSend trending "Show HN" to email
Triggers every day at 1pm Gets the current content from Hacker News Gets all the different submission items Extracts the rank, title and url Checks if it is a "Show HN" submission Combines the items into a simple email text Sends an email with the email text
By Jan OberhauserGenerate Podcast Transcript Summaries & Keywords with OpenAI and Gmail
How it works This advanced workflow transforms your long-form audio content (like podcast episodes or webinar recordings) into digestible, ready-to-use marketing assets. It's designed for podcasters, content creators, and marketers who want to maximize their content's reach. It automatically: Takes a full transcript of your audio/video content as input. Generates a concise, comprehensive summary of the episode using advanced AI. Extracts a list of key topics and keywords from the transcript, perfect for SEO, tagging, and content categorization. Delivers the summary and keywords directly to your inbox or a connected tool for easy access. Streamline your content repurposing pipeline and unlock new value from your audio and video assets with intelligent automation! Set up steps Setting up this powerful workflow typically takes around 20-30 minutes, as it involves multiple AI steps. You'll need to: Obtain API keys for your preferred AI service (e.g., OpenAI, Google AI). Have access to a method for generating transcripts from your audio/video (e.g., manually pasting, or using a separate transcription service like AssemblyAI, Whisper, etc.). Connect your preferred email service (e.g., Gmail) to receive the output. All detailed setup instructions and specific configuration guidance are provided within the workflow itself using sticky notes.
By Piotr SobolewskiAutomate prescription delivery via Google Sheets to email & WhatsApp
This is a fully working n8n workflow that sends prescriptions to patients via email and WhatsApp when a doctor enters prescription data into a Google Sheet. ๐ Google Sheets Structure Main Sheet: Required columns: prescription_id (unique ID) patient_name patient_email patient_phone doctor_name prescription_date prescription_details dosage_instructions followup_date (optional) prescription_status (set to "new" for new prescriptions) Log Sheet: This will be auto-created with columns for tracking sent notifications. ๐ง Required Credentials Setup Google Sheets OAuth2 API: Connect your Google account SMTP Credentials: For email sending (Gmail, Outlook, etc.) WhatsApp API: Meta Business WhatsApp API credentials โ๏ธ Configuration Steps Replace YOURGOOGLESHEET_ID with your actual Google Sheet ID Replace YOURWHATSAPPPHONENUMBERID with your WhatsApp Business phone number ID Update the email sender address in the "Send Email" node Set up your credentials in n8n ๐ Features Included Automated Trigger: Monitors Google Sheet for new prescriptions Smart Filtering: Only processes prescriptions with status "new" Rich Email Format: Professional HTML email with prescription details WhatsApp Integration: Sends formatted prescription text Comprehensive Logging: Tracks all sent notifications Status Updates: Marks prescriptions as "sent" after processing Error Handling: Logs success/failure status for both channels ๐ฑ Sample Data Format Add rows to your sheet like this: prescription_id: RX001 patient_name: John Doe patient_email: john@email.com patient_phone: +1234567890 doctor_name: Dr. Smith prescription_date: 2025-01-15 prescription_details: Amoxicillin 500mg capsules dosage_instructions: Take 1 capsule 3 times daily with food followup_date: 2025-01-22 prescription_status: new
By Oneclick AI SquadAutomatic workflow backups to GitLab with GPT-4.1 documentation generation
Auto backup n8n workflows to GitLab with AI-generated documentation This n8n template automatically backs up your workflows to a GitLab repository whenever they're updated or activated, and generates README documentation using AI. This workflow can be aslo added as a sub-workflow to any existing workflow to enable backup functionality. Who's it for This template is perfect for n8n users who want to: Maintain version control of their workflows Create automatic backups in Git repositories Generate documentation for their workflows using AI Keep their workflow library organized and documented How it works The workflow monitors n8n for workflow updates and activations, then automatically saves the workflow JSON to GitLab and generates a README file using OpenAI: Trigger Detection: Uses n8n Trigger to detect when workflows are updated or activated Workflow Retrieval: Fetches the complete workflow data using the n8n API Repository Check: Lists existing files in GitLab to determine if the workflow already exists Smart File Management: Either