Workflow Templates

Workflow Description: Turn a simple text idea into production-ready icons in seconds. With this workflow, you input a subject (e.g., “Copy”, “Banana”, “Slack Mute”), select a style (Flat, 3D, Cartoon, etc.), and off it goes. Here’s what happens: A form trigger collects your icon subject, style and optional background. The workflow uses an LLM to construct an optimised prompt. An image-generation model (OpenAI image API) renders a transparent-background, 400×400 px PNG icon. The icon is automatically uploaded to Google Drive, and both a download link and thumbnail are generated. A styled completion card displays the result and gives you a “One More Time” option. Perfect for designers, developers, no-code creators, UI builders and even home-automation geeks (yes, you can integrate it with Home Assistant or Stream Deck!). It saves you the manual icon-hunt grind and gives consistent visual output across style variants. 🔧 Setup Requirements: n8n instance (self-hosted or cloud) OpenAI API access (image generation enabled) Google Drive credentials (write access to a folder) (Optional) Modify to integrate Slack, Teams or other file-storage destinations ✅ Highlights & Benefits: Fully automated prompt creation → consistent icon quality Transparent background PNGs size-ready for UI use Saves icons to Drive + gives immediate link/thumbnail Minimal setup, high value for creative/automation workflows Easily extendable (add extra sizes, style presets, share via chat/bot) ⚠️ Notes & Best-Practices: Check your OpenAI image quota and costs - image generation may incur usage. Confirm Google Drive folder permissions to avoid upload failures. If you wish a different resolution or format (e.g., SVG), clone the image node and adjust parameters.

How it works • Webhook → urlscan.io → GPT-4o mini → Gmail • Payload example: { "url": "https://example.com" } • urlscan.io returns a Scan ID and raw JSON. • AI node classifies the scan as malicious / suspicious / benign, assigns a 1-10 risk score, and writes a two-sentence summary. • Gmail sends an alert that includes the URL, Scan ID, AI verdict, screenshot link, and full report link. Set-up steps (~5 min) • Create three credentials in n8n urlscan.io API key OpenAI API key (GPT-4o mini access) Gmail OAuth (or SMTP) • Replace those fields in the nodes, or reference env vars like {{ $env.OPENAI_API_KEY }}. • Switch the Webhook to Production → copy the live URL. • Test with: curl -X POST <your-webhook-url> \ -H "Content-Type: application/json" \ -d '{ "url": "https://example.com" }'

Ask natural-language questions about your Monday.com tasks (e.g., “Which tasks are overdue?”, “Show me all items stuck”, “Summarize what’s due this week”). The assistant fetches real data from your Monday.com board and answers based only on that. ⚙️ Setup Instructions 1️⃣ Set Up OpenAI Connection Go to OpenAI Platform Navigate to OpenAI Billing Add funds to your billing account Copy your API key into the OpenAI credentials in n8n 2️⃣ Connect Monday.com Node In Monday.com → go to your Admin → API Copy your Personal API Token Docs: Generate Monday API Token In n8n → Credentials → New → Monday.com API Paste your token and save. Open the Get many items node → choose your credential → select your Board ID and Group ID. 🧠 How it works Sample Chatbot**: webhook/chat trigger for your questions Get many items (Monday.com)**: pulls board/group tasks Set Fields → Combine → Convert to text**: formats task data OpenAI Chat Model + Memory**: lets you ask questions and keeps context across turns Chat with Monday.com**: generates the final AI answer 📬 Contact Need help customizing this for your own board structure? 📧 robert@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com

*Use Case: * Analyze images with multiple subjects. In this use case I have a bookshelf and am extracting and verifying book titles/authors from a bookshelf photo. *How it works: * 1) Webhook receives an image url from a front end in which a user can upload a picture. In this use case, it is an image of a book shelf. 2) Edit Field (Set): Saves image in a consistent location so AI can find it. 3) Analyze Image: Image is analyzed. Extracts titles from the book spines 4) Code: Splits extracted subjects to single item to be able to validate each item separately. Books are individualized to their own entity 5) *HTTP Request *validates each subject. Queries Google Books to validate books in case only partial titles were found. 6) Edit Field (Set): Tidies the result. 7) Code: Aggregates and deduplicates Titles and authors are aggregate into a list 8) Respond to Webhook returns list to front end How to use: Use with a frontend that can capture images and receive back the result. For this use case Supabase was used to store images from which the image analyzer could reference.

