Workflow Templates

🧠 Problem This Solves Managing credit card expenses can be tricky, especially when you want to stay transparent and keep your spouse in the loop. Most banks don't offer real-time notification sharing with family members, and manually updating expenses takes time and effort. This n8n workflow automates the entire process: tracking your HDFC credit card usage, logging it in Google Sheets, and sending an instant Telegram notification to your spouse. 👥 Who This Template Is For Couples who want shared visibility of credit card spending Individuals looking for automated personal finance tracking Anyone using HDFC Credit Card with email alerts enabled n8n users who want to integrate Gmail, Google Sheets, and Telegram ⚙️ Workflow Breakdown Here’s how the automation works: Gmail Trigger – Monitors your Gmail inbox for credit card transaction alerts from HDFC Bank. Email Parser – Extracts transaction details like amount, merchant name, date, and card type. Google Sheets Node – Logs the parsed transaction data into a structured Google Sheet for record-keeping. Telegram Node – Sends a message to your wife’s Telegram account with transaction details for instant notification. 🛾 Step-by-Step Setup Instructions Prerequisites An HDFC Credit Card with email alerts enabled A Gmail account connected to n8n A Google Sheet created with columns like Date, Amount, Merchant, Card, etc. A Telegram Bot and your wife’s Telegram Chat ID Set up Gmail Trigger Use the Gmail Trigger Node to monitor incoming emails from alerts@hdfcbank.net or similar. Filter emails with subject line containing keywords like Credit Card Transaction Alert. Extract Email Content Use the HTML Extract or Regex node to parse out transaction amount, merchant name, date, and card number from the email body. Log to Google Sheets Connect your Google Sheets account in n8n Use the Append Row node to add each transaction as a new row in your finance sheet. Send Telegram Message Set up a Telegram Bot and get the Chat ID of your wife’s Telegram account Format a message like: "💳 HDFC Transaction Alert: ₹5,000 at Amazon on 17 May via XXXX1234" Send it via the Telegram node 🛠️ Customization Tips 💡 Add Spending Limits: Add a condition node to alert only if the transaction exceeds a certain amount. 🧾 Category Mapping: Use additional logic to classify expenses (e.g., Shopping, Dining) based on keywords. 📊 Weekly Summary: Create another workflow that sends a weekly Telegram summary using data from Google Sheets. 🔐 Security Tip: Mask part of the card number before sending the Telegram message for added security.

Jura Coffee Counter: Webhook API & Google Sheets Logger ☕️ Track how many coffees your Jura E8 espresso machine makes — fully automated via webhook and Google Sheets. This workflow exposes a custom API endpoint that can be called by smart devices, such as an ESP8266 or ESP32 reading data from a Jura E8 coffee machine via Bluetooth Low Energy (BLE). The incoming data (including total coffee count) is timestamped and appended to a Google Sheet, making it easy to visualize or analyze your machine usage. ☕ Originally built for a Jura E8, based on AlexxIT/Jura reverse-engineering project. > 📝 This workflow uses Google Sheets as a logging backend. You can easily switch it to Airtable, Notion, or a database of your choice. Live example available at: https://halfbitstudio.com/o-nas/ > 🖥️ In our setup, this workflow is used to provide real-time coffee consumption stats displayed directly on our website. > 🔌 Some Jura machines require an accessory Bluetooth transmitter to enable connectivity. Communication is based on the Bluetooth Low Energy (BLE) protocol. Use Case Tracking usage of a Jura coffee machine Logging IoT sensor data into Google Sheets Creating dashboards for daily consumption Smart office setups with coffee stats! Features ☁️ Two Webhook endpoints: POST /{{WEBHOOK_POST_PATH}} — receives JSON from ESP (coffee machine reader) GET /{{WEBHOOK_GET_PATH}} — returns latest records as JSON 📅 Timestamping via Date & Time node 🔹 Coffee counter extraction from incoming JSON 🧾 Appends