Workflow Templates

This n8n workflow shows how using multimodal LLMs with AI vision can tackle tricky image validation tasks which are near impossible to achieve with code and often impractical to be done by humans at scale. You may need image validation when users submitted photos or images are required to meet certain criteria before being accepted. A wine review website may require users only submit photos of wine with labels, a bank may require account holders to submit scanned documents for verification etc. In this demonstration, our scenario will be to analyse a set of portraits to verify if they meet the criteria for valid passport photos according to the UK government website (https://www.gov.uk/photos-for-passports). How it works Our set of portaits are jpg files downloaded from our Google Drive using the Google Drive node. Each image is resized using the Edit Image node to ensure a balance between resolution and processing speed. Using the Basic LLM node, we'll define a "user message" option with the type of binary (data). This will allow us to pass our portrait to the LLM as an input. With our prompt containing the criteria pulled off the passport photo requirements webpage, the LLM is able to validate the photo does or doesn't meet its criteria. A structured output parser is used to structure the LLM's response to a JSON object which has the "is_valid" boolean property. This can be useful to further extend the workflow. Requirements Google Gemini API key Google Drive account Customising this workflow Not using Gemini? n8n's LLM node works with any compatible multimodal LLM so feel free to swap Gemini out for OpenAI's GPT4o or Antrophic's Claude Sonnet. Don't need to validate portraits? Try other use cases such as document classification, security footage analysis, people tagging in photos and more.

How it works Trigger: Listens for an incoming chat message Copy Assistant: Feeds the message (plus memory) into an OpenAI Chat Model and exposes two “tools” Cold Email Writer Tool Sales Letter Tool• Tool execution: Depending on the user’s intent, the appropriate tool generates the copy • Save output: Writes the generated email or sales letter into your target document via the Update a document node Set up steps • Configure your OpenAI Chat Model credentials in n8n (no hard-coded keys!) • Add and authenticate the Simple Memory credential (to keep context across messages) • Create Google Docs (or MS Word) credentials for the Update a document node • Ensure your Chat trigger is pointing at your incoming-message endpoint • Mandatory: Drop sticky-note annotations on each tool node explaining where to enter API keys and how to tweak prompts Once everything’s wired up, send a test chat message like “Write me a cold email for a fintech startup” and watch the workflow spin up a polished draft in your document. How to use Import the workflow JSON into n8n. Configure your Chat trigger (webhook or form) to receive incoming messages. Send a chat prompt like: “Write me a cold email for a B2B SaaS offering.” The “Copy Assistant” custom GPT picks the right tool (Cold Email or Sales Letter). Generated copy is written directly into your linked Google Doc or Word document. Requirements OpenAI API Key (with Chat Completions & Custom GPTs enabled) Custom Assistant created in your ChatGPT dashboard (Assistant ID pasted into the Chat Model node) n8n instance (Cloud or self-hosted) with credentials set up for: Simple Memory (to persist context) Google Docs or Microsoft Word (for document output) Customising this workflow Tweak system and user prompts inside the Copy Assistant node to fit your brand voice. Swap in Slack, Teams or email nodes instead of a document writer to deliver copy where you need it. Add or remove tools (e.g., “Follow-up Email Writer”) by duplicating the existing tool pattern. Use sticky-note annotations on every node to explain where to enter API keys, Assistant IDs, or prompt tweaks.

