Workflow Templates

This n8n template introduces the Dynamic Prompts Ai workflow pattern which are incredible for certain types of data extraction tasks where attributes are unknown or need to remain flexible. The general idea behind this pattern is that the prompts for requested attributes to be extracted live outside the template and so can be changed at any time - without needing to edit the template. This seriously cuts down on maintainance requirements and is reusable for any number of tables at little cost. Check out the video demo I did for n8n Studio here: https://www.youtube.com/watch?v=_fNAD1u8BZw Check out the example Airtable here: https://airtable.com/appAyH3GCBJ56cfXl/shrXzR1Tj99kuQbyL Looking for the Baserow Version? https://n8n.io/workflows/2780-ai-data-extraction-with-dynamic-prompts-and-baserow/ How it works Given we have an "input" field for context and a number of fields for the data we want to extract, this template will run in the background to react to any changes to either the "input" or fields and automatically update the rows accordingly. The key is that Airtable fields have a special property called the "field description". In this pattern, we use this property to allow the user to store a simple prompt describing the data that should exist in the column. Our n8n template reads these column descriptions aka "prompts" to use as instructions to perform tasks on the "input". In this template, the "input" is a PDF of a resume/CV and the columns are attributes a HR person would want to extract from it - such as full name, address, last position, years of experience etc. How to use First publish this template and ensure it's accessible via webhook URL. You then have to run the "create airtable webhooks" mini-flow to configure your Airtable to send change events to the n8n template. This mini-flow exists in the template but you'll have to update the IDs. Check the template for more instructions. Requirements Airtable for Tables/Database OpenAI for LLM and extraction. Feel free to choose another LLM if preferred. Customising this workflow If you're not using files, you can replace the "input" field with anything you like. For example, the "input" could be single line text.

This n8n workflow processes incoming Telegram messages, differentiating between text and voice messages. How it works: Message Trigger: The workflow initiates when a new message is received via the Telegram "Message Trigger" node. Switch Node: This node acts as a router. It examines the incoming message: If the message is text, it directs the flow along the "text" branch. If the message contains voice, it directs the flow along the "voice" branch. Get Audio File: For audio messages, this node downloads the audio file from Telegram. Transcribe Audio: The downloaded audio file is then sent to an "OpenAI Transcribe Recording" node, which uses OpenAI's whisper-1 speech-to-text model to convert the audio into a text transcript. Send Transcription Message: Regardless of whether the original message was text or transcribed audio, the final text content is then passed to a "Send transcription message" node. Setup Requirements: Telegram Bot Token**: You will need a Telegram bot token configured in the "Message Trigger" node to receive messages. OpenAI API Key**: An OpenAI API key is required for the "Transcribe audio" node to perform speech transcription. Additional Notes: This workflow provides a foundational step for building more complex AI-driven applications. The transcribed text or original text message can be easily piped into an AI agent (e.g., a large language model) for analysis, response generation, or interaction with other tools, extending the bot's capabilities beyond simple message reception and transcription. 👉 Need Help? Feel free to contact us at 1 Node. Get instant access to a library of free resources we created.

📧 Email Validation Workflow Using APILayer API This n8n workflow enables users to validate email addresses in real time using the APILayer Email Verification API. It's particularly useful for preventing invalid email submissions during lead generation, user registration, or newsletter sign-ups, ultimately improving data quality and reducing bounce rates. ⚙️ Step-by-Step Setup Instructions Trigger the Workflow Manually: The workflow starts with the Manual Trigger node, allowing you to test it on demand from the n8n editor. Set Required Fields: The Set Email & Access Key node allows you to enter: email: The target email address to validate. access_key: Your personal API key from apilayer.net. Make the API Call: The HTTP Request node dynamically constructs the URL: https://apilayer.net/api/check?access_key={{ $json.access_key }}&email={{ $json.email }} It sends a GET request to the APILayer endpoint and returns a detailed response about the email's validity. (Optional): You can add additional nodes to filter, store, or react to the results depending on your needs. 🔧 How to Customize Replace the manual trigger with a webhook or schedule trigger to automate validations. Dynamically map the email and access_key values from previous nodes or external data sources. Add conditional logic to filter out invalid emails, log them into a database, or send alerts via Slack or Email. 💡 Use Case & Benefits Email validation is crucial in maintaining a clean and functional mailing list. This workflow is especially valuable in: Sign-up forms where real-time email checks prevent fake or disposable emails. CRM systems to ensure user-entered emails are valid before saving them. Marketing pipelines to minimize email bounce rates and increase campaign deliverability. Using APILayer’s trusted validation service, you can verify whether an email exists, check if it’s a role-based address (like info@ or support@), and identify disposable email services—all with a simple workflow. Keywords: email validation, n8n workflow, APILayer API, verify email, real-time email check, clean email list, reduce bounce rate, data accuracy, API integration, no-code automation

