Workflow Templates

🎥 n8n Workflow: Generate AI Videos with HeyGen 🚀 Overview This automation connects directly to HeyGen's powerful AI video generation platform. It allows you to programmatically create videos with digital avatars and voiceovers, perfect for scaling your content creation for social media, marketing campaigns, or personalized messages without ever opening a video editor. 😩 The Problem Creating video content is incredibly time-consuming and expensive. You have to write scripts, record audio, find actors or create complex animations, piece everything together in an editor, and then wait for it to render. Every minor change or personalization requires repeating the entire frustrating process. This manual work is a major bottleneck, making it nearly impossible to produce large volumes of high-quality video content quickly and affordably. ✨ The Solution This workflow acts as your personal, automated video production assistant! When you provide a script, the automation instantly sends instructions to HeyGen to begin creating your video. It tells the AI which avatar and voice to use and starts the generation process. Then, it cleverly waits and periodically checks the status until your new video is finished and ready. It’s a completely hands-off process that transforms simple text into professional AI videos on demand. 🔧 What It Does Send a request to HeyGen's API to generate a video with: Custom avatar Scripted voice-over Background color and dimension Wait 30 seconds Check video status Loop until video is completed, failed, or still processing ⚙️ Simple Setup This workflow is a pre-built blueprint, designed to be up and running in minutes! Upload:** Simply upload the provided JSON file into your n8n instance. Connect:** Connect your app credentials (e.g., your HeyGen account). The workflow will show you exactly where. Activate:** Turn the workflow on, and it's ready to go! Let your new automated employee get to work. This free n8n workflow allows you to generate AI videos using HeyGen via their API. 🌐 Explore more workflows ❤️ Buy more workflows at: adamcrafts 🦾 Custom workflows at: adamcrafts@cloudysoftwares.com adamaicrafts@gmail.com > Build once, customize endlessly, and scale your video content like never before. 🚀

