Workflow Templates

This n8n workflow automates the process of scraping LinkedIn profiles using the Apify platform and organizing the extracted data into Google Sheets for easy analysis and follow-up. Use Cases Lead Generation**: Extract contact information and professional details from LinkedIn profiles Recruitment**: Gather candidate information for talent acquisition Market Research**: Analyze professional networks and industry connections Sales Prospecting**: Build targeted prospect lists with detailed professional information How It Works 1. Workflow Initialization & Input Webhook Start Scraper**: Triggers the entire scraping workflow Read LinkedIn URLs**: Retrieves LinkedIn profile URLs from Google Sheets Schedule Scraper Trigger**: Sets up automated scheduling for regular scraping 2. Data Processing & Extraction Data Formatting**: Prepares and structures the LinkedIn URLs for processing Fetch Profile Data**: Makes HTTP requests to Apify API with profile URLs Run Scraper Actor**: Executes the Apify LinkedIn scraper actor Get Scraped Results**: Retrieves the extracted profile data from Apify 3. Data Storage & Completion Save to Google Sheets**: Stores the scraped profile data in organized spreadsheet format Update Progress Tracker**: Updates workflow status and progress tracking Process Complete Wait**: Ensures all operations finish before final steps Send Success Notification**: Alerts users when scraping is successfully completed Requirements Apify Account Active Apify account with sufficient credits API token for authentication Access to LinkedIn Profile Scraper actor Google Sheets Google account with Sheets access Properly formatted input sheet with LinkedIn URLs Credentials configured in n8n n8n Setup HTTP Request node credentials for Apify Google Sheets node credentials Webhook endpoint configured How to Use Step 1: Prepare Your Data Create a Google Sheet with LinkedIn profile URLs Ensure the sheet has a column named 'linkedin_url' Add any additional columns for metadata (name, company, etc.) Step 2: Configure Credentials Set up Apify API credentials in n8n Configure Google Sheets authentication Update webhook endpoint URL Step 3: Customize Settings Adjust scraping parameters in the Apify node Modify data fields to extract based on your needs Set up notification preferences Step 4: Execute Workflow Trigger via webhook or manual execution Monitor progress through the workflow Check Google Sheets for scraped data Review completion notifications Good to Know Rate Limits**: LinkedIn scraping is subject to rate limits. The workflow includes delays to respect these limits. Data Quality**: Results depend on profile visibility and LinkedIn's anti-scraping measures. Costs**: Apify charges based on compute units used. Monitor your usage to control costs. Compliance**: Ensure your scraping activities comply with LinkedIn's Terms of Service and applicable laws. Customizing This Workflow Enhanced Data Processing Add data enrichment steps to append additional information Implement duplicate detection and merge logic Create data validation rules for quality control Advanced Notifications Set up Slack or email alerts for different scenarios Create detailed reports with scraping statistics Implement error recovery mechanisms Integration Options Connect to CRM systems for automatic lead creation Integrate with marketing automation platforms Export data to analytics tools for further analysis Troubleshooting Common Issues Apify Actor Failures**: Check API limits and actor status Google Sheets Errors**: Verify permissions and sheet structure Rate Limiting**: Implement longer delays between requests Data Quality Issues**: Review scraping parameters and target profiles Best Practices Test with small batches before scaling up Monitor Apify credit usage regularly Keep backup copies of your data Regular validation of scraped information accuracy