Idea The idea for app came since I wanted to build a unique gift for my niece because she gets excited for her birthday (which Im going to miss this year). The web app has a simple countdown (in html and JS) but more importantly, there is an AI agent that will answer some specific questions and know her preferences. How it works The questions from app are sent via web hook to N8N which has pulls preferences file (about her likes, dislikes, personality) from postgre and AI Agent that will answer questions/respond. The current status is stored back in postgre (especially about status of cat and universe happenings) before responding back. Features Integrated AI chatbot via N8N webhook Persistent conversation history Minimizable chat interface Fallback support for offline testing Features: -- Wheres Mittens - This is a query to track her lost cat in multiverse. -- Multiverse updates with recent update stored Pre Requisites Postgre SQL database is available. Alternatively, use any other database but change the N8N nodes. LLM Api Key. Step by Step Instructions Export this N8N Workflow. Modify LLM API Key, I used openAI, 4.1 For web app scofflding,you will need Node, HTML and Javascript. I've created a mini version using Node and JS with web app and N8N connection settings here: <https://github.com/productiser/FiBirthdayAgent> PostgreSQL Database Script (1 table for memory and context storage): CREATE TABLE fifi_world_context ( id TEXT PRIMARY KEY, -- e.g., 'agent_fifi' cat_location TEXT, -- e.g., "Bubble Nebula" cat_activity TEXT, -- e.g., "Playing laser tag with moon mice" fifi_preferences JSONB, -- e.g., likes/dislikes/foods/shows world_history TEXT, -- Summary of narrative events last_updated TIMESTAMP DEFAULT CURRENT_TIMESTAMP ); 5.Modify system prompt as per your needs. Built With N8N Self hosted Self hosted web app Hosted on Vercel Total spend = <£1 (AI costs only) Total Time = <1 day Support Watch this video for web app overview and how it looks. <https://youtu.be/e7PlrTdvwoM> Contact me on info@pankstr.com/ superllmuser@gmail.com for any queries Hope you enjoy!!

Automate Telegram Chat Responses Using Google Gemini By WeblineIndia* ⚡ TL;DR (Quick Steps) Create a Telegram bot using @BotFather and copy the API Token. Obtain Google Gemini API Key via Google Cloud. Set up the n8n workflow: Trigger: Telegram message received. AI Model: Google Gemini generates response. Output: AI reply sent back to user via Telegram. Customize the system prompt, model, or message handling to suit your use case. 🧠 Description This n8n workflow enables seamless automation of real-time chat replies in Telegram by integrating with Google Gemini's Chat Model. Every time a user sends a message to your Telegram bot, the workflow routes it through the Gemini AI, which analyzes and crafts a professional response. This reply is then automatically delivered back to the user. The setup acts as a lightweight but powerful chatbot system — ideal for businesses, customer service, or even personal productivity bots. You can easily modify its tone, intelligence level, or logging mechanisms to cater to specific domains such as sales, tech support, or general Q&A. 🎯 Purpose of the Workflow The primary goal of this workflow is to automate intelligent, context-aware chat responses in Telegram using a robust AI model. It eliminates manual reply handling, enhances user engagement, and ensures 24/7 interaction capabilities — all through a no-code or low-code setup using n8n. 🛠️ Steps to Configure and Use ✅ Pre-Conditions / Requirements Telegram Bot Token**: Get it from @BotFather. Google Gemini API Key**: Available via Google Cloud PaLM/Gemini API access. n8n Instance**: Hosted or local instance with required nodes installed (Telegram, Basic LLM Chain, and Google Gemini support). 🔧 Setup Instructions Step 1: Telegram Trigger – Listen for Incoming Messages Add Telegram Trigger node. Select Trigger On: Message. Authenticate using your Telegram Bot Token. This will capture incoming messages from any user interacting with your bot. Step 2: Google Gemini AI – Generate a Smart Reply Add the Basic LLM Chain node. Connect the input message ({{$json.message.text}}) from the Telegram Trigger. System Prompt: > "You are an AI assistant. Reply to the following user message professionally:" Choose Google Gemini Chat Model (models/gemini-1.5-pro). Connect this node to receive the text input and pass it to Gemini for processing. Step 3: Telegram Reply – Send the AI Response Add a Telegram node (Operation: Send Message). Set Chat ID dynamically from the Telegram Trigger node. Input the generated message from the Gemini output. Enable Parse Mode as HTML for rich formatting. Final Step: Link All Nodes Receive Telegram Message → Generate AI Response → Send Telegram Reply. > Tip: Test the workflow by sending a message to your Telegram bot and ensure you receive an AI-generated reply. 🧩 Customization Guidance ✏️ Modify the AI tone by updating the system prompt. 🤖 Use other AI models (e.g., OpenAI GPT-4o). 🔍 Add filters to respond differently based on specific keywords. 📊 Extend the workflow to store chats in Google Sheets, Airtable, or databases for audit or analytics. 🌐 Multi-language support: Add translation layers before and after AI processing. 🛠️ Troubleshooting Guide No message received?** Check if your Telegram bot is active and webhook is working. AI not responding?** Validate your Google Gemini API key and usage quota. Wrong replies?** Refine the system prompt or validate message routing. Formatting issues?** Ensure Parse Mode is correctly set to HTML. 💡 Use Case Examples Customer Service Chatbot** for product queries. Educational Bots** for answering user questions on a topic. Mental Health Companion** that gives supportive replies. Event-based Announcers** or automatic responders during off-hours. > And many more! This workflow can be easily extended to support advanced use cases with just a few additional nodes. 👨‍💻 About the Creator This workflow is developed by WeblineIndia, a trusted provider of AI development services and process automation solutions. If you're looking to build or customize intelligent workflows like this, we invite you to get in touch with our team. We also offer specialized Python development and AI developer hiring services to supercharge your automation needs.