creates a new file or updates an existing one based on the repository state AI Documentation: Generates a README.md file using OpenAI's GPT model to document the workflow GitLab Storage: Saves both the workflow JSON and README to organized folders in your GitLab repository Requirements GitLab account with API access and a repository named "all_projects" n8n API credentials for accessing workflow data OpenAI API key for generating documentation GitLab personal access token with repository write permissions How to set up Configure GitLab credentials: Add your GitLab API credentials in the GitLab nodes Set up n8n API: Configure your n8n API credentials for the workflow retrieval node Add OpenAI credentials: Set up your OpenAI API key in the "Message a model" node Update repository details: Modify the owner and repository name in GitLab nodes to match your setup Test the workflow: Save and activate the workflow to test the backup functionality How to customize the workflow Change repository structure: Modify the file path expressions to organize workflows differently Customize commit messages: Update the commit message templates in GitLab nodes Enhance AI documentation: Modify the OpenAI prompt to generate different styles of documentation Add file filtering: Include conditions to backup only specific workflows Extend triggers: Add webhook or schedule triggers for different backup scenarios Multiple repositories: Duplicate GitLab nodes to backup to multiple repositories simultaneously
By ShohaniGenerate marketing reports from Google Sheets with GPT-4 insights and PDF.co
This workflow pulls marketing data from Google Sheets, aggregates spend by channel, generates an AI-written summary, and outputs a formatted PDF report using a custom HTML template on PDF.co. --- โ๏ธ Setup Instructions 1๏ธโฃ Prepare Your Google Sheet Copy this template into your Google Drive: Sample Marketing Data Add or update your marketing spend data in rows 2โ100. Connect Google Sheets in n8n Go to n8n โ Credentials โ New โ Google Sheets (OAuth2) Log in with your Google account and grant access Select the Spreadsheet ID and Worksheet in the workflow --- 2๏ธโฃ Set Up PDF.co for PDF Reports Create a free account at PDF.co In PDF.co Dashboard โ HTML to PDF Templates, create a new Mustache template Paste the HTML provided at the bottom of this description Save, and note your Template ID In n8n โ Credentials โ New โ PDF.co API, paste your API Key and save In the workflow, select your PDF.co credential in the Create PDF node Replace the templateId with your Template ID --- ๐ง How It Works Google Sheets Node: Pulls marketing spend data Summarize Nodes: Aggregate total spend and spend per channel OpenAI Node: Writes a daily summary of marketing performance Code Node: Converts aggregated data into the correct shape for the PDF template PDF.co Node: Generates a final, formatted PDF report --- ๐ฌ Contact Need help customizing this (e.g., filtering by campaign, sending reports by email, or formatting your PDF)? ๐ง robert@ynteractive.com ๐ Robert Breen ๐ ynteractive.com --- ๐ HTML Template (for PDF.co) > Paste this into a new HTML Template on PDF.co and reference its Template ID in your workflow. html <!DOCTYPE html> <html> <head> <meta charset="utf-8" /> <title>Invoice {{invoiceNumber}}</title> <style> body { font-family: Arial, Helvetica, sans-serif; margin: 36px; color: 222; } .header { display: flex; justify-content: space-between; align-items: center; } .brand { max-height: 56px; } h1 { margin: 12px 0 4px; font-size: 22px; } .meta { font-size: 12px; color: 555; } .two-col { display: flex; gap: 24px; margin-top: 16px; } .box { flex: 1; border: 1px solid ddd; padding: 12px; border-radius: 6px; } .label { font-size: 11px; color: 666; text-transform: uppercase; letter-spacing: .02em; } table { width: 100%; border-collapse: collapse; margin-top: 16px; } th, td { border-bottom: 1px solid eee; padding: 10px 8px; font-size: 13px; } th { background: fafafa; text-align: left; } tfoot td { border-top: 2px solid ddd; font-size: 13px; } .right { text-align: right; } .totals td { padding: 6px 8px; } .grand { font-weight: 700; font-size: 14px; } .notes { margin-top: 18px; font-size: 12px; color: 444; } </style> </head> <body> <div> <div> <h1>Invoice {{invoiceNumber}}</h1> <div>Date: {{invoiceDate}} | Due: {{dueDate}}</div> </div> {{company.logoUrl}} <img src alt="Logo" /> {{/company.logoUrl}} </div> <div> <div> <div>From</div> <div><strong>{{company.name}}</strong></div> <div>{{company.address}}</div> <div>{{company.phone}}</div> <div>{{company.email}}</div> </div> <div> <div>Bill To</div> <div><strong>{{billTo.name}}</strong></div> <div>{{billTo.address}}</div> <div>{{billTo.email}}</div> </div> </div> <table> <thead> <tr> <th></th> <th>Description</th> <th>Qty</th> <th>Unit Price</th> <th>Line Total</th> </tr> </thead> <tbody> {{items}} <tr> <td>{{line}}</td> <td>{{description}}</td> <td>{{qty}}</td> <td>{{unitPriceFmt}}</td> <td>{{lineTotalFmt}}</td> </tr> {{/items}} </tbody> <tfoot> <tr> <td colspan="4">Subtotal</td> <td>{{subTotalFmt}}</td> </tr> <tr> <td colspan="4">Tax ({{taxRatePct}})</td> <td>{{taxAmountFmt}}</td> </tr> <tr> <td colspan="4">Discount</td> <td>-{{discountFmt}}</td> </tr> <tr> <td colspan="4">Total</td> <td>{{totalFmt}}</td> </tr> </tfoot> </table> <div> <strong>Notes:</strong> {{notes}}<br /> <strong>Terms:</strong> {{terms}} </div> </body> </html>
