by Angel Menendez
Who is this for? This workflow is for professionals and teams who want to automate LinkedIn message replies with intelligent, human-like responses — without losing control over tone or accuracy. Ideal for founders, sales teams, DevRel, or community managers handling high-volume inbound messages. What problem is this workflow solving? Responding to every LinkedIn message manually is slow and inconsistent. Basic AI bots generate replies without context or nuance. This subworkflow solves both problems by using structured message routing from Notion and profile insights from UniPile to craft smart, context-aware responses. What this workflow does This workflow takes the sender’s message and profile (from LinkedIn Auto Message Router with Request Detection) and references your centralized Notion database of message types. It uses that to either match the message to a known response or generate a new one using OpenAI's GPT model — all while following professional tone guidelines. This is the third workflow in a 3-part automation system: Receives data from LinkedIn Auto Message Router with Request Detection Uses UniPile LinkedIn Profile Lookup Subworkflow to enrich responses based on follower count or org data Example Use Case If a message comes from someone with low reach (e.g., under 1,000 followers), the AI politely deflects a meeting request. If an influencer reaches out, the AI immediately offers a booking link. Your team controls this logic by updating the Notion database — no edits to the workflow required. Setup Connect this workflow as a subworkflow in your router or Slack approval flow Store your Notion API key and database ID in n8n Provide the following parent inputs: message – The LinkedIn message text sender – Name of the sender chatid – Session ID (optional for memory) linkedinprofile – Enriched array with LinkedIn context (follower count, connection info, etc.) Add your preferred AI model credentials (supports OpenAI, Gemini, or Ollama) Optional: Customize system prompt to better match your brand voice How to customize this workflow to your needs Update the Notion schema to include industry-specific categories or actions Change the AI tone (e.g., humorous, more corporate, etc.) Add conditional logic for auto-sending messages without Slack approval Extend to support multiple platforms (e.g., email, X/Twitter, Instagram DMs)
by Yang
🧾 What this workflow does This workflow automatically generates avatar-style videos from the latest AI-related news using Dumpling AI and HeyGen. It runs every hour, scrapes trending articles, turns them into 30–60 second spoken scripts with GPT-4o, and produces short avatar videos with HeyGen. Finally, it logs the final video URL in a Google Sheet. 👤 Who is this for Newsletters and creators who want to automate AI trend updates Content marketers generating short-form video content Product teams experimenting with AI-generated summaries Automation enthusiasts combining LLMs + video + trending data ⚙️ How to set up 🔐 Requirements Dumpling AI API Key** stored securely as HTTP Header credential HeyGen API Key** added as an HTTP Header credential OpenAI API Key** for GPT-4o (can use GPT-4o-mini if preferred) Google Sheets account** with one column: Video link 🛠 Step-by-step setup Google Sheet Setup Create a Google Sheet with a single column named: Video link Update Credentials Use n8n’s credential manager to add tokens for: Dumpling AI HeyGen OpenAI Google Sheets Optional Customizations In the "Dumpling AI: Search AI News" node, you can change "query": "AI Agent" to other trending keywords (e.g., "Generative AI", "Autonomous Agents", etc.) Update the avatar_id and voice_id in the HeyGen request to match your preferred look/sound 🧠 How it works The Schedule Trigger runs hourly. Dumpling AI searches for fresh news related to "AI Agent." The top 4 news links are scraped for full content. Articles are merged and fed into GPT-4o via a LangChain Agent to produce a casual, conversational video script. HeyGen creates a video using the script, avatar, and voice. The workflow waits until the video rendering is complete. Once done, the final video link is logged into Google Sheets. 🧪 Customization Ideas Change the interval (e.g., every 6 hours, daily) Swap avatar/voice in HeyGen to fit your brand Expand to post the video directly to social media Add image background or B-roll overlays using Creatomate This is a fast, automated pipeline to create explainer-style AI news updates using real-time data and generative video tools.
