Workflow Templates

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Who is this for? This workflow is for anyone who receives invoices by email and wants to stay on top of payment deadlines without manual tracking. What problem is this workflow solving? Invoices often get buried in your inbox. This workflow uses AI to find them, extracts key details, and adds a task to remind you to pay before it’s overdue. No more missed payments. No more manual tracking. How it works? This workflow is triggered on a schedule (By default, every hour). It checks your Gmail inbox for unread messages. Each email is passed to an AI agent (using OpenAI), which decides whether it’s an invoice. If an invoice is found: A task is created in your Google Tasks with the payment reminder and due date. The email is labeled (for tracking) and marked as read. If not an invoice: The email is skipped (no action taken). How to set up? Connect these services in your n8n credentials: Gmail (OAuth2) OpenAI Google Tasks Create Gmail label Go to Gmail and create a label named Invoice. This label will be applied to processed invoice emails. Choose your Google Task list In the task creation node, select the correct task list for your reminders. Set the schedule In the Schedule Trigger node, choose how often it should check your inbox. How to customize this workflow to your needs? Change the Gmail label** Update the label applied to emails after they are processed. Edit the AI prompt** Adjust the system prompt in the OpenAI node if your invoices follow a unique format. Update the task format** Modify the task title and notes to suit how you like your reminders to look. Adjust the schedule** Run it more or less frequently based on how many invoices you receive.

This workflow illustrates how to use Perplexity AI in your n8n workflow. Perplexity is a free AI-powered answer engine that provides accurate, trusted, and real-time answers to any question. Credentials Setup 1/ Go to the perplexity dashboard, purchase some credits and create an API Key https://www.perplexity.ai/settings/api 2/ In the perplexity Request node, use Generic Credentials, Header Auth. For the name, use the value "Authorization" And for the value "Bearer pplx-e4...59ea" (Your Perplexity Api Key) AI Model Sonar Pro is the current top model used by perplexity. If you want to use a different one, check this page: https://docs.perplexity.ai/guides/model-cards

Automated monitoring system that tracks startup activities, funding events, and company updates in real-time, providing valuable market intelligence. 🚀 What It Does Real-time monitoring of startup activities Funding alerts and updates Competitor tracking Industry trend analysis Customizable watchlists 🎯 Perfect For Venture capitalists Startup founders Business development teams Market researchers Investment analysts ⚙️ Key Benefits ✅ Stay ahead of market movements ✅ Never miss important funding rounds ✅ Track competitor activities ✅ Identify emerging trends ✅ Save hours of manual research 🔧 What You Need Crunchbase API access n8n instance Notification preferences (email/Slack/Teams) 📊 Data Points Tracked New funding rounds Company updates Leadership changes Product launches Market expansions 🛠️ Setup & Support Quick Setup Deploy in 20 minutes with our step-by-step configuration guide 📺 Watch Tutorial 💼 Get Expert Support 📧 Direct Help Stay informed about the startup ecosystem with automated monitoring and alerts. Make data-driven decisions with timely, relevant information.

