Workflow Templates

This workflow is a experiment to build HTML pages from a user input using the new Structured Output from OpenAI. How it works: Users add what they want to build as a query parameter The OpenAI node generate an interface following a structured output defined in the body The JSON output is then converted to HTML along with a title The HTML is encapsulated in an HTML node (where the Tailwind css script is added) The HTML is rendered to the user via the Webhook response. Set up steps Create an OpenAI API Key Create the OpenAI credentials Use the credentials for both nodes HTTP Request (as Predefined Credential type) and OpenAI Activate your workflow Once active, go to the production URL and add what you'd like to build as the parameter "query" Example: https://production_url.com?query=a%20signup%20form Example of generated page

How it works This workflow changes the file name, and therefore the extension and MIME type, of any binary file passed to it. This is perfect for converting file formats on the fly, like turning a Telegram voice message (.oga) into an MP3 for an AI transcription service. Set New File Name: The SET OUTPUT FILE NAME node is where you define the desired output file name and extension (e.g., audio.mp3). It also dynamically captures the property name of the incoming binary (e.g., data). Extract Binary Data: The workflow temporarily converts the binary file into a Base64 text string to make it accessible in the next step. Rebuild Binary with New Name: A Code node takes the Base64 data and reconstructs it as a binary file, but this time, it assigns the new file name you specified. n8n automatically sets the MIME type based on the new file extension. Set up steps Setup time: < 1 minute This workflow is designed to be used as a sub-workflow. In your main workflow, add an Execute Sub-Workflow node where you need to change a file's type. In the Workflow parameter, select this "Change Binary MimeType/Extension" workflow. Open this workflow and go to the SET OUTPUT FILE NAME node. Modify the output_file_name value to your desired file name (e.g., voice_message.mp3 or document.pdf). Save this workflow. Now, any binary file you send to it from your main workflow will be returned with the new fileName and mimeType.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. What this workflow does Monitors Google Drive for new driver license image uploads Downloads and processes images using VLM Run AI OCR Extracts key information including license number, name, DOB, and dates Saves structured data to Google Sheets for instant access Setup Prerequisites: Google Drive account, VLM Run API credentials, Google Sheets access, self-hosted n8n. You need to install VLM Run community node Quick Setup: Configure Google Drive OAuth2 and create license upload folder Add VLM Run API credentials Set up Google Sheets integration for data storage Update folder/sheet IDs in workflow nodes Test with sample license images and activate Perfect for Customer onboarding and identity verification KYC compliance and document processing HR employee verification and record keeping Insurance claim processing and validation Any business requiring license data extraction Key Benefits Asynchronous processing** handles high-resolution images without timeouts Multi-format support** for JPG, PNG, PDF, HEIC, WebP formats Structured data output** ready for databases and integrations Eliminates manual entry** saving hours of data input time High accuracy OCR** with multi-state license support How to customize Extend by adding: Address and additional field extraction Data validation and error checking Integration with CRM or customer databases Email notifications for processing completion Audit trails and compliance reporting Duplicate detection and data deduplication This workflow transforms manual license data entry into an automated, accurate, and compliant process, making identity verification seamless and reliable for your business operations.