This workflow template, "Daily Gratitude Reminder Bot for LINE," is designed to help users cultivate a habit of gratitude by sending personalized, AI-generated reminders every evening at 9:00 PM. Using Azure OpenAI , the bot generates varied and engaging messages to prompt users to reflect on the positive aspects of their day. The reminders are then sent directly to users via the LINE messaging platform , ensuring a seamless and impactful experience. Whether you're a developer, counselor, or business owner, this template offers a customizable and scalable solution for promoting mental wellness and fostering a culture of gratitude. profile Qwen2.5-Max 2:56 pm Here’s a polished and detailed description for your "Daily Gratitude Reminder Bot for LINE" template, following the submission guidelines provided. This description is structured to meet all the requirements, including SEO optimization, clarity, and user convenience. Daily Gratitude Reminder Bot for LINE This workflow template, "Daily Gratitude Reminder Bot for LINE," is designed to help users cultivate a habit of gratitude by sending personalized, AI-generated reminders every evening at 9:00 PM. Using Azure OpenAI , the bot generates varied and engaging messages to prompt users to reflect on the positive aspects of their day. The reminders are then sent directly to users via the LINE messaging platform , ensuring a seamless and impactful experience. Whether you're a developer, counselor, or business owner, this template offers a customizable and scalable solution for promoting mental wellness and fostering a culture of gratitude. Who Is This Template For? Developers who want to integrate AI-powered workflows into messaging platforms like LINE. Counselors & Therapists looking to encourage mindfulness and emotional well-being among their clients. Businesses & Organizations focused on employee wellness or customer engagement through positive reinforcement. Educators & Nonprofits seeking tools to promote mental health awareness and self-care practices. What Problem Does This Workflow Solve? Gratitude journaling has been proven to improve mental health, reduce stress, and increase overall happiness. However, many people struggle to maintain the habit due to busy schedules or forgetfulness. This workflow solves that problem by automating daily reminders to reflect on positive experiences, making it easier for users to build and sustain a gratitude practice. What This Workflow Does Scheduled Trigger: The workflow is triggered every evening at 9:00 PM using a schedule node. AI-Powered Message Generation: An Azure OpenAI Chat Model generates a unique and engaging reminder message with a temperature setting of 0.9 to ensure variety and creativity. Message Formatting: The generated message is reformatted to comply with the LINE Push API requirements, ensuring smooth delivery. Push Notification via LINE: The formatted message is sent to the user via the LINE Push API , delivering the reminder directly to their chat. Setup Guide Pre-Requisites Access to an Azure OpenAI account with credentials. A LINE Developers Console account with access to the Push API. Basic knowledge of n8n workflows and JSON formatting. How to Customize This Workflow to Your Needs Change the Time: Adjust the schedule trigger to send reminders at a different time. Modify the Prompt: Edit the AI model's input prompt to generate messages tailored to your audience (e.g., focus on work achievements or personal growth). Expand Recipients: Update the LINE Push API node to send reminders to multiple users or groups. Integrate Additional Features: Add nodes to log user responses or track engagement metrics. Why Use This Template? Promotes Mental Wellness: Encourages users to reflect on positive experiences, improving emotional well-being. Highly Customizable: Easily adapt the workflow to suit different audiences and use cases. Scalable: Send reminders to one user or thousands, making it suitable for both personal and organizational use. AI-Powered Creativity: Avoid repetitive messages by leveraging AI to generate fresh and engaging content.