Effortless Task Management: Create Todoist Tasks Directly from Telegram with AI This n8n workflow empowers you to seamlessly manage your tasks by creating Todoist entries directly from Telegram, using the power of AI. Simply send a voice or text message to your Telegram bot, and this workflow will transform it into actionable tasks in your Todoist account. Who is this for? Busy professionals** who need a quick and easy way to capture tasks on the go. Students** looking to streamline their assignments and project management. Anyone** who wants to leverage AI for effortless task management. What Problem Does it Solve? This workflow eliminates the need to manually enter tasks into Todoist. It automates the process of capturing, organizing, and prioritizing tasks, saving you time and effort. What are the Benefits? Seamless Integration:** Connect your Telegram and Todoist accounts for a frictionless workflow. AI-Powered Task Breakdown:** LLM AI intelligently analyzes your messages and breaks them down into manageable sub-tasks. Voice-to-Task:** Create tasks with voice messages for hands-free convenience. Increased Productivity:** Capture and organize tasks quickly, keeping you focused and productive. Accessibility:** Access your tasks from anywhere with Todoist's mobile app and Google extension. How it Works Send a message: Send a voice or text message describing your task to your Telegram bot. AI analysis: The workflow uses an LLM (OpenAI Chat Model) to analyze your message and break it down into sub-tasks. Task creation: The workflow creates tasks in your Todoist account based on the AI's analysis. Notification: You receive a Telegram notification with a link to your newly created tasks in Todoist. Nodes in the Workflow Telegram Trigger:** Listens for incoming messages on Telegram. Switch:** Routes messages based on their type (voice or text). Telegram:** Fetches voice messages from Telegram. OpenAI:** Transcribes voice messages to text using OpenAI's Whisper API. Edit Fields:** Prepares the text for the LLM. Basic LLM Chain:** Analyzes messages and generates sub-tasks using OpenAI's GPT model. Structured Output Parser:** Extracts sub-tasks from the LLM's response. Todoist:** Creates tasks in your Todoist account. Telegram:** Sends a notification with a link to your Todoist tasks. Requirements Active n8n instance. Telegram account with a bot. Todoist account. OpenAI API key. Setup Information Import the workflow JSON into your n8n instance. Configure the Telegram Trigger node with your bot token. Set up the OpenAI credentials with your API key. Connect your Todoist account in the Todoist node. Customize the LLM prompt (optional) to fine-tune task creation. Additional Tips Explore Todoist's features to further organize and manage your tasks. Experiment with different LLM prompts to optimize task breakdown. Use n8n's features to automate other aspects of your workflow. This workflow combines the convenience of Telegram with the power of AI and Todoist to provide a seamless task management experience. Start managing your tasks effortlessly today!

Who is this for? Jira users who want to automate the generation of a Lessons Learned or Retrospective report after an Epic is Done. What problem is this workflow solving? / use case Lessons Learned / Retrospective reports are often omitted in Agile teams because they take time to write. With the use of n8n and AI this process can be automated. What is this workflow doing Triggers automatically upon an Epic reaching the "Done" status in Jira. Collects all related tasks and comments associated with the completed Epic. Intelligently filters the gathered data to provide the LLM with the most relevant information. Utilizes an LLM with a structured System Message to generate insightful reports. Delivers the finalized report directly to your specified Google Docs document. Setup Create a Jira API key and follow the Credentials Setup in the Jira trigger node. Create credentials for Google Docs and paste your document ID into the Node. How to customize this workflow to your needs Change the System Message in the AI Agent to fit your needs.

Good to know: This workflow automatically processes incoming emails (you can filter them base on your needs) and creates concise AI-powered summaries, then logs them to a Google Sheets spreadsheet for easy tracking and analysis. Who is this for? ➖Business professionals who receive many emails and need quick summaries ➖Customer service teams tracking email communications ➖Project managers monitoring email correspondence ➖Anyone who wants to automatically organize and summarize their email communications What problem is this workflow solving? This workflow solves the problem of email overload by automatically reading incoming emails, generating concise summaries using AI, and organizing them in a structured format. It eliminates the need to manually read through every email to understand the key points and maintains a searchable record of communications. What this workflow does: ✅Monitors your Gmail inbox for new emails ✅Filters emails based on specific criteria (sender validation) ✅Extracts key information (sender, date, subject, content) ✅Uses AI to generate concise summaries of email content ✅Automatically logs all data including the AI summary to a Google Sheets spreadsheet How it works: 1️⃣Gmail trigger monitors for new emails at specified intervals 2️⃣Email data is processed and formatted using JavaScript 3️⃣A conditional check validates the sender 4️⃣AI agent (powered by Groq's language model) reads the email content and generates a summary 5️⃣All information is automatically appended to a Google Sheets document How to use: Set up Gmail OAuth2 credentials in n8n Configure Google Sheets OAuth2 credentials Set up Groq API credentials for AI processing Create a Google Sheets document and update the document ID Customize the sender validation criteria as needed Activate the workflow Requirements: ✅n8n instance (cloud or self-hosted) ✅Gmail account with OAuth2 access ✅Google Sheets account ✅AI API ✅Basic understanding of n8n workflow Customizing this workflow: 🟢Modify the Gmail trigger filters to target specific labels or criteria 🟢Adjust the sender validation logic in the conditional node 🟢Customize the AI prompt to change summary style or focus 🟢Add additional data fields to the Google Sheets output 🟢Change the polling frequency for checking new emails 🟢Switch to different AI models by replacing the Groq node