This automated n8n workflow tracks booked flight fares post-purchase using Amadeus and Skyscanner APIs to detect drops for refund or credit opportunities. It streamlines fare monitoring, updates booking statuses, and notifies users via SMS or email. Fundamental Aspects Fare Check Trigger** - Initiates the workflow Get Tracked Bookings** - Retrieves existing booking data Prepare Fare Query** - Prepares query parameters Search Current Fares** - Queries Skyscanner for current fares Analyze Fare Drops** - Identifies significant fare reductions Update Fare Tracking** - Updates fare tracking records Update Booking Status** - Updates status based on fare changes Check if Notification Needed** - Determines if alerts are required Send Fare Drop Email** - Notifies users via email Notify Slack Team** - Alerts the team via Slack Check Refund Eligible** - Assesses refund eligibility Initiate Refund Process** - Starts refund procedure if eligible Check if SMS Needed** - Decides if SMS alert is necessary Send SMS Alert** - Sends SMS notification Setup Instructions Import the workflow into n8n Configure API credentials for Amadeus and Skyscanner Run the workflow Verify notifications and refund processes Features Fare Monitoring** - Tracks and compares fares using Amadeus and Skyscanner Alert System** - Sends email and SMS notifications for fare drops Refund Management** - Checks and initiates refund processes Trend Analysis** - Analyzes fare trends for strategic decisions DB Queries Get Tracked Bookings Columns:** - booking_id, passenger_name, email, phone, flight_number, departure_date, origin, destination, airline, booking_class, original_fare, booking_date, confirmation_code, tracking_enabled, last_checked, current_lowest_fare, trend. Update Fare Tracking Columns:** - booking_id, check_date, lowest_fare, fare_source, savings_amount, savings_percentage, fare_trend, priority_level, action_recommended, refund_eligible, available_fares_json, updated_at. Update Booking Status: Columns** - last_checked, current_lowest_fare, booking_id. DB Setup: Create tables 'bookings' and 'fare_tracking' with above columns, set 'booking_id' as primary key, and ensure proper indexing for performance. Run queries after configuring DB connection in n8n with appropriate credentials. Parameters to Configure amadeus_api_key**: Amadeus API key skyscanner_api_key**: Skyscanner API key email_recipients**: List of email addresses for alerts sms_recipients**: List of phone numbers for SMS alerts slack_channel**: Slack channel for team notifications refund_threshold**: Minimum fare drop for refund eligibility

Who is this for? This workflow is for everyone who wants to have easier access to their Odoo sales data without complex queries. Use Case To have a clear overview of your sales data in Odoo you typically needs to extract data from it manually to analyse it. This workflow uses OpenAI's language models to create an intelligent chatbot that provides conversational access to your Odoo sales opportunity data. How it works Creates a summary of all Odoo sales opportunities using OpenAI Uses that summary as context for the OpenAI chat model Keeps the summary up to date using a schedule trigger Set up steps: Configure the Odoo credentials Configure OpenAI credentials Toggle "Make Chat Publicly Available" from the Chat Trigger node.