Built this for a dedicated Slack outage-notifications channel — works well on both desktop and mobile. This is for: IT Administrators & small MSPs looking to streamline M365 alerts from one or multiple mailboxes into a single or specific Slack channels IT Admins who prefer ChatOps over management-by-email What does it do Scans for M365 outage alerts emails (every 1 min) Checks if it impacts a specific user region (if the alert calls it out, countries have to be manually set) Summarizes the incident using OpenAI o4-mini (cheap model - or you can swap for local Ollama) Sends a Slack Block to your outage channel with incident link (can be extended) Deletes the original alert email after successful delivery Credentials Outlook: Create an Outlook credential (OAuth2.0) to point to the mailbox (regular or shared) where M365 service alerts will be received Slack: Create a Slack bot credential with access to the slack channel you want updates posted to OpenAI: Create a OpenAI credential that has access to the GPT-4O-MINI model. Recommend you use projects in OpenAI so that you may set a per-project-budget and not impact other projects. Review this OpenAI documentation for more info on managing Projects in the API portal. Expect this to consume no more than 1-2 cents per month on average. Setup Download & import the workflow Modify the first Outlook block (Check for 365 Service Alert) to use the Outlook credential Modify the OpenAI block's system prompt to call out the countries your users reside in ie. "- Assume the organization has users primarily in the U.S. and Australia. If those regions are affected, state: "Your users may have been affected." Otherwise, add: "No impact expected for your user base."" ← swap U.S. & Australia for desired countries Modify the Slack block (Post outage to Slack) to specify the channel updates will be posted to Sample Slack Output Workflow Diagram

WordPress Post Auto-Categorization Workflow 💡 Click here to read detailed case study 📺 Click here to watch youtube tutorial 🎯 Purpose Automatically categorize WordPress blog posts using AI, saving hours of manual work. This workflow analyzes your post titles and assigns them to predefined categories using artificial intelligence. 🔄 What This Workflow Does • Connects to your WordPress site • Retrieves all uncategorized posts • Uses AI to analyze post titles • Automatically assigns appropriate category IDs • Updates posts with new categories • Processes dozens of posts in minutes ⚙️ Setup Requirements WordPress site with admin access Predefined categories in WordPress OpenAI API credentials (or your preferred AI provider) n8n with WordPress credentials 🛠️ Configuration Steps Add your WordPress categories (manually in WordPress) Note down category IDs Update the AI prompt with your category IDs Configure WordPress credentials in n8n Set up AI API connection 🔧 Customization Options • Modify AI prompts for different categorization criteria • Adjust for multiple category assignments • Add tag generation functionality • Customize for different content types • Add additional metadata updates ⚠️ Important Notes • Backup your WordPress database before running • Test with a few posts first • Review AI categorization results initially • Categories must be created manually first 🎁 Bonus Features • Can be modified for tag generation • Works with scheduled posts • Handles bulk processing • Maintains categorization consistency Perfect for content managers, bloggers, and website administrators looking to organize their WordPress content efficiently. #n8n #WordPress #ContentManagement #Automation #AI Created by rumjahn