This n8n workflow provides a simple yet powerful utility to convert Unix timestamps (seconds since epoch) into the universally recognized ISO 8601 date and time format. This is crucial for harmonizing date data across different systems, databases, and applications. 🔧 How it works Receive Timestamp Webhook: This node acts as the entry point, listening for incoming POST requests. It expects a JSON body containing a single property: timestamp, which should be a Unix timestamp in seconds (e.g., 1678886400). Convert to ISO 8601: This node takes the timestamp received from the webhook. Since JavaScript's Date object typically uses milliseconds, it multiplies the Unix timestamp by 1000. It then uses new Date(...).toISOString() to convert this into an ISO 8601 formatted string (e.g., 2023-03-15T00:00:00.000Z) and assigns it to a new property called convertedTime. Respond with Converted Time: This node sends the convertedTime property back as the response to the original webhook caller. 👤 Who is it for? This workflow is extremely useful for: Developers & Integrators: When working with APIs or databases that return dates as Unix timestamps, and you need to display them in a human-readable or standardized format in your applications or dashboards. Data Analysts & Scientists: For cleaning and transforming raw timestamp data from logs, event streams, or legacy systems into a consistent format for analysis. System Administrators: For debugging logs where timestamps are often in Unix format. Anyone Managing Data Imports/Exports: Ensuring date compatibility when moving data between different platforms. Automators: As a building block in larger workflows where incoming data has Unix timestamps that need to be normalized before further processing (e.g., adding to a spreadsheet, sending in an email, or performing date calculations). 📑 Data Structure When you trigger the webhook, send a POST request with a JSON body structured as follows: { "timestamp": 1678886400 } The workflow will return a JSON response similar to this: { "convertedTime": "2023-03-15T00:00:00.000Z" } ⚙️ Setup Instructions Import Workflow: In your n8n editor, click "Import from JSON" and paste the provided workflow JSON. Configure Webhook Path: Double-click the Receive Timestamp Webhook node. In the 'Path' field, set a unique and descriptive path (e.g., /convert-timestamp or /unix-to-iso). Activate Workflow: Save and activate the workflow. 📝 Tips This simple conversion workflow can be drastically enhanced and leveraged in many ways: Dynamic Output Formats: Upgrade: Modify the Convert to ISO 8601 node (or add a Function node after it) to accept an optional format parameter in the webhook. Leverage: Allow users to request formats like MM/DD/YYYY HH:mm:ss, YYYY-MM-DD, DD-MM-YYYY, or just the time, making the output directly usable in various contexts without further processing. Example using a Function node: const date = new Date($json.timestamp * 1000); const format = $json.format || 'iso'; // Default to ISO let output; switch (format.toLowerCase()) { case 'iso': output = date.toISOString(); break; case 'locale': // e.g., "3/15/2023, 12:00:00 AM UTC" output = date.toLocaleString('en-US', { timeZone: 'UTC' }); break; case 'dateonly': // e.g., "2023-03-15" output = date.toISOString().split('T')[0]; break; case 'timeonly': // e.g., "00:00:00 UTC" output = date.toLocaleTimeString('en-US', { timeZone: 'UTC', hour12: false }); break; default: output = date.toISOString(); // Fallback } return [{ json: { convertedTime: output } }]; Timezone Conversion: Upgrade: Combine this with the Time Zone Converter workflow (or integrate moment-timezone.js if using a Code node and have a self-hosted instance). Accept an optional targetTimeZone parameter in the webhook. Leverage: Convert the Unix timestamp directly into a human-readable date and time in a specific target timezone, which is incredibly valuable for global scheduling or reporting. Error Handling and Input Validation: Upgrade: Add an IF node after the Receive Timestamp Webhook. Check if isNaN($json.body.timestamp) or if typeof $json.body.timestamp !== 'number'. Leverage: If the input timestamp is invalid, branch to a Respond to Webhook node that returns a clear error message (e.g., "Invalid timestamp provided. Please provide a numeric Unix timestamp in seconds."). This makes your API more robust. Reverse Conversion (ISO to Unix): Upgrade: Create a separate workflow, or add another branch to this one, to convert an ISO 8601 string back to a Unix timestamp. This provides a complete conversion utility. Example Set node value: ={{ new Date($json.body.isoString).getTime() / 1000 }} Integration with Data Pipelines: Upgrade: Use this workflow as a microservice in larger ETL (Extract, Transform, Load) pipelines. Leverage: If you're pulling data from a source that provides Unix timestamps (e.g., a logging system, IoT device, certain databases), send that data through this workflow to normalize the dates before loading them into your analytics database, CRM, or data warehouse. Automated Reporting: Upgrade: If you have a system that generates reports with Unix timestamps, trigger this webhook for each timestamp. Leverage: Produce reports with human-readable dates for better readability and decision-making for non-technical stakeholders. This workflow is a cornerstone for any automation involving diverse date and time data. By implementing the suggested upgrades, you can transform it from a basic converter into a highly flexible and reliable date-time processing hub.

This workflow automatically generates draft replies in Gmail. It's designed for anyone who manages a high volume of emails or often face writer's block when crafting responses. Since it doesn't send the generated message directly, you're still in charge of editing and approving emails before they go out. How It Works: Email Trigger: activates when new emails reach the Gmail inbox Assessment: uses OpenAI gpt-4o and a JSON parser to determine if a response is necessary. Reply Generation: crafts a reply with OpenAI GPT-4 Turbo Draft Integration: after converting the text to html, it places the draft into the Gmail thread as a reply to the first message Set Up Overview (~10 minutes): OAuth Configuration (follow n8n instructions here): Setup Google OAuth in Google Cloud console. Make sure to add Gmail API with the modify scope. Add Google OAuth credentials in n8n. Make sure to add the n8n redirect URI to the Google Cloud Console consent screen settings. OpenAI Configuration: add OpenAI API Key in the credentials Tweaking the prompt: edit the system prompt in the "Generate email reply" node to suit your needs Detailed Walkthrough Check out this blog post where I go into more details on how I built this workflow. Reach out to me here if you need help building automations for your business.

Use Case This workflow aims to enrich new contacts in Intercom. The more relevant the Intercom profile, the more useful it is. Once active, this n8n workflow will update contact data (phone, email) as well as location data from ExactBuyer. Setup Add a webhook url in Intercom to call this workflow Add your Exact Buyer API key Add your Intercom API key Activate workflow How to adjust this template There's plenty of interesting info that ExactBuyer returns that could be helpful. Take a look and update this workflow to add what you need.