This workflow is a building block designed to be called from other workflows via an Execute workflow node. When called from another workflow, and given the JSON input of a "pulse" field with the ID to pull from monday, this workflow will return: The items name and ID All column data, indexable by the column name All column data, indexable by the column's ID string All board relation columns, with their data and column values All subitems, with their data and column values For example: ++Prerequisites++ A monday.com account and credential A workflow that needs to get detailed data from a monday.com row The pulse id of the monday.com row to retreive data from. ++Setup++ Import the workflow Configure all monday nodes with your credentials and save the workflow Copy the workflow ID from it's URL In a different workflow, add an Edit Fields node, to output the field "pulse", with the monday item you want to retrieve. Feed the Edit Fields node with your pulse into an Execute workflow node, and paste the workflow ID from above into it This "pulse" field will tell the workflow what pulse to retreive. This can be populated by an expression in your workflow There is an example of the Edit Fields and Execute Workflow nodes in the template

Who Is This For This workflow is ideal for content creators, solo founders, marketers, and AI enthusiasts who want to automate the full process of blog content creation. It is especially useful for professionals in tech, AI, and automation who publish frequently and need SEO-ready content fast. What Problem Does This Workflow Solve Creating SEO-optimized blog content is time-consuming and requires consistency. Manually researching trending topics slows down the content pipeline. Formatting, publishing, and promoting across multiple platforms takes effort. This workflow automates the entire process from research to publication. What This Workflow Does Research: Uses Perplexity AI to gather up-to-date content ideas via form input. Content Generation: GPT-4 creates a short, SEO-optimized article (max 20 lines) with H1, H2 structure and meta-description. Publishing: Automatically posts the content to WordPress. Email Notification: Sends the article title and URL via Gmail. Slack Notification: Notifies a specified Slack channel when the article is live. Database Logging: Saves the article details to a Notion database. Setup Guide Prerequisites WordPress account with API access OpenAI API Key Perplexity API Key Slack Bot Token Notion integration (Database ID) Gmail API credentials (optional) Community Node Required: This workflow uses n8n-nodes-mcp, which only works on self-hosted instances of n8n. > To install: Go to Settings > Community Nodes > Install n8n-nodes-mcp Steps Import the workflow into your n8n instance Install the required community node (n8n-nodes-mcp) Set up API credentials for OpenAI, Perplexity, WordPress, Slack, Gmail, and Notion Customize the form trigger with your preferred prompt Run a test using a sample topic How to Customize This Workflow Modify the research prompt to match your niche or industry Adjust GPT-4 settings for tone, structure, or content length Customize Notion fields (e.g., add tags, categories, or labels) Add logic for generating or assigning featured images automatically

Automated Multilingual Gmail Draft Reply with OpenAI GPT-4o in n8n Who is this for? This workflow is ideal for anyone who receives a high volume of Gmail inquiries, especially those providing multilingual customer support or handling diverse client communications. What problem is this workflow solving? Managing frequent emails in multiple languages can be overwhelming. This workflow reduces manual drafting by automatically generating context-aware replies using OpenAI GPT-4o, letting users focus on personalization and quality assurance. What this workflow does Monitors your Gmail inbox for new emails with a specific label (e.g., "Inquiry"). Uses OpenAI GPT-4o for message assessment and language detection. Parses information using a JSON parser. Generates an AI-powered draft reply in the detected language via OpenAI GPT-4o. Converts the reply to HTML and saves it as a draft in the original Gmail thread for your review. Setup Connect your Gmail account and set up relevant labels in both Gmail and the workflow. Integrate your OpenAI credentials in n8n. Configure the workflow trigger for your desired labels. How to customize this workflow to your needs Adjust label names in both Gmail and the workflow for different email categories. Define custom starting and ending phrases for draft replies per supported language. Expand supported languages or modify AI prompt instructions to suit your brand’s tone.