Guidebook: How the Website ChatBot Template Works Chapter 1: Introduction & Objectives This guidebook provides a comprehensive walkthrough of the Website ChatBot developed using n8n and OpenAI. The chatbot is designed to qualify real estate leads and encourage site visits for the Alcove New Kolkata Sangam project through personalized, intelligent conversations. Chapter 2: Tools Required 1. n8n Workflow Automation Tool An open-source workflow builder to automate data flows between services. 2. OpenAI Account with GPT-4o-mini Access For generating AI-based chatbot responses. 3. Web Chat Widget Frontend integration that sends messages via webhook to the chatbot. Chapter 3: Workflow Breakdown Step 1: Webhook Receives POST requests from the chat widget. Endpoint: /webhook/chatbot-webhook Step 2: Set User Message Extracts message from the JSON body. Stores it as user_message. Step 3: Memory Setup Uses session ID to track conversation across messages. Step 4: OpenAI Chat Model GPT-4o-mini processes queries using the defined agent prompt. Step 5: AI Agent (Khusboo) Persona of a pre-sales agent. Uses AIDA + BANT + SPIN + PAS frameworks. Shares videos, responds in Hinglish, schedules site visits. Step 6: Respond to Webhook Formats the chatbot's reply into a JSON response. Chapter 4: Strategy & Psychology Behind Responses | Framework | Purpose | | --------- | ---------------------------------------------------- | | AIDA | Capture attention, interest, desire, action | | BANT | Qualify Budget, Authority, Need, Timing | | SPIN | Understand user's Situation, Problems, Implications | | PAS | Tackle objections using Problem, Agitation, Solution | The chatbot aims to qualify leads and gently move them toward booking a site visit without pushing or over-informing. Chapter 5: Setup Instructions A. n8n Workflow Setup Import the JSON workflow. Ensure OpenAI credentials are set up. Enable webhook at /webhook/chatbot-webhook. B. Frontend Widget Integration Send message as POST to the webhook with structure: { "message": "Looking for 2 BHK", "session_id": "user123" } Chapter 6: Testing & Troubleshooting Test via Postman Send sample request to verify AI response. Common Issues | Issue | Fix | | ---------------- | ----------------------------------- | | No response | Check webhook URL or credentials | | Repeated replies | Ensure memory node is active | | Wrong language | Check system message language rules | Chapter 7: Sample Conversations User: Hi, I’m looking for a home near the Ganga. Bot: Namaste! Main Khusboo hoon, Alcove New Kolkata Sangam se. Aapka naam kya hai? User: Rajat. Bot: Great Rajat! Kya aap apne family ke saath shift hone ka plan kar rahe ho? ... (continues using frameworks) Chapter 8: FAQs & Maintenance Tips Q: Can I update the AI agent persona? A: Yes, by modifying the system message inside the AI Agent node. Q: How do I share new videos or links? A: Add them in the sharingVideos or UserRequests section in the system message. Q: How to scale this for multiple projects? A: Duplicate the workflow and update the aboutProject and links accordingly. End of Guidebook.

Use Case When tracking your contacts and leads in Hubspot CRM, every new contact might be a potential customer. To guarantee that you're keeping the overview you'd normally need to look at every new lead that is coming in manually to identify high-quality leads to prioritize their engagement and optimize the sales process. This workflow saves the work and does it for you. What this workflow does The workflow runs every 5 minutes. On every run, it checks the Hubspot CRM for contacts that were added since the last check. It then checks if they meet certain criteria (in this case if they are making +5m annual revenue) and alerts you in Slack for every match. Setup Add Hubspot, and Slack credentials. Click on Test workflow. How to adjust this workflow to your needs Change the schedule interval Adjust the criteria to send alerts

This n8n template demonstrates how to get started with Gemini 2.0's new Bounding Box detection capabilities in your workflows. The key difference being this enables prompt-based object detection for images which is pretty powerful for things like contextual search over an image. eg. "Put a bounding box around all adults with children in this image" or "Put a bounding box around cars parked out of bounds of a parking space". How it works An image is downloaded via the HTTP node and an "Edit Image" node is used to extract the file's width and height. The image is then given to the Gemini 2.0 API to parse and return coordinates of the bounding box of the requested subjects. In this demo, we've asked for the AI to identify all bunnies. The coordinates are then rescaled with the original image's width and height to correctl align them. Finally to measure the accuracy of the object detection, we use the "Edit Image" node to draw the bounding boxes onto the original image. How to use Really up to the imagination! Perhaps a form of grounding for evidence based workflows or a higher form of image search can be built. Requirements Google Gemini for LLM Customising the workflow This template is just a demonstration of an experimental version of Gemini 2.0. It is recommended to wait for Gemini 2.0 to come out of this stage before using in production.

