Workflow Templates

How It Works Form Submission: The workflow starts with the On form submission node, which triggers when a user submits a contact form. The form collects the user's name, email, and message. Text Classification: The Text Classifier node uses an AI model (GPT-4) to classify the submitted message into one of the predefined categories: Request Quote: For quote requests. Product info: For general product inquiries. General problem: For issues or problems related to products. Order: For questions about placed orders. Other: For any messages that don’t fit the above categories. Email Routing: Based on the classification, the workflow routes the message to the appropriate department via email: Prod. Dep.: For product-related inquiries. Quote Dep.: For quote requests. Gen. Dep.: For general problems. Order Dep.: For order-related questions. Other Dep.: For all other inquiries. Each email includes the user's name, email, message, and the classified category. Data Logging: The workflow logs the form submission and classification results into a Google Sheets document. Each department has its own sheet where the data is appended, including: User’s name, email, and message. Submission date and time. Assigned category. Email recipient details. AI Model Integration: The OpenAI node provides the AI model (GPT-4) used by the Text Classifier to classify the messages. The model is instructed to classify the text into one of the predefined categories without additional explanations. Set Up Steps Configure the Form Trigger: Set up the On form submission node to collect user inputs (name, email, and message) and trigger the workflow. Set Up the Text Classifier: Configure the Text Classifier node to use the OpenAI model (GPT-4) for text classification. Define the categories and their descriptions (e.g., "Request Quote", "Product info", etc.). Set the fallback category to "Other" for unclassifiable messages. Configure Email Sending: Set up the Email Send nodes for each department (Prod. Dep., Quote Dep., Gen. Dep., Order Dep., Other Dep.). Configure the email subject, body, and reply-to address using the form data and classification results. Ensure SMTP credentials are correctly configured for sending emails. Set Up Google Sheets Integration: Configure the Google Sheets nodes to append data to the appropriate sheets for each department. Map the form data (name, email, message, date, category, and recipient) to the corresponding columns in the Google Sheets document. Test the Workflow: Submit a test form to ensure the workflow correctly classifies the message, sends the email to the right department, and logs the data in Google Sheets. Verify that the OpenAI model is classifying messages accurately. Activate the Workflow: Once tested, activate the workflow to automate the process of handling contact form submissions. Key Features Automated Classification**: Uses AI to classify messages into relevant categories, reducing manual effort. Email Routing**: Sends emails to the appropriate department based on the classification. Data Logging**: Logs all form submissions and classification results in Google Sheets for tracking and analysis. Scalability**: Easily adaptable to additional categories or departments by modifying the workflow. This workflow is ideal for eCommerce businesses or customer support teams looking to automate and streamline the handling of contact form submissions. Need help customizing? Contact me for consulting and support or add me on Linkedin.

Are you looking to create a counseling chatbot that provides emotional support and mental health guidance through the LINE messaging platform ? This guide will walk you through connecting LINE with powerful AI language models like GPT-4 to build a chatbot that supports users in navigating their emotions, offering 24/7 conversational therapy and accessible mental health resources . By leveraging LINE's webhook integration and Azure OpenAI , this template allows you to design a chatbot that is both empathetic and efficient, ensuring users receive timely and professional responses. Whether you're a developer, counselor, or business owner, this guide will help you create a customizable counseling chatbot tailored to your audience's needs. Who Is This Template For? Developers who want to integrate AI-powered chatbots into the LINE platform for mental health applications. Counselors & Therapists looking to expand their reach and provide automated emotional support to clients outside of traditional sessions. Businesses & Organizations focused on improving mental health accessibility and offering innovative solutions to their users. Educators & Nonprofits seeking tools to provide free or low-cost counseling services to underserved communities. How this work? Line Webhook to receive new message Send loading animation in Line Check if the input is text or not Send the text as prompt in chat model (GPT 4o) Reply the message to user (you'll need 'edit field' to format it before reply) Pre-Requisites You have access to the LINE Developers Console. An Azure OpenAI account with necessary credentials. Set-up To receive messages from LINE, configure your webhook: Set up a webhook in LINE Developer Console. Copy the Webhook URL from the Line Chatbot node and paste it into the LINE Console. Ensure to remove any 'test' part when moving to production. The loading animation reassures users that the system is processing their request. Authorize using header authorization Message Handling Use the Check Message Type IsText? node to verify if the incoming message is text. If the message type is text, proceed with ChatGPT processing; otherwise, send a reply indicating non-text inputs are not supported. AI Agent Configuration Define the system message within the AI Agent node to guide the conversation based on desired interaction principles. Connect the Azure OpenAI Chat Model to the AI Agent. Formatting Responses Ensure responses are properly formatted before sending them back to the user. Reply Message Use the ReplyMessage - Line node to send the formatted response. Ensure proper header authorization using Bearer tokens.