This workflow automates the process of writing tailored cover letters for job applications. It: Uses Apify’s Indeed Scraper to pull live job postings based on your chosen search term. Sends the job description along with your resume into OpenAI, which writes an optimized cover letter — one paragraph plus bullet points — only using details from your resume. Perfect for quickly generating professional, customized cover letters for each role you want to apply to. ⚙️ Setup Instructions 1️⃣ Set Up OpenAI Connection Go to OpenAI Platform Navigate to OpenAI Billing Add funds to your billing account Copy your API key into the OpenAI credentials in n8n 2️⃣ Set Up Apify Connection Go to Apify Console and sign up/login Get your API token here: Apify API Keys Set up this scraper in your Apify account: Indeed Scraper In n8n, create a HTTP Query Auth credential Query Key: token Value: YOUR_APIFY_API_KEY Attach this credential to the HTTP Request node (Search Indeed) 📬 Contact Information Need help customizing this workflow or building similar automations? 📧 robert@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com

This workflow creates a multilingual eCommerce chatbot that automatically detects the customer’s language and provides tailored responses. It is designed for online shops to improve customer support in English, Spanish, and French. The chatbot is powered by OpenAI’s GPT-5 Nano and runs entirely inside n8n, with built-in memory to keep conversations contextual and helpful. 🔑 Key Features Language Detection**: Identifies customer language automatically (English, Spanish, or French). Localized Responses**: Uses pre-defined system prompts for each language. Customer Support Ready**: Handles product questions, order tracking, returns, and general inquiries. Human Handoff**: If details are missing, it guides the user to contact human support. Conversation Memory**: Tracks sessions for smoother, contextual replies. ⚙️ Setup Instructions 1️⃣ Set Up OpenAI Connection Get API Key Go to OpenAI Platform Go to OpenAI Billing Add funds to your billing account Copy your API key into the OpenAI credentials in n8n 2️⃣ Configure Your Languages & Prompts Open the Set Node named Ecommerce Language Prompts. Update or expand the list of languages and their system prompts. Example already includes: English Spanish French That’s it! Your chatbot is ready to run 🎉 📬 Contact Information Need help customizing this workflow or building similar automations? 📧 Email: robert@ynteractive.com 🔗 LinkedIn: Robert Breen 🌐 Website: ynteractive.com

Turn Crisp chats into Helpdocs Automatically create help articles from resolved Crisp chats. This n8n workflow listens for chat events, formats Q&A pairs, and uses an LLM to generate a PII‑safe helpdoc saved to a Data Table. Highlights 🧩 Trigger: Crisp Webhook when a chat is marked resolved. 🗂️ Store: Each message saved in a Data Table (crisp). 🧠 Generate: LLM turns Q&A into draft helpdoc. 💾 Save: Draft stored in another Data Table (crisphelp) for review. How it works Webhook receives message:send, message:received, and state:resolved events from Crisp. Data Table stores messages by session_id. On state:resolved, workflow fetches the full chat thread. Code node formats messages into Q: and A: pairs. LLM (OpenAI gpt-4.1-mini) creates a redacted helpdoc. Data Table crisphelp saves the generated doc with publish = false. Requirements Crisp workspace with webhook access (Settings → Advanced → Webhooks) n8n instance with Data Tables and OpenAI credentials Customize Swap the model in the LLM node. Add a Slack or Email node after store-doc to alert reviewers. Extend prompt rules to strengthen PII redaction. Tips Ensure Crisp webhook URL is public. Check IF condition: {{$json.body.data.content.namespace}} == "state:resolved". Use the publish flag to control auto‑publishing. Category: AI • Automation • Customer Support