This n8n workflow template allows you to upload a photo to a SharePoint folder using the Microsoft Graph API. The workflow includes steps for authentication, retrieving a photo for testing purposes, setting the destination folder and file name, and uploading the photo. Who is this for? This workflow is ideal for users who need to automate the process of uploading images to SharePoint. It is particularly useful for developers, IT administrators, and anyone managing digital assets within a SharePoint environment. What problem is this workflow solving? / Use Case This workflow addresses the need to automate the uploading of photos to a specific SharePoint folder. By using the Microsoft Graph API, it ensures secure and efficient file management, reducing manual effort and potential errors. What this workflow does Trigger the Workflow: The workflow starts when the user clicks the 'Test workflow' button. Set Configuration: Sensitive data such as TENANT_ID, CLIENT_ID, and CLIENT_SECRET are set. Authentication: Obtains an access token from Microsoft Graph API using the provided credentials. Get Photo: Retrieves a sample photo from a URL for testing purposes. Set Destination: Sets the target folder and file name for the photo upload. Upload Photo: Uploads the photo to the specified SharePoint folder using the Microsoft Graph API. Setup Prerequisites Create an Application User: Follow this guide to create an application user. Set Permissions: Ensure the following permissions are set: Sites.ReadWrite.All: For SharePoint site access. Files.ReadWrite.All: For file upload operations. Authentication For successful authentication, provide the following: TENANT_ID CLIENT_ID CLIENT_SECRET Note: For demonstration purposes, these values are stored in a 'Set' node. In a production environment, ensure the safety of such data using credentials, secure vaults, or other safe methods. Set Destination The destination is defined by two parameters: TARGET_FOLDER: The folder path in SharePoint where the photo will be uploaded. FILE_NAME: The name of the file to be uploaded. Example: Desired file location: https://contoso.sharepoint.com/uploads/pictures from n8n/example.jpg Set the following: TARGET_FOLDER = /uploads/pictures from n8n FILE_NAME = example.jpg How to Customize This Workflow to Your Needs Update Sensitive Data: Replace the placeholder values for TENANT_ID, CLIENT_ID, and CLIENT_SECRET with your actual credentials. Change Destination: Modify the TARGET_FOLDER and FILE_NAME parameters to match your desired upload location and file name. Test with Different Photos: Update the URL in the 'Get Photo' node to test with different images. Sticky Notes Workflow Overview This sticky note explains the overall purpose and dependencies of the workflow. Authentication Details This sticky note provides details on the authentication process and the importance of securing sensitive data. Set Destination Details This sticky note explains how to set the destination folder and file name for the photo upload. By following these guidelines, you can easily customize and use this workflow to automate photo uploads to SharePoint using the Microsoft Graph API.

This workflow syncs Outlook Calendar events to a Notion database. The Outlook Calendar event must be within a specific time frame (default of within next year) for the workflow to pick up the event. The event subject will be the title of the Notion page, and the event link will be added to the Notion page as a property. Prerequisites Notion account and Notion credentials. Microsoft account and Microsoft credentials. How it works On scheduled intervals, find all Outlook Calendar events within a specific time frame. For each event, check if the event already exists in the Notion database. If it does not exist, create a new page in the Notion database, otherwise update the existing page. Setup This workflow requires that you set up a Notion database or use an existing one with at least the following fields: Title (title) Date (date) Event ID (text) Link (URL)

How it works Trigger the workflow manually via the n8n UI. Define key parameters like the image prompt, number of images, size, quality, and model. Send a POST request to OpenAI’s image generation API using those inputs. Split the API response to handle multiple images. Convert the base64 image data into downloadable binary files. Set up steps Initial setup takes around 5–10 minutes. You’ll need an OpenAI API key, a configured HTTP Request node with credentials, and to customize the prompt/parameter fields in the “Set Variables” node. No advanced config or external services needed. Important Note You have to make sure to complete OpenAI's new verification requirements to use their new image API: https://help.openai.com/en/articles/10910291-api-organization-verification It only takes a few minutes and does not cost any money.

