Workflow Templates

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

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

Who is this for? This workflow is designed for n8n users and developers who need to automate the documentation process of their n8n workflows. It's particularly useful for teams looking to streamline their documentation efforts and ensure consistency across their workflow documentation. What problem is this workflow solving? / Use case The primary problem this workflow addresses is the manual and time-consuming process of creating documentation for n8n workflows. It automates the generation of concise, clear, and comprehensive documentation directly from the workflow's JSON, making it easier for both technical and non-technical users to understand what the workflow does and how it operates. What this workflow does Upon receiving a form submission with the workflow title and JSON, this workflow automatically generates documentation that includes: A brief introduction to the workflow. The trigger mechanism (webhook URLs for test and production environments, or cron schedules). Setup requirements, including necessary credentials and external dependencies. Setup Credentials Setup: Ensure you have OpenAI API credentials configured in n8n to use the GPT model for generating documentation text. Form Submission: Users must submit the form with the workflow title and JSON. The form is accessible via: Test URL: domain/form-test/{webhookId} Production URL: domain/form/{webhookId} How to customize this workflow to your needs Modify Trigger URLs**: Adjust the webhook or form URLs based on your domain and specific n8n setup. Customize Documentation Template**: Edit the OpenAI node's prompt to change the structure or details of the generated documentation. Extend Functionality**: Add nodes to integrate with other systems (e.g., automatically publishing the documentation to a wiki or sending it via email). This workflow simplifies the documentation process, making it accessible and manageable for teams of all sizes and technical abilities. By automating documentation, it ensures that all workflows are properly documented, enhancing understanding and efficiency within teams.

This n8n template demonstrates how you can automate community moderation using human-in-the-loop functionality for Discord. The use-case is for detecting and dealing with spam messages in a predefined and consistent way. Human-in-the-loop allows for a balance between overly aggressive bots and time and effort from the moderation team. How it works A scheduled trigger is used to scan the most recent messages in a Discord Channel. Messages are tagged via the "Remove Duplicates" node so they don't get processed again in the future. Messages are grouped by user to allow for minimising of number of notifications sent. An AI text classifier node is then used to detect for spam in each user's message. When detected, a notification is sent to a moderation channel using the Send-and-wait mode for Discord. This notification comes with an n8n form and dropdown list of predefined actions to take in dealing with the spam messages. Once sent the workflow waits until a response is received. Once a moderator selects an action, the workflow continues and carries out a predefined moderation action. How to use Depending on how busy your community is and subject to spammers, you may need to increase the scheduled interval. Add as many or few moderation actions as required. Remember to activate the workflow to get it started. Requirements Discord channel for messages to moderate OpenAI for text classification Customising this template It is possible to cover multiple channels. Add as many as your community needs. Not using Discord. The template can also work in slack or other services which offer the same bot functionality.

How it works Ever wonder how to make your workflows smarter? How to handle different types of data in different ways? This template is a hands-on tutorial that teaches you the three most fundamental nodes for controlling the flow of your automations: Merge, IF, and Switch. To make it easy to understand, we use a simple package sorting center analogy: Data Items** are packages on a conveyor belt. The Merge Node is where multiple conveyor belts combine into one. The IF Node is a simple sorting gate with two paths (e.g., "Fragile" or "Not Fragile"). The Switch Node is an advanced sorting machine that routes packages to many different destinations. This workflow takes you on a step-by-step journey through the sorting center: Creating Packages: Three different "packages" (two letters and one parcel) are created using Set nodes. Merging: The first Merge node combines all three packages onto a single conveyor belt so they can be processed together. Simple Sorting: An IF node checks if a package is fragile. If true, it's sent down one path; if false, it's sent down another. Re-Grouping: After being processed separately, another Merge node brings the packages back together. This "Split > Process > Merge" pattern is a critical concept in n8n! Advanced Sorting: A Switch node inspects each package's destination and routes it to the correct output (London, New York, Tokyo, or a Default bin). By the end, you'll see how all packages have been correctly sorted, and you'll have a solid understanding of how to build intelligent, branching logic in your own workflows. Set up steps Setup time: 0 minutes! This template is a self-contained tutorial and requires zero setup. There are no credentials or external services to configure. Simply click the "Execute Workflow" button. Follow the flow from left to right, clicking on each node to see its output and reading the detailed sticky notes to understand what's happening at each stage.