Mistral OCR is a super convenient way to parse and extract data from multi-page PDFs or single images using AI. What makes it special and differs it from the competition is that Mistral OCR also performs document page splitting and markdown conversion. This helps reduce dependencies required for document parsing workflows where tools like StirlingPDF. Read the official documentation on Mistral OCR API here: https://docs.mistral.ai/capabilities/document/#tag/ocr/operation/ocr_v1_ocr_post How it works To access Mistral-OCR, you'll need to use Mistral Cloud API via the HTTP request node Mistral OCR can only accept 2 file types: PDF and Image. Here, we use 2 different request to the Mistral-OCR API to parse a bank statement PDF and an screenshot of a bank statement to extract the tables. Next, we explore a more secure method of uploading documents to the Mistral OCR API by using Mistral's cloud storage. In example 2, we first store a copy of our documents to Mistral cloud and then generate a signed URL to retreive the file before sending it to Mistral OCR. This ensures the file is not accessible publicly and protects it from unauthorised access. Finally, another way to use Mistral-OCR is via document understanding. This allows you to ask questions about the document rather than extract contents from it. In example 3, I demonstrate this use-case asking Mistral-small to tell me how many deposits are shown in the bank statement. How to use Ensure your documents are either publicly accessible for Mistral-OCR or upload them to Mistral Cloud. Alternatively, signed urls from AWS S3 or Cloudflare R2 should also work. Requirements Mistral Cloud account and API Key. You'll also need credit on your account to use Mistral-OCR. Customising the workflow Mistral-OCR also works for images such as charts and diagrams so try using it on Financial Reports. Mistral-OCR is even cheaper with batching enabled. This returns your results within 24hrs but is half the price per page.