By Robert BreenAutomatically Classify Zoho Desk Support Tickets using Gemini AI
Automatically Classify Support Tickets in Zoho Desk with AI with Gemini Transform your customer support workflow with intelligent ticket classification. This automation leverages AI to automatically categorize incoming support tickets in Zoho Desk, reducing manual work and ensuring faster ticket routing to the right teams. How It Works Fetches all tickets from Zoho Desk with pagination support Filters unclassified tickets (where classification field is null) Retrieves complete ticket threads for full conversation context Uses OpenRouter AI (GPT-4, Claude, or other models) to classify tickets into predefined categories Updates tickets in Zoho Desk with accurate classifications automatically Use Cases Customer Support Teams: Automatically route tickets to specialized departments (billing, technical, sales) Help Desks: Prioritize urgent issues and categorize feature requests Prerequisites Active Zoho Desk account with API access OpenRouter API account (supports multiple AI models) Basic understanding of OAuth2 authentication Predefined ticket categories in your Zoho Desk setup Setup Steps Time: ~15 minutes Configure Zoho Desk OAuth2 - Follow our step-by-step GitHub guide for OAuth2 credential setup Set up OpenRouter API - Create an account and generate API keys at openrouter.ai Customize classifications - Define your ticket categories (e.g., Technical, Billing, Feature Request, Bug Report) Adapt the workflow - Modify for any field: status, priority, tags, assignment, or custom fields Review API documentation - Check Zoho Desk Search API docs for advanced filtering options Test thoroughly - Run manual triggers before automation Note: This workflow demonstrates proper Zoho Desk API integration, including OAuth2 authentication and pagination handlingโtwo common integration challenges.
By Julian KaiserQuickBooks Online MCP Server - add QuickBooks tool to any AI (like Claude)
Video Introduction [](https://youtu.be/mprQ4CY3yn0) Want to automate your inbox or need a custom workflow? ๐ Book a Call | ๐ฌ DM me on Linkedin --- What This Workflow Does This workflow creates an AI-powered chatbot that can answer natural language questions about your QuickBooks Online data. Using OpenAI's GPT models and the Model Context Protocol (MCP), the agent can retrieve customer information, analyze balances, and provide insights through a conversational interface. Users can simply ask questions like "How many customers do we have?" or "What's our total customer balance?" and get instant answers from live QuickBooks data. Key Features Natural language queries: Ask questions about your QuickBooks data in plain English MCP architecture: Uses Model Context Protocol to manage tools efficiently, making it easy to expand with additional QuickBooks operations Public chat interface: Share the chatbot URL with team members who need QuickBooks insights without direct access Real-time data: Queries live QuickBooks data for up-to-date answers Common Use Cases Customer service teams checking account balances without logging into QuickBooks Sales teams quickly looking up customer information Finance teams getting quick answers about customer data Managers monitoring key metrics through conversational queries Setup Requirements QuickBooks Developer Account: Register at developer.intuit.com and create an app with Accounting scope permissions. You'll receive a Client ID and Client Secret. Configure OAuth: In your Intuit Developer dashboard, add the redirect URL provided by n8n when creating QuickBooks credentials. Set the environment to Sandbox for testing, or complete Intuit's app approval process for Production use. OpenAI API: Add your OpenAI API credentials to power the chat model. The workflow uses GPT-4.1-mini by default, but you can select other models based on your performance and cost requirements. Chat Access: The chat trigger is set to public by default. Configure access settings based on your security requirements before sharing the chat URL.
By Milan Vasarhelyi - SmoothWork