📊 Google Sheets MCP Workflow – AI Meets Spreadsheets! 😄 ✨ What It Does This n8n workflow lets you chat with your spreadsheets using AI + MCP! From reading and updating data to creating sheets, it’s your smart assistant for Google Sheets 📈🤖 🚀 Cool Features 💬 Natural language commands (e.g. "Add a new lead: John Doe") ✏️ Full CRUD (Create, Read, Update, Delete) 🧠 AI-powered analysis & smart workflows 🗂️ Multi-sheet support 🔗 Works with ChatGPT, Claude, and more (via MCP) 💡 Use Cases Data Tasks: “Update status to 'Done' in row 3” Sheet Ops: “Create a ‘Marketing 2024’ sheet” Business Flows: “Summarize top sales from Q2” 🛠️ Quick Setup Import Workflow into n8n Copy the JSON In n8n → Import JSON → Paste & Save ✅ Connect Google Sheets Create a project in Google Cloud Enable Sheets & Drive APIs Create OAuth2 credentials In n8n → Add Google Sheets OAuth2 credential → Connect 🔐 Add Your Credentials Get your credential ID Open each Google Sheets node → Update with your new credential ID Link to AI (Optional 😊) MCP webhook is pre-set Plug it into your AI tool (like ChatGPT) Send test command → Watch the magic happen ✨ ✅ Test It Out Try these fun commands: 🆕 "Add entry: Jane Doe, janed@example.com" 🔍 "Read data from Sales 2024" 🧹 "Clear data from A1:C5" ➕ "Create sheet 'Budget 2025'" ❌ "Delete sheet 'Test'" 🧠 MCP Command List (AI-Callable Functions) These are the tasks the AI can perform via MCP: Add a new entry to a sheet Read data from a sheet Update a row in a sheet Delete a row from a sheet Create a new sheet Delete an existing sheet Clear data from a specific range Summarize data from a sheet using AI ⚙️ Tips & Fixes OAuth2 Errors? Re-authenticate and check scopes Confirm redirect URI is exact Permissions? Spreadsheet must be shared with edit access Use service accounts for production Webhook Not Firing? Double-check the URL Trigger it manually to test

How it works This workflow automates the transformation of standard product images into professional product photography featuring human models It uses AI to analyze product images, create tailored photography prompts, and generate high-quality enhanced versions Set up steps You'll need an OpenAI API key and access to gpt-image-1 (verify your organization) Set up a Google Sheets spreadsheet with columns: Image-URL, Prompt, Output Create a Google Drive folder to store the generated images Requirements: OpenAI API access (for image generation and analysis) Google Sheets and Google Drive accounts Basic product images (URLs) as input The spreadsheet must contain a column named "Image-URL" with links to the product images This workflow automatically: Reads product image URLs from your Google Sheet Downloads the images for processing Analyzes each image to understand what product it contains Creates specialized photography prompts ensuring each product is shown with a human model Generates professional product photography using OpenAI's image generation capabilities Uploads results to Google Drive and updates your spreadsheet with links Extra: You can also use the included simple image generation workflow to directly create images via prompt without product image input. This option lets you quickly generate images through the OpenAI API using just text prompts

What it does This workflow scrapes the top 10 pages on SERP and conducts an in-depth analysis of the keyword intent for each ranking keyword, saving the information to a Google Sheet for further analysis. How does this workflow work? We add our keywords and country code to a Google sheet that we need to monitor and research on Run the system Scrape the top 10 pages Analyze the intents of the top 10 and update to a Google sheet Technical Setup Make a copy of this G sheet Add your desired keywords to the Google sheet Map keyword and country code Update the Zone name to match your zone on Bright Data Run the scraper Upon successful scraping, we run an intent classifier to determine the intents for each ranking page and update the G sheet. Setting up the Serp Scraper in Bright Data On Bright Data, go to the Proxies & Scraping tab Under SERP API, create a new zone Give it a suitable name and description. The default is serp_api Add this to your account Add your credentials as a header credential