How it works Automatically generates trending LinkedIn content topics using AI Researches current industry angles and hooks Writes posts in your authentic voice using OpenAI Creates professional images with DALL-E Posts everything on schedule without manual intervention Set up steps Connect OpenAI API for content generation and image creation Link LinkedIn API for automated posting Configure scheduling triggers (daily/weekly posting) Customize prompts to match your writing style and industry Set up content approval workflows (optional) Results you can expect 400% increase in profile views within 3 weeks Generate 120+ posts per month vs manual 12 posts Free up 15+ hours weekly for revenue-generating activities Consistent posting schedule that builds audience engagement Professional content that converts followers to clients Time to set up: 30-45 minutes Technical level: Beginner to intermediate APIs required: OpenAI, LinkedIn API Cost: OpenAI usage fees only (approximately $5-15/month) This workflow transforms LinkedIn content creation from a time-consuming daily task into a fully automated system that works while you sleep. Perfect for entrepreneurs, marketers, and content creators who want consistent LinkedIn presence without the manual effort.

This n8n workflow automates posting Amazon affiliate products to Mastodon — complete with image upload, description, and a shortened tracking URL using Shlink. 🔧 How it works Input Source: The workflow starts by reading from a connected Google Sheet that contains: SHlink (Shortlink) Amazon Link Description (Optional) PicURL Send /NO or YES A Send column (used as a flag to check if the row was already posted) Image Upload: It fetches the product image via HTTP and uploads it directly to a Mastodon instance via the /media API endpoint. URL Shortening (Shlink): The original Amazon URL is shortened using your self-hosted or cloud-hosted Shlink instance to enable click tracking and better presentation. Text Generation: A two-line promotional text is automatically generated using a Language Model (LLM), based on the product description. Posting to Mastodon: The post is then published on Mastodon with: The image The generated text The shortened Shlink URL Row Update: Once published, the Send column in the Google Sheet is updated to "YES" to prevent duplicates. Requirements ✅ Shlink – Required for shortening and tracking Amazon URLs ✅ Google Sheet – Used as a product queue and post ✅ Google Sheet Example https://link.unixweb.home64.de/w7VqY ✅ Mastodon account – OAuth2 credentials with write scope ✅ Product image URL – Must be valid and accessible ✅ n8n credentials – Set up for Google Sheets, Mastodon, and optionally OpenRouter or other LLM providers This workflow is ideal for content creators, affiliate marketers, and automation fans who want to save time and optimize reach across the Fediverse. #affiliate #amazon #mastodon #advertisment