This workflow allows users to generate AI videos using Google Veo3, save them to Google Drive, generate optimized YouTube titles with GPT-4o, and automatically upload them to YouTube with Upload-Post. The entire process is triggered from a Google Sheet that acts as the central interface for input and output. IT automates video creation, uploading, and tracking, ensuring seamless integration between Google Sheets, Google Drive, Google Veo3, and YouTube. Benefits of this Workflow 💡 No Code Interface**: Trigger and control the video production pipeline from a simple Google Sheet. ⚙️ Full Automation**: Once set up, the entire video generation and publishing process runs hands-free. 🧠 AI-Powered Creativity**: Generates engaging YouTube titles using GPT-4o. Leverages advanced generative video AI from Google Veo3. 📁 Cloud Storage & Backup**: Stores all generated videos on Google Drive for safekeeping. 📈 YouTube Ready**: Automatically uploads to YouTube with correct metadata, saving time and boosting visibility. 🧪 Scalable**: Designed to process multiple video prompts by looping through new entries in Google Sheets. 🔒 API-First**: Utilizes secure API-based communication for all services. How It Works Trigger: The workflow can be started manually ("When clicking ‘Test workflow’") or scheduled ("Schedule Trigger") to run at regular intervals (e.g., every 5 minutes). Fetch Data: The "Get new video" node retrieves unfilled video requests from a Google Sheet (rows where the "VIDEO" column is empty). Video Creation: The "Set data" node formats the prompt and duration from the Google Sheet. The "Create Video" node sends a request to the Fal.run API (Google Veo3) to generate a video based on the prompt. Status Check: The "Wait 60 sec." node pauses execution for 60 seconds. The "Get status" node checks the video generation status. If the status is "COMPLETED," the workflow proceeds; otherwise, it waits again. Video Processing: The "Get Url Video" node fetches the video URL. The "Generate title" node uses OpenAI (GPT-4.1) to create an SEO-optimized YouTube title. The "Get File Video" node downloads the video file. Upload & Update: The "Upload Video" node saves the video to Google Drive. The "HTTP Request" node uploads the video to YouTube via the Upload-Post API. The "Update Youtube URL" and "Update result" nodes update the Google Sheet with the video URL and YouTube link. Set Up Steps Google Sheet Setup: Create a Google Sheet with columns: PROMPT, DURATION, VIDEO, and YOUTUBE_URL. Share the Sheet link in the "Get new video" node. API Keys: Obtain a Fal.run API key (for Veo3) and set it in the "Create Video" node (Header: Authorization: Key YOURAPIKEY). Get an Upload-Post API key (for YouTube uploads) and configure the "HTTP Request" node (Header: Authorization: Apikey YOUR_API_KEY). YouTube Upload Configuration: Replace YOUR_USERNAME in the "HTTP Request" node with your Upload-Post profile name. Schedule Trigger: Configure the "Schedule Trigger" node to run periodically (e.g., every 5 minutes). Need help customizing? Contact me for consulting and support or add me on Linkedin.

This template will create a nightly backup of all your n8n workflows to a Dropbox folder. Each night, the previous night's backups are moved into an "old" folder, and renamed with the date they were taken. Backups over a specified age are deleted. (this is disabled by default for safety until you manually enable and verify it with your own setup) Prerequisites Dropbox account and credentials A destination folder for backups Setup Update all dropbox nodes with your credential Edit the Schedule Trigger node with the desired time to run the backup Edit the DESTINATION FOLDER node to specify the path in dropbox to upload to. This should be a folder and include the trailing / If you want to automatically purge old backups Edit the PURGE DAYS node to specify the age to purge Enable the PURGE DAYS node, and the 3 subsequent nodes Enable the workflow to run on the specified schedule