This workflow is for automating and centralizing your bookmarking process using AI-powered tagging and seamless integration between your Android device and a self-hosted Read Deck platform (https://readeck.org/en/). This workflow eliminates manual entry, organizes links with smart AI-generated tags, and ensures your bookmarks are always accessible, searchable, and secure. How It Works 📱 Android Shortcut Integration Use the HTTP Shortcuts app to create a 1-tap trigger that sends URLs and titles from your Android phone directly to n8n. 🤖 AI-Powered Tagging & Processing Leverage ChatGPT-4 to analyze content context and auto-generate relevant tags (e.g., “Tech Tutorials,” “Productivity Tools”). Extract clean titles and URLs from messy shared data (even from apps like Twitter or Reddit). 🔗 Readeck Integration Automatically save processed bookmarks to your self-hosted Readeck-like platform with structured metadata (title, URL, tags). ⚡ Silent Automation It runs in the background—no pop-ups or interruptions. 🔒 Pro Security Optional authentication (API tokens, headers) to protect your data. Use Case Perfect for researchers, content creators, or anyone drowning in tabs who wants to: Save articles, videos, or social posts in one click. Organize bookmarks with AI-generated tags. Build a personal knowledge base that’s always accessible. Tutorial 1️⃣ Set Up Android Shortcut Install "HTTP Shortcuts" and configure it to send data to your n8n webhook. Enable “Share Menu” to trigger bookmarks from any app. 2️⃣ Configure n8n Workflow Import the template and add your Read Deck API token (or similar service). 3️⃣ Test & Scale Share a link from your phone—watch it appear in Read Deck instantly! Add error handling or notifications for advanced use. Note: For self-hosted platforms, ensure your instance is publicly accessible (or use a VPN). Why Choose This Workflow? Zero Manual Entry: Save hours of copying/pasting. AI Organization: Say goodbye to chaotic bookmark folders. Privacy First: Host your data on your terms. Transform your bookmarking chaos into a streamlined system—try “Save: Bookmark” today! 🚀