How it Works This workflow automates the complete newsletter management process from content creation to client delivery, using Google Sheets, AI content generation, Google Drive, and Gmail. Whether you're a content creator, marketing agency, or small business owner, this workflow helps you automate newsletter creation and manage client communications with built-in approval workflows — all triggered from a simple spreadsheet. 🎯 Use Case Ideal for: Marketing Teams** streamlining newsletter distribution Agencies** managing multiple client newsletters Content Creators** automating regular communications Small Businesses** maintaining customer engagement Setup Instructions 1. Upload the Spreadsheet File name: Newsletter_Management Sheet structure: | ID | Topic | Client Name | Client Email | Status | Created Date | Send Date | Add newsletter topics and set their Status as Pending 2. Configure Google Sheets Nodes Connect your Google account to: Get topic from newsletter sheet Pick records to send email to client Get Client email address Update Status as Generated Update status as Sent 3. Add API Credentials OpenAI API Key** → for AI content generation Google Drive Access** → for document storage Gmail Account** → for sending newsletters and notifications 4. Activate the Workflow Once live, the workflow will: Manual Path: Generate newsletter content from pending topics Scheduled Path: Send approved newsletters to clients automatically Track status updates throughout the entire process Store generated content in Google Drive Send admin notifications and client emails 🔁 Workflow Logic Main Workflow (Content Generation) Trigger: Manual activation for newsletter creation Retrieve: Pending topics from Google Sheets Validate: Status confirmation (Pending only) Generate: AI-powered HTML newsletter content Store: Upload to Google Drive Notify: Send completion email to admin Update: Mark status as "Generated" Scheduled Workflow (Client Distribution) Trigger: Schedule-based activation Retrieve: Approved newsletters from Google Sheets Validate: Status confirmation (Approved only) Lookup: Client email addresses Loop: Process multiple recipients Send: Personalized newsletters via Gmail Update: Mark status as "Sent" 🧩 Node Descriptions | Node Name | Description | |-----------|-------------| | When clicking 'Test workflow' | Manual trigger to start newsletter generation | | Get topic from newsletter sheet | Retrieves pending newsletter topics from Google Sheets | | Validate Status as Pending | Checks whether status is 'Pending' for processing | | Create HTML for Newsletter | AI-powered content generation using OpenAI | | Prepare Data to create word doc | Formats generated content for document creation | | Upload doc to google drive | Stores completed newsletters in Google Drive | | Send an email to admin | Notifies administrators of completion | | Update Status as Generated | Marks processed items as 'Generated' | | Schedule Trigger | Automated trigger for client email distribution | | Pick records to send email to client | Retrieves approved newsletters for sending | | Validate Status as Approved | Ensures only approved content is processed | | Get Client email address | Fetches client contact information | | Loop Over Items | Processes multiple newsletter recipients | | Send email to client | Delivers personalized newsletters via Gmail | | Update status as Sent | Marks newsletters as successfully delivered | 🛠️ Customization Tips Modify AI prompts for different content styles and tones Add Slack notifications instead of or alongside Gmail Export to different formats (PDF, Word, etc.) Schedule multiple sending times for different client segments Add approval workflows with webhook triggers Integrate with CRM systems for client management 📒 Suggested Sticky Notes for Workflow | Node/Section | Sticky Note Content | |--------------|---------------------| | Manual Trigger | "Click to start newsletter generation process" | | AI Content Generation | "Customize prompts here for different newsletter styles" | | Google Drive Upload | "Organized storage - change folder structure as needed" | | Gmail Admin Notification | "Update admin email addresses and notification templates" | | Schedule Trigger | "Set optimal sending times for your audience" | | Client Email Loop | "Handles bulk sending - monitors for delivery errors" | | Status Updates | "Maintains audit trail - prevents duplicate processing" | 📎 Required Files | File Name | Purpose | |-----------|---------| | Newsletter_Management.xlsx | Google Sheet to manage topics, clients, and status tracking | | Client_Database.xlsx | Client contact information and preferences | | Newsletter_Workflow.json | Main n8n workflow export for this automation | 🧪 Testing Tips Add one test topic with status = Pending and run manual trigger Verify AI content generation produces quality HTML Check Google Drive upload and folder organization Test admin email delivery and formatting Add test client with valid email for scheduled workflow Monitor workflow logs for API responses and errors Confirm status updates occur at each step 🏷 Suggested Tags & Categories #Newsletter #EmailMarketing #ContentGeneration #ClientCommunication #Automation #GoogleWorkspace #AIContent #MarketingAutomation #WorkflowManagement #BusinessProcess 🔧 Prerequisites Google Workspace account (Sheets, Drive, Gmail) OpenAI API account with GPT-4 access n8n instance (Cloud or self-hosted) Basic understanding of Google Sheets and email marketing 📊 Expected Performance Setup Time**: 30-45 minutes Monthly Executions**: 100-500 (varies by newsletter frequency) Processing Time**: 2-5 minutes per newsletter Scalability**: Handles 100+ clients efficiently 🚨 Important Notes Ensure proper Google API permissions are configured Monitor OpenAI API usage and rate limits Set up error handling for failed email deliveries Regularly backup your Google Sheets data Test thoroughly before production deployment 💡 Advanced Features Approval Workflows**: Add manual approval steps between generation and sending A/B Testing**: Create multiple versions and track performance Analytics Integration**: Connect with Google Analytics for tracking Multi-language Support**: Generate content in different languages Dynamic Personalization**: Use client data for personalized content

This workflow facilitates seamless synchronization between Entra (Microsoft Azure AD) and Zammad. It automates the following processes: Fetch Entra Contacts: Create Universal User Object: Extracts key user information, such as email, phone, and name, and formats it for Zammad compatibility. Synchronize with Zammad: Identifies users in Zammad who need updates based on Entra data. Adds new users from Entra to Zammad. Deactivates users in Zammad if they are no longer in Entra. Key Features Dynamic Matching**: Compares contacts from Entra with existing Zammad users based on email and updates records accordingly. Efficient Management**: Automatically creates, updates, or deactivates Zammad users based on their status in Entra. Custom Fields**: Supports custom field mapping, ensuring enriched user profiles in Zammad. Setup Instructions Microsoft Entra Integration: Ensure proper API permissions for accessing Entra contacts. Configure Microsoft OAuth2 credentials in n8n. Zammad Integration: Set up Zammad API credentials with appropriate access rights. Customize the workflow to include additional fields or map existing fields as needed. Run Workflow: Trigger the workflow manually or set up an automation schedule (e.g., daily sync). Review created/updated/deactivated users in Zammad. Use Cases IT Administration**: Keep your support system in sync with the organization’s Entra data. Customer Management**: Ensure accurate and up-to-date user records in Zammad. Prerequisites Access to an Entra (Azure AD) environment with contacts data. A Zammad instance with API credentials for user management. A custom field in Zammad User Object (entra_key) of type String. A custom field in Zammad User Object (entra_object_type) of type `Single selection field with two key value pairs user = User contact = Contact` This workflow is fully customizable and can be adapted to your organization’s specific needs. Save time and reduce manual errors by automating your user sync process with this template! If you have found an error or have any suggestions, please report them here on Github.