This n8n template provides a simple yet powerful utility for validating if a given string input is a valid JSON format. You can use this to pre-validate data received from external sources, ensure data integrity before further processing, or provide immediate feedback to users submitting JSON strings. 🔧 How it works Webhook: This node acts as the entry point for the workflow, listening for incoming POST requests. It expects a JSON body with a single property: jsonString: The string that you want to validate as JSON. Code (JSON Validator): This node contains custom JavaScript code that attempts to parse the jsonString provided in the webhook body. If the jsonString can be successfully parsed, it means it's valid JSON, and the node returns an item with valid: true. If parsing fails, it catches the error and returns an item with valid: false and the specific error message. This logic is applied to each item passed through the node, ensuring all inputs are validated. Respond to Webhook: This node sends the validation result (either valid: true or valid: false with an error message) back to the service that initiated the webhook request. 👤 Who is it for? This workflow is ideal for: Developers & Integrators: Pre-validate JSON payloads from external systems (APIs, webhooks) before processing them in your workflows, preventing errors. Data Engineers: Ensure the integrity of JSON data before storing it in databases or data lakes. API Builders: Offer a dedicated endpoint for clients to test their JSON strings for validity. Customer Support Teams: Quickly check user-provided JSON configurations for errors. Anyone handling JSON data: A quick and easy way to programmatically check JSON string correctness without writing custom code in every application. 📑 Data Structure When you trigger the webhook, send a POST request with a JSON body structured as follows: { "jsonString": "{\"name\": \"n8n\", \"type\": \"workflow\"}" } Example of an invalid JSON string: { "jsonString": "{name: \"n8n\"}" // Missing quotes around 'name' } The workflow will return a JSON response indicating validity: For a valid JSON string: { "valid": true } For an invalid JSON string: { "valid": false, "error": "Unexpected token 'n', \"{name: \"n8n\"}\" is not valid JSON" } ⚙️ Setup Instructions Import Workflow: In your n8n editor, click "Import from JSON" and paste the provided workflow JSON. Configure Webhook Path: Double-click the Webhook node. In the 'Path' field, set a unique and descriptive path (e.g., /validate-json). Activate Workflow: Save and activate the workflow. 📝 Tips This JSON validator workflow is a solid starting point. Consider these enhancements: Enhanced Error Feedback: Upgrade: Add a Set node after the Code node to format the error message into a more user-friendly string before responding. Leverage: Make it easier for the caller to understand the issue. Logging Invalid Inputs: Upgrade: After the Code node, add an IF node to check if valid is false. If so, branch to a node that logs the invalid jsonString and error to a Google Sheet, database, or a logging service. Leverage: Track common invalid inputs for debugging or improvement. Transforming Valid JSON: Upgrade: If the JSON is valid, you could add another Function node to parse the jsonString and then operate on the parsed JSON data directly within the workflow. Leverage: Use this validator as the first step in a larger workflow that processes JSON data. Asynchronous Validation: Upgrade: For very large JSON strings or high-volume requests, consider using a separate queueing mechanism (e.g., RabbitMQ, SQS) and an asynchronous response pattern. Leverage: Prevent webhook timeouts and improve system responsiveness.