structured rows to Google Sheets 📤 Webhook response for external status or dashboards Setup Instructions Jura Coffee Machine Integration (Hardware) Use an ESP device (e.g. ESP8266 or ESP32) to connect to the Jura E8 via Bluetooth Low Energy (BLE). Send POST requests with JSON payload: { "total_coffees": 123 } Reverse-engineered protocol reference: AlexxIT/Jura Google Sheets Configuration Create a new Google Sheet with column headers like: date | time | coffee counter Connect your Google account in n8n and authorize access to this sheet. Replace the documentId and sheetName fields in the Google Sheets nodes: Use full URL to your spreadsheet Use the actual sheet name (e.g. Sheet1) Environment Variables & Placeholders | Placeholder | Description | | ------------------------ | ----------------------------------------------- | | {{WEBHOOK_POST_PATH}} | Endpoint to receive coffee counter data | | {{WEBHOOK_GET_PATH}} | Endpoint to return latest data (for dashboards) | | {{SHEET_ID}} | Google Spreadsheet ID | | {{GOOGLE_CREDENTIALS}} | OAuth2 credentials for Google Sheets | | {{DATA_COLUMNS}} | Column names in the target sheet | Testing the Workflow Send test request: Use Postman or ESP to send a POST request to /{{WEBHOOK_POST_PATH}} Body should include total_coffees value Check Google Sheet: Open your sheet and verify that a new row was appended Test GET endpoint: Access the second webhook URL (e.g. /{{WEBHOOK_GET_PATH}}) in browser or fetch via API Optional: Use Respond to Webhook output in a dashboard or frontend Customization Tips Sheet format**: Add more columns if you want to track additional data (e.g. machine temperature, errors) Output format**: Replace Google Sheets with any other storage (e.g. MySQL, Notion) Auth layer**: Add basic auth or token verification if needed for public exposure Notifications**: Send alerts to Discord/Slack when reaching thresholds (e.g. 200 coffees brewed) Tags: google-sheets, iot, webhook, jura, coffee, api, automation

🧾 What this workflow does This workflow turns YouTube video links into ready-to-edit newsletter drafts using Dumpling AI and GPT-4o. It reads new video URLs from a Google Sheet, extracts their transcripts, summarizes them into email-friendly content, and logs the finished draft back into the same sheet. An email notification is also sent to alert the user once each draft is created. 👤 Who is this for Newsletter writers or marketers repurposing video content YouTube creators building email follow-ups from videos Agencies or VAs batching social → email content Automation users streamlining content workflows ⚙️ How to set up ✅ Requirements Google Sheet** with the following columns: link — YouTube video URL blog post — for saving the generated newsletter draft Active accounts for: Dumpling AI (API for YouTube transcripts) OpenAI GPT-4 or GPT-4o Google Sheets Gmail (OAuth2 credential) 🔧 Setup steps Connect all credentials using n8n's Credential Manager: Google Sheets (OAuth2) Dumpling AI (via HTTP Header Auth) OpenAI Gmail Update the sheet ID and tab name in both Google Sheets nodes. Customize the GPT-4o prompt (optional): Located in the “GPT-4o: Write Newsletter Draft from Transcript” node You can edit tone, structure, and audience targeting in the system message Verify email recipient in the Gmail node and update if needed. 🧠 How it works The workflow is triggered manually or on schedule. It pulls YouTube links without drafts from the sheet. Each video’s transcript is fetched using Dumpling AI. GPT-4o summarizes the transcript into a clean, friendly newsletter format. The draft is written back to the same row in Google Sheets. An email is sent to notify the user that the draft is ready. 🛠️ Customization ideas Send finished drafts to Notion or Airtable instead of Sheets Generate social media posts from the same transcript Add automatic review steps using GPT scoring or editing Trigger this on new form submissions or YouTube uploads instead This is a fast, AI-powered way to turn long-form video content into clean, polished newsletters — ready to share or schedule with minimal editing.