This automated n8n workflow continuously monitors airline schedule changes by fetching real-time flight data, comparing it with stored schedules, and instantly notifying both internal teams and affected passengers through multiple communication channels. The system ensures stakeholders are immediately informed of any flight delays, cancellations, gate changes, or other critical updates. Good to Know Flight data accuracy depends on the aviation API provider's update frequency and reliability Critical notifications (cancellations, major delays) trigger immediate passenger alerts via SMS and email Internal Slack notifications keep operations teams informed in real-time Database logging maintains a complete audit trail of all schedule changes The system processes only confirmed schedule changes to avoid false notifications Passenger notifications are sent only to those with confirmed tickets for affected flights How It Works Schedule Trigger - Automatically runs every 30 minutes to check for flight schedule updates Fetch Airline Data - Retrieves current flight information from aviation APIs Get Current Schedules - Pulls existing schedule data from the internal database Process Changes - Compares API data with database records to identify schedule changes Check for Changes - Determines if any updates require processing and notifications Update Database - Saves schedule changes to the internal flight database Notify Slack Channel - Sends operational updates to the flight operations team Check Urgent Notifications - Identifies critical changes requiring immediate passenger alerts Get Affected Passengers - Retrieves contact information for passengers on changed flights Send Email Notifications - Dispatches detailed schedule change emails via SendGrid Send SMS (Critical Only) - Sends urgent text alerts for cancellations and major delays Update Internal Systems - Syncs changes with other airline systems via webhooks Log Sync Activity - Records all synchronization activities for audit and monitoring Data Sources The workflow integrates with multiple data sources and systems: Aviation API (Primary Data Source) Real-time flight status and schedule data Departure/arrival times, gates, terminals Flight status (on-time, delayed, cancelled, diverted) Aircraft and route information Internal Flight Database flight_schedules table - Current schedule data with columns: flight_number (text) - Flight identifier (e.g., "AA123") departure_time (timestamp) - Scheduled departure time arrival_time (timestamp) - Scheduled arrival time status (text) - Flight status (active, delayed, cancelled, diverted) gate (text) - Departure gate number terminal (text) - Terminal identifier airline_code (text) - Airline IATA code origin_airport (text) - Departure airport code destination_airport (text) - Arrival airport code aircraft_type (text) - Aircraft model updated_at (timestamp) - Last update timestamp created_at (timestamp) - Record creation timestamp passengers table - Passenger contact information with columns: passenger_id (integer) - Unique passenger identifier name (text) - Full passenger name email (text) - Email address for notifications phone (text) - Mobile phone number for SMS alerts notification_preferences (json) - Communication preferences created_at (timestamp) - Registration timestamp updated_at (timestamp) - Last profile update tickets table - Booking and ticket status with columns: ticket_id (integer) - Unique ticket identifier passenger_id (integer) - Foreign key to passengers table flight_number (text) - Flight identifier flight_date (date) - Travel date seat_number (text) - Assigned seat ticket_status (text) - Status (confirmed, cancelled, checked-in) booking_reference (text) - Booking confirmation code fare_class (text) - Ticket class (economy, business, first) created_at (timestamp) - Booking timestamp updated_at (timestamp) - Last modification timestamp sync_logs table - Audit trail and system logs with columns: log_id (integer) - Unique log identifier workflow_name (text) - Name of the workflow that created the log total_changes (integer) - Number of schedule changes processed sync_status (text) - Status (completed, failed, partial) sync_timestamp (timestamp) - When the sync occurred details (json) - Detailed log information and changes error_message (text) - Error details if sync failed execution_time_ms (integer) - Processing time in milliseconds Communication Channels Slack - Internal team notifications SendGrid - Passenger email notifications Twilio - Critical SMS alerts Internal webhooks - System integrations How to Use Import the workflow into your n8n instance Configure aviation API credentials (AviationStack, FlightAware, or airline-specific APIs) Set up PostgreSQL database connection with required tables Configure Slack bot token for operations team notifications Set up SendGrid API key and email templates for passenger notifications Configure Twilio credentials for SMS alerts (critical notifications only) Test with sample flight data to verify all notification channels Adjust monitoring frequency and severity thresholds based on operational needs Monitor sync logs to ensure reliable data synchronization Requirements API Access Aviation data provider (AviationStack, FlightAware, etc.) SendGrid account for email delivery Twilio account for SMS notifications Slack workspace and bot token Database Setup PostgreSQL database with flight schedule tables Passenger and ticket management tables Audit logging tables for tracking changes Infrastructure n8n instance with appropriate node modules Reliable internet connection for API calls Proper credential management and security Customizing This Workflow Modify the Process Changes node to adjust change detection sensitivity, add custom business rules, or integrate additional data sources like weather or airport operational data. Customize notification templates in the email and SMS nodes to match your airline's branding and communication style. Adjust the Schedule Trigger frequency based on your operational requirements and API rate limits.