Track NFT market trends, collections, and trades in real time—directly from Telegram! This master workflow integrates the OpenSea API, GPT-4o-mini AI, and Telegram, allowing users to request natural-language NFT analytics and receive structured insights instantly. Whether you're an NFT trader, collector, or market analyst, this Telegram-native assistant brings you on-demand market intelligence—powered by OpenSea and AI. > ⚠️ Important: This workflow requires three sub-workflows to function properly. These must be downloaded and published in your n8n instance. 🧩 Required Sub-Workflows To activate this template, download and publish the following workflows: Analyze NFT Market Trends with AI-Powered OpenSea Analytics Agent Tool Get Real-time NFT Insights with OpenSea AI-Powered NFT Agent Tool Get Real-time NFT Marketplace Insights with OpenSea Marketplace Agent Tool 📌 You can also find these by visiting my Creator profile: 👉 https://n8n.io/creators/don-the-gem-dealer/ How It Works A Telegram bot receives a message (e.g., “Top sales for Azuki”). The AI router in this workflow determines which agent should process the request: Marketplace Agent → Listings, offers, and orders Analytics Agent → Sales volume, price trends, wallet behavior NFT Agent → Metadata, traits, ownership info The selected agent queries the OpenSea API using your API key. The response is processed using GPT-4o-mini, formatted, and sent back via Telegram. What You Can Do with This Agent 🔹 Discover undervalued NFTs based on trait rarity and price 🔹 Track market trends for any collection in real time 🔹 Compare collection performance by volume, sales, and listings 🔹 Analyze flipping trends and whale activity across wallets 🔹 Retrieve NFT ownership and metadata instantly 🔹 View trait-specific offers for insight into rarity-driven demand Example Queries You Can Use ✅ "What are the cheapest NFTs in the Pudgy Penguins collection?" ✅ "Get sales volume for Azuki and CloneX over the last 30 days." ✅ "Who owns Bored Ape #456?" ✅ "Show the best current offers for Moonbirds." Set Up Steps Create a Telegram Bot Use @BotFather to create your bot and get the API token. Get an OpenSea API Key Apply for your API key via the OpenSea Developer Portal. Configure n8n Credentials Add your Telegram Bot and OpenSea API Key under Credentials in n8n. Download Required Sub-Workflows Install and publish the following workflows: Analytics Agent Tool NFT Agent Tool Marketplace Agent Tool Deploy & Test Chat with your Telegram bot. Try: "Compare BAYC and Azuki volume" or "Show listings for Doodles." ✅ Final Notes > If your queries don’t respond correctly, make sure all three sub-workflows are installed and published, not just saved. 🚀 Dominate the NFT market with AI-powered OpenSea intelligence—right from your Telegram inbox!

Tags: Supply Chain, Logistics, Control Tower Context Hey! I’m Samir, a Supply Chain Engineer and Data Scientist from Paris, and the founder of LogiGreen Consulting. We design tools to help companies improve their logistics processes using data analytics, AI, and automation—to reduce costs and minimize environmental impact. > Let’s use N8N to build smarter and more sustainable supply chains! 📬 For business inquiries, you can add me on LinkedIn Who is this template for? This workflow template is designed for logistics operations that need a monitoring solution for their distribution chains. Connected to your Transportation Management Systems, this AI agent can answer any question about the shipments handled by your distribution teams. How does it work? The workflow is connected to a Google BigQuery table that stores outbound order data (customer deliveries). Here’s what the AI agent does: 🤔 Receives a user question via chat. 🧠 Understands the request and generates the correct SQL query. ✅ Executes the SQL query using a BigQuery node. 💬 Responds to the user in plain English. Thanks to the chat memory, users can ask follow-up questions to dive deeper into the data. What do I need to get started? This workflow requires no advanced programming skills. You’ll need: A Google BigQuery account with an SQL table storing transactional records. An OpenAI API key (GPT-4o) for the chat model. Next Steps Follow the sticky notes in the workflow to configure each node and start using AI to support your supply chain operations. 🎥 Watch My Tutorial 🚀 Curious how N8N can transform your logistics operations? Notes The chat trigger can easily be replaced with Teams, Telegram, or Slack for a better user experience. You can also connect this to a customer chat window using a webhook. This workflow was built using N8N version 1.82.1 Submitted: March 24, 2025

This is the workflow powering the n8n demo shown at StrapiConf 2022. The workflow searches matching Tweets every 30 minutes using the Interval node and listens to Form submissions using the Webhook node. Sentiment analysis is handled by Google using the Google Cloud Natural Language node before the result is stored in Strapi using the Strapi node. (These were originally two separate workflows that have been combined into one to simplify sharing.)