This n8n workflow demonstrates how to automate customer interactions and appointment management via WhatsApp Business bot. After submitting a Google Form, the user receives a notification via WhatsApp. These notifications are sent via a template message. In case user sends a message to the bot, the text and user data is stored in Google Sheets. To reply back to the user, fill in the ReplyText column and change the Status to 'Ready'. In a few seconds n8n will fetch the unsent replies and deliver them one by one via WhatsApp Business node. Customize this workflow to fit your specific needs, connect different online services and enhance your customer communication! 🎉 Setup Instructions To get this workflow up and running, you'll need to: 👇 Create a WhatsApp template message on the Meta Business portal. Obtain an Access Token and WhatsApp Business Account ID from the Meta Developers Portal. This is needed for the WhatsApp Business Node to send messages. Set up a WhatsApp Trigger node with App ID and App Secret from the Meta Developers Portal. Right after that copy the WhatsApp Trigger URL and add it as a Callback URL in the Meta Developers Portal. This trigger is needed to receive incoming messages and their status updates. Connect your Google Sheets account for data storage and management. Check out the documentation page. ⚠️ Important Notes WhatsApp allows automatic custom text messages only within 24 hours of the last user message. Outside with time frame only approved template messages can be sent. The workflow uses a Google Sheet to manage form submissions, incoming messages and prepare responses. You can replace these nodes and connect the WhatsApp bot with other systems.

This powerful n8n automation sends you daily weather updates directly to your Telegram chat using live data from OpenWeatherMap. It supports automatic daily updates and manual lookups via form input. ✅ Prerequisites Before you begin, make sure you have: A working n8n instance (v1.0 or later recommended). An account with OpenWeatherMap (free plan is sufficient). A Telegram Bot created via @BotFather. Your Telegram user ID or chat ID. 🔐 API & Bot Setup 🧩 OpenWeatherMap API Go to https://openweathermap.org/api Sign up and verify your account. Navigate to API Keys in your account dashboard. Copy your API key (used later in the HTTP Request node). 🤖 Telegram Bot Open @BotFather in Telegram. Run /newbot and follow the prompts: Choose a name and username for your bot. You’ll get a bot token (copy this). Start a chat with your new bot to activate it. To get your Telegram User ID, use @userinfobot or an n8n Telegram Trigger node. 🔄 Trigger Options ⏰ Schedule Trigger (Automatic) Runs daily at 8:00 AM IST. Ideal for consistent, passive updates. 📝 Form Trigger (Manual) Input 🌆 City and 🌍 Country manually. Instantly receive weather info in Telegram. 🧠 How the Flow Works Trigger Activated (Scheduled or Form) City & Country fetched (default or from form) HTTP Request sent to OpenWeatherMap with API key Weather Data Parsed & Formatted: 📅 Current Date 📍 City & Country 🌤️ Weather Description 🌡️ Temperature (°C) 💧 Humidity (%) 🌬️ Wind Speed (m/s) 🔼 Atmospheric Pressure 🌅 Sunrise Time (IST) 🌇 Sunset Time (IST) Message Sent to Telegram 🧰 Nodes Used Schedule Trigger** – Runs every day at 8:00 AM IST Form Trigger** – Accepts user input Set Node** – Default city/country values and date formatting HTTP Request** – Calls OpenWeatherMap API Function Node** – Converts timestamps to IST Telegram Node** – Sends formatted weather message 📦 Example Telegram Output 📅 Wednesday, 10 July 2025 🌤 Weather in Mumbai, IN: Condition: Clear sky Temperature: 30°C 💧 Humidity: 70% 🌬 Wind Speed: 3 m/s 🔼 Pressure: 1013 hPa 🌅 Sunrise: 5:57:12 AM 🌇 Sunset: 6:53:45 PM 🛠️ Customization Tips 🏙️ Change Default City/Country Locate the Set Node (used before the API call). Replace "Mumbai" and "IN" with your preferred location. Or connect the Form Trigger input to allow dynamic values. 🕗 Change Schedule Time Open the Schedule Trigger node. Adjust to your preferred time zone and daily timing (e.g., 7 AM IST). 🧪 Add Extra Data OpenWeatherMap returns more fields like visibility, UV index, etc. You can include these in your Telegram message via the Function Node and Set Node.