Create a Telegram bot that answers questions using AI-powered web search from Linkup and an LLM agent (GPT-4.1). This template handles both text and voice messages (voice transcribed via a Mistral model by default), routes queries through an agent that can call a Linkup tool to fetch up-to-date information from the web, and returns concise, Telegram-friendly replies. A security switch lets you restrict use to a single Telegram username for private testing, or remove the filter to make the bot public. Who is this for? Anyone needing quick answers:** Build a personal assistant that can look up current events, facts, and general knowledge on the web. Support & ops teams:** Provide quick, web-sourced answers to user questions without leaving Telegram. Developers & automation engineers:** Use this as a reference for integrating agents, transcription, and web search tools inside n8n. No-code builders:** Quickly deploy a chat interface that uses Linkup for accurate, source-backed answers from the web. What it does / What problem does this solve? Provides accurate, source-backed answers:* Routes queries to *Linkup** so replies are grounded in up-to-date web search results instead of the LLM's static knowledge. Handles voice & text transparently:* Accepts Telegram voice messages, transcribes them (via the *Mistral** API node by default), and treats transcripts the same as typed text. Simple agent + tool architecture:* Uses a *LangChain AI Agent* with a *Web search** tool to separate reasoning from information retrieval. Privacy control:* Includes a *Myself?** filter to restrict access to a specific Telegram username for safe testing. How it works Trigger: Telegram Trigger receives incoming messages (text or voice). Route: Message Router detects voice vs text. Voice files are fetched with Get Audio File. Transcribe: Mistral transcribe receives the audio file and returns a transcript; the transcript or text is normalized into preset_user_message and consolidated in Consolidate user message. Agent: AI Agent (GPT-4.1-mini configured) runs with a system prompt that instructs it to call the Web search tool when up-to-date knowledge is required. Respond: The agent output is sent back to the user via Telegram answer. How to set up Create a Linkup account: Sign up at https://linkup.so to get your API key. They offer a free tier with monthly credits. Add credentials in n8n: Configure Telegram API, OpenAI (or your LLM provider), and Mistral Cloud credentials in n8n. Configure Linkup tool: In the Web search node, find the "Headers" section. In the Authorization header, replace Bearer <your-linkup-api-key> with your actual Linkup API Key. Set Telegram privacy (optional): Edit the Myself? If node and replace <Replace with your Telegram username> with your username to restrict access. Remove the node to allow public use. Adjust transcription (optional): Swap the Mistral transcribe HTTP node for another provider (OpenAI, Whisper, etc.). Connect LLM: In OpenAI Chat Model node, add your OpenAI API key (or configure another LLM node) and ensure the AI Agent node references this model. Activate workflow: Activate the workflow and test by messaging your bot in Telegram. Requirements An n8n instance (cloud or self-hosted) A Telegram Bot token added in n8n credentials A Linkup account and API Key An LLM provider account (OpenAI or equivalent) for the OpenAI Chat Model node A Mistral API key (or other transcription provider) for voice transcription How to take it further Add provenance & sources:** Parse Linkup responses and include short citations or source links in the agent replies. Rich replies:** Use Telegram media (images, files) or inline keyboards to create follow-up actions (open web pages, request feedback, escalate to humans). Multi-user access control:** Replace the single-username filter with a list or role-based access system (Airtable or Google Sheets lookup) to allow multiple trusted users. Logging & analytics:* Save queries and agent responses to *Airtable* or *Google Sheets** for monitoring, quality checks, and prompt improvement.

✅ What problem does this workflow solve? Call centers often record conversations for quality control and training, but reviewing every transcript manually is tedious and inefficient. This workflow automates sentiment analysis for each call, providing structured feedback across multiple key categories, so managers can focus on improving performance and training. ⚙️ What does this workflow do? Accepts a Google Sheet containing: Call transcript Agent name Customer name Analyzes each call transcript across multiple sentiment dimensions: 👋 Greeting Sentiment 🧑‍💼 Agent Friendliness ❓ Problem-Solving Sentiment 🙂 Customer Sentiment 👋 Closing Sentiment ✅ Issue Resolved (Yes/No) Add Conversation Topics discussed in a call Calculates an overall call rating based on combined analysis. Updates the Google Sheet with: Individual sentiment scores Issue resolution status Final call rating 🔧 Setup Instructions 📄 Google Sheets Prepare a sheet with the following columns: Transcript Agent Name Customer Name The workflow will append results in new columns automatically: Greeting Sentiment Closing Sentiment Agent Friendliness Problem Solving Customer Sentiment Issue Resolved Overall Call Rating (out of 5 or 10) 🧠 OpenAI Setup Connect OpenAI API to perform NLP-based sentiment classification. For each transcript, use structured prompts to analyze individual components. 🧠 How it Works – Step-by-Step Sheet Scan – The workflow reads rows from the provided Google Sheet. Loop Through Calls – For each transcript, it: Sends prompts to OpenAI to analyze: Greeting tone (friendly/neutral/rude) Problem-solving quality (clear/confusing/helpful) Closing sentiment Agent attitude Customer satisfaction Whether the issue was resolved Calculates a composite rating from all factors. Update Sheet – All analyzed data is written back into the Google Sheet. 📊 Example Output https://docs.google.com/spreadsheets/d/1aWU28D_73nvkDMPfTkPkaV53kHgX7cg0W4NwLzGFEGU/edit?gid=0#gid=0 👤 Who can use this? This workflow is ideal for: ☎️ Call Centers 🎧 Customer Support Teams 🧠 Training & QA Departments 🏢 BPOs or Support Vendors If you want deeper insight into every customer interaction, this workflow delivers quantified, actionable sentiment metrics automatically. 🛠 Customization Ideas 📅 Add scheduled runs (daily/weekly) to auto-analyze new calls. 📝 Export flagged or low-rated calls into a review dashboard. 🧩 Integrate with Slack or email to send alerts for low-score calls. 🗂 Filter by agent, category, or score to track performance trends. 🚀 Ready to Use? Just connect: ✅ Google Sheets (with transcript data) ✅ OpenAI API …and this workflow will automatically turn your raw call transcripts into actionable sentiment insights.

