Workflow Templates

Tired of manually watching long YouTube videos just to extract the main points? With our YouTube Transcript & Summary Automation, you can instantly turn any video into an actionable, AI-generated summary — all from a simple Google Sheet. What this automation does: Reads video URLs from Google Sheets (just add your links!) Generates accurate transcripts using Supadata.ai — with 100 free uses/month Creates a smart summary using DeepSeek AI: 🔹 Short summary of the video 🔹 Key points 🔹 Main topics Youtube tutorial: https://www.youtube.com/watch?v=uj7KaFSh95Y Automatically updates your Google Sheet with the transcript and the AI-generated summary How to set it up: Create a simple Google Sheet with these columns: Url – link to the YouTube video Status – set to pending to trigger the automation, updated to done after completion Transcript – filled automatically Summary – filled automatically Once your sheet is ready, the automation takes care of the rest — no technical skills needed. Why you'll love it: This is the perfect tool for content creators, researchers, marketers, and educators who want to save time, extract insights faster, and never miss key ideas from long videos. Want something custom? Got feedback or want to build your own custom automation or workflow? We’d love to hear from you! Reach out to us at jacobmarketingservice@gmail.com — let’s bring your idea to life.

Fire Flux Image Generator Description The image generation model tailored for local development and personal use Overview This n8n workflow integrates with the Replicate API to use the fire/flux model. This powerful AI model can generate high-quality image content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Required Parameters prompt** (string): Prompt for generated image Optional Parameters seed** (integer, default: 0): Random seed. Set for reproducible generation go_fast** (boolean, default: True): Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16 megapixels** (string, default: 1): Approximate number of megapixels for generated image num_outputs** (integer, default: 1): Number of outputs to generate aspect_ratio** (string, default: 2:1): Aspect ratio for the generated image output_format** (string, default: png): Format of the output images output_quality** (integer, default: 80): Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs num_inference_steps** (integer, default: 4): Number of denoising steps. 4 is recommended, and lower number of steps produce lower quality outputs, faster. disable_safety_checker** (boolean, default: False): Disable safety checker for generated images. How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate image content Access the generated output from the final node API Reference Model: fire/flux API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of image generation parameters

Takes your raw, unpolished voice transcripts and transforms them into well-structured LinkedIn posts using AI. Perfect for when you have good ideas but they come out as rambling thoughts. The Problem: You record voice memos with great ideas, but when you read the transcript, it's full of "ums," incomplete sentences, and scattered thoughts. Turning that into a professional LinkedIn post takes forever. The Solution: Email your raw transcript to this workflow. It combines your unpolished content with examples from your inspiration document (posts you've saved that match your desired style), then uses AI to create a clean, engaging LinkedIn post. What actually happens: You email a raw voice transcript to your workflow email -The workflow pulls style examples from your Google Doc AI reformats your scattered thoughts into a coherent 150-300 word LinkedIn post You get an email back with the polished content + suggested image description Copy, paste, and post to LinkedIn You provide: The raw transcript (from your phone's voice recorder or any transcription tool), a Google Doc with LinkedIn posts you admire for style reference. You get: Professional LinkedIn content that sounds like you, but organized and polished. Technical requirements: Anthropic API, email account, Google Doc with example posts. This is basically having an AI writing assistant that knows your voice and preferred style, turning your brain dumps into professional content.

Workflow updated on 17/06/2024:** Added 'Summarize' node to avoid creating a row for each Notion content block in the Supabase table.* Store Notion's Pages as Vector Documents into Supabase This workflow assumes you have a Supabase project with a table that has a vector column. If you don't have it, follow the instructions here: Supabase Langchain Guide Workflow Description This workflow automates the process of storing Notion pages as vector documents in a Supabase database with a vector column. The steps are as follows: Notion Page Added Trigger: Monitors a specified Notion database for newly added pages. You can create a specific Notion database where you copy the pages you want to store in Supabase. Node: Page Added in Notion Database Retrieve Page Content: Fetches all block content from the newly added Notion page. Node: Get Blocks Content Filter Non-Text Content: Excludes blocks of type "image" and "video" to focus on textual content. Node: Filter - Exclude Media Content Summarize Content: Concatenates the Notion blocks content to create a single text for embedding. Node: Summarize - Concatenate Notion's blocks content Store in Supabase: Stores the processed documents and their embeddings into a Supabase table with a vector column. Node: Store Documents in Supabase Generate Embeddings: Utilizes OpenAI's API to generate embeddings for the textual content. Node: Generate Text Embeddings Create Metadata and Load Content: Loads the block content and creates associated metadata, such as page ID and block ID. Node: Load Block Content & Create Metadata Split Content into Chunks: Divides the text into smaller chunks for easier processing and embedding generation. Node: Token Splitter