Task: Conditional filtering and branching items Why: Filtering and branching data based on conditions allows you to build complex workflows that work with more than one data flow scenario Main use cases: Filter out data that is not relevant for the rest of the workflow Split data to several branches of the workflow, where we want the data to be treated differently in the rest of the workflow

This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. Welcome to my Wikipedia Podcast Telegram Bot Workflow! This workflow creates an intelligent Telegram bot that transforms Wikipedia articles into engaging 5-minute podcast episodes using natural language queries and voice messages. What this workflow does This workflow processes incoming Telegram messages (text or voice, e.g. "Berlin") and generates professional podcast content about any Wikipedia topic (e.g. "Berlin", "Shakespeare", etc.). The AI agent researches the requested subject, creates a structured podcast script, and delivers it as high-quality audio directly through Telegram. Key Features: Voice message support (speech-to-text and text-to-speech) Wikipedia research integration for accurate content Professional podcast structure (intro, main content, outro) Natural-sounding AI voice synthesis Conversational and educational tone optimized for audio consumption This workflow has the following sequence: Telegram Trigger - Receives incoming messages (text or voice) from users via Telegram bot Text or Voice Switch - Routes the message based on input type (text message vs. voice message) Voice Message Processing (if voice input): Retrieval of voice file from Telegram Transcription of voice message to text using OpenAI Whisper Text Message Preparation (if text input) - Prepares the text message for the AI agent Wikipedia Podcast Agent - Core AI agent that: Researches the requested topic using Wikipedia tool Creates a professional 5-minute podcast script (600-750 words) Follows structured format: intro, main content, outro Uses conversational, accessible, and enthusiastic tone ElevenLabs Text to Speech - Converts the podcast script into natural-sounding audio using AI voice synthesis Send Voice Response - Delivers the generated podcast audio back to the user via Telegram Requirements: Telegram Bot API**: Documentation Create a bot via @BotFather on Telegram Get bot token and configure webhook Anthropic API** (Claude 4 Sonnet): Documentation Used for AI agent processing and podcast script generation Provides Wikipedia research capabilities OpenAI API**: Documentation Used for speech transcription (Whisper model) ElevenLabs API**: Documentation Used for high-quality text-to-speech generation Provides natural-sounding voice synthesis Important: The workflow uses the Wikipedia tool integrated with Claude 4 Sonnet to ensure accurate and comprehensive research. The AI agent is specifically prompted to create engaging, educational podcast content suitable for audio consumption. Configuration Notes: Update the Telegram chat ID in the trigger for your specific bot Modify the voice selection in ElevenLabs for different narrator styles The system prompt can be customized for different podcast formats or target audiences Supports both individual users and can be extended for group chats Feel free to contact me via LinkedIn, if you have any questions!

This n8n template showcases the new HTTP tool released in version 1.47.0. Overall, the tool helps simplify AI Agent workflows where custom sub-workflows were performing the same simple http requests. Comparisons 1. AI agent that can scrape webpages Remake of https://n8n.io/workflows/2006-ai-agent-that-can-scrape-webpages/ Changes: Replaces Execute Workflow Tool and Subworkflow Replaces Response Formatting 2. Allow your AI to call an API to fetch data Remake of https://n8n.io/workflows/2094-allow-your-ai-to-call-an-api-to-fetch-data/ Changes: Replaces Execute Workflow Tool and Subworkflow Replaces Manual Query Params Definitions Replaces Response Formatting