This no-code n8n workflow finds recent Instagram posts by hashtag, scrapes profile data, and uses an AI agent to evaluate whether each account is a good collaboration lead. The workflow filters based on the number of followers and the content of their bio, and outputs structured reasoning for outreach decisions. Perfect for creators, marketers, or business developers looking to automate influencer or community partnership prospecting—especially in niche ecosystems like n8n. ✅ Key Features 🔍 Hashtag Discovery**: Finds recent Instagram posts from a specified hashtag (e.g., #n8n) 👤 Account Scraping**: Retrieves profile details such as follower count and biography 🧠 AI Evaluation**: Uses OpenAI and LangChain to determine if the profile is a good fit for outreach 📦 Structured Output**: Returns a JSON object with "Yes/No" lead status and reasoning 🛠️ Manual Execution**: Run on demand using the manual trigger 🧰 What You'll Need | Tool / API | Purpose | Setup Steps | |-------------------------|------------------------------------------|-------------| | Apify Account | To access Instagram scraping actors | Create account → Generate API Token → Use in httpQueryAuth credential in n8n | | OpenAI API Key | To power the AI decision-making agent | Sign up at OpenAI → Create API key → Paste into OpenAI credential in n8n | | LangChain Plugin for n8n | AI Orchestration with System Message | Install LangChain nodes from Community Nodes (already installed in this workflow) | 🔧 Step-by-Step Setup 1️⃣ Manual Trigger Node**: When clicking ‘Execute workflow’ Use**: Allows you to run the workflow manually while testing. 2️⃣ Define Hashtag Node**: Create Search Term Value**: Sets "n8n" as the default Instagram hashtag to scan. You can edit this to any other hashtag you'd like. 3️⃣ Find Recent Posts Node**: Find Recent Posts API**: Apify Instagram Hashtag Scraper Auth Setup**: Go to your Apify Console Click “Create new token” In n8n, create a new HTTP Query Auth credential Set token in the token query param (e.g., ?token=yourTokenHere) Choose the credential in this node 4️⃣ Scrape Each Profile Node**: Scrape Accounts API**: Apify Instagram Profile Scraper Body**: JSON with usernames from the hashtag search Note**: Uses the same httpQueryAuth credential as the previous node. 5️⃣ Extract Fields Node**: Set bio and follower count What it does**: Extracts biography and followersCount from the profile JSON and stores them in clean variables for AI input. 6️⃣ AI Lead Scoring Node**: AI Agent Purpose**: Uses GPT-4o-mini to analyze the bio and follower count Prompt Details**: 7️⃣ AI Model Node**: OpenAI Chat Model Model**: gpt-4o-mini Credential**: Connect your OpenAI account via API Key. Go to OpenAI API Keys Copy your key and create a new OpenAI API credential in n8n. 8️⃣ Output Parser Node**: Structured Output Parser What it does**: Parses the response from the AI into structured JSON for further use (e.g., storing leads, sending to Airtable, etc.) 🧪 Sample Output { "lead status": "Yes", "Reasoning": "The user has 3.5k followers and their bio shows they build automations with n8n." } 📬 Need More Help? If you'd like assistance setting this up, customizing it to your niche, or expanding it to score and store leads automatically — I can help! 👤 Robert Breen Automation Consultant | AI Workflow Designer | n8n Expert 📧 robert@ynteractive.com 🌐 ynteractive.com 🔗 LinkedIn

Explorium Prospects Search Chatbot Template Download the following json file and import it to a new n8n workflow: mcp\_to\_prospects\_to\_csv.json Overview This n8n workflow creates a chatbot that understands natural language requests for finding business prospects and automatically: Interprets your query using AI (Claude Sonnet 3.7) Converts it to proper Explorium API filters Validates the API request structure Fetches prospect data from Explorium Exports results as a downloadable CSV file Perfect for sales teams, recruiters, and business development professionals who need to quickly find and export targeted prospect lists without learning complex API syntax. Key Features Natural Language Interface**: Simply describe who you're looking for in plain English Smart Query Translation**: AI converts your request to valid API parameters Built-in Validation**: Ensures API calls meet Explorium's requirements Error Recovery**: Automatically retries with corrections if validation fails Pagination