Overview An intelligent automation workflow that monitors your Gmail inbox and sends AI-powered summaries of important emails directly to your Telegram chat. Perfect for staying updated on critical communications without constantly checking your email. 🌟 Key Features Real-time Email Monitoring**: Checks Gmail every minute for new emails Smart Content Filtering**: Only processes emails containing important keywords AI-Powered Summarization**: Uses GPT-4o-mini to create concise, human-readable summaries Instant Telegram Notifications**: Delivers summaries directly to your preferred Telegram chat Customizable Keywords**: Easily modify filters to match your specific needs 🔧 How It Works Workflow Steps: Email Trigger: Continuously monitors your Gmail inbox for new messages Smart Filter: Analyzes email subject and body for important keywords (sales, jobs, etc.) AI Processing: Sends relevant emails to OpenAI for intelligent summarization Telegram Delivery: Sends formatted summary to your Telegram chat Sample Output: 📦 Your Flipkart order "Bluetooth Speaker" was delivered today. Enjoy! 💰 Invoice from AWS for $23.50 is due by July 20. Check billing portal. ✅ HR shared your July payslip. No action needed unless there's an error. 🛠 Setup Requirements Gmail account with OAuth2 credentials OpenAI API key Telegram bot token and chat ID N8N instance (cloud or self-hosted) 📋 Use Cases Business Alerts**: Payment due notices, invoice reminders E-commerce**: Order confirmations, delivery updates HR Communications**: Payslips, policy updates, announcements Security**: Login alerts, security notifications Job Hunting**: Application responses, interview invitations ⚙️ Customization Options Keyword Filters**: Add/remove keywords in the filter node (invoice, payment, security, delivery, etc.) AI Prompt**: Modify the summarization style and format Polling Frequency**: Adjust email checking interval Multiple Chats**: Send to different Telegram chats based on email type 🔒 Privacy & Security Processes emails locally through n8n No email content stored permanently Uses secure OAuth2 authentication Respects Gmail API rate limits 📊 Performance Lightweight and efficient Minimal resource usage Fast AI processing with GPT-4o-mini Reliable Telegram delivery 💡 Pro Tips Start with broad keywords and refine based on results Use multiple condition branches for different email types Set up different Telegram chats for work vs personal emails Monitor your OpenAI usage to avoid unexpected costs

This workflow takes two inputs, YouTube video URL (required) and a description of what information to extract from the video. If the description/"what you want" field is left empty, the default prompt will generate a detailed summary and description of the video's contents. However, you can ask for something more specific using this field/input. ++ Don't forget to make the workflow Active and use the production URL from the form node. Benefits Instant Summary Generation - Convert hours of watching YouTube videos to familiar, structured paragraphs and sentences in less than a minute Live Integration - Generate a summary or extract information on the contents of a YouTube video whenever, wherever Virtually Complete Automation - All that needs to be done is to add the video URL and describe what you want to know from the video Presentation - You can ask for a specific structure or tone to better help you understand or study the contents of the video How It Works Smart Form Interface: Simple N8N form captures video URL and description of what's to be extracted Designed for rapid and repeated completion anywhere and anytime Description Check: Uses JavaScript to determine if the description was filled in or left empty If the description field was left empty, the default prompt is, "Please be as descriptive as possible about the contents being spoken of in this video after giving a detailed summary." If the description field is filled, then the filled input will be used to describe what information to extract from the video HTTP Request: We're using Gemini API, specifically the video understanding endpoint We make a post HTTP request passing the video URL and the description of what information to extract Setup Instructions: HTTP Request Setup: Sign up for a Google Cloud account, join the Developer Program and get