AI-Powered Daily Gmail Digest Summary using LangChain & OpenRouter This n8n template helps you automatically summarize your daily Gmail messages using OpenRouter's GPT model via LangChain. It generates a structured email digest highlighting key information, tasks, issues, and action items — all delivered to your inbox every morning. Who’s it for Busy professionals who want a quick overview of their daily emails Founders or managers needing to track team or client communication Anyone looking to automate inbox triage and reduce time spent on emails How it works / What it does This n8n workflow runs every morning at 7 AM, automatically: Fetches emails from the last 24 hours Collects important fields: sender, subject, and snippets Feeds them into an AI-powered agent (OpenRouter + LangChain) The AI: Extracts key topics, tasks, deadlines, and issues Formats the info clearly with a bullet-point summary Sends the final summarized report to your inbox How to set up Clone or import the workflow into your n8n instance Replace <Your Email ID> in the Code node with your actual Gmail address (or remove if not needed) Ensure your Gmail and OpenRouter credentials are set up in n8n Update the recipient email in the Send Summary node if you want it sent to a fixed address Activate the workflow once tested How to customize the workflow Change Summary Style:** Edit the system message in the LangChain Agent to match your tone (e.g. casual, business, detailed) Adjust Digest Time:** Change the Schedule Trigger to any preferred hour Customize Recipients:** Change or add recipients dynamically or statically in the Gmail send node Filter Email Type:** Modify the Gmail query in the Code node to include filters like from:, is:unread, subject:project

This n8n template offers a simple yet capable chatbot assistant who can answer course enquiries over SMS. Given the right access to data, AI Agents are capable of planning and performing relatively complex research tasks to get their answers. In this example, the agent must first understand the database schema, retrieve lists of values before generating it's own query to search over the database. Checkout the example database here - https://airtable.com/appO5xvP1aUBYKyJ7/shr8jSFDaghubDOrw How it works A Twilio trigger gives us the ability to receive SMS input into our workflow via webhook. The message is then directed to our AI agent who is instructed to assist the user and use the course database as reference. The database is an Airtable base. The agent autonomously figures out which tool it needs to use and generates it's own "filter_by_formula" query to search over the available courses. On successful search results, the Agent can then use this information to answer the user's query. The Agent's output is logged in a second sheet of the Airtable base. We can use this later for analysis and lead gen. Finally, the response is sent back to the user through SMS using Twilio. How to use Ensure your Twilio number is set to forward messages to this workflow's webhook URL. Configure and update the course database as required. If you're not interested in courses, you can swap this out for inventory, deliveries or any other data relevant to your business. Ask questions like: "Can you help me find suitable courses to fill my Wednesday mornings?" "Which courses are being instructed by profession Lee?" "I'm interested in creative arts. What courses are available which could be relevant to me?" Requirements Twilio for SMS receiving and sending OpenAI for LLM and Agent Airtable for Course Database Customising this workflow Add additional tools and expand the range of queries the agent is able to answer or assist with. Not using Airtable? This technique also works with SQL databases like PostgreSQL.

Who's this for? If you own a website and need to analyze your keyword rankings If you need to create a keyword report on your rankings If you want to grow your keyword positions SerpBear is an opensourced SEO tool specifically for keyword analytics. Click here to read details of how I use it Example output of A.I. Key Observations about Ranking Performance: The top-performing keyword is “Openrouter N8N” with a current position of 7 and an improving trend. Two keywords, “Best Docker Synology” and “Bitwarden Synology”, are not ranking in the top 100 and have a stable trend. Three keywords, “Obsidian Second Brain”, “AI Generated Reference Letter”, and “Actual Budget Synology”, and “N8N Workflow Generator” are not ranking well and have a declining trend. Keywords showing the most improvement: “Openrouter N8N” has an improving trend and a relatively high ranking of 7. Keywords needing attention: “Obsidian Second Brain” has a declining trend and a low ranking of 69. “AI Generated Reference Letter” has a declining trend and a low ranking of 84. “Actual Budget Synology”, “N8N Workflow Generator”, “Best Docker Synology”, and “Bitwarden Synology” are not ranking in the top 100. Use case Instead of hiring an SEO expert, I run this report weekly. It checks the keyword rankings of the past week and gives me recommendations on what to improve. How it works The workflow gathers SerpBear analytics for the past 7 days. It passes the data to openrouter.ai for A.I. analysis. Finally it saves to baserow. How to use this Input your SerpBearcredentials Enter your domain name Input your Openrouter.ai credentials Input your baserow credentials You will need to create a baserow database with columns: Date, Note, Blog Created by Rumjahn