Analyze and Explore your ZenDesk Support Requests using AI-Powered Knowledge Graph This template helps you create an interactive InfraNodus knowledge graph for your ZenDesk tickets using any search criteria (e.g. after a certain date, specific status, sender, keyword) that will automatically be sent to a selected Slack channel. Here's an example of the InfraNodus graph that shows the main topics and gaps in ZenDesk support tickets: You can use the workflow to: Get an instant overview of the main topics your customers are talking about Generate business and product ideas based on the blind spots identified using the InfraNodus AI See which topics correlate to the negative / positive sentiment understanding the weak and strong sides of your product and support Receive daily notifications on the main topics your customers are talking about via Slack / Telegram / Email and other channels Perform detailed search using a password-protected web form for tickets filtered by a certain date, status, tag, sender, keyword. Use the interactive graph to explore specific topics and concepts your customers are talking about — a great way to engage with their concerns in a non-linear way, bypassing the boring tabular interface Use the graph to explore the support requests by specific segments — e.g. status, priority, sentiment, tags, urgency. Use the graph generated as an AI expert available to your AI agents in other n8n workflows via InfraNodus GraphRAG. For instance, you could connect your knowledge base to the support tickets graph and let the agent discover possible solutions to your customers' most typical problems. See an sample template here. How it works You can start this workflow manually, with a daily / weekly trigger, or via a password-protected web form, where you can provide search requests. Once started, it will perform a ZenDesk tickets search with the default or your custom criteria. Then it will use the search results to generate an InfraNodus graph (or add the new data to an existing one), and — finally — use the InfraNodus AI endpoints to generate a topical summary and a product business idea based on the blind spots identified. The results are delivered a channel of your choice. Here's a description step by step: Start the workflow (manually or on schedule) Assign values to variables (search criteria, graph name) Perform ZenDesk support tickets search Convert the data received and submit it to InfraNodus to generate a knowledge graph Generate topical summary with InfraNodus Generate a business idea with InfraNodus (you can also change the setting to generate a question instead) Send a notification via Slack / Telegram / Email or back to the webform How to use You need an InfraNodus API account and key to use this workflow. You also need a ZenDesk account. It takes about 5 minutes to set everything up. Create an InfraNodus account. Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes. Add the authorization key to all the InfraNodus HTTP nodes in the template (Steps 3, 5, and 6). Generate a ZenDesk authorization token following the instructions in n8n's ZenDesk node (Step 3). Optionally: connect your Slack or Telegram or Gmail account to receive automated notifications with the link to the graph, once the workflow is ready (it takes about 30 seconds to run). Run it with using the form to play around with the search criteria that works best for you (you can leave everything empty at first), then choose the parameters you like and activate the Daily Trigger node to receive executive summaries to a channel of your choice. Open the graph in InfraNodus and use our customer feedback analysis guide to explore the graph and generate new insights. Requirements An InfraNodus account and API key A ZenDesk API key (Optional) — a Slack / Telegram / Gmail connection for notifications FAQ 1. What are the best use cases to try? I love to set the graph to deliver me a daily visual briefing of what's happening in my support portal. It shows me the main topics and gaps and generates product ideas based on them. Great to keep the pulse on the business. I also really like generating a graph for the past week manually, using the form, and then exploring the graph in InfraNodus directly using the customer feedback analysis workflow to: discover main topics my customers are talking about? understand the topics that have the most negative connotation for them (using the sentiment filter)? discover some support tickets that need more attention or that talk about the topics I'm personally interested in and engage with the client identify the gaps in your customers' discourse based on the blind spots — useful for generating ideas, see the graph below with a demo of how it works: 2. Why use the graph and not just AI summary? AI summary will just give you generic results. You'll see what you already know. Using the graph helps you deconstruct the discourse and get a much more nuanced understanding of the main pain points and interests of your customers. The auto-generated InfraNodus summary and business ideas have a direct explainable connection to the discourse, so you can always see where they are coming from and maintain the focus on all the topics, rather than the most prominent ones. Additionally, having an interactive graph opens a possibility to explore your customers' concerns in a more engaging way, finding the topics and concepts that are relevant to your interests or to your agents' expertise, helping you find the conversations that you'd otherwise have missed. 3. Is my customers' data safe? Absolutely. InfraNodus' terms of use and privacy policy state that the customers' data and text graphs are not used in AI training and are not offered to any third parties. Its underlying API system uses the Open API which explicitly states that data is not used for training either. So all the customers' data are private and safe. As an extra precaution, you can always delete the graphs after you analyzed them, in which case there is no trace of this data left on the servers. Customizing this workflow Check out the complete setup guide for this workflow at https://support.noduslabs.com/hc/en-us/articles/20447530961308-Zendesk-Tickets-Summarization-Sentiment-Analysis-and-Slack-Integration-with-n8n-and-InfraNodus For support with this template, please, contact https://support.noduslabs.com For more InfraNodus n8n workflows, please, see our creators page: https://n8n.io/creators/infranodus/ To learn more about InfraNodus, GraphRAG, and knowledge graph analysis: https://infranodus.com

README Automating Video File Download from Sample.cat with Airtop.ai Use Case Automating file downloads from web pages is useful for scenarios like bulk media retrieval, dataset access, or recurring content backups. This workflow ensures a hands-free, consistent process for retrieving downloadable content. What This Automation Does This automation performs a reliable download of a video file from a specified webpage using the following steps: Initiates an Airtop browser session. Opens a specified URL containing downloadable media. Interacts with the page to click the download button. Waits for the file to be processed and made available. Retrieves metadata to confirm availability. Downloads the file. Terminates the browser session to clean up resources. How It Works Manual Trigger: Activated by user test. Session: Starts an Airtop browser session. Window: Navigates to https://sample.cat/en/webm. Interaction: Simulates a click on the download button for the video titled “SD 640x360 (Seawater, drone view video, 30 FPS)”. Wait: Pauses for 10 seconds to allow the file to be ready for download. Get File Data: Checks for downloadable files in the session. Download File: Retrieves the file using its ID. Terminate: Ends the browser session to free up resources. Setup Requirements Airtop API Key — required to authenticate API calls. Next Steps Enhance with Retry Logic**: Loop file availability check until status = available for more robust automation. Customize File Targets**: Dynamically pass URLs and button descriptors for multi-source downloads. Connect to Storage**: Pipe downloaded files to cloud storage or databases for archiving. Read more about automating file downloads from the web