by Yaron Been
Workflow Overview This cutting-edge n8n workflow is a powerful automation tool designed to revolutionize how content creators and marketers engage with YouTube channels. By leveraging AI and the YouTube Data API, this workflow automatically: Discovers New Content: Monitors a specific YouTube channel Retrieves the latest video in real-time Checks for new uploads at regular intervals Generates Intelligent Comments: Uses advanced AI (OpenAI's GPT models) to analyze video metadata Crafts contextually relevant, human-like comments Ensures each comment feels organic and engaging Seamless Deployment: Automatically posts the AI-generated comment directly on the video Eliminates manual interaction Increases potential channel visibility and engagement Key Benefits 🤖 Full Automation: No manual comment writing required 💡 Smart Contextual Comments: AI understands video content ⏱️ Time-Saving: Instant engagement without human intervention 📈 Potential Increased Visibility: Regular, intelligent interactions Setup Requirements YouTube Data API Credentials Obtain a Google Cloud API key Configure channel ID you want to target Set up OAuth2 authentication for comment posting OpenAI API Access Create an OpenAI account Generate an API key for comment generation Select preferred GPT model (GPT-4o, GPT-3.5, etc.) n8n Installation Install n8n (cloud or self-hosted) Import the workflow configuration Configure API credentials Set up scheduling preferences Potential Use Cases Content Creators monitoring competitor channels Marketing teams maintaining online presence Social media managers automating engagement Researchers tracking specific YouTube channels Future Enhancements Logging comment history Dynamic OAuth2 token management Multi-channel support Sentiment analysis for comment generation Connect With Me Got questions? Want to dive deeper? 📧 Email: Yaron@nofluff.online 🎥 YouTube: @YaronBeen 💼 LinkedIn: Yaron Been **Unlock the power of AI-driven YouTube engagement – automate, optimize, and amplify your online# Automate YouTube Engagement with GPT-4o Generated Comments Workflow Overview This n8n automation leverages AI to streamline YouTube channel engagement, providing a sophisticated solution for content interaction. By combining the YouTube Data API and OpenAI's GPT-4o, the workflow: Intelligent Content Discovery: Dynamically monitors specified YouTube channels Real-time detection of new video uploads Configurable monitoring intervals AI-Powered Comment Generation: Utilizes GPT-4o for contextual analysis Generates nuanced, platform-appropriate comments Ensures authentic, relevant interactions Automated Engagement: Seamlessly posts AI-crafted comments Enhances channel visibility Reduces manual social media management Key Benefits 🤖 Advanced Automation: AI-driven engagement 💡 Contextual Intelligence: GPT-4o powered insights ⏱️ Efficiency Optimization: Instant, scalable interactions 📈 Strategic Visibility: Consistent, meaningful channel presence Detailed Setup Instructions Prerequisites n8n instance (cloud or self-hosted) YouTube Data API access OpenAI API key Target YouTube channel(s) Configuration Steps YouTube Data API Setup Create a Google Cloud project Enable YouTube Data API v3 Generate OAuth2 credentials Store credentials securely in n8n OpenAI API Configuration Create OpenAI account Generate API key Select GPT-4o model Configure API key in n8n credentials Workflow Customization Replace placeholder channel IDs Adjust monitoring frequency Customize AI prompt for comment generation Configure OAuth2 authentication Workflow Customization Options Modify AI prompt to match specific content styles Add keyword filters for video selection Implement multi-channel support Create custom engagement rules Potential Use Cases Content creator audience engagement Brand social media management Community interaction automation Research and monitoring Ethical Considerations Maintain transparency about AI-generated comments Respect platform guidelines Avoid spam or misleading interactions Ensure comments add genuine value Future Enhancement Roadmap Advanced sentiment analysis Multi-language support Engagement performance tracking Adaptive comment generation Security Best Practices Never hardcode API keys Use n8n's credential management Implement secure OAuth2 authentication Regularly rotate API credentials Technical Requirements n8n v0.220.0 or higher YouTube Data API v3 OpenAI API access Stable internet connection Workflow Architecture [YouTube Channel Trigger] ⬇️ [Fetch Latest Video] ⬇️ [AI Comment Generation] ⬇️ [Post Comment] #YouTubeAutomation #AIEngagement #ContentMarketing #SocialMediaTech #GPT4Automation #WorkflowInnovation #AIComments #DigitalMarketing Connect With Me Exploring AI-Powered Social Media Automation? 📧 Email: Yaron@nofluff.online 🎥 YouTube: @YaronBeen 💼 LinkedIn: Yaron Been Transform your YouTube engagement with intelligent, responsible automation! Note: This workflow template is a starting point. Always customize and test thoroughly in your specific environment.