How It Works This workflow transforms n8n into a smart Web Lead Form alternative to Salesforce's traditional Web-to-Lead, capturing leads, creating Salesforce records, and sending AI-personalized responses via email or SMS. Capture Submission**: User submits form data (name, email, phone, description, preference) via n8n's hosted form. Create Lead**: Maps data to a new Salesforce Lead. Personalize Message**: Uses OpenAI to generate a tailored welcome based on description and preference (detailed for email, concise for SMS). Route Outreach**: Branches to send via Twilio SMS or SMTP email depending on preference. Set Up Steps Setup takes about 15-30 minutes if you have credentials ready. Focus on connecting services; detailed configs are in workflow sticky notes. Duplicate this template in n8n. Add your Salesforce, OpenAI, Twilio, and SMTP credentials (no hardcoding—use n8n's credential manager). Customize form fields if needed and test with sample data. Activate and share the form URL on your site. n8n Web to Lead Form.json

💬 Chat with Your Trello Board (n8n + OpenAI) 📖 Description Turn your Trello board into a conversational assistant. This workflow pulls your board → lists → cards, aggregates the context, and lets you ask natural-language questions (“what’s overdue?”, “summarize In Progress”, “what changed this week?”). OpenAI reasons over the live board data and replies with concise answers or summaries. Great for standups, planning, and quick status checks—without opening Trello. > Setup steps are already embedded in the workflow (Trello API + OpenAI + board URL). Just follow the sticky notes inside the canvas. 🧪 Example prompts “Give me a one-paragraph summary of the board.” “List all cards due this week with their lists.” “What’s blocking items in ‘In Progress’?” “Show new cards added in the last 2 days.” ⚙️ Setup Instructions 1️⃣ Connect Trello (Developer API) Get your API key: https://trello.com/app-key Generate a token (from the same page → Token) In n8n → Credentials → New → Trello API, paste API Key and Token, save. Open each Trello node (Get Board, Get Lists, Get Cards) and select your Trello credential. 2️⃣ Set Up OpenAI Connection Go to OpenAI Platform Navigate to OpenAI Billing Add funds to your billing account Copy your API key into the OpenAI credentials in n8n 3️⃣ Add Your Board URL to “Get Board” Copy your Trello board URL (e.g., https://trello.com/b/DCpuJbnd/administrative-tasks). Open the Get Board node → Resource: Board, Operation: Get. In ID, choose URL mode and paste the board URL. The node will resolve the board and output its id → used by Get Lists / Get Cards. 📬 Contact Need help customizing this or adding Slack/Email outputs? 📧 robert@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com

Spark your creativity instantly in any chat—turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. 📋 What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing 🔧 Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation 🔑 Required Credentials OpenAI API Setup Go to platform.openai.com → API keys (sidebar) Click "Create new secret key" → Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai → Dashboard → API Keys Generate a new API key → Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) ⚙️ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflow—chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" 🎯 Use Cases Content Creators**: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators**: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization**: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming**: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration ⚠️ Troubleshooting Invalid JSON from AI Agent**: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403)**: Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely**: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters**: Tweak agent prompt to enforce fuller structures like V1V2[C]; verify output length in executions