Support**: Handles large result sets automatically CSV Export**: Clean, formatted output ready for CRM import Conversation Memory**: Maintains context for follow-up queries Example Queries The chatbot understands queries like: "Find marketing directors at SaaS companies in New York with 50-200 employees" "Get me CTOs from fintech startups in California" "Show me sales managers at healthcare companies with revenue over $10M" "Find engineers at Microsoft with 3-5 years experience" "Get customer service leads from e-commerce companies in Europe" Prerequisites Before setting up this workflow, ensure you have: n8n instance with chat interface enabled Anthropic API key for Claude Explorium API credentials (Bearer token) - Get explorium api key Basic understanding of n8n chat workflows Supported Filters The chatbot can search using these criteria: Company Filters Size**: 1-10, 11-50, 51-200, 201-500, 501-1000, 1001-5000, 5001-10000, 10001+ employees Revenue**: Ranges from $0-500K up to $10T+ Age**: 0-3, 3-6, 6-10, 10-20, 20+ years Location**: Countries, regions, cities Industry**: Google categories, NAICS codes, LinkedIn categories Name**: Specific company names Prospect Filters Job Level**: CXO, VP, Director, Manager, Senior, Entry, etc. Department**: Sales, Marketing, Engineering, Finance, HR, etc. Experience**: Total months and current role duration Location**: Country and region codes Contact Info**: Filter by email/phone availability Installation & Setup Step 1: Import the Workflow Copy the workflow JSON from the template In n8n: Workflows → Add Workflow → Import from File Paste the JSON and click Import Step 2: Configure Anthropic Credentials Click on the Anthropic Chat Model1 node Under Credentials, click Create New Add your Anthropic API key Name: "Anthropic API" Save credentials Step 3: Configure Explorium Credentials You'll need to set up Explorium credentials in two places: For MCP Client: Click on the MCP Client node Under Credentials, create new Header Auth Add your authentication header (usually Authorization: Bearer YOUR_TOKEN) Save credentials For API Calls: Click on the Prospects API Call node Use the same Header Auth credentials created above Verify the API endpoint is correct Step 4: Activate the Workflow Save the workflow Click the Active toggle to enable it The chat interface will now be available Step 5: Access the Chat Interface Click on the When chat message received node Copy the webhook URL Access this URL in your browser to start chatting How It Works Workflow Architecture Chat Trigger: Receives natural language queries from users Memory Buffer: Maintains conversation context AI Agent: Interprets queries and generates API parameters Validation: Checks API structure against Explorium requirements API Call: Fetches prospect data with pagination Data Processing: Formats results for CSV export File Conversion: Creates downloadable CSV file Processing Flow User Query → AI Interpretation → Validation → API Call → CSV Export ↑ ↓ └──── Error Correction Loop ←──────┘ Validation Rules The workflow validates: Filter keys are allowed by Explorium API Values match expected formats (e.g., valid country codes) Range filters have proper gte/lte values No duplicate values in arrays Required structure is maintained Usage Guide Basic Conversation Flow Start with your query: "Find me VPs of Sales at software companies in the US" Bot processes and responds: Generates API filters Validates the structure Fetches data Returns CSV download link Refine if needed: "Can you also include directors and filter for companies with 100+ employees?" Query Tips Be specific**: Include job titles, departments, company details Use standard terms**: "CTO" instead of "Chief Technology Officer" Specify locations**: Use country names or standard codes Include size/revenue**: Helps narrow results effectively Advanced Queries Combine multiple criteria: "Find engineering managers and senior engineers at B2B SaaS companies in New York and California with 50-500 employees and revenue over $5M who have been in their role for at least 1 year" Output Format The CSV file includes: Prospect ID Name (first, last, full) Location (country, region, city) LinkedIn profile Experience summary Skills and interests Company details Job information Business ID Troubleshooting Common Issues "Validation failed" errors Check that your query uses supported filter values