This n8n workflow verifies the deliverability of mailing addresses stored in Groundhogg CRM by integrating with Lob’s address verification service. Who is this for? This template is designed for Groundhogg CRM users who need to ensure the accuracy of mailing addresses stored in their CRM systems. What problem is this workflow solving? / Use Case This workflow addresses the challenge of maintaining accurate mailing addresses in CRM databases by verifying the deliverability of addresses. What this workflow does A new contact is created in Groundhogg CRM Webhook sent to n8n Verify if the address is deliverable via LOB Report back to Groundhogg CRM Set Up Steps Watch this setup video: https://www.youtube.com/watch?v=nrV0P0Yz8FI Takes 10-30 minutes to set up Accounts Needed: Groundhogg CRM LOB Account (https://www.lob.com $0.00/mo 300 US addresses Verifications) n8n Before using this template, ensure you have API keys for your Groundhogg CRM app and Lob. Set up authentication for both services within n8n. How to customize this workflow to your needs You can customize this workflow by adjusting the trigger settings to match Groundhogg CRM’s workflow configuration. Additionally, you can modify the actions taken based on the deliverability outcome, such as updating custom fields or sending notifications.

Description This workflow automatically scans food delivery platforms and restaurant websites to find the best deals and discounts. It helps you save money on meals by aggregating special offers and promotions in one place. Overview This workflow automates finding the best food deals and discounts from various websites. It uses Bright Data to scrape deal information and can be configured to send you notifications or save the deals to a spreadsheet. Tools Used n8n:** The automation platform that orchestrates the workflow. Bright Data:** For scraping food deal websites without getting blocked. (Optional) Google Sheets/Discord/Telegram:** To store or get notified about the deals. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Configure Bright Data: Add your Bright Data credentials to the Bright Data node. Set Up Notifications (Optional): Configure the nodes for Google Sheets, Discord, or Telegram if you want to receive notifications. Customize: Specify the websites you want to scrape for deals. Use Cases Foodies:** Always be the first to know about the best restaurant deals in your city. Students:** Save money by finding cheap eats and special offers. Families:** Plan your meals around the best grocery and restaurant discounts. Connect with Me Website:** https://www.nofluff.online YouTube:** https://www.youtube.com/@YaronBeen/videos LinkedIn:** https://www.linkedin.com/in/yaronbeen/ Get Bright Data:** https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #fooddeals #brightdata #webscraping #discounts #fooddiscounts #mealdeals #restaurantdeals #savemoney #foodoffers #n8nworkflow #workflow #nocode #foodtech #dealfinder #specialoffers #fooddelivery #budgetmeals #foodsavings #dealhunting #foodautomation #moneysaving #foodhacks #bestdeals #foodscraping

Run Apache Airflow DAG and Retrieve XCom Value What this workflow does This workflow integrates the Apache Airflow API DAGRun and XCom. It enables n8n to trigger Airflow DAGs and retrieve the execution results. Preparation: Update Airflow API Link Prefix Navigate to the airflow-api node. Update the prefix of the Airflow API link in the format: http(s)://ip:port. Example: https://airflow.example.com Configure Authentication Go to the Airflow: dag_run node. Update the Basic Auth credentials with your Airflow username and password. Repeat this step for Airflow: dag_run - state and Airflow: dag_run - get result nodes. Security Note: Using Basic Authentication requires storing credentials in plaintext. If possible, consider using API Keys or Tokens for enhanced security. An example is setting Airflow's API Authentication to basic\_auth. Choose other authentication methods if needed. Ensure the user account has the following permissions: can create on DAG Runs, can read on DAG Runs, can read on XComs, can edit on DAGs, and can read on DAGs. How to Use: To execute this workflow, use the Execute Sub-workflow node with the following input parameters: dag\_id**: The DAG ID (name) in Airflow that you want to trigger. task\_id**: The Task ID (name) from which you want to retrieve the XCom return\_value. conf**: Input data for the Airflow DAG run. wait**: Delay (in seconds) between each Airflow: dag_run - state check. wait\_time**: The maximum time (in seconds) to wait for Airflow: dag_run - state before returning an error. Output: The workflow returns the XCom result from Airflow: dag_run - get result. The XCom return_value is stored in the value field.