your Gemini API key Get curl for Gemini Video Understanding API The video understanding relies on the inputs from the form, code and HTTP request node, so correct mapping is essential for the workflow to function correctly. Feel free to reach out for additional help or clarification at my Gmail: terflix45@gmail.com, and I'll get back to you as soon as I can. Setup Steps: Code Node Setup: The code node is used as a filter to ensure a description prompt is always passed on. Use the JavaScript code below for that effect: // Loop over input items and add a new field called 'myNewField' to the JSON of each one for (const item of $input.all()) { item.json.myNewField = 1; if ($input.first().json['What u want?'].trim() == "") { $input.first().json['What do you want?'] = "Please be as descriptive as possible about the contents being spoken of this video after giving a detailed summary"; } } return $input.all(); // End of Code HTTP Request: To use Gemini Video Understanding, you'll need your Gemini API key Go to https://ai.google.dev/gemini-api/docs/video-understanding#youtube. This link will take you directly to the snippet. Just select REST programming language, copy that curl command, then paste it into the HTTP Request node Replace "Please summarize the video in 3 sentences." with the code node's output, which should either be the default description or the one entered by the user (second output field variable) Replace "https://www.youtube.com/watch?v=9hE5-98ZeCg" with the n8n form node's first output field, which should be the YouTube video URL variable Replace $GEMINI_API_KEY with your API key Redirect: Use n8n form node, page type "Final Ending" to redirect user to the initial n8n form for another analysis or preferred destination

This workflow syncs Shopify customers to your HubSpot account as contacts. Whenever somebody makes a purchase on Shopify, it automatically adds them as a new customer to your Hubspot account if the customer doesn’t exist yet. Also, this workflow creates or updates contacts from new paid orders on Shopify by adding the amount and order close date of the deal. Prerequisites Shopify account and Shopify credentials HubSpot account and HubSpot credentials How it works Shopify trigger starts the workflow whenever an order is updated. HubSpot node creates or updates the contact who made the order update. Set node sorts and passes only the userid. Merge node merges data of both inputs, the order and the customer. Hubspot node looks up if the order already exists. If node splits the workflow conditionally, based on data received. If the order is new, the new deal is created in the Hubspot node.

Description: This n8n workflow automates a Discord bot to fetch messages from a specified channel and send AI-generated responses in threads. It ensures smooth message processing and interaction, making it ideal for managing community discussions, customer support, or AI-based engagement. This workflow leverages Redis for memory persistence, ensuring that conversation history is maintained even if the workflow restarts, providing a seamless user experience. How It Works The bot listens for new messages in a specified Discord channel. It sends the messages to an AI model for response generation. The AI-generated reply is posted as a thread under the original message. The bot runs on an Ubuntu server and is managed using PM2 for uptime stability. The Discord bot (Python script) acts as the bridge, capturing messages from Discord and sending them to the n8n webhook. The n8n workflow then processes these messages, interacts with the AI model, and sends the AI's response back to Discord via the bot. Prerequisites to host Bot Sign up on Pella, which is a managed hosting service for Discord Bots. (Easy Setup) A Redis instance for memory persistence. Redis is an in-memory data structure store, used here to store and retrieve conversation history, ensuring that the AI can maintain context across multiple interactions. This is crucial for coherent and continuous conversations. Set Up Steps 1️⃣ Create a Discord Bot Go to the Discord Developer Portal. Click “New Application”, enter a name, and create it. Navigate to Bot > Reset Token, then copy the Bot Token. Enable Privileged Gateway Intents (Presence, Server Members, Message Content). Under OAuth2 > URL Generator, select bot scope and required permissions. Copy the generated URL, open it in a browser, select your server, and click Authorize. 