Architecture Agent Overview The Architect Agent listens to Slack messages and generates full data architecture blueprints in response. Powered by Claude 3.5 (Anthropic) for reasoning and design, and Tavily for real-time web search, this agent creates production-ready data pipeline scaffolds on-demand — transforming natural language prompts into structured data engineering solutions. Capabilities Understands and interprets user requests from Slack Designs end-to-end data pipelines architectures using industry best practices. Outputs include High-level architecture diagrams Required Connections To operate correctly, the following integrations must be in place: Slack API Token with permission to read messages and post responses Tavily API Key for external search functionality Claude 3.5 API Access via Anthropic Detailed configuration instructions are provided in the workflow Setup time <15 minutes Example input: "Create a data pipeline orchestrated by Airflow, running on a Docker image. It should connect to a MySQL database, load in the data into a PostgreSQL DB (incremental load) and then transform the data into business-oriented tables also in the PostgreSQL database. Create an example setup with raw sales data." Customising this workflow Try saving outputs to Google Drive to store all your architecture blueprints

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Description See the transformation in action! Here's an example of what this workflow can achieve: This automation template is designed for content creators, social media managers, and anyone looking to breathe new life into old family photos and historical images. It transforms any old black and white or sepia photograph into a colorized, animated video using cutting-edge AI technology, then automatically publishes the results across multiple social media platforms including Facebook, Instagram, YouTube, and X (Twitter). The workflow combines powerful AI services to create engaging content from vintage photographs: first enhancing and colorizing the image using FLUX Kontext, then bringing it to life with realistic animations using Kling Video AI, and finally distributing the results across your social media channels automatically. Note: The estimated cost per workflow execution is approximately $0.29 USD, covering the AI processing for both image colorization and video animation. The upload-post node only works for self-hosted n8n instances, but you can use the standard HTTP request node for uploading content on n8n Cloud.* Who Is This For? Content Creators & Social Media Managers:** Transform historical content into engaging videos that capture audience attention and drive engagement across platforms. Family History Enthusiasts:** Bring old family photos to life by adding color and motion, creating emotional connections with your audience. Marketing Professionals:** Leverage nostalgic content for brand storytelling, using vintage aesthetics to create compelling social media campaigns. Digital Artists & Photo Restorers:** Streamline the process of enhancing and sharing restored vintage photographs with automated AI enhancement. Social Media Influencers:** Create unique, eye-catching content from historical images that stands out in crowded social feeds. What Problem Does This Workflow Solve? Creating engaging social media content from old photos typically requires multiple manual steps: photo restoration, colorization, animation, and then individual posting to each platform. This workflow addresses these challenges by: Automating Photo Enhancement:** Uses advanced AI (FLUX Kontext) to automatically colorize and enhance old photographs, removing artifacts and improving quality. Creating Dynamic Content:** Transforms static images into animated videos using Kling Video AI, making historical photos come alive with natural movements. Streamlining Multi-Platform Publishing:** Automatically distributes the final animated videos across Facebook, Instagram, YouTube, and X with a single workflow execution. Saving Time & Effort:** Eliminates the need for manual photo editing, video creation, and individual social media posting. How It Works Photo Upload: Users submit old photographs through a simple web form, with optional custom animation descriptions. Image Enhancement: The workflow uploads the photo to imgbb, then sends it to FLUX Kontext AI for colorization and quality enhancement. Animation Creation: The colorized image is processed by Kling Video AI to create a 5-second animated video with natural movements. Cloud Storage: The final video is automatically saved to Google Drive for backup and easy access. Multi-Platform Publishing: The animated video is simultaneously posted to Facebook, Instagram, YouTube, and X using the upload-post service. Setup FAL.AI API Key: Sign up at fal.ai and add your API key to the HTTP Request nodes for both FLUX Kontext and Kling Video AI services. ImgBB API Token: Create a free account at api.imgbb.com to get an API token for image hosting, then update the "Upload Image to imgbb" node. Google Drive Connection: Connect your Google Drive account to enable automatic video storage and backup. Upload-Post Service: Create an account at upload-post.com to get your API credentials for multi-platform social media posting. Important: The upload-post node currently only works with self-hosted n8n instances. For n8n Cloud users, replace the upload-post node with standard HTTP request nodes to publish to each social media platform individually. Form Customization: (Optional) Modify the form fields in the "Photo Upload Form" node to collect additional information or customize the user experience. Requirements Accounts:** n8n, FAL.AI, ImgBB, Google Drive, upload-post.com API Keys & Credentials:** FAL.AI API Key, ImgBB API Token, Google Drive OAuth2, Upload-post.com API Token & User ID File Types:** Supports JPG, PNG image formats for photo uploads Cost:** Approximately $0.29 USD per workflow execution for AI processing Transform your old photographs into viral social media content with this powerful AI-driven workflow that handles everything from restoration to distribution automatically.