Universal AI Assistant - Webhook-Ready Conversational AI Transform any platform into an intelligent conversational experience with this plug-and-play n8n workflow. This AI assistant can be seamlessly integrated into websites, mobile apps, or any system that supports webhook connections. Key Features: 🔗 Universal Integration - Connect to any platform via webhook (websites, apps, bots) 🧠 Powered by Google Gemini 2.0 Flash - Fast, accurate, and context-aware responses 💾 Session Memory - Maintains conversation context for natural follow-up interactions ⚡ Real-time Responses - Instant webhook responses for smooth user experiences 🎯 Customizable Personality - Easy prompt modification for brand-specific tone Perfect For: Website Chat Widgets - Add AI support to any website instantly WhatsApp/Telegram Bots - Power messaging platforms with intelligent responses Mobile App Integration - Embed conversational AI into iOS/Android apps Customer Support Systems - Automate first-line support with context retention Lead Qualification - Intelligent pre-screening of prospects before human handoff Simple Implementation: Just send POST requests to the webhook URL with: json{ "message": "User's question here", "sessionId": "unique-session-identifier" } Ready to deploy in minutes - No complex setup required. Perfect for small businesses wanting to add AI capabilities without technical overhead. This workflow gives you a production-ready foundation that you can customize for specific client needs. The session-based memory makes it ideal for customer support scenarios where context matters, and the webhook approach means it integrates with virtually any platform your clients are already using.

This workflow captures Squarespace newsletter signups in a Google Sheet and automatically creates new Mailchimp contacts in the selected audience. It overcomes the limitation in Squarespace’s native Mailchimp integration, which only supports new, empty audiences. You can trigger the workflow manually or schedule it for continuous synchronization. Step-by-step tutorial First, you need to connect Squarespace newsletter block submission to Google Drive In Mailchimp node, choose your targeted audience in List Name or ID Connect a Squarespace Form to Google Drive To connect a form to Google Drive: In the form's storage options, click Connect on Google Drive. Log into your Google account. Click Allow to permit Squarespace to connect to Google Drive. Enter a Spreadsheet Name. This creates a new spreadsheet for your form submissions. Columns in my sheet: Submitted On Email Address Name This structure is inspired by Squarespace’s newsletter block connection, but you can modify it based on your preferred data format. 👉 Clone my Google Sheets template Requirements Credentials To use this workflow, you need: Mailchimp API Key** – Required to add contacts to Mailchimp. Google Sheets API credentials** – Required to retrieve signups from the spreadsheet. 📌 Mailchimp API Authentication Guide Explore More Templates 👉 Check out my other n8n templates

🎉 Do you want to master AI automation, so you can save time and build cool stuff? I’ve created a welcoming Skool community for non-technical yet resourceful learners. 👉🏻 Join the AI Atelier 👈🏻 This workflow provides an API endpoint to generate speech from text using Elevenlabs.io, a popular text-to-speech service. Step 1: Configure Custom Credentials in n8n To set up your credentials in n8n, create a new custom authentication entry with the following JSON structure: { "headers": { "xi-api-key": "your-elevenlabs-api-key" } } Replace "your-elevenlabs-api-key" with your actual Elevenlabs API key. Step 2: Send a POST Request to the Webhook Send a POST request to the workflow's webhook endpoint with these two parameters: voice_id: The ID of the voice from Elevenlabs that you want to use. text: The text you want to convert to speech. This workflow has been a significant time-saver in my video production tasks. I hope it proves just as useful to you! Happy automating! The n8Ninja