2️⃣ Deploy the Bot on Pella Create a new folder discord-bot and navigate into it: Create and configure an .env file to store your bot token: Copy the code to .env: (You can copy the webhook URL from the n8n workflow) TOKEN=your-bot-token-here WEBHOOK_URL=https://your-domain.tld/webhook/getmessage Create file main.py copy the below code and save it: Copy this Bot script to main.py: import discord import requests import json import os from dotenv import load_dotenv Load environment variables from .env file load_dotenv() TOKEN = os.getenv("TOKEN") WEBHOOK_URL = os.getenv("WEBHOOK_URL") Bot Configuration LISTEN_CHANNELS = ["YOUR_CHANNEL_ID_1", "YOUR_CHANNEL_ID_2"] # Replace with your target channel IDs Intents setup intents = discord.Intents.default() intents.messages = True # Enable message event intents.guilds = True intents.message_content = True # Required to read messages client = discord.Client(intents=intents) @client.event async def on_ready(): print(f'Logged in as {client.user}') @client.event async def on_message(message): if message.author == client.user: return # Ignore bot's own messages if str(message.channel.id) in LISTEN_CHANNELS: try: fetched_message = await message.channel.fetch_message(message.id) # Ensure correct fetching payload = { "channel_id": str(fetched_message.channel.id), # Ensure it's string "chat_message": fetched_message.content, "timestamp": str(fetched_message.created_at), # Ensure proper formatting "message_id": str(fetched_message.id), # Ensure ID is a string "user_id": str(fetched_message.author.id) # Ensure user ID is also string } headers = {'Content-Type': 'application/json'} response = requests.post(WEBHOOK_URL, data=json.dumps(payload), headers=headers) if response.status_code == 200: print(f"Message sent successfully: {payload}") else: print(f"Failed to send message: {response.status_code}, Response: {response.text}") except Exception as e: print(f"Error fetching message: {e}") client.run(TOKEN) Create requirements.txt and copy: discord python-dotenv 3️⃣ Follow the video to set up the bot which will run 24/7 Tutorial - https://www.youtube.com/watch?v=rNnK3XlUtYU Note: Free Plan will expire after 24 hours, so please opt for the Paid Plan in Pella to keep your bot running. 4️⃣ n8n Workflow Configuration The n8n workflow consists of the following nodes: Get Discord Messages (Webhook):** This node acts as the entry point for messages from the Discord bot. It receives the channel_id, chat_message, timestamp, message_id, and user_id from Discord when a new message is posted in the configured channel. Its webhook path is /getmessage and it expects a POST request. Chat Agent (Langchain Agent):** This node processes the incoming Discord message (chat_message). It is configured as a conversational agent, integrating the language model and memory to generate an appropriate response. It also has a prompt to keep the reply concise, under 1800 characters. OpenAI -4o-mini (Langchain Language Model):** This node connects to the OpenAI API and uses the gpt-4o-mini-2024-07-18 model for generating AI responses. It is the core AI component of the workflow. Message History (Redis Chat Memory):** This node manages the conversation history using Redis. It stores and retrieves chat messages, ensuring the Chat Agent maintains context for each user based on their user_id. This is critical for coherent multi-turn conversations. Calculator (Langchain Tool):** This node provides a calculator tool that the AI agent can utilize if a mathematical calculation is required within the conversation. This expands the capabilities of the AI beyond just text generation. Response fromAI (Discord):** This node sends the AI-generated response back to the Discord channel. It uses the Discord Bot API credentials and replies in a thread under the original message (message_id) in the specified channel_id. Sticky Note1, Sticky Note2, Sticky Note3, Sticky Note4, Sticky Note5, Sticky Note:** These are informational nodes within the workflow providing instructions, code snippets for the Discord bot, and setup guidance for the user. These notes guide the user on setting up the .env file, requirements.txt, the Python bot code, and general recommendations for channel configuration and adding tools. 