Ensure location names are spelled correctly Verify company sizes/revenues match allowed ranges No results returned Broaden your search criteria Check if the company exists in Explorium's database Verify filter combinations aren't too restrictive Chat not responding Ensure workflow is activated Check all credentials are properly configured Verify webhook URL is accessible Large result sets timing out Try adding more specific filters Limit results by location or company size Use the size parameter (max 10,000) Error Messages The bot provides clear feedback: Invalid filters**: Shows which filters aren't supported Value errors**: Lists correct options for each field API failures**: Explains connection or authentication issues Performance Optimization Best Practices Start broad, then narrow: Begin with basic criteria and add filters Use business IDs: When targeting specific companies Limit by contact info: Add has_email: true for actionable leads Batch by location: Process regions separately for large searches API Limits Maximum 10,000 results per search Pagination handles up to 100 records per page Rate limits apply based on your Explorium subscription Customization Options Modify AI Behavior Edit the AI Agent system message to: Change response format Add custom filters Adjust interpretation logic Include additional instructions Extend Functionality Add nodes to: Send results via email Import directly to CRM Schedule recurring searches Create custom reports Integration Ideas Connect to Slack for team queries Add to CRM workflows Create lead scoring systems Build automated outreach campaigns Security Considerations API credentials are stored securely in n8n Chat sessions are isolated No prospect data is stored permanently CSV files are generated on-demand Support Resources For issues with: n8n platform**: Check n8n documentation Explorium API**: Contact Explorium support Anthropic/Claude**: Refer to Anthropic docs Workflow logic**: Review node configurations

🧾 What this workflow does This workflow takes a reference ad image and brand website, then uses GPT-4, LangChain, and Dumpling AI to generate 10 high-quality image variations for ad testing. These image variations are visually consistent but subtly different in background, mood, lighting, and tone — perfect for performance testing on platforms like Meta Ads or TikTok. 👤 Who is this for DTC marketers and brand designers testing ad creatives Creative teams automating visual experimentation Content agencies using AI for fast ad mockups Performance marketers running multivariate testing ⚙️ How to set up ✅ Requirements You’ll need the following tools set up in n8n: Google Drive (OAuth2 credential) Google Sheets (OAuth2 credential) OpenAI API (for GPT-4 or GPT-4o) Dumpling AI API (via HTTP header authentication) 🛠️ Steps to configure Google Sheet Setup Create a sheet with one column: Image URL Update the Sheet ID and tab name in the final Google Sheets node. Drive Setup Create a folder in Google Drive for storing the reference image. Replace the folderId in the “Upload Ad Image to Google Drive” node. Dumpling AI API Key Use n8n’s credential manager (HTTP Header Auth) — do not hardcode the key. OpenAI API Key Required for both image description and LangChain agent prompt generation. Form Inputs Required Brand Name Brand Website Ad Image (upload field) 🧠 How it works A user submits the brand name, website, and a reference ad image through a form. The image is uploaded to Google Drive. GPT-4o describes the image’s visual style (e.g., mood, lighting, composition). GPT-4 analyzes the brand’s website to define its visual aesthetic. A LangChain agent uses both analyses to create 10 tightly scoped variation prompts. Dumpling AI generates a new image for each prompt using its “FLUX.1-pro” model. Each new image’s link is logged into Google Sheets. 🛠️ How to customize 🧪 Change prompt logic to experiment with different variations (e.g., theme, season). 🎨 Switch image model in Dumpling AI to one that supports your desired style. 🔗 Log additional metadata (prompt, timestamp) to Google Sheets. 📤 Connect output images to Airtable, Notion, or a review tool like Figma. 🎯 Modify GPT system message to reflect a different tone or brand strategy. This workflow gives creative teams and marketers an instant, AI-powered ad image testing system — built on real brand visuals, not generic stock content.