How it works This workflow scrapes the latest Artificial Intelligence articles from TechCrunch, then processes and classifies the content using OpenAI and LangChain nodes. The final result is saved to Google Sheets and sent as a summary to a Telegram group. Workflow Logic: Trigger: Schedules daily at 6AM Bangkok time. Scraper: Extracts URLs and publish dates from TechCrunch's AI category. Filter: Only continues if the article is from yesterday (to avoid duplication). Content Fetch: Downloads and extracts article body text. AI Agent: Summarizes the article in Thai. Scores it using strict journalism criteria (max 100). Categorizes the news into one of 9 predefined categories. Output: Saves all structured data to Google Sheets. Sends a summary to a Telegram group. Set up steps 🕒 Estimated setup time: 10–15 minutes Connect your credentials: Google Sheets (OAuth2) Telegram OpenAI account (via LangChain model) Update the Telegram chatId and Google Sheets documentId/sheetName values. Deploy and activate the workflow. It runs daily without manual intervention.

Who is this for? This template is designed for internal support teams, product specialists, and knowledge managers who want to build an AI-powered knowledge assistant with retrieval-augmented generation (RAG) and reinforcement learning from human feedback (RLHF) via Telegram. What problem is this workflow solving? Manual knowledge management and answering support queries can be time-consuming and error-prone. This solution automates importing and indexing official documentation into MongoDB vector search and enhances AI responses with Telegram-based user feedback to continuously improve answer quality. What these workflows do Workflow 1: Document ingestion & indexing Manually triggered workflow imports product documentation from Google Docs. Documents are split into manageable chunks and embedded using OpenAI embeddings. Embedded document chunks are stored in MongoDB Atlas vector store to enable semantic search. Workflow 2: Telegram chat with RLHF feedback loop Listens for user messages via Telegram bot integration. Uses vector similarity search on MongoDB to retrieve relevant documentation chunks. Generates answers with OpenAI GPT-4o-mini model using retrieval-augmented generation. Sends answers back via Telegram and waits for user feedback (approval or disapproval). Captures feedback, maps it as positive or negative, and stores it with the conversation data for future model improvement. Setup Setting up vector embeddings Authenticate Google Docs and connect your Google Docs URL containing the product documentation you want to index. Authenticate MongoDB Atlas and connect the collection where you want to store the vector embeddings. Create a search index on this collection to support vector similarity queries. Ensure the index name matches the one configured in n8n (data_index). See the example MongoDB search index template below for reference. Setting up chat with Telegram RLHF Create a bot in Telegram with @botFather using the /newbot command. Connect the MongoDB database and search index used for vector search in the previous workflow. Also create two new collections in MongoDB Atlas: one for feedback and one for chat history. Create a search index for feedback, copying the provided template. Configure the AI system prompt in the “Knowledge Base Agent” node, making sure it references all three tools connected (productDocs, feedbackPositive, feedbackNegative) as provided in the template prompt. Make sure Product documentation and feedback collections must connect to the same MongoDB database. There are three distinct MongoDB collections: one for product documentation, one for feedback, and one for chat history (chat history collection can be separate). Telegram API credentials are valid and webhook URLs are correctly set up. MongoDB Search Index Templates Documentation Collection Index { "mappings": { "dynamic": false, "fields": { "_id": { "type": "string" }, "text": { "type": "string" }, "embedding": { "type": "knnVector", "dimensions": 1536, "similarity": "cosine" }, "source": { "type": "string" }, "doc_id": { "type": "string" } } } } Feedback Collection Index { "mappings": { "dynamic": false, "fields": { "prompt": { "type": "string" }, "response": { "type": "string" }, "text": { "type": "string" }, "embedding": { "type": "knnVector", "dimensions": 1536, "similarity": "cosine" }, "feedback": { "type": "token" } } } }