This n8n template demonstrates how to create an automated emotional story generation system that produces structured video prompts and generates corresponding images using AI. The workflow creates a complete story with 5 scenes featuring a Pakistani character named Yusra, converts them into Veo 3 video generation prompts, and generates images for each scene. Use cases include: Automated story creation for social media content Video pre-production with AI-generated storyboards Content creation for educational or entertainment purposes Multi-scene narrative development with consistent character design Good to know: Uses Gemini 2.5 Flash Lite for story generation and prompt conversion Uses Gemini 2.0 Flash Exp for image generation The image generation model may be geo-restricted in some regions Workflow includes automatic Google Drive organization and Google Sheets tracking How it works: Story Creation: Gemini AI creates a 5-scene emotional story featuring Yusra, a Pakistani girl aged 20-25 in traditional dress Folder Organization: AI generates a unique folder name with timestamp for project organization Google Sheets Setup: Creates a new sheet to track all scenes and their processing status Scene Processing: Each scene is processed individually with character and action prompts Veo 3 Prompt Conversion: Converts natural language scene descriptions into structured JSON format optimized for Veo 3 video generation, including parameters like: Detailed scene descriptions Camera movements and angles Lighting and mood settings Style and quality specifications Aspect ratios and technical parameters Image Generation: Uses Gemini's image generation model to create visual representations of each scene File Management: Automatically uploads images to Google Drive and organizes them in project folders Status Tracking: Updates Google Sheets with processing status and file URLs Automated Workflow: Includes conditional logic to handle different processing states and file movements How to use: Execute the workflow manually or set up automated triggers The system will automatically create a new story with 5 scenes Each scene gets processed through the AI pipeline Generated images are organized in Google Drive folders Track progress through the Google Sheets interface The workflow handles all file management and status updates automatically Requirements: Gemini API access for both text and image generation Google Drive for file storage and organization Google Sheets for project tracking and management n8n instance with appropriate node access Customizing this workflow: Modify the character description in the Story Creator node Adjust the number of scenes by changing the story prompt Customize the Veo 3 prompt parameters for different video styles Add additional AI models or processing steps Integrate with other content creation tools Modify the folder naming convention or organization structure Technical Features: Automated retry logic for failed operations Conditional processing based on status flags Batch processing for multiple scenes Error handling and status tracking File organization with timestamp-based naming Integration with Google Workspace services This template is perfect for content creators, educators, or anyone looking to automate story-based content creation with AI assistance.

n8n Workflow Backup to Google Drive – Automated Export of All Your Workflows This workflow is designed to automatically create backups of all your workflows in n8n and store them as individual .json files in Google Drive. It's a fully automated system that helps developers, agencies, or automation teams ensure their automation logic is always safe, versioned, and ready to restore or share. What is this for? If you’re building and managing multiple automations inside n8n, losing a workflow due to accidental deletion or misconfiguration can cost you hours of work. This template solves that by exporting all your workflows into separate files and storing them in a dated Google Drive folder. It helps with disaster recovery, version tracking, and team collaboration — without any manual exporting. How this works: -Once triggered (manually or via a schedule), the workflow performs the following steps: -Creates a new folder in your Google Drive, named with today’s date (e.g. “Workflow Backups Monday 16-05-2025”). -Connects to your n8n instance using the internal API and retrieves a list of all existing workflows. -Iterates over each workflow, converts it into a .json file using the built-in file conversion node. -Uploads each individual .json file to the newly created folder in Google Drive. -Optionally, the workflow finds and deletes old backup folders to keep your Google Drive clean and avoid clutter. You get a clean, timestamped folder with all your flows — ready to restore, send, or store securely. You can trigger it manually or schedule it (e.g., to run weekly on Monday mornings). How to set it up: Import the provided workflow JSON into your n8n instance. Set up your credentials: -Replace the placeholder “Google demo” with your actual Google Drive OAuth2 credentials in all Google Drive nodes. -Replace the placeholder “n8n demo” with your n8n API credentials so the workflow can fetch your flows. -Go to the node “Create new folder” and replace the folder ID with your own destination folder in Google Drive where backups should be stored. -(Optional) Enable the “Schedule Trigger” to run the backup automatically once a week or on your preferred interval. You’re ready to go — test it with the Manual Trigger first and check your Google Drive for results.