Architecture Agent Overview The Architect Agent listens to Slack messages and generates full data architecture blueprints in response. Powered by Claude 3.5 (Anthropic) for reasoning and design, and Tavily for real-time web search, this agent creates production-ready data pipeline scaffolds on-demand — transforming natural language prompts into structured data engineering solutions. Capabilities Understands and interprets user requests from Slack Designs end-to-end data pipelines architectures using industry best practices. Outputs include High-level architecture diagrams Required Connections To operate correctly, the following integrations must be in place: Slack API Token with permission to read messages and post responses Tavily API Key for external search functionality Claude 3.5 API Access via Anthropic Detailed configuration instructions are provided in the workflow Setup time <15 minutes Example input: "Create a data pipeline orchestrated by Airflow, running on a Docker image. It should connect to a MySQL database, load in the data into a PostgreSQL DB (incremental load) and then transform the data into business-oriented tables also in the PostgreSQL database. Create an example setup with raw sales data." Customising this workflow Try saving outputs to Google Drive to store all your architecture blueprints

Yelp Business Scraper by URL via Bright Data API with Google Sheets Storage Overview This n8n workflow automates the process of scraping comprehensive business information from Yelp using individual business URLs. It integrates with Bright Data for professional web scraping and Google Sheets for centralized data storage, providing detailed business intelligence for market research, competitor analysis, and lead generation. Workflow Components 1. 📥 Form Trigger Type**: Form Trigger Purpose**: Initiates the workflow with user-submitted Yelp business URL Input Fields**: URL (Yelp business page URL) Function**: Captures target business URL to start the scraping process 2. 🔍 Trigger Bright Data Scrape Type**: HTTP Request (POST) Purpose**: Sends scraping request to Bright Data API for Yelp business data Endpoint**: https://api.brightdata.com/datasets/v3/trigger Parameters**: Dataset ID: gd_lgugwl0519h1p14rwk Include errors: true Limit multiple results: 5 Limit per input: 20 Function**: Initiates comprehensive business data extraction from Yelp 3. 📡 Monitor Snapshot Status Type**: HTTP Request (GET) Purpose**: Monitors the progress of the Yelp scraping job Endpoint**: https://api.brightdata.com/datasets/v3/progress/{snapshot_id} Function**: Checks if the business data scraping is complete 4. ⏳ Wait 30 Sec for Snapshot Type**: Wait Node Purpose**: Implements intelligent polling mechanism Duration**: 30 seconds Function**: Pauses workflow before rechecking scraping status to optimize API usage 5. 🔁 Retry Until Ready Type**: IF Condition Purpose**: Evaluates scraping completion status Condition**: status === "ready" Logic**: True: Proceeds to data retrieval False: Loops back to status monitoring with wait 6. 📥 Fetch Scraped Business Data Type**: HTTP Request (GET) Purpose**: Retrieves the final scraped business information Endpoint**: https://api.brightdata.com/datasets/v3/snapshot/{snapshot_id} Format**: JSON Function**: Downloads completed Yelp business data with comprehensive details 7. 📊 Store to Google Sheet Type**: Google Sheets Node Purpose**: Stores scraped business data for analysis and storage Operation**: Append rows Target**: "Yelp scraper data by URL" sheet Data Mapping**: Business Name, Overall Rating, Reviews Count Business URL, Images/Videos URLs Additional business metadata fields Workflow Flow Form Input → Trigger Scrape → Monitor Status → Wait 30s → Check Ready ↑ ↓ └─── Loop ─────┘ ↓ Fetch Data → Store to Sheet Configuration Requirements API Keys & Credentials Bright Data API Key**: Required for Yelp business scraping Google Sheets OAuth2**: For data storage and export access n8n Form Webhook**: For user input collection Setup Parameters Google Sheet ID**: Target spreadsheet identifier Dataset ID**: gd_lgugwl0519h1p14rwk (Yelp business scraper) Form Webhook ID**: User input form identifier Google Sheets Credential ID**: OAuth2 authentication Key Features Comprehensive Business Data Extraction Complete business profile information Customer ratings and review counts Contact details and business hours Photo and video content URLs Location and category information Intelligent Status Monitoring Real-time scraping progress tracking Automatic retry mechanisms with 30-second intervals Status validation before data retrieval Error handling and timeout management Centralized Data Storage Automatic Google Sheets export