Trump-o-meter: Extract and Evaluate Truth Social Posts Use Case Automatically extracting posts from Donald Trump's Truth Social account and estimating their potential impact on the U.S. stock market enables teams to monitor high-profile communications that may influence financial markets. This automation streamlines intelligence gathering for analysts, traders, and policy observers. What This Automation Does This automation retrieves up to 3 posts from Donald Trump's Truth Social profile and outputs structured information including: Author name Image URL Post text Post URL Estimated stock market impact: Direction: positive, negative, or neutral Magnitude: None, Small, Medium, Large How It Works Creates a browser session on Truth Social using an Airtop profile. Navigates to https://truthsocial.com/@realDonaldTrump. Uses a natural language prompt with a defined JSON schema to extract structured data for up to 3 posts. Splits the results into individual post items. Filters posts that contain actual content and have a non-zero estimated market impact. Sends selected posts and impact summaries to a Slack channel. Terminates the browser session to clean up. Setup Requirements Airtop API Key — free to generate. An Airtop Profile that is connected and logged into Truth Social. A Slack workspace and authorized app with write permissions to a target channel. Next Steps Integrate with Trading Signals**: Link output to financial alert systems or dashboards for timely insights. Expand Monitoring**: Extend to other high-impact accounts (e.g., politicians, CEOs). Enhance Analysis**: Add sentiment scoring or topic classification for deeper context. Legal Disclaimer This tool is intended solely for informational and analytical purposes. The market impact estimations provided are speculative and should not be construed as financial advice. Do not make investment decisions based on this automation. Always consult with a licensed financial advisor before making any trades. Read more about Trump-o-meter automation

🧾 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.

🧾 What this workflow does This workflow takes a reference ad image and brand website, then uses GPT-4, LangChain, and Dumpling AI to generate 10 high-quality image variations for ad testing. These image variations are visually consistent but subtly different in background, mood, lighting, and tone — perfect for performance testing on platforms like Meta Ads or TikTok. 👤 Who is this for DTC marketers and brand designers testing ad creatives Creative teams automating visual experimentation Content agencies using AI for fast ad mockups Performance marketers running multivariate testing ⚙️ How to set up ✅ Requirements You’ll need the following tools set up in n8n: Google Drive (OAuth2 credential) Google Sheets (OAuth2 credential) OpenAI API (for GPT-4 or GPT-4o) Dumpling AI API (via HTTP header authentication) 🛠️ Steps to configure Google Sheet Setup Create a sheet with one column: Image URL Update the Sheet ID and tab name in the final Google Sheets node. Drive Setup Create a folder in Google Drive for storing the reference image. Replace the folderId in the “Upload Ad Image to Google Drive” node. Dumpling AI API Key Use n8n’s credential manager (HTTP Header Auth) — do not hardcode the key. OpenAI API Key Required for both image description and LangChain agent prompt generation. Form Inputs Required Brand Name Brand Website Ad Image (upload field) 🧠 How it works A user submits the brand name, website, and a reference ad image through a form. The image is uploaded to Google Drive. GPT-4o describes the image’s visual style (e.g., mood, lighting, composition). GPT-4 analyzes the brand’s website to define its visual aesthetic. A LangChain agent uses both analyses to create 10 tightly scoped variation prompts. Dumpling AI generates a new image for each prompt using its “FLUX.1-pro” model. Each new image’s link is logged into Google Sheets. 🛠️ How to customize 🧪 Change prompt logic to experiment with different variations (e.g., theme, season). 🎨 Switch image model in Dumpling AI to one that supports your desired style. 🔗 Log additional metadata (prompt, timestamp) to Google Sheets. 📤 Connect output images to Airtable, Notion, or a review tool like Figma. 🎯 Modify GPT system message to reflect a different tone or brand strategy. This workflow gives creative teams and marketers an instant, AI-powered ad image testing system — built on real brand visuals, not generic stock content.