This workflow enables you to automate the daily monitoring of how an AI model (like ChatGPT) responds to specific queries relevant to your market. It identifies mentions of your brand and predefined competitors, logs detailed interactions in Google Sheets, and delivers a comprehensive email report. Main Use Cases Monitor how your brand is mentioned by AI in response to relevant user queries. Track mentions of key competitors to understand AI's comparative positioning. Gain insights into AI's current knowledge and portrayal of your brand and market landscape. Automate daily intelligence gathering on AI-driven brand perception. How it works The workflow operates as a scheduled process, organized into these stages: Configuration & Scheduling Triggers daily (or can be run manually). Key variables are defined within the workflow: your brand name (e.g., "YourBrandName"), a list of queries to ask the AI, and a list of competitor names to track in responses. AI Querying For each predefined query, the workflow sends a request to the OpenAI ChatGPT API (via an HTTP Request node). Response Analysis Each AI response is processed by a Code node to: Check if your brand name is mentioned (case-insensitive). Identify if any of the listed competitors are mentioned (case-insensitive). Extract the core AI response content (limited to 500 characters for brevity in logs/reports). Data Logging to Google Sheets Detailed results for each query—including timestamp, date, the query itself, query index, your brand name, the AI's response, whether your brand was mentioned, and any errors—are appended to a specified Google Sheet. Email Report Generation A comprehensive HTML email report is compiled. This report summarizes: Total queries processed, number of times your brand was mentioned, total competitor mentions, and any errors encountered. A summary of competitor mentions, listing each competitor and how many times they were mentioned. A detailed table listing each query, whether your brand was mentioned, and which competitors (if any) were mentioned in the AI's response. Automated Reporting The generated HTML email report is sent to specified recipients, providing a daily snapshot of AI interactions. Summary Flow: Schedule/Workflow Trigger → Initialize Brand, Queries, Competitors (in Code node) → For each Query: Query ChatGPT API → Process AI Response (Check for Brand & Competitor Mentions) → Log Results to Google Sheets → Generate Consolidated HTML Email Report → Send Email Notification Benefits: Fully automated daily monitoring of AI responses concerning your brand and competitors. Provides objective insights into how AI models are representing your brand in user interactions. Delivers actionable competitive intelligence by tracking competitor mentions. Centralized logging in Google Sheets for historical analysis and trend spotting. Easily customizable with your specific brand, queries, competitor list, and reporting recipients.

For Who? Content Creators Youtube Automation Marketing Team How it works? 1 - Enter the ID of the YTB channel to trigger the workflow when a new video is posted 2 - Apify scrape the last YTB video of the channel 3 - Wait until the dataset is completed in Apify and get it 4 - Verify if Metadata are not already generated and generate them with LLM 5 - Format all the data created and update YTB Video 📺 YouTube Video Tutorial: SETUP Setup Input YTB Chanel : Go to the channel's page on YouTube, and look at the URL of the page. The channel ID is the value that comes after channel/ in the URL. Add it after "?channel_id=" You can also use free tools available to retrieve channel ID. Setup Output YTB Video Update : Connect your YTB account to your n8n instance thanks to the Google Cloud Console. You can find tutorials by typing "youtube api Oauth" on Google. APIs : For the following third-party integrations, replace ==[YOUR_API_TOKEN]== with your API Token or connect your account via Client ID / Secret to your n8n instance : Apify : https://docs.apify.com/api/v2/getting-started Youtube : https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.youtube/?utm_source=n8n_app&utm_medium=node_settings_modal-credential_link&utm_campaign=n8n-nodes-base.youTube#templates-and-examples 👨‍💻 More Workflows : https://n8n.io/creators/nasser/

Who this is for This template is for everyone that wants to download their n8n Cloud invoices automatically as a PDF instead of downloading them manually. How it works This workflow checks your Gmail inbox for new n8n invoice emails from n8n's payment provider Paddle. Once it finds something, it converts the URL into a PDF using pdflayer and saves it in Google Drive. Setup Setup your Gmail and Google Drive credentials Create a free account at https://pdflayer.com/ Insert your pdflayer API key into the Setup node Insert the URL to the wanted drive folder into the setup node (make sure to remove everything after the ?) How to adjust it to your need Instead of saving the PDF in Google drive, you could also save it in your local system, any other storage provider or send the PDF automatically to the right person in your company.