by n8n Team
This template quickly shows how to use RAG in n8n. Who is this for? This template is for everyone who wants to start giving knowledge to their Agents through RAG. Requirements Have a PDF with custom knowledge that you want to provide to your agent. Setup No setup required. Just hit Execute Workflow, upload your knowledge document and then start chatting. How to customize this to your needs Add custom instructions to your Agent by changing the prompts in it. Add a different way to load in knowledge to your vector store, e.g. by looking at some Google Drive files or loading knowledge from a table. Exchange the Simple Vector Store nodes with your own vector store tools ready for production. Add a more sophisticated way to rank files found in the vector store. For more information read our docs on RAG in n8n.
by Oneclick AI Squad
This automated n8n workflow delivers an instant DevOps toolkit by installing Docker, K3s, Jenkins, Grafana, and more on a Linux server within 10 seconds. It optimizes performance, enhances security, and provides ready-to-use templates for DevOps projects. Main Components Configure Parameters** - Defines server details, tool versions, and credentials System Preparation** - Updates the system and installs base packages Install Docker** - Deploys Docker Engine and Docker Compose Install Kubernetes** - Sets up K3s cluster with kubectl, Helm, and k9s Install Jenkins** - Configures Jenkins CI/CD server with Docker integration Install Monitoring** - Deploys Prometheus and Grafana using Helm charts Create DevOps User** - Establishes a dedicated user with appropriate permissions Security Configuration** - Implements firewall, VS Code, and Terraform Final Configuration** - Sets up sample projects and configuration files Setup Complete** - Provides a summary and access details Essential Prerequisites Linux server with SSH access Root-level administrative privileges Customization Guide Adjust tool versions or credentials in the Configure Parameters node Modify the number of nodes or security settings as needed Features 🔧 Core DevOps Tools Installed: Docker - Container platform with Docker Compose Kubernetes - K3s (lightweight) with kubectl and Helm Jenkins - CI/CD automation server Prometheus - Monitoring and alerting Grafana - Visualization and dashboards ⚡ Optimizations Made: Streamlined Commands - Combined multiple operations into single bash scripts Reduced Nodes - 10 nodes vs 12 in original (more efficient) Better Error Handling - Each step includes verification Cloud-Ready - Includes AWS CLI, Azure CLI, and Google Cloud SDK Security First - Proper firewall configuration and user permissions Parameters to Configure server_host: Your Linux server IP address server_user: SSH username (typically 'root') server_password: SSH password docker_version: Docker version to install k3s_version: K3s version to install username: DevOps username user_password: Password for the DevOps user How to Use Copy the JSON code from the artifact Open your n8n workspace Select "Import from JSON" or "+" → "From JSON" Paste the JSON code Configure parameters in the "Configure Parameters" node with your server details Run the workflow Workflow Actions Install: Deploys Docker, K3s, Jenkins, Prometheus, and Grafana with optimizations Create User: Sets up a DevOps user with necessary permissions Configure: Applies security settings and provides templates
by Oliver Bardenheier
🛠️Setup Guide 'Get OVH Invoices to Google Sheets' Author: Oliver Bardenheier Who is this for? This Workflow is for all users who have services (Domains, BareMetal, VPS, Cloud, etc.) with Provider OVH.com (European API) It automatically retrieves invoice data, -files and puts the Data in a Google Spreadsheet for further processing. What problem is this workflow solving? / use case Currently the invoices from OVH do not come as an attachment via mail, it is just a link. So, the receiver has to be logged in to the ovh account to download the file. Even more effort if one is using 2FA. This workflow retrieves all information through the oauth2 token. What this workflow does This Workflow automatically retrieves invoice data, -files from Your OVH.com account and puts the Data in a Google Spreadsheet for further processing. It also saves the invoice PDF to a certain (yearly) folder in Your Google Drive. Setup Make a copy of this Google Sheet Template Set the timeframe for the query to Your likings in "Query Latest OVH Invoices" You could set an email trigger before and make the frame only one day. Log into Your OVH Account and get Your Credentials here Authentication using oAuth2 Authorization Code "Login with OVHcloud SSO" You need to Authorize OVHcloud API console If this worked fine You'll see a green text: "Access Token Received" Head over to the OVH API Console to get Your Token. Set Up Header Auth in the HTTP nodes: Authentication = Generic Credential Type Generic Auth Type = Header Auth Header Auth = Your OVH Header Credentials: -- a.) In every API Call in the console You'll find a curl example, just take the data from the line including: -H "authorization: Bearer eyJhxxxxxxxxxxxxxxxxxxxxxxxxxxxxx......" -- b.) Create a new Credential in n8n for the header auth. Put in the 'name' Field: authorization Copy Your Token including Bearer in the value field: 'Bearer eyJhxxxxxxxxxxxxxxxxxxxxxxxxxxxxx......' How to customize this workflow to your needs You can put in a mail trigger that activates on every incoming invoice mail from OVH. Adjusting the timeframe to get invoices from a certain time period, or remove the time variables completely to get ALL invoices.