5️⃣ Setting up Redis Choose a Redis Hosting Provider: You can use a cloud provider like Redis Labs, Aiven, or set up your own Redis instance on a VPS. Obtain Redis Connection Details: Once your Redis instance is set up, you will need the host, port, and password (if applicable). Configure n8n Redis Nodes: In your n8n workflow, configure the "Message History" node with your Redis connection details. Ensure the Redis credential ✅ redis-for-n8n is properly set up with your Redis instance details (host, port, password). 6️⃣ Customizing the Template AI Model:** You can easily swap out the "OpenAI -4o-mini" node with any other AI service supported by n8n (e.g., Cohere, Hugging Face) to use a different language model. Ensure the new language model node is connected to the ai_languageModel input of the "Chat Agent" node. Agent Prompt:** Modify the text parameter in the "Chat Agent" node to change the AI's persona, provide specific instructions, or adjust the response length. Additional Tools:** The "Calculator" node is an example of an AI tool. You can add more Langchain tool nodes (e.g., search, data lookup) and connect them to the ai_tool input of the "Chat Agent" node to extend the AI's capabilities. Refer to the "Sticky Note5" in the workflow for a reminder. Channel Filtering:** Adjust the LISTEN_CHANNELS list in the main.py file of your Discord bot to include or exclude specific Discord channel IDs where the bot should listen for messages. Thread Management:** The "Response fromAI" node can be modified to change how threads are created or managed, or to send responses directly to the channel instead of a thread. The current setup links the response to the original message ID (message_reference). 7️⃣ Testing Instructions Start the Discord Bot: Ensure your main.py script is running on Pella. Activate the n8n Workflow: Make sure your n8n workflow is active and listening for webhooks. Send a Message in Discord: Go to one of the LISTEN_CHANNELS in your Discord server and send a message. Verify Response: The bot should capture the message, send it to n8n, receive an AI-generated response, and post it as a thread under your original message. Check Redis: Verify that the conversation history is being stored and updated correctly in your Redis instance. Look for keys related to user IDs. ✅ Now your bot is running in the background! 🚀

🌤️ Daily Weather Forecast Bot A comprehensive n8n workflow that fetches detailed weather forecasts from OpenWeatherMap and sends beautifully formatted daily summaries to Telegram. 📋 Features 📊 Daily Overview**: Complete temperature range, rainfall totals, and wind conditions ⏰ Hourly Forecast**: Weather predictions at key times (9AM, 12PM, 3PM, 6PM, 9PM) 🌡️ Smart Emojis**: Context-aware weather icons and temperature indicators 💡 Smart Recommendations**: Contextual advice (umbrella alerts, clothing suggestions, sun protection) 🌪️ Enhanced Details**: Feels-like temperature, humidity levels, wind speed, UV warnings 📱 Rich Formatting**: HTML-formatted messages with emojis for excellent readability 🕐 Timezone-Aware**: Proper handling of Luxembourg timezone (CET/CEST) 🛠️ What This Workflow Does Triggers daily at 7:50 AM to send morning weather updates Fetches 5-day forecast from OpenWeatherMap API with 3-hour intervals Processes and analyzes weather data with smart algorithms Formats comprehensive report with HTML styling and emojis Sends to Telegram with professional formatting and actionable insights ⚙️ Setup Instructions 1. OpenWeatherMap API Sign up at OpenWeatherMap Get your free API key (1000 calls/day included) Replace API_KEY in the HTTP Request node URL 2. Telegram Bot Message @BotFather on Telegram Send /newbot command and follow instructions Copy the bot token to n8n credentials Get your chat ID by messaging the bot, then visiting: https://api.telegram.org/bot<YOUR_BOT_TOKEN>/getUpdates Update the chatId parameter in the Telegram node 3. Location Configuration Default location: Strassen, Luxembourg To change: modify q=Strassen in the HTTP Request URL Format: q=CityName,CountryCode (e.g., q=Paris,FR) 🎯 Technical Details API Source**: OpenWeatherMap 5-day forecast Schedule**: Daily at 7:50 AM (configurable) Format**: HTML with rich emoji formatting Error Handling**: 3 retry attempts with 