🧪 Binance SM 1hour Indicators Tool A precision trading signal engine that interprets 1-hour candlestick indicators for Binance Spot Market pairs using a GPT-4.1-mini LLM. Ideal for swing traders seeking directional bias and momentum clarity across medium timeframes. 🎥 Watch Tutorial: 🎯 Purpose This tool provides a structured 1-hour market read using: RSI** (Relative Strength Index) MACD** (Moving Average Convergence Divergence) BBANDS** (Bollinger Bands) SMA & EMA** (Simple and Exponential Moving Averages) ADX** (Average Directional Index) It’s invoked as a sub-agent in broader AI workflows, such as the Binance Financial Analyst Tool and the Spot Market Quant AI Agent. ⚙️ Key Features | Feature | Description | | ---------------------- | ------------------------------------------------------------- | | 🔄 Subworkflow Trigger | Runs only when called by parent agent (not standalone) | | 🧠 GPT-4.1-mini LLM | Translates numeric indicators into natural-language summaries | | 📊 Real-time Data | Pulls latest 40×1h candles via internal webhook from Binance | | 📥 Input Format | { "message": "ETHUSDT", "sessionId": "telegram_chat_id" } | | 📤 Output Format | JSON summary + Telegram-friendly HTML overview | 💡 Example Output 📊 1h Technical Overview – ETHUSDT • RSI: 59 (Neutral) • MACD: Bullish Crossover • BBANDS: Price at Upper Band • EMA > SMA → Positive Slope • ADX: 28 → Moderate Trend Strength 🧩 Use Cases | Scenario | Result | | -------------------------------------- | ----------------------------------------------- | | Mid-frame market alignment | Verifies momentum between 15m and 4h timeframes | | Quant AI Agent input | Supplies trend context for entry/exit decisions | | Standalone medium-term signal snapshot | Validates swing trade setups or filters noise | 📦 Installation Instructions Import workflow into your n8n instance Confirm internal webhook /1h-indicators is live and authorized Insert your OpenAI credentials for GPT-4.1-mini node Use only when triggered via: Binance Financial Analyst Tool Binance Spot Market Quant AI Agent 🧾 Licensing & Support 🔗 Don Jayamaha – LinkedIn linkedin.com/in/donjayamahajr © 2025 Treasurium Capital Limited Company Architecture, prompts, and signal logic are proprietary. Redistribution or commercial use requires explicit licensing. No unauthorized cloning permitted.

Adobe developer API Did you know that Adobe provides an API to perform all sort of manipulation on PDF files : Split PDF, Combine PDF OCR Insert page, delete page, replace page, reorder page Content extraction (text content, tables, pictures) ... The free tier allows up to 500 PDF operation / month. As it comes directly from Adobe, it works often better than other alternatives. Adobe documentation: https://developer.adobe.com/document-services/docs/overview/pdf-services-api/howtos/ https://developer.adobe.com/document-services/docs/overview/pdf-extract-api/gettingstarted/ What does this workflow do The API is a bit painful to use. To perform a transformation on a PDF it requires to Authenticate and get a temporal token Register a new asset (file) Upload you PDF to the registered asset Perform a query according to the transformation requested Wait for the query to be proccessed by Adobe backend Download the result This workflow is a generic wrapper to perform all these steps for any transformation endpoint. I usually use it from other workflow with an Execute Workflow node. Examples are given in the workflow. Example use case This service is useful for example to clean PDF data for an AI / RAG system. My favorite use-case is to extract table as images and forward images to an AI for image recognition / description which is often more accuarate than feedind raw tabular data to a LLM.

This workflow is created by AI developers at WeblineIndia. It streamlines the process of managing content by automatically identifying and fetching the most recently added Google Doc file from your Google Drive. It extracts the content of the document for processing and leverages an AI model to generate a concise and meaningful summary of the extracted text. The summarized content is then stored in a designated Google Sheet, alongside relevant details like the document name and the date it was added, providing an organized and easily accessible reference for future use. This automation simplifies document handling, enhances productivity, and ensures seamless data management. Steps : Fetch the Most Recent Document from Google Drive Action:** Use the Google Drive Node. Details:** List files, filter by date to fetch the most recently added .doc file, and retrieve its file ID and metadata. Extract Content from the Document Action:** Use the Google Docs Node. Details:** Set the operation to "Get Content," pass the file ID, and extract the document's text content. Summarize the Document Using an AI Model Action:** Use an AI Model Node (e.g., OpenAI, ChatGPT). Details:** Provide the extracted text to the AI model, use a prompt to generate a summary, and capture the result. Store the Summarized Content in Google Sheets Action:** Use the Google Sheets Node. Details:** Append a new row to the target sheet with details such as the original document name, summary, and date added. About WeblineIndia WeblineIndia specializes in delivering innovative and custom AI solutions to simplify and automate business processes. If you need any help, please reach out to us.