by Mutasem
Use Case Track all Linear tickets in Google sheets. Useful if you want to do some custom analysis but don't want to pay for Linear's Plus features (Linear Insights) or that it does not cover. Setup Add Linear API header key Add Google sheets creds Update which teams to get tickets from in Graphql Nodes Update which Google Sheets page to write all the tickets to You only need to add one column, id, in the sheet. Google Sheets node in automatic mapping mode will handle adding the rest of the columns. Set any custom data on each ticket Activate workflow 🚀 How to adjust this template Set any custom fields you want to get out of this, that you can quickly do in n8n.
by Danielle Gomes
Automatically classify incoming leads based on the sentiment of their message using Google Gemini, store them in Supabase by category, and send tailored WhatsApp messages via the official WhatsApp Cloud API. ✅ Use Case: This workflow is ideal for sales, onboarding, and customer support teams who want to: Understand the tone and urgency of each lead Prioritize hot leads instantly Send smart, automatic WhatsApp replies based on user sentiment 🧠 How it works: Capture lead via a Typeform webhook Clean and structure the data (name, email, message, etc.) Run sentiment analysis using Google Gemini to classify the message as: Positive → Hot Lead Neutral → Warm Lead Negative → Cold Lead Store lead data in Supabase under the corresponding category Merge data to unify flow paths Send WhatsApp message using the official WhatsApp Cloud API, with a custom reply for each sentiment result 🔧 Tools used: Typeform (incoming data) Google Gemini (AI-based sentiment classification) Supabase (database) WhatsApp Cloud API (response automation) 🏷 Tags: AI, Sentiment Analysis, Lead Qualification, Supabase, WhatsApp, Gemini, Typeform, CRM, Automation, Customer Engagement
by David Roberts
Overview This workflow takes some French text, and translates it into spoken audio. It then transcribes that audio back into text, translates it into English and generates an audio file of the English text. To do so, it uses ElevenLabs (which has a free tier) and OpenAI. Setup These steps should only take a few minutes: In ElevenLabs, add a voice to your voice lab and copy its ID. Add it to the 'Set voice ID' node Get your ElevenLabs API key (click your name in the bottom-left of ElevenLabs and choose ‘profile’) In the 'Generate French audio' node, create a new header auth cred. Set the name to xi-api-key and the value to your API key In the 'credential' field of the 'Transcribe audio' node, create a new OpenAI cred with your OpenAI API key Run the workflow by clicking the orange button at the bottom of the canvas
by Alex Kim
🎬 Google Veo 3 Prompt and Video Generator via Leonardo.ai + Claude 4 Transform text descriptions into cinematic videos using Google's Veo 3 model through Leonardo.ai's platform! 🚀 What This Workflow Does This advanced automation pipeline takes your creative ideas and turns them into professional-quality videos using Google's powerful Veo 3 model (accessed via Leonardo.ai), enhanced by Claude 4's sophisticated prompt engineering. ✨ Key Features 🤖 AI-Powered Prompt Enhancement**: Uses Claude 4 Sonnet with Wikipedia integration to craft optimal Google Veo 3 prompts 🎥 Professional Video Generation**: Leverages Google's Veo 3 model through Leonardo.ai for high-quality text-to-video conversion ☁️ Automatic Cloud Storage**: Videos are automatically saved to your Google Drive 📋 Structured Prompting**: Follows Google Veo3 best practices with 8 essential elements (Subject, Context, Action, Style, Camera Motion, Composition, Ambiance, Audio) ⚡ Hands-Off Processing**: Set it and forget it - the workflow handles the entire pipeline 🔧 How It Works Input Your Concept - Describe your video idea in the "Video Context" node AI Enhancement - Claude 4 transforms your description into a cinematic Google Veo 3 prompt using advanced techniques Video Generation - Google's Veo 3 model (via Leonardo.ai) creates