This workflow randomly select recipes from a Mealie instance (can use a specific category) and then creates a meal plan in Mealie with those recipes. How it works: Workflow has a scheduled trigger (set to run weekly on a Friday) Config node sets a few properties to configure the workflow A call to the Mealie API to get the list of recipes The code node holds most of the logic, this will loop through the number of recipes defined in the config node and randomly select a recipe from the list (making sure not to double up any recipes) Once all the recipes are selected it will call the Mealie API to set up the meal plan on the days Setup Add your Mealie API token as a credential and set it on the Http Request nodes Set the relevant schedule trigger to run when you like Update the Config node with the config you want numberOfRecipes - Number of recipes to populate for the meal plan offsetPlanDays - Number of days in the future to start the plan (0 will start it today, 1 tomorrow, etc.) mealieCategoryId - A category id of the category you want to pull in recipes from (default to select from all recipes) mealieBaseUrl - The base url of your Mealie instance

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Automatically transform your video uploads into AI-powered summaries with key topic extraction and instant team notifications. What this workflow does Monitors Google Drive for new video uploads Downloads and processes videos using VLM Run AI Generates intelligent summaries with key topics extracted Posts results to Slack for immediate team access Setup Prerequisites: Google Drive account, VLM Run API credentials, Slack workspace, self-hosted n8n. You need to install VLM Run community node Quick Setup: Configure Google Drive OAuth2 and create video upload folder Add VLM Run API credentials Set up Slack integration for notifications Update folder/channel IDs in workflow nodes Test and activate Perfect for Meeting recordings and training videos Webinar summaries and educational content Content analysis and team collaboration Any video content requiring quick insights Key Benefits Asynchronous processing** handles large files without timeouts Multi-format support** for MP4, AVI, MOV, WebM, MKV Instant team updates** via Slack notifications Saves hours** of manual video review time How to customize Extend by adding: Video categorization and tagging Integration with project management tools Email notifications alongside Slack Searchable video databases with summaries This workflow transforms lengthy videos into actionable insights, making your content instantly accessible and shareable with your team.

This n8n template allows you to monitor hourly weather conditions in a specific city using OpenWeatherMap and log the results to a Google Sheet. It’s perfect for anyone needing periodic weather tracking—whether you're managing logistics, travel planning, or environmental monitoring. 🔧 How it works A Schedule Trigger activates the workflow every hour. The Get Weather Data from OpenWeatherMap node fetches real-time weather details using the city name you specify. An IF node checks if the weather description contains "rain" or the temperature is below a set threshold. If the condition is true, the data is formatted with city, temperature, humidity, and conditions. The Google Sheets node appends this formatted information to your designated sheet. 👤 Who is it for? This workflow is ideal for: Operations teams monitoring weather-sensitive logistics Researchers collecting climate data Developers and hobbyists learning how to connect APIs with Google Sheets 🗂️ Google Sheet Structure Your Google Sheet should have the following columns: city (string) temperature (K) (number) humidity (number) conditions (string) status (string) ⚙️ Setup Instructions Create a Google Sheet with the above columns. Set up your Google Service Account credentials in n8n. Replace the API key in the HTTP Request node with your own OpenWeatherMap credential. Specify your target city and ensure your OpenWeatherMap account is active. Adjust the frequency in the Schedule Trigger as needed (default: every hour).