Enhance Query Resolution with the Knowledge Base Tool! Our KB Tool - Confluence KB is crafted to seamlessly integrate into the IT Ops AI SlackBot Workflow, enhancing the IT support process by enabling sophisticated search and response capabilities via Slack. Workflow Functionality: Receive Queries**: Directly accepts user queries from the main workflow, initiating a dynamic search process. AI-Powered Query Transformation**: Utilizes OpenAI's models or local ai to refine user queries into searchable keywords that are most likely to retrieve relevant information from the Knowledge Base. Confluence Integration**: Executes searches within Confluence using the refined keywords to find the most applicable articles and information. Deliver Accurate Responses**: Gathers essential details from the Confluence results, including article titles, links, and summaries, preparing them to be sent back to the parent workflow for final user response. To view a demo video of this workflow in action, click here. Quick Setup Guide: Ensure correct configurations are set for OpenAI and Confluence API integrations. Customize query transformation logic as per your specific Knowledge Base structure to improve search accuracy. Need Help? Dive into our Documentation or get support from the Community Forum! Deploy this tool to provide precise and informative responses, significantly boosting the efficiency and reliability of your IT support workflow.

Who is this for? This workflow is perfect for marketers, SEO specialists, product teams, and competitive analysts who want to monitor and summarize public reviews of their competitors. It’s especially helpful for small teams who want fast insights from Google reviews without spending hours manually reading and sorting them. What problem is this workflow solving? Manually going through competitor reviews is time-consuming and repetitive. You risk missing patterns or insights, and it’s hard to share summaries with your team quickly. This workflow automatically scrapes reviews from Google and generates a structured summary of pain points and positive feedback. That way, you can focus on strategy instead of sorting through dozens of reviews. What this workflow does This automation watches for new competitor entries in a Google Sheet, then: Uses Dumpling AI to scrape the latest Google reviews (up to 20) for each business. Splits and cleans the reviews for analysis. Sends them to GPT-4o, which summarizes the most common complaints and praises. Saves the structured result back to the same Google Sheet. You’ll instantly get an overview of what people are saying about any competitor. Setup Google Sheet Setup Create a Google Sheet with at least one column: Business Add names or search queries for the competitors you want to analyze Optional: Add columns for Summary of Reviews and Pain Points Connect Dumpling AI Sign up at Dumpling AI Create an agent using the get-google-reviews endpoint Copy your agent key Use it in the HTTP Request node in this workflow OpenAI Setup Use your API key with GPT-4o access The prompt is already structured to generate grouped summaries from reviews Run the Workflow Trigger it manually or schedule it Make sure your Google Sheets, OpenAI, and Dumpling AI connections are active How to customize this workflow to your needs You can expand the number of reviews retrieved by changing the Dumpling AI agent config Replace Google Sheets with Airtable if you want more robust data views Add more fields like star ratings or review dates in your agent for richer analysis Change the GPT prompt to highlight emotional tone, urgency, or feature mentions 🧠 Node Details Google Sheets Trigger**: Watches for new competitor names HTTP Request (Dumpling AI)**: Scrapes 20 recent reviews from Google SplitOut Node**: Breaks review array into individual items Code Node**: Extracts and combines review text Edit Fields Node**: Structures the review content before GPT GPT-4o Node**: Analyzes and summarizes top pain points and praise Google Sheets Output**: Saves the summary back to the same sheet Dependencies Dumpling AI account and review scraping agent setup OpenAI API key with GPT-4o access Google Sheets OAuth2 credentials