Organized business data format Historical scraping records Easy sharing and collaboration URL-Based Processing Direct Yelp business URL input Single business deep-dive analysis Flexible input through web form Real-time workflow triggering Use Cases Market Research Competitor business analysis Local market intelligence gathering Industry benchmark establishment Service offering comparison Lead Generation Business contact information extraction Potential client identification Market opportunity assessment Sales prospect development Business Intelligence Customer sentiment analysis through ratings Competitor performance monitoring Market positioning research Brand reputation tracking Location Analysis Geographic business distribution Local competition assessment Market saturation evaluation Expansion opportunity identification Data Output Fields | Field | Description | Example | |-------|-------------|---------| | Name | Business name | "Joe's Pizza Restaurant" | | Overall Rating | Average customer rating | "4.5" | | Reviews Count | Total number of reviews | "247" | | URL | Original Yelp business URL | "https://www.yelp.com/biz/joes-pizza..." | | Images/Videos URLs | Media content links | "https://s3-media1.fl.yelpcdn.com/..." | Technical Notes Polling Interval**: 30-second status checks for optimal API usage Result Limiting**: Maximum 20 businesses per input, 5 multiple results Data Format**: JSON with structured field mapping Error Handling**: Comprehensive error tracking in all API requests Retry Logic**: Automatic status rechecking until completion Form Input**: Single URL field with validation Storage Format**: Structured Google Sheets with predefined columns Setup Instructions Step 1: Import Workflow Copy the JSON workflow configuration Import into n8n: Workflows → Import from JSON Paste configuration and save Step 2: Configure Bright Data Set up credentials: Navigate to Credentials → Add Bright Data API Enter your Bright Data API key Test connection Update API key references: Replace BRIGHT_DATA_API_KEY in all HTTP request nodes Verify dataset access for gd_lgugwl0519h1p14rwk Step 3: Configure Google Sheets Create target spreadsheet: Create new Google Sheet named "Yelp Business Data" or similar Copy the Sheet ID from URL Set up OAuth2 credentials: Add Google Sheets OAuth2 credential in n8n Complete authentication process Update workflow references: Replace YOUR_GOOGLE_SHEET_ID with actual Sheet ID Update YOUR_GOOGLE_SHEETS_CREDENTIAL_ID with credential reference Step 4: Test and Activate Test with sample URL: Use a known Yelp business URL Monitor execution progress Verify data appears in Google Sheet Activate workflow: Toggle workflow to "Active" Share form URL with users Sample Business Data The workflow captures comprehensive business information including: Basic Information**: Name, category, location Performance Metrics**: Ratings, review counts, popularity Contact Details**: Phone, website, address Visual Content**: Photos, videos, gallery URLs Operational Data**: Hours, services, amenities Customer Feedback**: Review summaries, sentiment indicators Advanced Configuration Batch Processing Modify the input to accept multiple URLs: [ {"url": "https://www.yelp.com/biz/business-1"}, {"url": "https://www.yelp.com/biz/business-2"}, {"url": "https://www.yelp.com/biz/business-3"} ] Enhanced Data Fields Add more extraction fields by updating the dataset configuration: Business hours and schedule Menu items and pricing Customer photos and reviews Special offers and promotions Notification Integration Add alert mechanisms: Email notifications for completed scrapes Slack messages for team updates Webhook triggers for external systems Error Handling Common Issues Invalid URL**: Ensure URL is a valid Yelp business page Rate Limiting**: Bright Data API usage limits exceeded Authentication**: Google Sheets or Bright Data credential issues Data Format**: Unexpected response structure from Yelp Troubleshooting Steps Verify URLs: Ensure Yelp business URLs are correctly formatted Check Credentials: Validate all API keys and OAuth tokens Monitor Logs: Review n8n execution logs for detailed errors Test Connectivity: Verify network access to all external services Performance Specifications Processing Time**: 2-5 minutes per business URL Data Accuracy**: 95%+ for publicly available business information Success Rate**: 90%+ for valid Yelp business URLs Concurrent Processing**: Depends on Bright Data plan limits Storage Capacity**: Unlimited (Google Sheets based) **For any questions or support, please contact: info@incrementors.com or fill out this form: https://www.incrementors.com/contact-us/