5-second delays Rate Limits**: Uses only 1 API call per day Timezone**: Europe/Luxembourg (handles CET/CEST automatically) 📊 Weather Data Analyzed Temperature ranges and "feels like" temperatures Precipitation forecasts and accumulation Wind speed and conditions Humidity levels and comfort indicators Cloud coverage and visibility UV index recommendations Time-specific weather patterns 💡 Smart Features Conditional Recommendations**: Only shows relevant advice Night/Day Awareness**: Different emojis for time of day Temperature Context**: Color-coded temperature indicators Weather Severity**: Appropriate icons for weather intensity Humidity Comfort**: Comfort level indicators Wind Analysis**: Descriptive wind condition text 🔧 Customization Options Schedule**: Modify trigger time in the Schedule node Location**: Change city in HTTP Request URL Forecast Hours**: Adjust desiredHours array in the code Temperature Thresholds**: Modify emoji temperature ranges Recommendation Logic**: Customize advice triggers 📱 Sample Output 🌤️ Weather Forecast for Strassen, LU 📅 Monday, 2 June 2025 📊 Daily Overview 🌡️ Range: 12°C - 22°C 💧 Comfortable (65%) ⏰ Hourly Forecast 🕒 09:00 ☀️ 15°C 🕒 12:00 🌤️ 20°C 🕒 15:00 ☀️ 22°C (feels 24°C) 🕒 18:00 ⛅ 19°C 🕒 21:00 🌙 16°C 📡 Data from OpenWeatherMap | Updated: 07:50 CET 🚀 Getting Started Import this workflow to your n8n instance Add your OpenWeatherMap API key Set up Telegram bot credentials Test manually first Activate for daily automated runs 📋 Requirements n8n instance (cloud or self-hosted) Free OpenWeatherMap API account Telegram bot token Basic understanding of n8n workflows Perfect for: Daily weather updates, team notifications, personal weather tracking, smart home automation triggers.

Purpose of workflow: The purpose of this workflow is to automate scraping of a website, transforming it into a structured format, and loading it directly into a Google Sheets spreadsheet. How it works: Web Scraping: Uses the Jina AI service to scrape website data and convert it into LLM-friendly text. Information Extraction: Employs an AI node to extract specific book details (title, price, availability, image URL, product URL) from the scraped data. Data Splitting: Splits the extracted information into individual book entries. Google Sheets Integration: Automatically populates a Google Sheets spreadsheet with the structured book data. Step by step setup: Set up Jina AI service: Sign up for a Jina AI account and obtain an API key. Configure the HTTP Request node: Enter the Jina AI URL with the target website. Add the API key to the request headers for authentication. Set up the Information Extractor node: Use Claude AI to generate a JSON schema for data extraction. Upload a screenshot of the target website to Claude AI. Ask Claude AI to suggest a JSON schema for extracting required information. Copy the generated schema into the Information Extractor node. Configure the Split node: Set it up to separate the extracted data into individual book entries. Set up the Google Sheets node: Create a Google Sheets spreadsheet with columns for title, price, availability, image URL, and product URL. Configure the node to map the extracted data to the appropriate columns.

Automated system to track and analyze technology stacks used by target companies, helping identify decision-makers and technology trends. 🚀 What It Does Tracks technology stack of target companies Identifies key decision-makers (CTOs, Tech Leads) Monitors technology changes and updates Provides competitive intelligence Generates actionable insights 🎯 Perfect For B2B SaaS companies Technology vendors Sales and business development teams Competitive intelligence analysts Market researchers ⚙️ Key Benefits ✅ Identify potential customers ✅ Stay ahead of technology trends ✅ Target decision-makers effectively ✅ Monitor competitor technology stacks ✅ Data-driven sales strategies 🔧 What You Need BuiltWith API key n8n instance CRM integration (optional) Email/Slack for alerts 📊 Data Tracked Company technologies Hosting providers Frameworks and libraries Analytics tools Marketing technologies 🛠️ Setup & Support Quick Setup Deploy in 20 minutes with our step-by-step guide 📺 Watch Tutorial 💼 Get Expert Support 📧 Direct Help Gain a competitive edge by understanding the technology landscape of your target market.