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. AI Arena - Debate of AI Agents to Optimize Answers and Simulate Diverse Scenarios Overview Version: 1.0 The AI Arena Workflow is designed to facilitate a refined answer generation process by enabling a structured debate among multiple AI agents. This workflow allows for diverse perspectives to be considered before arriving at a final output, enhancing the quality and depth of the generated responses. ✨ Features Multi-Agent Debate Simulation**: Engage multiple AI agents in a debate to generate nuanced responses. Configurable Rounds and Agents**: Easily adjust the number of debate rounds and participating agents to fit your needs. Contextualized AI Responses**: Each agent operates based on predefined roles and characteristics, ensuring relevant and focused discussions. JSON Output**: The final output is structured in JSON format, making it easy to integrate with other systems or workflows. 👤 Who is this for? This workflow is ideal for developers, data scientists, content creators, and businesses looking to leverage AI for decision-making, content generation, or any scenario requiring diverse viewpoints. It is particularly useful for those who need to synthesize information from multiple personalities or perspectives. 💡 What problem does this solve? The workflow addresses the challenge of generating nuanced responses by simulating a debate among AI agents. This approach ensures that multiple perspectives are considered, reducing bias and enhancing the overall quality of the output. Use-Case examples: 🗓️ Meeting/Interview Simulation ✔️ Quality Assurance 📖 Storywriter Test Environment 🏛️ Forum/Conference/Symposium Simulation 🔍 What this workflow does The workflow orchestrates a debate among AI agents, allowing them to discuss, critique, and suggest rewrites for a given input based on their roles and predefined characteristics. This collaborative process leads to a more refined and comprehensive final output. 🔄 Workflow Steps Input & Setup: The initial input is provided, and the AI environment is configured with necessary parameters. Round Execution: AI agents execute their roles, providing replies and actions based on the input and their individual characteristics. Round Results: The results of each round are aggregated, and a summary is created to capture the key points discussed by the agents. Continue to Next Round: If more rounds are defined, the process repeats until the specified number of rounds is completed. Final Output: The final output is generated based on the agents' discussions and suggestions, providing a cohesive response. ⚡ How to Use/Setup 🔐 Credentials Obtain an API key for the Mistral API or another LLM API. This key is necessary for the AI agents to function properly. 🔧 Configuration Set up the workflow in n8n, ensuring all nodes are correctly configured according to the workflow requirements. This includes setting the appropriate input parameters and defining the roles of each AI agent. This workflow uses a custom node for Global Variables called 'n8n-nodes-globals.' Alternatively, you can use the 'Edit Field (Set)' node to achieve the same functionality. ✏️ Customizing this workflow To customize the workflow, adjust the AI agent parameters in the JSON configuration. This includes defining their roles, personalities, and preferences, which will influence how they interact during the debate. One of the notes includes a ready-to-use example of how to customize the agents and the environment. You can simply edit it and insert it as your credential in the Global Variables node. 📌 Example An example with both input and final output is provided in a note within the workflow. 🛠️ Tools Used n8n: A workflow automation tool that allows users to connect various applications and services. Mistral API: A powerful language model API used for generating AI responses. (You can replace it with any LLM API of your choice) Podman: A container management tool that allows users to create, manage, and run containers without requiring a daemon. (It serves as an alternative to Docker for container orchestration.) ⚙️ n8n Setup Used n8n Version**: 1.100.1 n8n-nodes-globals**: 1.1.0 Running n8n via**: Podman 4.3.1 Operating System**: Linux ⚠️ Notes, Assumptions & Warnings Ensure that the AI agents are configured with clear roles to maximize the effectiveness of the debate. Each agent's characteristics should align with the overall goals of the workflow. The workflow can be adapted for various use cases, including meeting simulations, content generation, and brainstorming sessions. This workflow assumes that users have a basic understanding of n8n and JSON configuration. This workflow assumes that users have access to the necessary API keys and permissions to utilize the Mistral API or other LLM APIs. Ensure that the input provided to the AI agents is clear and concise to avoid confusion in the debate process. Ambiguous inputs may lead to unclear or irrelevant outputs. Monitor the output for relevance and accuracy, as AI-generated content may require human oversight to ensure it meets standards and expectations before being used in production. ℹ️ About Us This workflow was developed by the Hybroht team of AI enthusiasts and developers dedicated to enhancing the capabilities of AI through collaborative processes. Our goal is to create tools that harness the possibilities of AI technology and more.

Description: This template facilitates the transfer of a folder, along with all its files and subfolders, within a Nextcloud instance. The Nextcloud user must have access to both the source and destination folders. While Nextcloud allows folder movement, complications may arise when dealing with external storage that has rate limits. This workflow ensures the individual transfer of each file to avoid exceeding rate limits, particularly useful for setups involving external storage with rate limitations. How it works: Identify all files and subfolders within the specified source folder. Recursive search within subfolders for additional files. Replicate the folder structure in the target folder. Individually move each identified file to the corresponding location in the target folder. Set up steps: Set Nextcloud credentials for all Nextcloud nodes involved in the process. -Edit the trigger settings. Detailed instructions can be found within the respective trigger configuration. Initiate the workflow to commence the folder transfer process. Help If you need assistance with applying this template, feel free to reach out to me. You can find additional information about me and my services here. => https://nicokowalczyk.de/links I have also produced a video where I explain the workflow and provide an example. You can find this video over here. https://youtu.be/K1kmG_Q_jRk Cheers. Nico Kowalczyk