your video (720p resolution, ~8 seconds) Smart Waiting - 4-minute processing buffer ensures completion Auto-Download - Retrieves the finished video from Leonardo's servers Cloud Storage - Uploads directly to your Google Drive folder 💡 Perfect For Content Creators** looking to automate video production Marketing Teams** needing quick promotional videos Educators** creating engaging visual content Social Media Managers** generating scroll-stopping content Creative Professionals** exploring AI-assisted filmmaking 📋 Requirements Leonardo AI account with API access Anthropic API key (Claude 4 Sonnet) Google Drive integration N8N instance (cloud or self-hosted) 👨💻 About the Creator Created by: AlexK1919 - AI-Native Workflow Automation Architect, n8n Ambassador and Verified Partner, Co-Founder @ WotAI If you'd like to review more Google Veo 3 Prompts organized by business category, check out over 9,000+ free, pre-made prompts at: Google Veo 3 Prompts 📄 License This workflow is available under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license. You are free to use, adapt, and share this workflow for non-commercial purposes under the terms of this license. Full license details: https://creativecommons.org/licenses/by-nc-sa/4.0/ 🎯 Example Output Input: "Star Wars stormtrooper digging for uranium in desert, saying something funny" The AI generates a structured prompt with: Subject**: Detailed character description Context**: Desert environment specifics Action**: Dynamic digging movements Style**: Cinematic vlog aesthetic Camera**: Appropriate angles and movement Audio**: Dialogue, sound effects, and music ⚙️ Setup Notes Character Limit**: Prompts are optimized for Leonardo's 1,500 character API limit Processing Time**: Allow 4+ minutes for Google Veo3 video generation Quality**: 720p resolution with native audio generation Consistency**: Uses advanced Google Veo3 prompting for reliable results 🔄 Customization Options Modify the prompt engineering system message for different styles Adjust video resolution and model parameters Change storage destination (Google Drive folder) Add post-processing steps or notifications 📈 Why This Workflow Rocks Unlike simple text-to-video tools, this workflow: Intelligently enhances** your prompts using AI for Google Veo 3 Follows industry best practices** for Google Veo3 prompting Automates the entire pipeline** from idea to stored video Leverages multiple AI models** for superior results Handles technical details** like API limits and timing 🚨 Pro Tips Be specific in your initial context - detail creates better videos The workflow includes comprehensive Google Veo3 prompting guidelines Videos are typically 5-8 seconds - plan accordingly for longer content Experiment with different styles and camera movements optimized for Veo 3 The AI can access Wikipedia for factual enhancement Ready to revolutionize your video creation process? Import this workflow and start generating professional videos with just a text description! Perfect for anyone looking to harness the power of AI for content creation. Tags: #veo3 #GoogleVeo3 #AI #VideoGeneration #Leonardo #Claude #Automation #ContentCreation #GoogleAI
by Pavel Zamorev
This n8n template automates the transformation of raw meeting notes into structured tasks and documents using GPT (or another model) , syncing them to Notion and TickTick via a Telegram bot. Use Cases Automate note-taking and formatting for daily standups, brainstorming sessions, or client calls. Reduce cognitive load by eliminating manual tracking of ideas and tedious formatting. Convert discussions into actionable tasks instantly with TickTick and structured notes in Notion. How It Works Capture Notes: Send raw meeting notes to a Telegram bot. AI Processing: The workflow sends the text to AI, which: Removes duplicates and extracts key points. Formats content into structured Markdown notes for Notion. Identifies tasks with deadlines (e.g., "- Prepare presentation (Responsible: John, Deadline: Friday)"). Task Parsing: Extracts task titles, removing metadata like "Responsible" and "Deadline." Review & Edit: The bot returns formatted notes and tasks for review in Telegram. Sync & Publish: Notes are published to a Notion database. Tasks are exported to TickTick via API. Confirmation: A Telegram reaction (e.g., 👌 emoji) confirms successful processing. Setup Instructions Set Up Telegram Bot: Create a Telegram bot via BotFather and obtain an API token. Add the token to the "Telegram Trigger" and "Send-Edited-Notes" nodes under credentials (telegramApi). Configure OpenAI: Obtain an OpenAI API key and add it to the "Edit-Notes" node (openAiApi credentials). Ensure the model is set to gpt-4.1-mini in the node parameters. Set Up Notion: Create a Notion database for notes (e.g., "Meetings"). Add the database ID to the "Create a Database Page" node (databaseId). Configure Notion API credentials (notionApi) in the node. Set Up TickTick: Obtain a TickTick API key and add it to the "Create a Task" node (tickTickOAuth2Api credentials). Specify your TickTick project ID in the node (projectId). Deploy Workflow: Ensure your n8n instance is self-hosted to support community nodes (TickTick, Notion). Activate the workflow in n8n. Test: Send a test message to the Telegram bot (e.g., "Discussed project timeline. Tasks: - Prepare slides (Responsible: Alice, Deadline: Friday)"). Verify that notes appear in Notion, tasks in TickTick, and a 👌 reaction in Telegram. Configuration Examples Telegram Trigger: { "parameters": { "updates": ["message"], "additionalFields": {} }, "credentials": { "telegramApi": { "id": "your-telegram-api-id", "name": "meeting notes" } } } OpenAI Prompt (in "Edit-Notes" node): Analyze the quick meeting notes from {{ $json.message.text }} Generate meeting notes and a task list in the following format:\nMeeting Notes:\n- [Note 1]\n- [Note 2]\n\nTasks:\n- [Task 1] \n- [Task 2] Notion Database Page { "parameters": { "resource": "databasePage", "databaseId": "your-notion-database-id", "title": "MN {{ $now }}", "blockUi": { "blockValues": [ { "textContent": "{{ $json.message.text }}" } ] } } } Requirements Requires an OpenAI API key (or another model). APIs: Pre-configured Notion and TickTick API credentials are required. The template includes setup guides. Setup: Uses community nodes, requiring a self-hosted n8n instance. Customizing This Workflow Replace the Telegram bot with a webhook or form for alternative inputs (e.g., mobile apps). Modify the OpenAI prompt in the "Edit-Notes" node to customize note and task formats. Add filters in the "Split Notes and Tasks" node to prioritize tasks (e.g., ++#urgent++). Integrate Google Calendar via an additional HTTP Request node to auto-set deadlines based on text (e.g., "by Friday").
by Adam Janes
How it works The automation loads rows from a Google Sheet of leads that you want to contact. It makes a Google search via Apify for LinkedIn links based on the First name / Last name / Company. Another Apify actor fetches the right LinkedIn profile based on the first profile which is retuned The same process is done for the company that the lead works for, giving extra context. If the lead has a current company listed on their LinkedIn, we use that URL to do the lookup, rather than doing a separate Google search. A call is made to OpenRouter to get an LLM to generate an email based on a prompt designed to do personalized outreach. An email is sent via a Gmail node. Set up steps Connect your Google Sheets + Gmail accounts to use these APIs. Make an account with Apify and enter your credentials. Set your details in the "Set My Data" node to customize the workflow to revolve around your company + value proposition. I would recommend changing the prompt in the "Generate Personalized Email" node to match the tone of voice that you want your agent to have. You can change the guidelines to e.g. change whether the agent introduces itself, and give more examples in the style you want to make the output better.