Effortless Task Management: Create Todoist Tasks Directly from Telegram with AI This n8n workflow empowers you to seamlessly manage your tasks by creating Todoist entries directly from Telegram, using the power of AI. Simply send a voice or text message to your Telegram bot, and this workflow will transform it into actionable tasks in your Todoist account. Who is this for? Busy professionals** who need a quick and easy way to capture tasks on the go. Students** looking to streamline their assignments and project management. Anyone** who wants to leverage AI for effortless task management. What Problem Does it Solve? This workflow eliminates the need to manually enter tasks into Todoist. It automates the process of capturing, organizing, and prioritizing tasks, saving you time and effort. What are the Benefits? Seamless Integration:** Connect your Telegram and Todoist accounts for a frictionless workflow. AI-Powered Task Breakdown:** LLM AI intelligently analyzes your messages and breaks them down into manageable sub-tasks. Voice-to-Task:** Create tasks with voice messages for hands-free convenience. Increased Productivity:** Capture and organize tasks quickly, keeping you focused and productive. Accessibility:** Access your tasks from anywhere with Todoist's mobile app and Google extension. How it Works Send a message: Send a voice or text message describing your task to your Telegram bot. AI analysis: The workflow uses an LLM (OpenAI Chat Model) to analyze your message and break it down into sub-tasks. Task creation: The workflow creates tasks in your Todoist account based on the AI's analysis. Notification: You receive a Telegram notification with a link to your newly created tasks in Todoist. Nodes in the Workflow Telegram Trigger:** Listens for incoming messages on Telegram. Switch:** Routes messages based on their type (voice or text). Telegram:** Fetches voice messages from Telegram. OpenAI:** Transcribes voice messages to text using OpenAI's Whisper API. Edit Fields:** Prepares the text for the LLM. Basic LLM Chain:** Analyzes messages and generates sub-tasks using OpenAI's GPT model. Structured Output Parser:** Extracts sub-tasks from the LLM's response. Todoist:** Creates tasks in your Todoist account. Telegram:** Sends a notification with a link to your Todoist tasks. Requirements Active n8n instance. Telegram account with a bot. Todoist account. OpenAI API key. Setup Information Import the workflow JSON into your n8n instance. Configure the Telegram Trigger node with your bot token. Set up the OpenAI credentials with your API key. Connect your Todoist account in the Todoist node. Customize the LLM prompt (optional) to fine-tune task creation. Additional Tips Explore Todoist's features to further organize and manage your tasks. Experiment with different LLM prompts to optimize task breakdown. Use n8n's features to automate other aspects of your workflow. This workflow combines the convenience of Telegram with the power of AI and Todoist to provide a seamless task management experience. Start managing your tasks effortlessly today!

🗂️ Bulk File Upload to Google Drive with Folder Management How it works User submits files and target folder name via form Workflow checks if folder exists in Drive Creates folder if needed or uses existing one Processes and uploads all files maintaining structure Set up steps (Est. 10-15 mins) Set up Google Drive credentials in n8n Replace parent folder ID in search query with your Drive folder ID Configure form node with: Multiple file upload field Folder name text field Test workflow with sample files 💡 Detailed configuration steps and patterns are documented in sticky notes within the workflow. Perfect for: Bulk file organization Automated Drive folder management File upload automation Maintaining consistent file structures

What is it This workflow aims to build a simple bot that will send a message to a telegram channel every time there is a new saved item to the Reader. This workflow can be easily modify to support other way of sending the notification, thanks to existing n8n nodes. Warning: This is only for folks who already have access to the Reader, it won't work if you don't Also, this workflow use a file to store the last update time in order to not sync everything everytime. Setup The config node : It contains the telegram channel id It also contains the file used as storage To get the header auth, you have to : Go to the reader Open the devtools, Option + ⌘ + J (on macOS), or Shift + CTRL + J (on Windows/Linux) Go to network and find a profile_details/ request, click on it Go to Request Headers Copy the value for "Cookie" In n8n, set the name of the Header auth account to Cookie and the value with the one you copied before